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Tamiya E, Osaki S, Nagai H. Wireless electrochemiluminescent biosensors: Powering innovation with smartphone technology. Biosens Bioelectron 2024; 252:116083. [PMID: 38387231 DOI: 10.1016/j.bios.2024.116083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Revised: 01/21/2024] [Accepted: 01/26/2024] [Indexed: 02/24/2024]
Abstract
Energy supply and sensor response acquisition can be performed wirelessly, enabling biosensors as Internet of Thing (IoT) tools by linking wireless power supply and electrochemical sensors. Here, we used the electromagnetic induction method to clarify the conditions under which electrochemiluminescence is induced by a simple potential modulation circuit without an integrated circuit on the electrode chip that receives the power. Initially, the potential waveform obtained in a circuit with inductance and capacitance components that resonate with the transmission frequency and a diode for rectification was investigated to clarify the conditions inducing an electrochemiluminescence reaction at the printed electrode. A high-sensitivity complementary metal-oxide semiconductor camera built into the smartphone wirelessly detected the luminescence generated on the electrode chip. The images were quantitatively evaluated using open-source image analysis software which determine the sensitivity of detecting hydrogen peroxide. Glucose oxidase (GOD) encapsulated in a matrix of chitosan polymers and photocrosslinkable polymers was immobilized on a mass-producible and inexpensive printed electrode to maintain high activity. The immobilized membrane suppressed luminescence when immobilized on the working electrode; therefore, the enzyme was immobilized on the counter electrode for glucose measurement over a wide concentration. Thus, luminol electrochemiluminescence was induced on the electrode chip by wireless power supply from a smartphone. Human serum and artificial sweat samples were tested and indicated possibility for actual applications. In this way a fully wireless biosensor was developed with potential as an IoT biosensor.
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Affiliation(s)
- Eiichi Tamiya
- Advanced Photonics and Biosensing Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Photonics Center, Osaka University, 2-1 Yamadaoka, Suita 565-0871, Osaka, Japan; SANKEN, Osaka University, 8-1 Mihogaoka, Ibaraki 567-0047, Osaka, Japan.
| | - Shuto Osaki
- Advanced Photonics and Biosensing Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Photonics Center, Osaka University, 2-1 Yamadaoka, Suita 565-0871, Osaka, Japan
| | - Hidenori Nagai
- Advanced Photonics and Biosensing Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Photonics Center, Osaka University, 2-1 Yamadaoka, Suita 565-0871, Osaka, Japan
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Dawod A, Georgakopoulos D, Jayaraman PP, Nirmalathas A. A Survey of Techniques for Discovering, Using, and Paying for Third-Party IoT Sensors. Sensors (Basel) 2024; 24:2539. [PMID: 38676156 PMCID: PMC11054404 DOI: 10.3390/s24082539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 04/07/2024] [Accepted: 04/10/2024] [Indexed: 04/28/2024]
Abstract
The Internet of Things (IoT) includes billions of sensors and actuators (which we refer to as IoT devices) that harvest data from the physical world and send it via the Internet to IoT applications to provide smart IoT services and products. Deploying, managing, and maintaining IoT devices for the exclusive use of an individual IoT application is inefficient and involves significant costs and effort that often outweigh the benefits. On the other hand, enabling large numbers of IoT applications to share available third-party IoT devices, which are deployed and maintained independently by a variety of IoT device providers, reduces IoT application development costs, time, and effort. To achieve a positive cost/benefit ratio, there is a need to support the sharing of third-party IoT devices globally by providing effective IoT device discovery, use, and pay between IoT applications and third-party IoT devices. A solution for global IoT device sharing must be the following: (1) scalable to support a vast number of third-party IoT devices, (2) interoperable to deal with the heterogeneity of IoT devices and their data, and (3) IoT-owned, i.e., not owned by a specific individual or organization. This paper surveys existing techniques that support discovering, using, and paying for third-party IoT devices. To ensure that this survey is comprehensive, this paper presents our methodology, which is inspired by Systematic Literature Network Analysis (SLNA), combining the Systematic Literature Review (SLR) methodology with Citation Network Analysis (CNA). Finally, this paper outlines the research gaps and directions for novel research to realize global IoT device sharing.
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Affiliation(s)
- Anas Dawod
- Department of Computing Technologies, Swinburne University of Technology, Melbourne 3122, Australia; (D.G.); (P.P.J.)
| | - Dimitrios Georgakopoulos
- Department of Computing Technologies, Swinburne University of Technology, Melbourne 3122, Australia; (D.G.); (P.P.J.)
| | - Prem Prakash Jayaraman
- Department of Computing Technologies, Swinburne University of Technology, Melbourne 3122, Australia; (D.G.); (P.P.J.)
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Islam M, Jamil HMM, Pranto SA, Das RK, Amin A, Khan A. Future Industrial Applications: Exploring LPWAN-Driven IoT Protocols. Sensors (Basel) 2024; 24:2509. [PMID: 38676127 PMCID: PMC11054578 DOI: 10.3390/s24082509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 04/10/2024] [Accepted: 04/11/2024] [Indexed: 04/28/2024]
Abstract
The Internet of Things (IoT) will bring about the next industrial revolution in Industry 4.0. The communication aspect of IoT devices is one of the most critical factors in choosing the device that is suitable for use. Thus far, the IoT physical layer communication challenges have been met with various communications protocols that provide varying strengths and weaknesses. This paper summarizes the network architectures of some of the most popular IoT wireless communications protocols. It also presents a comparative analysis of some of the critical features, including power consumption, coverage, data rate, security, cost, and quality of service (QoS). This comparative study shows that low-power wide area network (LPWAN)-based IoT protocols (LoRa, Sigfox, NB-IoT, LTE-M) are more suitable for future industrial applications because of their energy efficiency, high coverage, and cost efficiency. In addition, the study also presents an Industrial Internet of Things (IIoT) application perspective on the suitability of LPWAN protocols in a particular scenario and addresses some open issues that need to be researched. Thus, this study can assist in deciding the most suitable IoT communication protocol for an industrial and production field.
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Affiliation(s)
- Mahbubul Islam
- Department of Computer Science, United International University, Dhaka 1212, Bangladesh;
| | - Hossain Md. Mubashshir Jamil
- Department of Electrical and Electronic Engineering, Islamic University of Technology, Gazipur 1704, Bangladesh; (H.M.M.J.); (S.A.P.)
| | - Samiul Ahsan Pranto
- Department of Electrical and Electronic Engineering, Islamic University of Technology, Gazipur 1704, Bangladesh; (H.M.M.J.); (S.A.P.)
| | - Rupak Kumar Das
- College of Information Sciences and Technology, Pennsylvania State University—University Park, University Park, PA 16802, USA;
| | - Al Amin
- Department of Information Systems, University of Maryland—Baltimore, Baltimore, MD 21201, USA;
| | - Arshia Khan
- Department of Computer Science, University of Minnesota—Duluth, Duluth, MN 55812, USA
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Kulkarni P, Pradeep B, Yusuf R, Alexander H, ElSayed H. Enhancing Occupant Comfort and Building Sustainability: Lessons from an Internet of Things-Based Study on Centrally Controlled Indoor Shared Spaces in Hot Climatic Conditions. Sensors (Basel) 2024; 24:1406. [PMID: 38474942 DOI: 10.3390/s24051406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/17/2023] [Accepted: 12/20/2023] [Indexed: 03/14/2024]
Abstract
It is well known that buildings have a sizeable energy and environmental footprint. In particular, in environments like university campuses, the occupants as well as occupancy in shared spaces varies over time. Systems for cooling in such environments that are centrally controlled are typically threshold driven and do not account for occupant feedback and thus are often relying on a reactive approach (fix after identifying problems). Therefore, having a fixed thermal operating set point may not be optimal in such cases-both from an occupant comfort and well-being as well as an energy efficiency perspective. To address this issue, a study was conducted which involved development and deployment of an experimental Internet of Things (IoT) prototype system and an Android application that facilitated people engagement on a university campus located in the UAE which typically exhibits hot climatic conditions. This paper showcases data driven insights obtained from this study, and in particular, how to achieve a balance between the conflicting goals of improving occupant comfort and energy efficiency. Findings from this study underscore the need for regular reassessments and adaptation. The proposed solution is low cost and easy to deploy and has the potential to reap significant savings through a reduction in energy consumption with estimates indicating around 50-100 kWh/day of savings per building and the resulting environmental impact. These findings would appeal to stakeholders who are keen to improve energy efficiency and reduce their operating expenses and environmental footprint in such climatic conditions. Furthermore, collective action from a large number of entities could result in significant impact through this cumulative effect.
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Affiliation(s)
- Parag Kulkarni
- College of Information Technology (CIT), United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
- National Water and Energy Centre (NWEC), United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
| | - Bivin Pradeep
- College of Information Technology (CIT), United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
| | - Rahemeen Yusuf
- Emirates Centre for Happiness Research, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
| | - Henry Alexander
- College of Information Technology (CIT), United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
| | - Hesham ElSayed
- College of Information Technology (CIT), United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
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Alasmary H. ScalableDigitalHealth (SDH): An IoT-Based Scalable Framework for Remote Patient Monitoring. Sensors (Basel) 2024; 24:1346. [PMID: 38400504 PMCID: PMC10893503 DOI: 10.3390/s24041346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 02/04/2024] [Accepted: 02/16/2024] [Indexed: 02/25/2024]
Abstract
Addressing the increasing demand for remote patient monitoring, especially among the elderly and mobility-impaired, this study proposes the "ScalableDigitalHealth" (SDH) framework. The framework integrates smart digital health solutions with latency-aware edge computing autoscaling, providing a novel approach to remote patient monitoring. By leveraging IoT technology and application autoscaling, the "SDH" enables the real-time tracking of critical health parameters, such as ECG, body temperature, blood pressure, and oxygen saturation. These vital metrics are efficiently transmitted in real time to AWS cloud storage through a layered networking architecture. The contributions are two-fold: (1) establishing real-time remote patient monitoring and (2) developing a scalable architecture that features latency-aware horizontal pod autoscaling for containerized healthcare applications. The architecture incorporates a scalable IoT-based architecture and an innovative microservice autoscaling strategy in edge computing, driven by dynamic latency thresholds and enhanced by the integration of custom metrics. This work ensures heightened accessibility, cost-efficiency, and rapid responsiveness to patient needs, marking a significant leap forward in the field. By dynamically adjusting pod numbers based on latency, the system optimizes system responsiveness, particularly in edge computing's proximity-based processing. This innovative fusion of technologies not only revolutionizes remote healthcare delivery but also enhances Kubernetes performance, preventing unresponsiveness during high usage.
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Affiliation(s)
- Hisham Alasmary
- Department of Computer Science, College of Computer Science, King Khalid University, Abha 61421, Saudi Arabia
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Plastras S, Tsoumatidis D, Skoutas DN, Rouskas A, Kormentzas G, Skianis C. Non-Terrestrial Networks for Energy-Efficient Connectivity of Remote IoT Devices in the 6G Era: A Survey. Sensors (Basel) 2024; 24:1227. [PMID: 38400391 PMCID: PMC10891744 DOI: 10.3390/s24041227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 02/06/2024] [Accepted: 02/12/2024] [Indexed: 02/25/2024]
Abstract
The Internet of Things (IoT) is gaining popularity and market share, driven by its ability to connect devices and systems that were previously siloed, enabling new applications and services in a cost-efficient manner. Thus, the IoT fuels societal transformation and enables groundbreaking innovations like autonomous transport, robotic assistance, and remote healthcare solutions. However, when considering the Internet of Remote Things (IoRT), which refers to the expansion of IoT in remote and geographically isolated areas where neither terrestrial nor cellular networks are available, internet connectivity becomes a challenging issue. Non-Terrestrial Networks (NTNs) are increasingly gaining popularity as a solution to provide connectivity in remote areas due to the growing integration of satellites and Unmanned Aerial Vehicles (UAVs) with cellular networks. In this survey, we provide the technological framework for NTNs and Remote IoT, followed by a classification of the most recent scientific research on NTN-based IoRT systems. Therefore, we provide a comprehensive overview of the current state of research in IoRT and identify emerging research areas with high potential. In conclusion, we present and discuss 3GPP's roadmap for NTN standardization, which aims to establish an energy-efficient IoRT environment in the 6G era.
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Affiliation(s)
- Stefanos Plastras
- Department of Information and Communication Systems Engineering, University of the Aegean, 83200 Samos, Greece; (D.T.); (D.N.S.); (G.K.); (C.S.)
| | - Dimitrios Tsoumatidis
- Department of Information and Communication Systems Engineering, University of the Aegean, 83200 Samos, Greece; (D.T.); (D.N.S.); (G.K.); (C.S.)
| | - Dimitrios N. Skoutas
- Department of Information and Communication Systems Engineering, University of the Aegean, 83200 Samos, Greece; (D.T.); (D.N.S.); (G.K.); (C.S.)
| | - Angelos Rouskas
- Department of Digital Systems, University of Piraeus, 18532 Piraeus, Greece;
| | - Georgios Kormentzas
- Department of Information and Communication Systems Engineering, University of the Aegean, 83200 Samos, Greece; (D.T.); (D.N.S.); (G.K.); (C.S.)
| | - Charalabos Skianis
- Department of Information and Communication Systems Engineering, University of the Aegean, 83200 Samos, Greece; (D.T.); (D.N.S.); (G.K.); (C.S.)
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Wiryasaputra R, Huang CY, Lin YJ, Yang CT. An IoT Real-Time Potable Water Quality Monitoring and Prediction Model Based on Cloud Computing Architecture. Sensors (Basel) 2024; 24:1180. [PMID: 38400338 PMCID: PMC10891771 DOI: 10.3390/s24041180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 02/01/2024] [Accepted: 02/01/2024] [Indexed: 02/25/2024]
Abstract
In order to achieve the Sustainable Development Goals (SDG), it is imperative to ensure the safety of drinking water. The characteristics of each drinkable water, encompassing taste, aroma, and appearance, are unique. Inadequate water infrastructure and treatment can affect these features and may also threaten public health. This study utilizes the Internet of Things (IoT) in developing a monitoring system, particularly for water quality, to reduce the risk of contracting diseases. Water quality components data, such as water temperature, alkalinity or acidity, and contaminants, were obtained through a series of linked sensors. An Arduino microcontroller board acquired all the data and the Narrow Band-IoT (NB-IoT) transmitted them to the web server. Due to limited human resources to observe the water quality physically, the monitoring was complemented by real-time notifications alerts via a telephone text messaging application. The water quality data were monitored using Grafana in web mode, and the binary classifiers of machine learning techniques were applied to predict whether the water was drinkable or not based on the data collected, which were stored in a database. The non-decision tree, as well as the decision tree, were evaluated based on the improvements of the artificial intelligence framework. With a ratio of 60% for data training: at 20% for data validation, and 10% for data testing, the performance of the decision tree (DT) model was more prominent in comparison with the Gradient Boosting (GB), Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM) modeling approaches. Through the monitoring and prediction of results, the authorities can sample the water sources every two weeks.
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Affiliation(s)
- Rita Wiryasaputra
- Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung 407224, Taiwan; (R.W.); (C.-Y.H.); (Y.-J.L.)
- Informatics Department, Krida Wacana University, Jakarta 11470, Indonesia
| | - Chin-Yin Huang
- Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung 407224, Taiwan; (R.W.); (C.-Y.H.); (Y.-J.L.)
| | - Yu-Ju Lin
- Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung 407224, Taiwan; (R.W.); (C.-Y.H.); (Y.-J.L.)
| | - Chao-Tung Yang
- Department of Computer Science, Tunghai University, Taichung 407224, Taiwan
- Research Center for Smart Sustainable Circular Economy, Tunghai University, Taichung 407224, Taiwan
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8
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Senger D, Gruber C, Kluss T, Johannsen C. Weight, temperature and humidity sensor data of honey bee colonies in Germany, 2019-2022. Data Brief 2024; 52:110015. [PMID: 38274156 PMCID: PMC10809063 DOI: 10.1016/j.dib.2023.110015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 01/27/2024] Open
Abstract
Humans have kept honeybees as livestock to harvest honey, wax and other products for thousands of years and still continue doing so. Today however, beekeepers in many parts of the world report unprecedented high numbers of colony losses. Sensor data from honey bee colonies can contribute to new insights about development and health factors for honey bee colonies. The data can be incorporated in smart decision support systems and warning tools for beekeepers. In this paper, we present sensor data from 78 honey bee colonies in Germany collected as part of a citizen science project. Each honey bee hive was equipped with five temperature sensors within the hive, one temperature sensor for outside measurements, a combined sensor for temperature, ambient air pressure and humidity, and a scale to measure the weight. During the data acquisition period, beekeepers used a web app to report their observations and beekeeping activities. We provide the raw data with a measurement interval of up to 5 s as well as aggregated data, with per minute, hourly or daily average values. Furthermore, we performed several preprocessing steps, removing outliers with a threshold based approach, excluding changes in weight that were induced by beekeeping activities and combining the sensor data with the most important meta-data from the beekeepers' observations. The data is organised in directories based on the year of recording. Alternatively, we provide subsets of the data structured based on the occurrence or non-occurrence of a swarming event or the death of a colony. The data can be analysed using methods from time series analysis, time series classification or other data science approaches to form a better understanding of specifics in the development of honey bee colonies.
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Affiliation(s)
- Diren Senger
- AG Cognitive Neuroinformatics, University of Bremen, Enrique-Schmidt-Str. 5, 28359 Breme
| | | | - Thorsten Kluss
- AG Cognitive Neuroinformatics, University of Bremen, Enrique-Schmidt-Str. 5, 28359 Breme
| | - Carolin Johannsen
- AG Cognitive Neuroinformatics, University of Bremen, Enrique-Schmidt-Str. 5, 28359 Breme
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Wang Z, Qiao X, Wang Y, Yu H, Mu C. IoT-based system of prevention and control for crop diseases and insect pests. Front Plant Sci 2024; 15:1323074. [PMID: 38371415 PMCID: PMC10870423 DOI: 10.3389/fpls.2024.1323074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 01/15/2024] [Indexed: 02/20/2024]
Abstract
Environmentally friendly technologies for the prevention and control of crop diseases and insect pests are important to reduce the use of chemical pesticides, improve the quality of agricultural products, protect the environment, and promote sustainable development of crop production. On the basis of Internet of Things (IoT) technology, we developed a prevention and control system for crop diseases and insect pests with two main components: a plant protection device (the hardware) and an information management system (the software). To be suitable for both facility- and field-based production scenarios, we incorporated two types of plant protection devices, utilizing ozone sterilization and light-trap technologies. The devices were equipped with various sensors to realize real-time collection and monitoring of data on the crop production environment. The information management system has an IoT-based architecture and includes a mobile device app to enable remote control of the plant protection devices for intelligent management of plant protection data. The system can achieve efficient management of large-scale equipment applications and multi-device collaborative work to prevent and control pests and diseases. The developed system has operated successfully for several years in China and has been applied to cucumber, tomato, rice, and other crops. We demonstrate the effectiveness and practicality of the system in a greenhouse facility and in the field.
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Affiliation(s)
- Zhibin Wang
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Engineering Research Center of Agricultural Internet of Things, Beijing, China
| | - Xiaojun Qiao
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Engineering Research Center of Agricultural Internet of Things, Beijing, China
| | - Ying Wang
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Engineering Research Center of Agricultural Internet of Things, Beijing, China
| | - Hao Yu
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Engineering Research Center of Agricultural Internet of Things, Beijing, China
| | - Cuixia Mu
- College of Data Science and Information Technology, China Women’s University, Beijing, China
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Canavese D, Mannella L, Regano L, Basile C. Security at the Edge for Resource-Limited IoT Devices. Sensors (Basel) 2024; 24:590. [PMID: 38257680 PMCID: PMC10818527 DOI: 10.3390/s24020590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 01/08/2024] [Accepted: 01/12/2024] [Indexed: 01/24/2024]
Abstract
The Internet of Things (IoT) is rapidly growing, with an estimated 14.4 billion active endpoints in 2022 and a forecast of approximately 30 billion connected devices by 2027. This proliferation of IoT devices has come with significant security challenges, including intrinsic security vulnerabilities, limited computing power, and the absence of timely security updates. Attacks leveraging such shortcomings could lead to severe consequences, including data breaches and potential disruptions to critical infrastructures. In response to these challenges, this research paper presents the IoT Proxy, a modular component designed to create a more resilient and secure IoT environment, especially in resource-limited scenarios. The core idea behind the IoT Proxy is to externalize security-related aspects of IoT devices by channeling their traffic through a secure network gateway equipped with different Virtual Network Security Functions (VNSFs). Our solution includes a Virtual Private Network (VPN) terminator and an Intrusion Prevention System (IPS) that uses a machine learning-based technique called oblivious authentication to identify connected devices. The IoT Proxy's modular, scalable, and externalized security approach creates a more resilient and secure IoT environment, especially for resource-limited IoT devices. The promising experimental results from laboratory testing demonstrate the suitability of IoT Proxy to secure real-world IoT ecosystems.
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Affiliation(s)
- Daniele Canavese
- IRIT, CNRS, 118 Route de Narbonne, CEDEX 9, F-31062 Toulouse, France
| | - Luca Mannella
- Dipartimento di Automatica e Informatica, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy
| | - Leonardo Regano
- Dipartimento di Ingegneria Elettrica ed Elettronica, Università degli Studi di Cagliari, Piazza d’Armi, 09123 Cagliari, Italy
| | - Cataldo Basile
- Dipartimento di Automatica e Informatica, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy
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Gao H, Lu Y, Yang S, Tan J, Nie L, Qu X. Energy Consumption Analysis for Continuous Phase Modulation in Smart-Grid Internet of Things of beyond 5G. Sensors (Basel) 2024; 24:533. [PMID: 38257627 PMCID: PMC10819143 DOI: 10.3390/s24020533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 01/24/2024]
Abstract
Wireless sensor network (WSN) underpinning the smart-grid Internet of Things (SG-IoT) has been a popular research topic in recent years due to its great potential for enabling a wide range of important applications. However, the energy consumption (EC) characteristic of sensor nodes is a key factor that affects the operational performance (e.g., lifetime of sensors) and the total cost of ownership of WSNs. In this paper, to find the modulation techniques suitable for WSNs, we investigate the EC characteristic of continuous phase modulation (CPM), which is an attractive modulation scheme candidate for WSNs because of its constant envelope property. We first develop an EC model for the sensor nodes of WSNs by considering the circuits and a typical communication protocol that relies on automatic repeat request (ARQ)-based retransmissions to ensure successful data delivery. Then, we use this model to analyze the EC characteristic of CPM under various configurations of modulation parameters. Furthermore, we compare the EC characteristic of CPM with that of other representative modulation schemes, such as offset quadrature phase-shift keying (OQPSK) and quadrature amplitude modulation (QAM), which are commonly used in communication protocols of WSNs. Our analysis and simulation results provide insights into the EC characteristics of multiple modulation schemes in the context of WSNs; thus, they are beneficial for designing energy-efficient SG-IoT in the beyond-5G (B5G) and the 6G era.
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Affiliation(s)
- Hongjian Gao
- State Grid Smart Grid Research Institute Co., Ltd., Beijing 102209, China; (H.G.)
| | - Yang Lu
- State Grid Smart Grid Research Institute Co., Ltd., Beijing 102209, China; (H.G.)
| | - Shaoshi Yang
- School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
- Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing 100876, China
| | - Jingsheng Tan
- School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
- Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing 100876, China
| | - Longlong Nie
- School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
- Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing 100876, China
| | - Xinyi Qu
- School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
- Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing 100876, China
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12
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Suriasni PA, Faizal F, Hermawan W, Subhan U, Panatarani C, Joni IM. IoT Water Quality Monitoring and Control System in Moving Bed Biofilm Reactor to Reduce Total Ammonia Nitrogen. Sensors (Basel) 2024; 24:494. [PMID: 38257587 PMCID: PMC10819107 DOI: 10.3390/s24020494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 12/31/2023] [Accepted: 01/09/2024] [Indexed: 01/24/2024]
Abstract
Traditional aquaculture systems appear challenged by the high levels of total ammoniacal nitrogen (TAN) produced, which can harm aquatic life. As demand for global fish production continues to increase, farmers should adopt recirculating aquaculture systems (RAS) equipped with biofilters to improve the water quality of the culture. The biofilter plays a crucial role in ammonia removal. Therefore, a biofilter such as a moving bed biofilm reactor (MBBR) biofilter is usually used in the RAS to reduce ammonia. However, the disadvantage of biofilter operation is that it requires an automatic system with a water quality monitoring and control system to ensure optimal performance. Therefore, this study focuses on developing an Internet of Things (IoT) system to monitor and control water quality to achieve optimal biofilm performance in laboratory-scale MBBR. From 35 days into the experiment, water quality was maintained by an aerator's on/off control to provide oxygen levels suitable for the aquatic environment while monitoring the pH, temperature, and total dissolved solids (TDS). When the amount of dissolved oxygen (DO) in the MBBR was optimal, the highest TAN removal efficiency was 50%, with the biofilm thickness reaching 119.88 μm. The forthcoming applications of the IoT water quality monitoring and control system in MBBR enable farmers to set up a system in RAS that can perform real-time measurements, alerts, and adjustments of critical water quality parameters such as TAN levels.
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Affiliation(s)
- Putu A. Suriasni
- Department of Physics, Faculty of Mathematics and Natural Science, Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia; (P.A.S.); (F.F.); (C.P.)
| | - Ferry Faizal
- Department of Physics, Faculty of Mathematics and Natural Science, Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia; (P.A.S.); (F.F.); (C.P.)
- Functional Nano Powder University Center of Excellence (FiNder U-CoE), Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia; (W.H.); (U.S.)
| | - Wawan Hermawan
- Functional Nano Powder University Center of Excellence (FiNder U-CoE), Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia; (W.H.); (U.S.)
- Department of Biology, Faculty of Mathematics and Natural Science, Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia
| | - Ujang Subhan
- Functional Nano Powder University Center of Excellence (FiNder U-CoE), Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia; (W.H.); (U.S.)
- Department of Fisheries, Faculty of Fisheries and Marine Science, Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Jatinangor, Sumedang 45363, West Java, Indonesia
| | - Camellia Panatarani
- Department of Physics, Faculty of Mathematics and Natural Science, Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia; (P.A.S.); (F.F.); (C.P.)
- Functional Nano Powder University Center of Excellence (FiNder U-CoE), Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia; (W.H.); (U.S.)
| | - I Made Joni
- Department of Physics, Faculty of Mathematics and Natural Science, Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia; (P.A.S.); (F.F.); (C.P.)
- Functional Nano Powder University Center of Excellence (FiNder U-CoE), Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia; (W.H.); (U.S.)
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Wang N, Liu Y, Feng Y, Yang J, Wu Y, Zhang B, Li Y, Li B, Wang S, Ye E, Zhang YW, Loh XJ, Zhou F, Li Z, Wang D. Revamping Triboelectric Output by Deep Trap Construction. Adv Mater 2023:e2303389. [PMID: 38153227 DOI: 10.1002/adma.202303389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 11/16/2023] [Indexed: 12/29/2023]
Abstract
High output performance is critical for building triboelectric nanogenerators (TENGs) for future multifunctional applications. Unfortunately, the high triboelectric charge dissipation rate has a significant negative impact on its electrical output performance. Herein, a new tribolayer is designed through introducing self-assembled molecules with large energy gaps on commercial PET fibric to form carrier deep traps, which improve charge retention while decreasing dissipation rates. The deep trap density of the PET increases by two orders of magnitude, resulting in an 86% reduction in the rate of charge dissipation and a significant increase in the charge density that can be accumulated on tribolayer during physical contact. The key explanation is that increasing the density of deep traps improves the dielectric's ability to store charges, making it more difficult for the triboelectric charges trapped by the tribolayer to escape from the deep traps, lowering the rate of charge dissipation. This TENG has a 1300% increase in output power density as a result of altering the deep trap density, demonstrating a significant improvement. This work describes a simple yet efficient method for building TENGs with ultra-high electrical output and promotes their practical implementation in the sphere of the Internet of Things.
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Affiliation(s)
- Nannan Wang
- State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou, 730000, China
- Institute of Sustainability for Chemicals, Energy, and Environment (ISCE2), Agency for Science, Technology and Research (A*STAR), 1 Pesek Road, Jurong Island, Singapore, 627833, Republic of Singapore
| | - Yizhe Liu
- State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou, 730000, China
- Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai, Yantai, 265503, China
| | - Yange Feng
- State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou, 730000, China
- Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai, Yantai, 265503, China
| | - Jing Yang
- Institute of High-Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore, 138632, Republic of Singapore
| | - Yaze Wu
- Institute of High-Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore, 138632, Republic of Singapore
| | - Boya Zhang
- State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Yixuan Li
- State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Bofan Li
- Institute of Sustainability for Chemicals, Energy, and Environment (ISCE2), Agency for Science, Technology and Research (A*STAR), 1 Pesek Road, Jurong Island, Singapore, 627833, Republic of Singapore
| | - Sheng Wang
- Institute of Sustainability for Chemicals, Energy, and Environment (ISCE2), Agency for Science, Technology and Research (A*STAR), 1 Pesek Road, Jurong Island, Singapore, 627833, Republic of Singapore
| | - Enyi Ye
- Institute of Sustainability for Chemicals, Energy, and Environment (ISCE2), Agency for Science, Technology and Research (A*STAR), 1 Pesek Road, Jurong Island, Singapore, 627833, Republic of Singapore
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore, 138634, Republic of Singapore
| | - Yong-Wei Zhang
- Institute of High-Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore, 138632, Republic of Singapore
| | - Xian Jun Loh
- Institute of Sustainability for Chemicals, Energy, and Environment (ISCE2), Agency for Science, Technology and Research (A*STAR), 1 Pesek Road, Jurong Island, Singapore, 627833, Republic of Singapore
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore, 138634, Republic of Singapore
| | - Feng Zhou
- State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Zibiao Li
- Institute of Sustainability for Chemicals, Energy, and Environment (ISCE2), Agency for Science, Technology and Research (A*STAR), 1 Pesek Road, Jurong Island, Singapore, 627833, Republic of Singapore
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Innovis #08-03, Singapore, 138634, Republic of Singapore
- Department of Materials Science and Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore, 117576, Singapore
| | - Daoai Wang
- State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou, 730000, China
- Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai, Yantai, 265503, China
- Qingdao Center of Resource Chemistry and New Materials, Qingdao, 266100, China
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Blanco-Carmona P, Baeza-Moreno L, Hidalgo-Fort E, Martín-Clemente R, González-Carvajal R, Muñoz-Chavero F. AIoT in Agriculture: Safeguarding Crops from Pest and Disease Threats. Sensors (Basel) 2023; 23:9733. [PMID: 38139579 PMCID: PMC10747752 DOI: 10.3390/s23249733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/05/2023] [Accepted: 12/06/2023] [Indexed: 12/24/2023]
Abstract
A significant proportion of the world's agricultural production is lost to pests and diseases. To mitigate this problem, an AIoT system for the early detection of pest and disease risks in crops is proposed. It presents a system based on low-power and low-cost sensor nodes that collect environmental data and transmit it once a day to a server via a NB-IoT network. In addition, the sensor nodes use individual, retrainable and updatable machine learning algorithms to assess the risk level in the crop every 30 min. If a risk is detected, environmental data and the risk level are immediately sent. Additionally, the system enables two types of notification: email and flashing LED, providing online and offline risk notifications. As a result, the system was deployed in a real-world environment and the power consumption of the sensor nodes was characterized, validating their longevity and the correct functioning of the risk detection algorithms. This allows the farmer to know the status of their crop and to take early action to address these threats.
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Affiliation(s)
- Pedro Blanco-Carmona
- Department of Electronic Engineering, University of Seville, 41092 Seville, Spain; (P.B.-C.); (L.B.-M.); (R.G.-C.); (F.M.-C.)
| | - Lucía Baeza-Moreno
- Department of Electronic Engineering, University of Seville, 41092 Seville, Spain; (P.B.-C.); (L.B.-M.); (R.G.-C.); (F.M.-C.)
| | - Eduardo Hidalgo-Fort
- Department of Electronic Engineering, University of Seville, 41092 Seville, Spain; (P.B.-C.); (L.B.-M.); (R.G.-C.); (F.M.-C.)
| | - Rubén Martín-Clemente
- Department of Signal Processing and Communications, University of Seville, 41092 Seville, Spain;
| | - Ramón González-Carvajal
- Department of Electronic Engineering, University of Seville, 41092 Seville, Spain; (P.B.-C.); (L.B.-M.); (R.G.-C.); (F.M.-C.)
| | - Fernando Muñoz-Chavero
- Department of Electronic Engineering, University of Seville, 41092 Seville, Spain; (P.B.-C.); (L.B.-M.); (R.G.-C.); (F.M.-C.)
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15
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Elfaki AO, Messoudi W, Bushnag A, Abuzneid S, Alhmiedat T. A Smart Real-Time Parking Control and Monitoring System. Sensors (Basel) 2023; 23:9741. [PMID: 38139588 PMCID: PMC10747061 DOI: 10.3390/s23249741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 11/12/2023] [Accepted: 12/02/2023] [Indexed: 12/24/2023]
Abstract
Smart parking is an artificial intelligence-based solution to solve the challenges of inefficient utilization of parking slots, wasting time, congestion producing high CO2 emission levels, inflexible payment methods, and protecting parked vehicles from theft and vandalism. Nothing is worse than parking congestion caused by drivers looking for open spaces. This is common in large parking lots, underground garages, and multi-story car parks, where visibility is limited and signage can be confusing or difficult to read, so drivers have no idea where available parking spaces are. In this paper, a smart real-time parking management system has been introduced. The developed system can deal with the aforementioned challenges by providing dynamic allocation for parking slots while taking into consideration the overall parking situation, providing a mechanism for booking a specific parking slot by using our Artificial Intelligence (AI)-based application, and providing a mechanism to ensure that the car is parked in its correct place. For the sake of providing cost flexibility, we have provided two technical solutions with cost varying. The first solution is developed based on a motion sensor and the second solution is based on a range-finder sensor. A plate detection and recognition system has been used to detect the vehicle's license plate by capturing the image using an IoT device. The system will recognize the extracted English alphabet and Hindu-Arabic Numerals. The proposed solution was built and field-tested to prove the applicability of the proposed smart parking solution. We have measured and analyzed keen data such as vehicle plate detection accuracy, vehicle plate recognition accuracy, transmission delay time, and processing delay time.
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Affiliation(s)
- Abdelrahman Osman Elfaki
- Faculty of Computers & Information Technology, University of Tabuk, Tabuk 47512, Saudi Arabia; (W.M.); (A.B.)
| | - Wassim Messoudi
- Faculty of Computers & Information Technology, University of Tabuk, Tabuk 47512, Saudi Arabia; (W.M.); (A.B.)
| | - Anas Bushnag
- Faculty of Computers & Information Technology, University of Tabuk, Tabuk 47512, Saudi Arabia; (W.M.); (A.B.)
| | - Shakour Abuzneid
- Department of Cybersecurity and Network, School of Criminal Justice Studies, Roger Williams University, Bristol, RI 02809, USA;
| | - Tareq Alhmiedat
- Faculty of Computers & Information Technology, University of Tabuk, Tabuk 47512, Saudi Arabia; (W.M.); (A.B.)
- Artificial Intelligence and Sensing Technologies (AIST) Center, University of Tabuk, Tabuk 47512, Saudi Arabia
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16
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Gómez-Marín E, Parrilla L, Tejero López JL, Morales DP, Castillo E. Toward Sensor Measurement Reliability in Blockchains. Sensors (Basel) 2023; 23:9659. [PMID: 38139505 PMCID: PMC10747797 DOI: 10.3390/s23249659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 11/30/2023] [Accepted: 12/04/2023] [Indexed: 12/24/2023]
Abstract
In this work, a secure architecture to send data from an Internet of Things (IoT) device to a blockchain-based supply chain is presented. As is well known, blockchains can process critical information with high security, but the authenticity and accuracy of the stored and processed information depend primarily on the reliability of the information sources. When this information requires acquisition from uncontrolled environments, as is the normal situation in the real world, it may be, intentionally or unintentionally, erroneous. The entities that provide this external information, called Oracles, are critical to guarantee the quality and veracity of the information generated by them, thus affecting the subsequent blockchain-based applications. In the case of IoT devices, there are no effective single solutions in the literature for achieving a secure implementation of an Oracle that is capable of sending data generated by a sensor to a blockchain. In order to fill this gap, in this paper, we present a holistic solution that enables blockchains to verify a set of security requirements in order to accept information from an IoT Oracle. The proposed solution uses Hardware Security Modules (HSMs) to address the security requirements of integrity and device trustworthiness, as well as a novel Public Key Infrastructure (PKI) based on a blockchain for authenticity, traceability, and data freshness. The solution is then implemented on Ethereum and evaluated regarding the fulfillment of the security requirements and time response. The final design has some flexibility limitations that will be approached in future work.
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Affiliation(s)
- Ernesto Gómez-Marín
- Infineon Technologies AG, 85579 Neubiberg, Germany;
- Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain; (J.L.T.L.); (D.P.M.); (E.C.)
| | - Luis Parrilla
- Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain; (J.L.T.L.); (D.P.M.); (E.C.)
| | - Jose L. Tejero López
- Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain; (J.L.T.L.); (D.P.M.); (E.C.)
| | - Diego P. Morales
- Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain; (J.L.T.L.); (D.P.M.); (E.C.)
| | - Encarnación Castillo
- Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, 18071 Granada, Spain; (J.L.T.L.); (D.P.M.); (E.C.)
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17
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Arepalli PG, Naik KJ. An IoT-based water contamination analysis for aquaculture using lightweight multi-headed GRU model. Environ Monit Assess 2023; 195:1516. [PMID: 37991560 DOI: 10.1007/s10661-023-12126-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 11/10/2023] [Indexed: 11/23/2023]
Abstract
Maintaining the quality of water is essential for the health and productivity of aquatic organisms, including fish in aquaculture ponds. However, water contamination can severely impact fish health and survival, making it necessary to develop monitoring systems that can detect early signs of water contamination. Initial deep learning models had limitations in capturing the temporal and spatial dependencies of time-series data, which can lead to inaccurate predictions. In this paper, we propose a smart monitoring system that uses IoT devices to collect water quality data and segment it into contaminated and non-contaminated categories based on a water toxic index (WTI), a measure of water contamination levels. To address the limitations of early deep learning models for classification of toxic and non-toxic water quality, an enhanced light-weight multi-headed gated recurrent unit (MHGRU) model that captures the spatial and temporal dependencies of water quality parameters. Our study demonstrates that the proposed model outperforms existing models, achieving an impressive accuracy of 99.7% when evaluated on real-time data. Notably, our model also excels when tested on a public dataset, achieving an accuracy of 99.12%. In comparison, best performed existing ANN models achieve accuracies of 99.52% and 98.71% on the respective datasets.
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Affiliation(s)
- Peda Gopi Arepalli
- Department of Computer Science & Engineering, National Institute of Technology Raipur, Raipur, India.
| | - K Jairam Naik
- Department of Computer Science & Engineering, National Institute of Technology Raipur, Raipur, India
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18
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Frank F, Böttger S, Mexis N, Anagnostopoulos NA, Mohamed A, Hartmann M, Kuhn H, Helke C, Arul T, Katzenbeisser S, Hermann S. CNT-PUFs: Highly Robust and Heat-Tolerant Carbon-Nanotube-Based Physical Unclonable Functions. Nanomaterials (Basel) 2023; 13:2930. [PMID: 37999284 PMCID: PMC10674552 DOI: 10.3390/nano13222930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 10/27/2023] [Accepted: 11/03/2023] [Indexed: 11/25/2023]
Abstract
In this work, we explored a highly robust and unique Physical Unclonable Function (PUF) based on the stochastic assembly of single-walled Carbon NanoTubes (CNTs) integrated within a wafer-level technology. Our work demonstrated that the proposed CNT-based PUFs are exceptionally robust with an average fractional intra-device Hamming distance well below 0.01 both at room temperature and under varying temperatures in the range from 23 ∘C to 120 ∘C. We attributed the excellent heat tolerance to comparatively low activation energies of less than 40 meV extracted from an Arrhenius plot. As the number of unstable bits in the examined implementation is extremely low, our devices allow for a lightweight and simple error correction, just by selecting stable cells, thereby diminishing the need for complex error correction. Through a significant number of tests, we demonstrated the capability of novel nanomaterial devices to serve as highly efficient hardware security primitives.
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Affiliation(s)
- Florian Frank
- Faculty of Computer Science and Mathematics, University of Passau, Innstraße 43, 94032 Passau, Germany; (F.F.); (N.M.); (N.A.A.); (T.A.)
| | - Simon Böttger
- Center for Microtechnologies, Chemnitz University of Technology, Reichenhainer Str. 70, 09126 Chemnitz, Germany; (S.B.); (A.M.); (M.H.); (H.K.); (C.H.)
- Center for Materials, Architectures and Integration of Nanomembranes (MAIN), Chemnitz University of Technology, 09107 Chemnitz, Germany
| | - Nico Mexis
- Faculty of Computer Science and Mathematics, University of Passau, Innstraße 43, 94032 Passau, Germany; (F.F.); (N.M.); (N.A.A.); (T.A.)
| | | | - Ali Mohamed
- Center for Microtechnologies, Chemnitz University of Technology, Reichenhainer Str. 70, 09126 Chemnitz, Germany; (S.B.); (A.M.); (M.H.); (H.K.); (C.H.)
| | - Martin Hartmann
- Center for Microtechnologies, Chemnitz University of Technology, Reichenhainer Str. 70, 09126 Chemnitz, Germany; (S.B.); (A.M.); (M.H.); (H.K.); (C.H.)
- Center for Materials, Architectures and Integration of Nanomembranes (MAIN), Chemnitz University of Technology, 09107 Chemnitz, Germany
| | - Harald Kuhn
- Center for Microtechnologies, Chemnitz University of Technology, Reichenhainer Str. 70, 09126 Chemnitz, Germany; (S.B.); (A.M.); (M.H.); (H.K.); (C.H.)
- Fraunhofer Institute for Electronic Nano Systems (ENAS), Technologie-Campus 3, 09126 Chemnitz, Germany
| | - Christian Helke
- Center for Microtechnologies, Chemnitz University of Technology, Reichenhainer Str. 70, 09126 Chemnitz, Germany; (S.B.); (A.M.); (M.H.); (H.K.); (C.H.)
- Fraunhofer Institute for Electronic Nano Systems (ENAS), Technologie-Campus 3, 09126 Chemnitz, Germany
| | - Tolga Arul
- Faculty of Computer Science and Mathematics, University of Passau, Innstraße 43, 94032 Passau, Germany; (F.F.); (N.M.); (N.A.A.); (T.A.)
- Computer Science Department, Technical University of Darmstadt, Hochschulstraße 10, 64289 Darmstadt, Germany
| | - Stefan Katzenbeisser
- Center for Microtechnologies, Chemnitz University of Technology, Reichenhainer Str. 70, 09126 Chemnitz, Germany; (S.B.); (A.M.); (M.H.); (H.K.); (C.H.)
| | - Sascha Hermann
- Center for Microtechnologies, Chemnitz University of Technology, Reichenhainer Str. 70, 09126 Chemnitz, Germany; (S.B.); (A.M.); (M.H.); (H.K.); (C.H.)
- Center for Materials, Architectures and Integration of Nanomembranes (MAIN), Chemnitz University of Technology, 09107 Chemnitz, Germany
- Center for Advancing Electronics Dresden (CFAED), 01062 Dresden, Germany
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Singh AK, Mahto SK, Sinha R, Alibakhshikenari M, Al-Gburi AJA, Ahmad A, Kouhalvandi L, Virdee BS, Dalarsson M. Low-Loss Paper-Substrate Triple-Band-Frequency Reconfigurable Microstrip Antenna for Sub-7 GHz Applications. Sensors (Basel) 2023; 23:8996. [PMID: 37960695 PMCID: PMC10648291 DOI: 10.3390/s23218996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/31/2023] [Accepted: 11/01/2023] [Indexed: 11/15/2023]
Abstract
In this paper, a low-cost resin-coated commercial-photo-paper substrate is used to design a printed reconfigurable multiband antenna. The two PIN diodes are used mainly to redistribute the surface current that provides reconfigurable properties to the proposed antenna. The antenna size of 40 mm × 40 mm × 0.44 mm with a partial ground, covers wireless and mobile bands ranging from 1.91 GHz to 6.75 GHz. The parametric analysis is performed to achieve optimized design parameters of the antenna. The U-shaped and C-shaped emitters are meant to function at 2.4 GHz and 5.9 GHz, respectively, while the primary emitter is designed to operate at 3.5 GHz. The proposed antenna achieved peak gain and radiation efficiency of 3.4 dBi and 90%, respectively. Simulated and measured results of the reflection coefficient, radiation pattern, gain, and efficiency show that the antenna design is in favorable agreement. Since the proposed antenna achieved wideband (1.91-6.75 GHz) using PIN diode configuration, using this technique the need for numerous electronic components to provide multiband frequency is avoided.
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Affiliation(s)
- Ajit Kumar Singh
- Indian Institute of Information Technology, Ranchi 834010, India
| | | | - Rashmi Sinha
- National Institute of Technology, Jamshedpur 831014, India
| | - Mohammad Alibakhshikenari
- Department of Signal Theory and Communications, Universidad Carlos III de Madrid, 28911 Leganés, Madrid, Spain
| | - Ahmed Jamal Abdullah Al-Gburi
- Center for Telecommunication Research & Innovation (CeTRI), Fakulti Teknologi dan Kejuruteraan Elektronik dan Komputer (FTKEK), Universiti Teknikal Malaysia Melaka (UTeM), Ayer Keroh 75450, Malaysia
| | - Ashfaq Ahmad
- Chemistry Department, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
| | - Lida Kouhalvandi
- Department of Electrical and Electronics Engineering, Dogus University, Istanbul 34775, Turkey
| | - Bal S. Virdee
- Center for Communications Technology, London Metropolitan University, London N7 8DB, UK
| | - Mariana Dalarsson
- Department of Electrical Engineering, School of Electrical Engineering and Computer Science, KTH Royal Institiute of Technology, 100 44 Stockholm, Sweden
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20
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Younas MI, Iqbal MJ, Aziz A, Sodhro AH. Toward QoS Monitoring in IoT Edge Devices Driven Healthcare-A Systematic Literature Review. Sensors (Basel) 2023; 23:8885. [PMID: 37960584 PMCID: PMC10650388 DOI: 10.3390/s23218885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 10/20/2023] [Accepted: 10/26/2023] [Indexed: 11/15/2023]
Abstract
Smart healthcare is altering the delivery of healthcare by combining the benefits of IoT, mobile, and cloud computing. Cloud computing has tremendously helped the health industry connect healthcare facilities, caregivers, and patients for information sharing. The main drivers for implementing effective healthcare systems are low latency and faster response times. Thus, quick responses among healthcare organizations are important in general, but in an emergency, significant latency at different stakeholders might result in disastrous situations. Thus, cutting-edge approaches like edge computing and artificial intelligence (AI) can deal with such problems. A packet cannot be sent from one location to another unless the "quality of service" (QoS) specifications are met. The term QoS refers to how well a service works for users. QoS parameters like throughput, bandwidth, transmission delay, availability, jitter, latency, and packet loss are crucial in this regard. Our focus is on the individual devices present at different levels of the smart healthcare infrastructure and the QoS requirements of the healthcare system as a whole. The contribution of this paper is five-fold: first, a novel pre-SLR method for comprehensive keyword research on subject-related themes for mining pertinent research papers for quality SLR; second, SLR on QoS improvement in smart healthcare apps; third a review of several QoS techniques used in current smart healthcare apps; fourth, the examination of the most important QoS measures in contemporary smart healthcare apps; fifth, offering solutions to the problems encountered in delivering QoS in smart healthcare IoT applications to improve healthcare services.
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Affiliation(s)
- Muhammad Irfan Younas
- Department of Computer System Engineering, Sukkur IBA University, Sukkur 65200, Pakistan;
- Institute of Space Science and Technology, University of Karachi, Karachi 75270, Pakistan;
| | - Muhammad Jawed Iqbal
- Institute of Space Science and Technology, University of Karachi, Karachi 75270, Pakistan;
| | - Abdul Aziz
- Department of Electrical Engineering, Sukkur IBA University, Sukkur 65200, Pakistan;
| | - Ali Hassan Sodhro
- Department of Computer Science, Kristianstad University, 29188 Kristianstad, Sweden
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21
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Medvedev A, Hassani A, Belov G, Weerasinghe S, Huang GL, Zaslavsky A, Loke SW, Jayaraman PP. Refresh Rate-Based Caching and Prefetching Strategies for Internet of Things Middleware. Sensors (Basel) 2023; 23:8779. [PMID: 37960478 PMCID: PMC10649153 DOI: 10.3390/s23218779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 10/23/2023] [Accepted: 10/25/2023] [Indexed: 11/15/2023]
Abstract
One of the research directions in Internet of Things (IoT) is the field of Context Management Platforms (CMPs) which is a specific type of IoT middleware. CMPs provide horizontal connectivity between vertically oriented IoT silos resulting in a noticeable difference in how IoT data streams are processed. As these context data exchanges can be monetised, there is a need to model and predict the context metrics and operational costs of this exchange to provide relevant and timely context in a large-scale IoT ecosystem. In this paper, we argue that caching all transient context information to satisfy this necessity requires large amounts of computational and network resources, resulting in tremendous operational costs. Using Service Level Agreements (SLAs) between the context providers, CMP, and context consumers, where the level of service imperfection is quantified and linked to the associated costs, we show that it is possible to find efficient caching and prefetching strategies to minimize the context management cost. So, this paper proposes a novel method to find the optimal rate of IoT data prefetching and caching. We show the main context caching strategies and the proposed mathematical models, then discuss how a correctly chosen proactive caching strategy and configurations can help to maximise the profit of CMP operation when multiple SLAs are defined. Our model is accurate up to 0.0016 in Root Mean Square Percentage Error against our simulation results when estimating the profits to the system. We also show our model is valid using the t-test value tending to 0 for all the experimental scenarios.
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Affiliation(s)
- Alexey Medvedev
- School of Information Technology, Deakin University, Geelong, VIC 3145, Australia; (A.M.); (A.H.); (G.-L.H.); (A.Z.); (S.W.L.)
| | - Alireza Hassani
- School of Information Technology, Deakin University, Geelong, VIC 3145, Australia; (A.M.); (A.H.); (G.-L.H.); (A.Z.); (S.W.L.)
| | - Gleb Belov
- Faculty of Information Technology, Monash University, Clayton, VIC 3168, Australia;
| | - Shakthi Weerasinghe
- School of Information Technology, Deakin University, Geelong, VIC 3145, Australia; (A.M.); (A.H.); (G.-L.H.); (A.Z.); (S.W.L.)
| | - Guang-Li Huang
- School of Information Technology, Deakin University, Geelong, VIC 3145, Australia; (A.M.); (A.H.); (G.-L.H.); (A.Z.); (S.W.L.)
| | - Arkady Zaslavsky
- School of Information Technology, Deakin University, Geelong, VIC 3145, Australia; (A.M.); (A.H.); (G.-L.H.); (A.Z.); (S.W.L.)
| | - Seng W. Loke
- School of Information Technology, Deakin University, Geelong, VIC 3145, Australia; (A.M.); (A.H.); (G.-L.H.); (A.Z.); (S.W.L.)
| | - Prem Prakash Jayaraman
- School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC 3122, Australia;
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22
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Lin YW, Lin YB, Chang TCY, Lu BX. An Edge Transfer Learning Approach for Calibrating Soil Electrical Conductivity Sensors. Sensors (Basel) 2023; 23:8710. [PMID: 37960410 PMCID: PMC10647256 DOI: 10.3390/s23218710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 10/18/2023] [Accepted: 10/23/2023] [Indexed: 11/15/2023]
Abstract
Smart agriculture utilizes Internet of Things (IoT) technologies to enable low-cost electrical conductivity (EC) sensors to support farming intelligence. Due to aging and changes in weather and soil conditions, EC sensors are prone to long-term drift over years of operation. Therefore, regular recalibration is necessary to ensure data accuracy. In most existing solutions, an EC sensor is calibrated by using the standard sensor to build the calibration table. This paper proposes SensorTalk3, an ensemble approach of machine learning models including XGBOOST and Random Forest, which can be executed at an edge device (e.g., Raspberry Pi) without GPU acceleration. Our study indicates that the soil information (both temperature and moisture sensor data) plays an important role in SensorTalk3, which significantly outperforms the existing calibration approaches. The MAPE of SensorTalk3 can be as low as 1.738%, compared to the 7.792% error of the original sensor. Our study indicates that when the errors of uncalibrated moisture and temperature sensors are not larger than 8.3%, SensorTalk3 can accurately calibrate EC. SensorTalk3 can perform model training during data collection at the edge node. When all training data are collected, AI training is also finished at the edge node. Such an AI training approach has not been found in existing edge AI approaches. We also proposed the dual-sensor detection solution to determine when to conduct recalibration. The overhead of this solution is less than twice the optimal detection scenario (which cannot be achieved practically). If the two non-standard sensors are homogeneous and stable, then the optimal detection scenario can be approached. Conventional methods require training calibration AI models in the cloud. However, SensorTalk3 introduces a significant advancement by enabling on-site transfer learning in the edge node. Given the abundance of farming sensors deployed in the fields, performing local transfer learning using low-cost edge nodes proves to be a more cost-effective solution for farmers.
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Affiliation(s)
- Yun-Wei Lin
- College of Artificial Intelligence, National Yang Ming Chiao Tung University, Tainan 711, Taiwan;
| | - Yi-Bing Lin
- College of Artificial Intelligence, National Yang Ming Chiao Tung University, Tainan 711, Taiwan;
- College of Humanities and Sciences, China Medical University, Taichung 406, Taiwan
- Miin Wu School of Computing, National Cheng Kung University, Tainan 701, Taiwan
- College of Computer Science, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan
- Department of Computer Science and Information Engineering, Asia University, Taichung 413, Taiwan
- Research Center for Information Technology Innovation, Academia Sinica, Taipei 115, Taiwan
| | | | - Bo-Xun Lu
- College of Artificial Intelligence, National Yang Ming Chiao Tung University, Tainan 711, Taiwan;
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23
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El-Shafeiy E, Alsabaan M, Ibrahem MI, Elwahsh H. Real-Time Anomaly Detection for Water Quality Sensor Monitoring Based on Multivariate Deep Learning Technique. Sensors (Basel) 2023; 23:8613. [PMID: 37896705 PMCID: PMC10610887 DOI: 10.3390/s23208613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 10/08/2023] [Accepted: 10/18/2023] [Indexed: 10/29/2023]
Abstract
With the increased use of automated systems, the Internet of Things (IoT), and sensors for real-time water quality monitoring, there is a greater requirement for the timely detection of unexpected values. Technical faults can introduce anomalies, and a large incoming data rate might make the manual detection of erroneous data difficult. This research introduces and applies a pioneering technology, Multivariate Multiple Convolutional Networks with Long Short-Term Memory (MCN-LSTM), to real-time water quality monitoring. MCN-LSTM is a cutting-edge deep learning technology designed to address the difficulty of detecting anomalies in complicated time series data, particularly in monitoring water quality in a real-world setting. The growing reliance on automated systems, the Internet of Things (IoT), and sensor networks for continuous water quality monitoring is driving the development and deployment of the MCN-LSTM approach. As these technologies become more widely used, the rapid and precise identification of unexpected or aberrant data points becomes critical. Technical difficulties, inherent noise, and a high data influx pose significant hurdles to manual anomaly detection processes. The MCN-LSTM technique takes advantage of deep learning by integrating Multiple Convolutional Networks and Long Short-Term Memory networks. This combination of approaches offers efficient and effective anomaly detection in multivariate time series data, allowing for identifying and flagging unexpected patterns or values that may signal water quality issues. Water quality data anomalies can have far-reaching repercussions, influencing future analyses and leading to incorrect judgments. Anomaly identification must be precise to avoid inaccurate findings and ensure the integrity of water quality tests. Extensive tests were carried out to validate the MCN-LSTM technique utilizing real-world information obtained from sensors installed in water quality monitoring scenarios. The results of these studies proved MCN-LSTM's outstanding efficacy, with an impressive accuracy rate of 92.3%. This high level of precision demonstrates the technique's capacity to discriminate between normal and abnormal data instances in real time. The MCN-LSTM technique is a big step forward in water quality monitoring. It can improve decision-making processes and reduce adverse outcomes caused by undetected abnormalities. This unique technique has significant promise for defending human health and maintaining the environment in an era of increased reliance on automated monitoring systems and IoT technology by contributing to the safety and sustainability of water supplies.
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Affiliation(s)
- Engy El-Shafeiy
- Department of Computer Science, Faculty of Computers and Artificial Intelligence, University of Sadat City, Sadat City 32897, Monufia, Egypt;
| | - Maazen Alsabaan
- Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia;
| | - Mohamed I. Ibrahem
- School of Computer and Cyber Sciences, Augusta University, Augusta, GA 30912, USA;
- Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo 11672, Egypt
| | - Haitham Elwahsh
- Computer Science Department, Faculty of Computers and Information, Kafrelsheikh University, Kafrelsheikh 33516, Egypt
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24
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Chen SL, Chou HS, Huang CH, Chen CY, Li LY, Huang CH, Chen YY, Tang JH, Chang WH, Huang JS. An Intelligent Water Monitoring IoT System for Ecological Environment and Smart Cities. Sensors (Basel) 2023; 23:8540. [PMID: 37896631 PMCID: PMC10611331 DOI: 10.3390/s23208540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/06/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023]
Abstract
Global precipitation is becoming increasingly intense due to the extreme climate. Therefore, creating new technology to manage water resources is crucial. To create a sustainable urban and ecological environment, a water level and water quality control system implementing artificial intelligence is presented in this research. The proposed smart monitoring system consists of four sensors (two different liquid level sensors, a turbidity and pH sensor, and a water oxygen sensor), a control module (an MCU, a motor, a pump, and a drain), and a power and communication system (a solar panel, a battery, and a wireless communication module). The system focuses on low-cost Internet of Things (IoT) devices along with low power consumption and high precision. This proposal collects rainfall from the preceding 10 years in the application region as well as the region's meteorological bureau's weekly weather report and uses artificial intelligence to compute the appropriate water level. More importantly, the adoption of dynamic adjustment systems can reserve and modify water resources in the application region more efficiently. Compared to existing technologies, the measurement approach utilized in this study not only achieves cost savings exceeding 60% but also enhances water level measurement accuracy by over 15% through the successful implementation of water level calibration decisions utilizing multiple distinct sensors. Of greater significance, the dynamic adjustment systems proposed in this research offer the potential for conserving water resources by more than 15% in an effective manner. As a result, the adoption of this technology may efficiently reserve and distribute water resources for smart cities as well as reduce substantial losses caused by anomalous water resources, such as floods, droughts, and ecological concerns.
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Affiliation(s)
- Shih-Lun Chen
- Department of Electronic Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan; (S.-L.C.); (H.-S.C.); (C.-H.H.); (C.-Y.C.); (L.-Y.L.)
| | - He-Sheng Chou
- Department of Electronic Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan; (S.-L.C.); (H.-S.C.); (C.-H.H.); (C.-Y.C.); (L.-Y.L.)
| | - Chun-Hsiang Huang
- Department of Electronic Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan; (S.-L.C.); (H.-S.C.); (C.-H.H.); (C.-Y.C.); (L.-Y.L.)
| | - Chih-Yun Chen
- Department of Electronic Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan; (S.-L.C.); (H.-S.C.); (C.-H.H.); (C.-Y.C.); (L.-Y.L.)
| | - Liang-Yu Li
- Department of Electronic Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan; (S.-L.C.); (H.-S.C.); (C.-H.H.); (C.-Y.C.); (L.-Y.L.)
| | - Ching-Hui Huang
- Department of Interior Design, Chung Yuan Christian University, Taoyuan City 320314, Taiwan;
| | - Yu-Yu Chen
- Department of Interior Design, Chung Yuan Christian University, Taoyuan City 320314, Taiwan;
| | - Jyh-Haw Tang
- Department of Civil Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan;
| | - Wen-Hui Chang
- Department of Applied Linguistics and Language Studies, Chung Yuan Christian University, Taoyuan City 320314, Taiwan
| | - Je-Sheng Huang
- Department of Commercial Design, Chung Yuan Christian University, Taoyuan City 320314, Taiwan;
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25
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Yogeshwar A, Kamalakkannan S. Proposed association rule hiding based privacy preservation model with block chain technology for IoT healthcare sector. Comput Methods Biomech Biomed Engin 2023; 26:1898-1915. [PMID: 36580033 DOI: 10.1080/10255842.2022.2156287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 12/04/2022] [Indexed: 12/30/2022]
Abstract
The purpose of this study is to improve healthcare system performance by utilizing cutting-edge computing technologies like blockchain and the Internet of Things. Blockchain-based data transfer, Association Rule hiding, and ideal key generation are the three primary aspects of the proposed work. Initially, data are altered using blockchain, then the data enter the Proposed Association Rule concealing stage. In this research a novel association rule concealment phase is implemented, which has three crucial processes: (1) data pattern mining using the improved apiori algorithm, (2) detection of sensitive data based on the improved apiori algorithm, and (3) a method for cleaning and restoring data. Using the generated optimal key, the sanitized sensitive data are recovered. Keys are critical to both the data sanitization and restoration procedures. Hence, a multi-objective hybrid optimization model is known as the Rock Hyraxes Updated Marriage in Honey Bee Optimization (RHUMBO) is employed. Then, the confidentiality of the suggested model's performance has been validated. From the experimental analysis the proposed model achieved 97% for Cleveland dataset at 90th learning percentage which is the best score. And the cost function of the suggested model is minimum (∼0.08 at 100th iteration).
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Affiliation(s)
- A Yogeshwar
- Department of Computer Science, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, India
| | - S Kamalakkannan
- Department of Information Technology, Vels Institute of Science Technology & Advanced Studies (VISTAS), Pallavaram, Chennai, India
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26
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Mahalingam A, Perumal G, Subburayalu G, Albathan M, Altameem A, Almakki RS, Hussain A, Abbas Q. ROAST-IoT: A Novel Range-Optimized Attention Convolutional Scattered Technique for Intrusion Detection in IoT Networks. Sensors (Basel) 2023; 23:8044. [PMID: 37836874 PMCID: PMC10575244 DOI: 10.3390/s23198044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 09/17/2023] [Accepted: 09/22/2023] [Indexed: 10/15/2023]
Abstract
The Internet of Things (IoT) has significantly benefited several businesses, but because of the volume and complexity of IoT systems, there are also new security issues. Intrusion detection systems (IDSs) guarantee both the security posture and defense against intrusions of IoT devices. IoT systems have recently utilized machine learning (ML) techniques widely for IDSs. The primary deficiencies in existing IoT security frameworks are their inadequate intrusion detection capabilities, significant latency, and prolonged processing time, leading to undesirable delays. To address these issues, this work proposes a novel range-optimized attention convolutional scattered technique (ROAST-IoT) to protect IoT networks from modern threats and intrusions. This system uses the scattered range feature selection (SRFS) model to choose the most crucial and trustworthy properties from the supplied intrusion data. After that, the attention-based convolutional feed-forward network (ACFN) technique is used to recognize the intrusion class. In addition, the loss function is estimated using the modified dingo optimization (MDO) algorithm to ensure the maximum accuracy of classifier. To evaluate and compare the performance of the proposed ROAST-IoT system, we have utilized popular intrusion datasets such as ToN-IoT, IoT-23, UNSW-NB 15, and Edge-IIoT. The analysis of the results shows that the proposed ROAST technique did better than all existing cutting-edge intrusion detection systems, with an accuracy of 99.15% on the IoT-23 dataset, 99.78% on the ToN-IoT dataset, 99.88% on the UNSW-NB 15 dataset, and 99.45% on the Edge-IIoT dataset. On average, the ROAST-IoT system achieved a high AUC-ROC of 0.998, demonstrating its capacity to distinguish between legitimate data and attack traffic. These results indicate that the ROAST-IoT algorithm effectively and reliably detects intrusion attacks mechanism against cyberattacks on IoT systems.
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Affiliation(s)
- Anandaraj Mahalingam
- Department of Information Technology, PSNA College of Engineering and Technology, Dindigul 624622, Tamil Nadu, India
| | - Ganeshkumar Perumal
- College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia (M.A.); (A.A.); (R.S.A.)
| | - Gopalakrishnan Subburayalu
- Department of Information Technology, Hindustan Institute of Technology and Science, Chennai 603103, Tamil Nadu, India
| | - Mubarak Albathan
- College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia (M.A.); (A.A.); (R.S.A.)
| | - Abdullah Altameem
- College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia (M.A.); (A.A.); (R.S.A.)
| | - Riyad Saleh Almakki
- College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia (M.A.); (A.A.); (R.S.A.)
| | - Ayyaz Hussain
- Department of Computer Science, Quaid-i-Azam University, Islamabad 44000, Pakistan;
| | - Qaisar Abbas
- College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia (M.A.); (A.A.); (R.S.A.)
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27
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Chowdhary A, Jha K, Zhao M. Generative Adversarial Network (GAN)-Based Autonomous Penetration Testing for Web Applications. Sensors (Basel) 2023; 23:8014. [PMID: 37766067 PMCID: PMC10534908 DOI: 10.3390/s23188014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 09/15/2023] [Accepted: 09/19/2023] [Indexed: 09/29/2023]
Abstract
The web application market has shown rapid growth in recent years. The expansion of Wireless Sensor Networks (WSNs) and the Internet of Things (IoT) has created new web-based communication and sensing frameworks. Current security research utilizes source code analysis and manual exploitation of web applications, to identify security vulnerabilities, such as Cross-Site Scripting (XSS) and SQL Injection, in these emerging fields. The attack samples generated as part of web application penetration testing on sensor networks can be easily blocked, using Web Application Firewalls (WAFs). In this research work, we propose an autonomous penetration testing framework that utilizes Generative Adversarial Networks (GANs). We overcome the limitations of vanilla GANs by using conditional sequence generation. This technique helps in identifying key features for XSS attacks. We trained a generative model based on attack labels and attack features. The attack features were identified using semantic tokenization, and the attack payloads were generated using conditional sequence GAN. The generated attack samples can be used to target web applications protected by WAFs in an automated manner. This model scales well on a large-scale web application platform, and it saves the significant effort invested in manual penetration testing.
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Affiliation(s)
- Ankur Chowdhary
- 6sense Insights Inc., San Francisco, CA 94105, USA
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85281, USA
| | - Kritshekhar Jha
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85281, USA
| | - Ming Zhao
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85281, USA
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28
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Khan MNU, Tang Z, Cao W, Abid YA, Pan W, Ullah A. Fuzzy-Based Efficient Healthcare Data Collection and Analysis Mechanism Using Edge Nodes in the IoMT. Sensors (Basel) 2023; 23:7799. [PMID: 37765857 PMCID: PMC10535922 DOI: 10.3390/s23187799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 08/29/2023] [Accepted: 08/30/2023] [Indexed: 09/29/2023]
Abstract
The Internet of Things (IoT) is an advanced technology that comprises numerous devices with carrying sensors to collect, send, and receive data. Due to its vast popularity and efficiency, it is employed in collecting crucial data for the health sector. As the sensors generate huge amounts of data, it is better for the data to be aggregated before being transmitting the data further. These sensors generate redundant data frequently and transmit the same values again and again unless there is no variation in the data. The base scheme has no mechanism to comprehend duplicate data. This problem has a negative effect on the performance of heterogeneous networks.It increases energy consumption; and requires high control overhead, and additional transmission slots are required to send data. To address the above-mentioned challenges posed by duplicate data in the IoT-based health sector, this paper presents a fuzzy data aggregation system (FDAS) that aggregates data proficiently and reduces the same range of normal data sizes to increase network performance and decrease energy consumption. The appropriate parent node is selected by implementing fuzzy logic, considering important input parameters that are crucial from the parent node selection perspective and share Boolean digit 0 for the redundant values to store in a repository for future use. This increases the network lifespan by reducing the energy consumption of sensors in heterogeneous environments. Therefore, when the complexity of the environment surges, the efficiency of FDAS remains stable. The performance of the proposed scheme has been validated using the network simulator and compared with base schemes. According to the findings, the proposed technique (FDAS) dominates in terms of reducing energy consumption in both phases, achieves better aggregation, reduces control overhead, and requires the fewest transmission slots.
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Affiliation(s)
- Muhammad Nafees Ulfat Khan
- School of Information and Communication Engineering, Guilin University of Electronic Technology, Guilin 541004, China;
| | - Zhiling Tang
- Guangxi Key Laboratory of Wireless Broadband Communication and Signal Processing, School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China; (W.C.); (W.P.)
| | - Weiping Cao
- Guangxi Key Laboratory of Wireless Broadband Communication and Signal Processing, School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China; (W.C.); (W.P.)
| | - Yawar Abbas Abid
- School of Computers and Cyberspace Security, Guilin University of Electronic Technology, Guilin 541004, China;
- Department of Computers Science, COMSATS University Islamabad, Sahiwal Campus, Sahiwal 57000, Pakistan
| | - Wanghua Pan
- Guangxi Key Laboratory of Wireless Broadband Communication and Signal Processing, School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China; (W.C.); (W.P.)
| | - Ata Ullah
- Department of Computer Science, National University of Modern Languages (NUML), Islamabad 44000, Pakistan;
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29
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Rana M, Mamun Q, Islam R. Enhancing IoT Security: An Innovative Key Management System for Lightweight Block Ciphers. Sensors (Basel) 2023; 23:7678. [PMID: 37765734 PMCID: PMC10535244 DOI: 10.3390/s23187678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/30/2023] [Accepted: 09/01/2023] [Indexed: 09/29/2023]
Abstract
This research paper presents a study on designing and implementing a robust key management scheme for lightweight block ciphers in Internet of Things (IoT) networks. Key management is a critical concern for IoT devices due to their limited resources and susceptibility to security threats. The proposed scheme utilises partial key pre-distribution to achieve lightweight and secure key management. The protocol's security has been analysed against various attacks, demonstrating its resistance. Performance evaluation results indicate that the proposed key management technique is suitable for resource-constraint IoT networks, as it reduces communication overhead, power consumption, and storage space requirements. The methodology employed in this research includes designing and implementing the proposed key management scheme and conducting scenario-based analyses of its functionality. The results affirm that the proposed solution effectively ensures secure communication in IoT networks. Overall, this research contributes to developing a secure and efficient key management scheme for lightweight block ciphers in IoT networks.
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Affiliation(s)
- Muhammad Rana
- School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW 2678, Australia
| | - Quazi Mamun
- School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW 2678, Australia
| | - Rafiqul Islam
- School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW 2678, Australia
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30
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Fay CD, Healy JP, Diamond D. Advanced IoT Pressure Monitoring System for Real-Time Landfill Gas Management. Sensors (Basel) 2023; 23:7574. [PMID: 37688023 PMCID: PMC10490650 DOI: 10.3390/s23177574] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/25/2023] [Accepted: 08/29/2023] [Indexed: 09/10/2023]
Abstract
This research presents a novel stand-alone device for the autonomous measurement of gas pressure levels on an active landfill site, which enables the real-time monitoring of gas dynamics and supports the early detection of critical events. The developed device employs advanced sensing technologies and wireless communication capabilities, enabling remote data transmission and access via the Internet. Through extensive field experiments, we demonstrate the high sampling rate of the device and its ability to detect significant events related to gas generation dynamics in landfills, such as flare shutdowns or blockages that could lead to hazardous conditions. The validation of the device's performance against a high-end analytical system provides further evidence of its reliability and accuracy. The developed technology herein offers a cost-effective and scalable solution for environmental landfill gas monitoring and management. We expect that this research will contribute to the advancement of environmental monitoring technologies and facilitate better decision-making processes for sustainable waste management.
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Affiliation(s)
- Cormac D. Fay
- SMART Infrastructure Facility, Engineering and Information Sciences, University of Wollongong, Wollongong, NSW 2522, Australia
- CLARITY: Centre for Sensor Web Technologies, Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
- National Centre for Sensor Research (NCSR), Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
- Insight Centre for Data Analytics, Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
| | - John P. Healy
- CLARITY: Centre for Sensor Web Technologies, Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
- National Centre for Sensor Research (NCSR), Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
| | - Dermot Diamond
- CLARITY: Centre for Sensor Web Technologies, Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
- National Centre for Sensor Research (NCSR), Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
- Insight Centre for Data Analytics, Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
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31
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Kane L, Liu V, McKague M, Walker G. An Experimental Field Comparison of Wi-Fi HaLow and LoRa for the Smart Grid. Sensors (Basel) 2023; 23:7409. [PMID: 37687866 PMCID: PMC10490590 DOI: 10.3390/s23177409] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/17/2023] [Accepted: 08/22/2023] [Indexed: 09/10/2023]
Abstract
IEEE 802.11ah, or Wi-Fi HaLow, is a long-range Internet of Things (IoT) communication technology with promising performance claims. Being IP-based makes it an attractive prospect when interfacing with existing IP networks. Through real-world performance experiments, this study evaluates the network performance of Wi-Fi HaLow in terms of throughput, latency, and reliability against IEEE 802.11n (Wi-Fi n) and a competing IoT technology LoRa. These experiments are enabled through three proposed network evaluation architectures that facilitate remote control of the devices in a secure manner. The performance of Wi-Fi HaLow is then assessed against the network requirements of various smart grid applications. Wi-Fi HaLow offers promising performance when compared to rival technology LoRa. This study is the first to evaluate Wi-Fi HaLow in an authentic experimental way, providing performance data and insights that are not possible through simulation and modelling alone. This work provides the basis for further evaluation and implementation of this emerging technology.
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Affiliation(s)
- Luke Kane
- Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia; (V.L.); (M.M.)
- Cyber Security Cooperative Research Centre, Brisbane, QLD 4000, Australia
| | - Vicky Liu
- Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia; (V.L.); (M.M.)
| | - Matthew McKague
- Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia; (V.L.); (M.M.)
| | - Geoffrey Walker
- Faculty of Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia;
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32
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Pinelo J, Rocha AD, Arvana M, Gonçalves J, Cota N, Silva P. Unveiling LoRa's Oceanic Reach: Assessing the Coverage of the Azores LoRaWAN Network from an Island. Sensors (Basel) 2023; 23:7394. [PMID: 37687849 PMCID: PMC10490279 DOI: 10.3390/s23177394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 08/17/2023] [Accepted: 08/21/2023] [Indexed: 09/10/2023]
Abstract
In maritime settings, effective communication between vessels and land infrastructure is crucial, but existing technologies often prove impractical for energy-sensitive IoT applications, like deploying sensors at sea. In this study, we explore the viability of a low-power, cost-effective wireless communication solution for maritime sensing data. Specifically, we conduct an experimental assessment of the Azorean Long Range Wide Area Network (LoRaWAN) coverage. Our tests involve positioning the gateway at the island's highest point and installing end nodes on medium-sized fishing vessels. Through measurements of received signal strength indicator (RSSI), signal-to-noise ratio (SNR), and lines of sight (LOS), we showcase the potential of LoRaWAN transmissions to achieve communication distances exceeding 130 km in a LOS-free scenario over the ocean. These findings highlight the promising capabilities of LoRaWAN for reliable and long-range maritime communication of sensing data.
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Affiliation(s)
- João Pinelo
- Atlantic International Research Centre, 9700-702 Angra do Heroísmo, Portugal;
| | - André Dionísio Rocha
- NOVA School of Science and Technology, Center of Technology and Systems (UNINOVA-CTS) and Associated Lab of Intelligent Systems (LASI), NOVA University Lisbon, 2829-516 Lisbon, Portugal; (A.D.R.); (M.A.)
| | - Miguel Arvana
- NOVA School of Science and Technology, Center of Technology and Systems (UNINOVA-CTS) and Associated Lab of Intelligent Systems (LASI), NOVA University Lisbon, 2829-516 Lisbon, Portugal; (A.D.R.); (M.A.)
| | - João Gonçalves
- Independent Researcher, 9700-702 Angra do Heroísmo, Portugal
| | - Nuno Cota
- Instituto Superior de Engenharia de Lisboa, 1959-007 Lisboa, Portugal;
| | - Pedro Silva
- Atlantic International Research Centre, 9700-702 Angra do Heroísmo, Portugal;
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33
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Singh D, Biswal AK, Samanta D, Singh V, Kadry S, Khan A, Nam Y. Smart high-yield tomato cultivation: precision irrigation system using the Internet of Things. Front Plant Sci 2023; 14:1239594. [PMID: 37674739 PMCID: PMC10477787 DOI: 10.3389/fpls.2023.1239594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 07/25/2023] [Indexed: 09/08/2023]
Abstract
The Internet of Things (IOT)-based smart farming promises ultrafast speeds and near real-time response. Precision farming enabled by the Internet of Things has the potential to boost efficiency and output while reducing water use. Therefore, IoT devices can aid farmers in keeping track crop health and development while also automating a variety of tasks (such as moisture level prediction, irrigation system, crop development, and nutrient levels). The IoT-based autonomous irrigation technique makes exact use of farmers' time, money, and power. High crop yields can be achieved through consistent monitoring and sensing of crops utilizing a variety of IoT sensors to inform farmers of optimal harvest times. In this paper, a smart framework for growing tomatoes is developed, with influence from IoT devices or modules. With the help of IoT modules, we can forecast soil moisture levels and fine-tune the watering schedule. To further aid farmers, a smartphone app is currently in development that will provide them with crucial data on the health of their tomato crops. Large-scale experiments validate the proposed model's ability to intelligently monitor the irrigation system, which contributes to higher tomato yields.
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Affiliation(s)
- Debabrata Singh
- Department of Computer Application (CA), Institute of Technical Education and Research (ITER), Siksha ‘O’Anusandhan (SOA) Deemed to be University, Bhubaneswar (BBSR), Odisha, India
| | - Anil Kumar Biswal
- Department of Computer Science and Engineering (CSE), Institute of Technical Education and Research (ITER), Siksha ‘O’Anusandhan (SOA) Deemed to be University, Bhubaneswar (BBSR), Odisha, India
| | - Debabrata Samanta
- Department of Computing and Information Technologies, RIT Kosovo (A.U.K), Rochester Institute of Technology – RIT Global, Kosovo, Albania
| | - Vijendra Singh
- School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
| | - Seifedine Kadry
- Department of Applied Data Science, Noroff University College, Kristiansand, Norway
- Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, United Arab Emirates
- Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon
- MEU Research Unit, Middle East University, Amman, Jordan
| | - Awais Khan
- Department of ICT Convergence, Soonchunhyang University, Asan, Republic of Korea
| | - Yunyoung Nam
- Department of ICT Convergence, Soonchunhyang University, Asan, Republic of Korea
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Hamzei M, Khandagh S, Jafari Navimipour N. A Quality-of-Service-Aware Service Composition Method in the Internet of Things Using a Multi-Objective Fuzzy-Based Hybrid Algorithm. Sensors (Basel) 2023; 23:7233. [PMID: 37631769 PMCID: PMC10458659 DOI: 10.3390/s23167233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/06/2023] [Accepted: 08/10/2023] [Indexed: 08/27/2023]
Abstract
The Internet of Things (IoT) represents a cutting-edge technical domain, encompassing billions of intelligent objects capable of bridging the physical and virtual worlds across various locations. IoT services are responsible for delivering essential functionalities. In this dynamic and interconnected IoT landscape, providing high-quality services is paramount to enhancing user experiences and optimizing system efficiency. Service composition techniques come into play to address user requests in IoT applications, allowing various IoT services to collaborate seamlessly. Considering the resource limitations of IoT devices, they often leverage cloud infrastructures to overcome technological constraints, benefiting from unlimited resources and capabilities. Moreover, the emergence of fog computing has gained prominence, facilitating IoT application processing in edge networks closer to IoT sensors and effectively reducing delays inherent in cloud data centers. In this context, our study proposes a cloud-/fog-based service composition for IoT, introducing a novel fuzzy-based hybrid algorithm. This algorithm ingeniously combines Ant Colony Optimization (ACO) and Artificial Bee Colony (ABC) optimization algorithms, taking into account energy consumption and Quality of Service (QoS) factors during the service selection process. By leveraging this fuzzy-based hybrid algorithm, our approach aims to revolutionize service composition in IoT environments by empowering intelligent decision-making capabilities and ensuring optimal user satisfaction. Our experimental results demonstrate the effectiveness of the proposed strategy in successfully fulfilling service composition requests by identifying suitable services. When compared to recently introduced methods, our hybrid approach yields significant benefits. On average, it reduces energy consumption by 17.11%, enhances availability and reliability by 8.27% and 4.52%, respectively, and improves the average cost by 21.56%.
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Affiliation(s)
- Marzieh Hamzei
- Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz 51376-53515, Iran
| | - Saeed Khandagh
- Electrical Engineering Department, Tabriz Branch, University of Applied Sciences and Technology, Tabriz 51376-53515, Iran
| | - Nima Jafari Navimipour
- Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Kadir Has University, 34083 Istanbul, Turkey
- Future Technology Research Center, National Yunlin University of Science and Technology, Douliou 64002, Taiwan
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35
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Ruminot N, Estevez C, Montejo-Sánchez S. A Novel Approach of a Low-Cost Voltage Fault Injection Method for Resource-Constrained IoT Devices: Design and Analysis. Sensors (Basel) 2023; 23:7180. [PMID: 37631717 PMCID: PMC10459605 DOI: 10.3390/s23167180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Revised: 07/31/2023] [Accepted: 08/04/2023] [Indexed: 08/27/2023]
Abstract
The rapid development of the Internet of Things (IoT) has brought about the processing and storage of sensitive information on resource-constrained devices, which are susceptible to various hardware attacks. Fault injection attacks (FIAs) stand out as one of the most widespread. Particularly, voltage-based FIAs (V-FIAs) have gained popularity due to their non-invasive nature and high effectiveness in inducing faults by pushing the IoT hardware to its operational limits. Improving the security of devices and gaining a comprehensive understanding of their vulnerabilities is of utmost importance. In this study, we present a novel fault injection method and employ it to target an 8-bit AVR microcontroller. We identify the optimal attack parameters by analyzing the detected failures and their trends. A case study is conducted to validate the efficacy of this new method in a more realistic scenario, focusing on a simple authentication method using the determined optimal parameters. This analysis not only demonstrates the feasibility of the V-FIA but also elucidates the primary characteristics of the resulting failures and their propagation in resource-constrained devices. Additionally, we devise a hardware/software countermeasure that can be integrated into any resource-constrained device to thwart such attacks in IoT scenarios.
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Affiliation(s)
- Nicolás Ruminot
- Department of Electrical Engineering, Universidad de Chile, Santiago 8940577, Chile; (N.R.); (C.E.)
| | - Claudio Estevez
- Department of Electrical Engineering, Universidad de Chile, Santiago 8940577, Chile; (N.R.); (C.E.)
| | - Samuel Montejo-Sánchez
- Programa Institucional de Fomento a la Investigación, Desarrollo e Innovación, Universidad Tecnológica Metropolitana, Santiago 8940577, Chile
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36
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Quattrocchi A, Martella F, Lukaj V, De Leo R, Villari M, Montanini R. Designing a Low-Cost System to Monitor the Structural Behavior of Street Lighting Poles in Smart Cities. Sensors (Basel) 2023; 23:6993. [PMID: 37571776 PMCID: PMC10422296 DOI: 10.3390/s23156993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 08/01/2023] [Accepted: 08/04/2023] [Indexed: 08/13/2023]
Abstract
The structural collapse of a street lighting pole represents an aspect that is often underestimated and unpredictable, but of relevant importance for the safety of people and things. These events are complex to evaluate since several sources of damage are involved. In addition, traditional inspection methods are ineffective, do not correctly quantify the residual life of poles, and are inefficient, requiring enormous costs associated with the vastness of elements to be investigated. An advantageous alternative is to adopt a distributed type of Structural Health Monitoring (SHM) technique based on the Internet of Things (IoT). This paper proposes the design of a low-cost system, which is also easy to integrate in current infrastructures, for monitoring the structural behavior of street lighting poles in Smart Cities. At the same time, this device collects previous structural information and offers some secondary functionalities related to its application, such as meteorological information. Furthermore, this paper intends to lay the foundations for the development of a method that is able to avoid the collapse of the poles. Specifically, the implementation phase is described in the aspects concerning low-cost devices and sensors for data acquisition and transmission and the strategies of information technologies (ITs), such as Cloud/Edge approaches, for storing, processing and presenting the achieved measurements. Finally, an experimental evaluation of the metrological performance of the sensing features of this system is reported. The main results highlight that the employment of low-cost equipment and open-source software has a double implication. On one hand, they entail advantages such as limited costs and flexibility to accommodate the specific necessities of the interested user. On the other hand, the used sensors require an indispensable metrological evaluation of their performance due to encountered issues relating to calibration, reliability and uncertainty.
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Affiliation(s)
- Antonino Quattrocchi
- Department of Engineering, University of Messina, C.da di Dio, 98166 Messina, Italy; (F.M.); (V.L.); (R.D.L.); (R.M.)
| | - Francesco Martella
- Department of Engineering, University of Messina, C.da di Dio, 98166 Messina, Italy; (F.M.); (V.L.); (R.D.L.); (R.M.)
| | - Valeria Lukaj
- Department of Engineering, University of Messina, C.da di Dio, 98166 Messina, Italy; (F.M.); (V.L.); (R.D.L.); (R.M.)
| | - Rocco De Leo
- Department of Engineering, University of Messina, C.da di Dio, 98166 Messina, Italy; (F.M.); (V.L.); (R.D.L.); (R.M.)
| | - Massimo Villari
- Department of Mathematics, Computer Science, Physics and Earth Science (MIFT), University of Messina, Viale Ferdinando Stagno d’Alcontres 31, 98166 Messina, Italy;
| | - Roberto Montanini
- Department of Engineering, University of Messina, C.da di Dio, 98166 Messina, Italy; (F.M.); (V.L.); (R.D.L.); (R.M.)
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37
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Parez S, Dilshad N, Alghamdi NS, Alanazi TM, Lee JW. Visual Intelligence in Precision Agriculture: Exploring Plant Disease Detection via Efficient Vision Transformers. Sensors (Basel) 2023; 23:6949. [PMID: 37571732 PMCID: PMC10422257 DOI: 10.3390/s23156949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 07/31/2023] [Accepted: 08/01/2023] [Indexed: 08/13/2023]
Abstract
In order for a country's economy to grow, agricultural development is essential. Plant diseases, however, severely hamper crop growth rate and quality. In the absence of domain experts and with low contrast information, accurate identification of these diseases is very challenging and time-consuming. This leads to an agricultural management system in need of a method for automatically detecting disease at an early stage. As a consequence of dimensionality reduction, CNN-based models use pooling layers, which results in the loss of vital information, including the precise location of the most prominent features. In response to these challenges, we propose a fine-tuned technique, GreenViT, for detecting plant infections and diseases based on Vision Transformers (ViTs). Similar to word embedding, we divide the input image into smaller blocks or patches and feed these to the ViT sequentially. Our approach leverages the strengths of ViTs in order to overcome the problems associated with CNN-based models. Experiments on widely used benchmark datasets were conducted to evaluate the proposed GreenViT performance. Based on the obtained experimental outcomes, the proposed technique outperforms state-of-the-art (SOTA) CNN models for detecting plant diseases.
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Affiliation(s)
- Sana Parez
- Department of Software, Sejong University, Seoul 05006, Republic of Korea;
| | - Naqqash Dilshad
- Department of Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Republic of Korea;
| | - Norah Saleh Alghamdi
- Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia;
| | - Turki M. Alanazi
- Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia;
| | - Jong Weon Lee
- Department of Software, Sejong University, Seoul 05006, Republic of Korea;
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38
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Ndaguba E, Cilliers J, Ghosh S, Herath S, Mussi ET. Operability of Smart Spaces in Urban Environments: A Systematic Review on Enhancing Functionality and User Experience. Sensors (Basel) 2023; 23:6938. [PMID: 37571721 PMCID: PMC10422534 DOI: 10.3390/s23156938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 06/09/2023] [Accepted: 06/15/2023] [Indexed: 08/13/2023]
Abstract
This literature review highlights the emergence of the Internet of Things (IoT) and the proliferation of connected devices as the driving force behind the adoption of smart spaces. This review also discusses the various applications of smart spaces, including smart homes, smart cities, and smart healthcare: (1) Background: the aim of this research is to provide a comprehensive overview of the concept of smart spaces, including their key features, technologies, and applications in built environments and urban areas; (2) Methods: The study adopts a qualitative approach, drawing on secondary sources, such as academic journals, reports, and online sources; (3) Results: The findings suggest that smart spaces have the potential to transform the way people interact with their environment and each other. They could improve efficiency, safety, and quality of life. However, there are also concerns about privacy and security in relation to the collection and use of personal data; (4) Conclusions: The study concludes that smart spaces have significant theoretical and practical implications for various fields, including architecture, urban planning, and healthcare. The theoretical implications include the need for new models and frameworks to understand the complex relationships between technology, space, and society. The practical implications involve the development of new standards and regulations to ensure the responsible and ethical use of smart spaces.
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Affiliation(s)
- Emeka Ndaguba
- Centre for Development Support, University of the Free State, Bloemfontein 9301, South Africa
- School of Built Environment, Faculty of Design Architecture and Building, University of Technology Sydney, Ultimo, NSW 2007, Australia; (J.C.); (S.G.); (S.H.); (E.T.M.)
| | - Jua Cilliers
- School of Built Environment, Faculty of Design Architecture and Building, University of Technology Sydney, Ultimo, NSW 2007, Australia; (J.C.); (S.G.); (S.H.); (E.T.M.)
- Unit for Environmental Sciences and Management, North-West University, Potchefstroom 2531, South Africa
| | - Sumita Ghosh
- School of Built Environment, Faculty of Design Architecture and Building, University of Technology Sydney, Ultimo, NSW 2007, Australia; (J.C.); (S.G.); (S.H.); (E.T.M.)
| | - Shanaka Herath
- School of Built Environment, Faculty of Design Architecture and Building, University of Technology Sydney, Ultimo, NSW 2007, Australia; (J.C.); (S.G.); (S.H.); (E.T.M.)
| | - Eveline Tancredo Mussi
- School of Built Environment, Faculty of Design Architecture and Building, University of Technology Sydney, Ultimo, NSW 2007, Australia; (J.C.); (S.G.); (S.H.); (E.T.M.)
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39
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Farhad A, Pyun JY. LoRaWAN Meets ML: A Survey on Enhancing Performance with Machine Learning. Sensors (Basel) 2023; 23:6851. [PMID: 37571633 PMCID: PMC10422334 DOI: 10.3390/s23156851] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 07/24/2023] [Accepted: 07/27/2023] [Indexed: 08/13/2023]
Abstract
The Internet of Things is rapidly growing with the demand for low-power, long-range wireless communication technologies. Long Range Wide Area Network (LoRaWAN) is one such technology that has gained significant attention in recent years due to its ability to provide long-range communication with low power consumption. One of the main issues in LoRaWAN is the efficient utilization of radio resources (e.g., spreading factor and transmission power) by the end devices. To solve the resource allocation issue, machine learning (ML) methods have been used to improve the LoRaWAN network performance. The primary aim of this survey paper is to study and examine the issue of resource management in LoRaWAN that has been resolved through state-of-the-art ML methods. Further, this survey presents the publicly available LoRaWAN frameworks that could be utilized for dataset collection, discusses the required features for efficient resource management with suggested ML methods, and highlights the existing publicly available datasets. The survey also explores and evaluates the Network Simulator-3-based ML frameworks that can be leveraged for efficient resource management. Finally, future recommendations regarding the applicability of the ML applications for resource management in LoRaWAN are illustrated, providing a comprehensive guide for researchers and practitioners interested in applying ML to improve the performance of the LoRaWAN network.
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Affiliation(s)
| | - Jae-Young Pyun
- Wireless and Mobile Communication System Laboratory, Department of Information and Communication Engineering, Chosun University, Gwangju 61452, Republic of Korea;
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40
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Shen L, Zhang Z, Zhou Y, Xu Y. Applying Blockchain Technology and the Internet of Things to Improve the Data Reliability for Livestock Insurance. Sensors (Basel) 2023; 23:6290. [PMID: 37514585 PMCID: PMC10384577 DOI: 10.3390/s23146290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 06/28/2023] [Accepted: 07/08/2023] [Indexed: 07/30/2023]
Abstract
Animal husbandry is a vital sector in China's agriculture sector, contributing to over one-third of its agricultural output, and more than 40% of farmers' income. However, this industry is vulnerable to risks arising from production and operation, such as disease outbreaks, natural disasters, and market fluctuations. Livestock insurance can help mitigate these risks, but the lack of reliable data on shed environments has hindered its effectiveness. The objective of this study is to propose a livestock shed environmental regulatory platform that utilizes blockchain and the Internet of Things to ensure data authenticity, real-time monitoring, and transparency in the regulatory process. The platform also automates the insurance process, reducing costs and improving efficiency. The proposed platform employs blockchain to ensure data authenticity and devices to monitor and collect real-time environmental data. It also utilizes smart contracts to automate the insurance process, from negotiating and signing contracts to making insurance claims. The system's design rationale, architecture, and implementation are detailed. The proposed platform has been implemented and currently manages over 300,000 livestock animals with more than 350,000 insurance contracts signed. The use of blockchain and the Internet of Things has ensured data authenticity, real-time monitoring, and transparency in the regulatory process, while the automation of the insurance process has reduced costs and improved efficiency. The proposed livestock shed environmental regulatory platform has the potential to improve the effectiveness of livestock insurance in China by addressing the critical issue of data reliability. The use of blockchain and the Internet of Things has enabled real-time monitoring, data authenticity, and transparency in the regulatory process, while the automation of the insurance process has improved efficiency and reduced costs. This platform could serve as a model for other countries looking to improve the effectiveness of their livestock insurance programs.
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Affiliation(s)
- Lihua Shen
- Zhijiang College, Zhejiang University of Technology, Shaoxing 312030, China
- School of Management, Zhejiang University of Technology, Hangzhou 310014, China
| | - Zhibin Zhang
- School of Management, Zhejiang University of Technology, Hangzhou 310014, China
| | - Youmei Zhou
- Department of Landscape Architecture, Tongji University, Shanghai 200092, China
| | - Yingying Xu
- School of Humanities and Social Science, Beihang University, Beijing 100191, China
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Kuaban GS, Gelenbe E, Czachórski T, Czekalski P, Tangka JK. Modelling of the Energy Depletion Process and Battery Depletion Attacks for Battery-Powered Internet of Things (IoT) Devices. Sensors (Basel) 2023; 23:6183. [PMID: 37448032 DOI: 10.3390/s23136183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 06/15/2023] [Accepted: 06/28/2023] [Indexed: 07/15/2023]
Abstract
The Internet of Things (IoT) is transforming almost every industry, including agriculture, food processing, health care, oil and gas, environmental protection, transportation and logistics, manufacturing, home automation, and safety. Cost-effective, small-sized batteries are often used to power IoT devices being deployed with limited energy capacity. The limited energy capacity of IoT devices makes them vulnerable to battery depletion attacks designed to exhaust the energy stored in the battery rapidly and eventually shut down the device. In designing and deploying IoT devices, the battery and device specifications should be chosen in such a way as to ensure a long lifetime of the device. This paper proposes diffusion approximation as a mathematical framework for modelling the energy depletion process in IoT batteries. We applied diffusion or Brownian motion processes to model the energy depletion of a battery of an IoT device. We used this model to obtain the probability density function, mean, variance, and probability of the lifetime of an IoT device. Furthermore, we studied the influence of active power consumption, sleep time, and battery capacity on the probability density function, mean, and probability of the lifetime of an IoT device. We modelled ghost energy depletion attacks and their impact on the lifetime of IoT devices. We used numerical examples to study the influence of battery depletion attacks on the distribution of the lifetime of an IoT device. We also introduced an energy threshold after which the device's battery should be replaced in order to ensure that the battery is not completely drained before it is replaced.
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Affiliation(s)
- Godlove Suila Kuaban
- Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, 44-100 Gliwice, Poland
| | - Erol Gelenbe
- Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, 44-100 Gliwice, Poland
| | - Tadeusz Czachórski
- Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, 44-100 Gliwice, Poland
| | - Piotr Czekalski
- Department of Computer Graphics, Vision and Digital System, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland
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42
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Neto ECP, Dadkhah S, Ferreira R, Zohourian A, Lu R, Ghorbani AA. CICIoT2023: A Real-Time Dataset and Benchmark for Large-Scale Attacks in IoT Environment. Sensors (Basel) 2023; 23:5941. [PMID: 37447792 PMCID: PMC10346235 DOI: 10.3390/s23135941] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 06/16/2023] [Accepted: 06/20/2023] [Indexed: 07/15/2023]
Abstract
Nowadays, the Internet of Things (IoT) concept plays a pivotal role in society and brings new capabilities to different industries. The number of IoT solutions in areas such as transportation and healthcare is increasing and new services are under development. In the last decade, society has experienced a drastic increase in IoT connections. In fact, IoT connections will increase in the next few years across different areas. Conversely, several challenges still need to be faced to enable efficient and secure operations (e.g., interoperability, security, and standards). Furthermore, although efforts have been made to produce datasets composed of attacks against IoT devices, several possible attacks are not considered. Most existing efforts do not consider an extensive network topology with real IoT devices. The main goal of this research is to propose a novel and extensive IoT attack dataset to foster the development of security analytics applications in real IoT operations. To accomplish this, 33 attacks are executed in an IoT topology composed of 105 devices. These attacks are classified into seven categories, namely DDoS, DoS, Recon, Web-based, brute force, spoofing, and Mirai. Finally, all attacks are executed by malicious IoT devices targeting other IoT devices. The dataset is available on the CIC Dataset website.
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Affiliation(s)
| | - Sajjad Dadkhah
- Faculty of Computer Science, University of New Brunswick (UnB), Fredericton, NB E3B 5A3, Canada; (E.C.P.N.); (R.F.); (A.Z.); (R.L.); (A.A.G.)
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43
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Shah SL, Abbas ZH, Abbas G, Muhammad F, Hussien A, Baker T. An Innovative Clustering Hierarchical Protocol for Data Collection from Remote Wireless Sensor Networks Based Internet of Things Applications. Sensors (Basel) 2023; 23:5728. [PMID: 37420893 DOI: 10.3390/s23125728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 05/31/2023] [Accepted: 06/13/2023] [Indexed: 07/09/2023]
Abstract
Recently, unmanned aerial vehicles (UAVs) have emerged as a viable solution for data collection from remote Internet of Things (IoT) applications. However, the successful implementation in this regard necessitates the development of a reliable and energy-efficient routing protocol. This paper proposes a reliable and an energy-efficient UAV-assisted clustering hierarchical (EEUCH) protocol designed for remote wireless sensor networks (WSNs) based IoT applications. The proposed EEUCH routing protocol facilitates UAVs to collect data from ground sensor nodes (SNs) that are equipped with wake-up radios (WuRs) and deployed remotely from the base station (BS) in the field of interest (FoI). During each round of the EEUCH protocol, the UAVs arrive at the predefined hovering positions at the FoI, perform clear channel assignment, and broadcast wake-up calls (WuCs) to the SNs. Upon receiving the WuCs by the SNs' wake-up receivers, the SNs perform carrier sense multiple access/collision avoidance before sending joining requests to ensure reliability and cluster-memberships with the particular UAV whose WuC is received. The cluster-member SNs turn on their main radios (MRs) for data packet transmission. The UAV assigns time division multiple access (TDMA) slots to each of its cluster-member SNs whose joining request is received. Each SN must send the data packets in its assigned TDMA slot. When data packets are successfully received by the UAV, it sends acknowledgments to the SNs, after which the SNs turn off their MRs, completing a single round of the protocol. The proposed EEUCH routing protocol with WuR eliminates the issue of cluster overlapping, improves the overall performance, and increases network stability time by a factor of 8.7. It also improves energy efficiency by a factor of 12.55, resulting in a longer network lifespan compared to Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. Moreover, EEUCH collects 5.05 times more data from the FoI than LEACH. These results are based on simulations in which the EEUCH protocol outperformed the existing six benchmark routing protocols proposed for homogeneous, two-tier, and three-tier heterogeneous WSNs.
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Affiliation(s)
- Syed Luqman Shah
- Telecommunication and Networking (TeleCoN) Research Center, GIK Institute of Engineering Sciences and Technology, Topi 23640, Pakistan
| | - Ziaul Haq Abbas
- Faculty of Electrical Engineering, GIK Institute of Engineering Sciences and Technology, Topi 23640, Pakistan
| | - Ghulam Abbas
- Faculty of Computer Science and Engineering, GIK Institute of Engineering Sciences and Technology, Topi 23640, Pakistan
| | - Fazal Muhammad
- Department of Electrical Engineering, University of Engineering and Technology, Mardan 23200, Pakistan
| | - Aseel Hussien
- College of Engineering, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Thar Baker
- School of Architecture, Technology and Engineering, University of Brighton, Brighton BN2 4GJ, UK
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44
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Osamy W, Khedr AM, Alwasel B, Salim A. DGTTSSA: Data Gathering Technique Based on Trust and Sparrow Search Algorithm for WSNs. Sensors (Basel) 2023; 23:5433. [PMID: 37420600 DOI: 10.3390/s23125433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/24/2023] [Accepted: 06/04/2023] [Indexed: 07/09/2023]
Abstract
Wireless Sensor Networks (WSNs) have been successfully utilized for developing various collaborative and intelligent applications that can provide comfortable and smart-economic life. This is because the majority of applications that employ WSNs for data sensing and monitoring purposes are in open practical environments, where security is often the first priority. In particular, the security and efficacy of WSNs are universal and inevitable issues. One of the most effective methods for increasing the lifetime of WSNs is clustering. In cluster-based WSNs, Cluster Heads (CHs) play a critical role; however, if the CHs are compromised, the gathered data loses its trustworthiness. Hence, trust-aware clustering techniques are crucial in a WSN to improve node-to-node communication as well as to enhance network security. In this work, a trust-enabled data-gathering technique based on the Sparrow Search Algorithm (SSA) for WSN-based applications, called DGTTSSA, is introduced. In DGTTSSA, the swarm-based SSA optimization algorithm is modified and adapted to develop a trust-aware CH selection method. A fitness function is created based on the nodes' remaining energy and trust values in order to choose more efficient and trustworthy CHs. Moreover, predefined energy and trust threshold values are taken into account and are dynamically adjusted to accommodate the changes in the network. The proposed DGTTSSA and the state-of-the-art algorithms are evaluated in terms of the Stability and Instability Period, Reliability, CHs Average Trust Value, Average Residual Energy, and Network Lifetime. The simulation results indicate that DGTTSSA selects the most trustworthy nodes as CHs and offers a significantly longer network lifetime than previous efforts in the literature. Moreover, DGTTSSA improves the instability period compared to LEACH-TM, ETCHS, eeTMFGA, and E-LEACH up to 90%, 80%, 79%, 92%, respectively, when BS is located at the center, up to 84%, 71%, 47%, 73%, respectively, when BS is located at the corner, and up to 81%, 58%, 39%, 25%, respectively, when BS is located outside the network.
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Affiliation(s)
- Walid Osamy
- Computer Science Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha 13513, Egypt
- Unit of Scientific Research, Applied College, Qassim University, Buraydah 52571, Saudi Arabia
| | - Ahmed M Khedr
- Computer Science Department, University of Sharjah, Sharjah 27272, United Arab Emirates
- Mathematics Department, Zagazig University, Zagazig 44523, Egypt
| | - Bader Alwasel
- Unit of Scientific Research, Applied College, Qassim University, Buraydah 52571, Saudi Arabia
| | - Ahmed Salim
- Mathematics Department, Zagazig University, Zagazig 44523, Egypt
- Department of Computer Science, College of Science and Arts, Qassim University, P.O. Box 931, Buridah 51931, Saudi Arabia
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45
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Zehra S, Faseeha U, Syed HJ, Samad F, Ibrahim AO, Abulfaraj AW, Nagmeldin W. Machine Learning-Based Anomaly Detection in NFV: A Comprehensive Survey. Sensors (Basel) 2023; 23:s23115340. [PMID: 37300067 DOI: 10.3390/s23115340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 05/29/2023] [Accepted: 05/30/2023] [Indexed: 06/12/2023]
Abstract
Network function virtualization (NFV) is a rapidly growing technology that enables the virtualization of traditional network hardware components, offering benefits such as cost reduction, increased flexibility, and efficient resource utilization. Moreover, NFV plays a crucial role in sensor and IoT networks by ensuring optimal resource usage and effective network management. However, adopting NFV in these networks also brings security challenges that must promptly and effectively address. This survey paper focuses on exploring the security challenges associated with NFV. It proposes the utilization of anomaly detection techniques as a means to mitigate the potential risks of cyber attacks. The research evaluates the strengths and weaknesses of various machine learning-based algorithms for detecting network-based anomalies in NFV networks. By providing insights into the most efficient algorithm for timely and effective anomaly detection in NFV networks, this study aims to assist network administrators and security professionals in enhancing the security of NFV deployments, thus safeguarding the integrity and performance of sensors and IoT systems.
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Affiliation(s)
- Sehar Zehra
- FAST School of Computing, National University of Computer and Emerging Sciences, Karachi 75030, Pakistan
- College Education & Literacy Department, Khursheed Government Girls Degree College, Government of Sindh, Karachi 75230, Pakistan
| | - Ummay Faseeha
- FAST School of Computing, National University of Computer and Emerging Sciences, Karachi 75030, Pakistan
- Department of Computer Science, Main Campus, Jinnah University For Women, Karachi 74600, Pakistan
| | - Hassan Jamil Syed
- FAST School of Computing, National University of Computer and Emerging Sciences, Karachi 75030, Pakistan
- Faculty of Computing & Informatics, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu 88400, Sabah, Malaysia
- Cyber Security Research Lab, Faculty of Computing and Informatics, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu 88400, Sabah, Malaysia
| | - Fahad Samad
- FAST School of Computing, National University of Computer and Emerging Sciences, Karachi 75030, Pakistan
| | - Ashraf Osman Ibrahim
- Faculty of Computing & Informatics, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu 88400, Sabah, Malaysia
- Creative Advanced Machine Intelligence Research Centre, Faculty of Computing and Informatics, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu 88400, Sabah, Malaysia
| | - Anas W Abulfaraj
- Department of Information Systems, King Abdulaziz University, Rabigh 21911, Saudi Arabia
| | - Wamda Nagmeldin
- Department of Information Systems, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
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46
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Zhou W, Ye KH, Yuan S, Li L. A cycle-level recovery method for embedded processor against HT tamper. Heliyon 2023; 9:e17085. [PMID: 37360108 PMCID: PMC10285180 DOI: 10.1016/j.heliyon.2023.e17085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2023] Open
Abstract
As the core of Internet of Things (IoT), embedded processors are being used more and more extensive. However, embedded processors face various hardware security issues such as hardware trojans (HT) and code tamper attacks. In this paper, a cycle-level recovery method for embedded processor against HT tamper is proposed, which builds two hardware-implementation units, a General-Purpose Register (GPRs) backup unit and a PC rollback unit. Once a HT tamper is detected, the two units will carry out fast recovery through rolling back to the exact PC address corresponding to the wrong instruction and resuming the instruction execution. An open RISC-V core of PULPino is adopted for recovery mechanism verification, the experimental results and hardware costs show that the proposed method could guarantee the processor restore from abnormal state in real time with a reasonable hardware overhead.
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Affiliation(s)
- Wanting Zhou
- Research Institute of Electronic Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xi Yuan Ave., West High-Tech Zone, Chengdu, 611731, Sichuan, China
| | - Kuo-Hui Ye
- Department of Information Management, National Dong Hwa University, No. 1, Sec. 2, Da Hsueh Rd., Shoufeng, Hualien, 97001, Taiwan (Province of China)
| | - Shiwei Yuan
- Research Institute of Electronic Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xi Yuan Ave., West High-Tech Zone, Chengdu, 611731, Sichuan, China
| | - Lei Li
- Research Institute of Electronic Science and Technology, University of Electronic Science and Technology of China, No. 2006, Xi Yuan Ave., West High-Tech Zone, Chengdu, 611731, Sichuan, China
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47
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Molina Araque S, Martinez I, Papadopoulos GZ, Montavont N, Toutain L. Yet Another Compact Time Series Data Representation Using CBOR Templates (YACTS). Sensors (Basel) 2023; 23:s23115124. [PMID: 37299850 DOI: 10.3390/s23115124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 05/23/2023] [Accepted: 05/23/2023] [Indexed: 06/12/2023]
Abstract
The Internet of Things (IoT) technology is growing rapidly, while the IoT devices are being deployed massively. However, interoperability with information systems remains a major challenge for this accelerated device deployment. Furthermore, most of the time, IoT information is presented as Time Series (TS), and while the majority of the studies in the literature focus on the prediction, compression, or processing of TS, no standardized representation format has emerged. Moreover, apart from interoperability, IoT networks contain multiple constrained devices which are designed with limitations, e.g., processing power, memory, or battery life. Therefore, in order to reduce the interoperability challenges and increase the lifetime of IoT devices, this article introduces a new format for TS based on CBOR. The format exploits the compactness of CBOR by leveraging delta values to represent measurements, employing tags to represent variables, and utilizing templates to convert the TS data representation into the appropriate format for the cloud-based application. Moreover, we introduce a new refined and structured metadata to represent additional information for the measurements, then we provide a Concise Data Definition Language (CDDL) code to validate the CBOR structures against our proposal, and finally, we present a detailed performance evaluation to validate the adaptability and the extensibility of our approach. Our performance evaluation results show that the actual data sent by IoT devices can be reduced by between 88% and 94% compared to JavaScript Object Notation (JSON), between 82% and 91% compared to Concise Binary Object Representation (CBOR) and ASN.1, and between 60% and 88% compared to Protocol buffers. At the same time, it can reduce Time-on-Air by between 84% and 94% when a Low Power Wide Area Networks (LPWAN) technology such as LoRaWAN is employed, leading to a 12-fold increase in battery life compared to CBOR format or between a 9-fold and 16-fold increase when compared to Protocol buffers and ASN.1, respectively. In addition, the proposed metadata represent an additional 0.5% of the overall data transmitted in cases where networks such as LPWAN or Wi-Fi are employed. Finally, the proposed template and data format provide a compact representation of TS that can significantly reduce the amount of data transmitted containing the same information, extend the battery life of IoT devices, and improve their lifetime. Moreover, the results show that the proposed approach is effective for different data types and it can be integrated seamlessly into existing IoT systems.
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Affiliation(s)
| | | | | | | | - Laurent Toutain
- IMT Atlantique Campus Rennes, SRCD, IRISA, 35510 Brest, France
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48
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Kumar K, Chaudhri SN, Rajput NS, Shvetsov AV, Sahal R, Alsamhi SH. An IoT-Enabled E-Nose for Remote Detection and Monitoring of Airborne Pollution Hazards Using LoRa Network Protocol. Sensors (Basel) 2023; 23:4885. [PMID: 37430799 DOI: 10.3390/s23104885] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 05/05/2023] [Accepted: 05/09/2023] [Indexed: 07/12/2023]
Abstract
Detection and monitoring of airborne hazards using e-noses has been lifesaving and prevented accidents in real-world scenarios. E-noses generate unique signature patterns for various volatile organic compounds (VOCs) and, by leveraging artificial intelligence, detect the presence of various VOCs, gases, and smokes onsite. Widespread monitoring of airborne hazards across many remote locations is possible by creating a network of gas sensors using Internet connectivity, which consumes significant power. Long-range (LoRa)-based wireless networks do not require Internet connectivity while operating independently. Therefore, we propose a networked intelligent gas sensor system (N-IGSS) which uses a LoRa low-power wide-area networking protocol for real-time airborne pollution hazard detection and monitoring. We developed a gas sensor node by using an array of seven cross-selective tin-oxide-based metal-oxide semiconductor (MOX) gas sensor elements interfaced with a low-power microcontroller and a LoRa module. Experimentally, we exposed the sensor node to six classes i.e., five VOCs plus ambient air and as released by burning samples of tobacco, paints, carpets, alcohol, and incense sticks. Using the proposed two-stage analysis space transformation approach, the captured dataset was first preprocessed using the standardized linear discriminant analysis (SLDA) method. Four different classifiers, namely AdaBoost, XGBoost, Random Forest (RF), and Multi-Layer Perceptron (MLP), were then trained and tested in the SLDA transformation space. The proposed N-IGSS achieved "all correct" identification of 30 unknown test samples with a low mean squared error (MSE) of 1.42 × 10-4 over a distance of 590 m.
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Affiliation(s)
- Kanak Kumar
- Department of Electronics Engineering, Indian Institute of Technology (BHU), Varanasi 221005, India
| | - Shiv Nath Chaudhri
- Department of Electronics Engineering, Indian Institute of Technology (BHU), Varanasi 221005, India
- Department of Electronics and Communication Engineering, Santhiram Engineering College, Nandyal 518501, India
| | - Navin Singh Rajput
- Department of Electronics Engineering, Indian Institute of Technology (BHU), Varanasi 221005, India
| | - Alexey V Shvetsov
- Department of Smart Technologies, Moscow Polytechnic University, 107023 Moscow, Russia
- Department of Transport, North-Eastern Federal University, 677000 Yakutsk, Russia
| | - Radhya Sahal
- School of Computer Science and IT, University College Cork, T12 K8AF Cork, Ireland
- Faculty of Computer Science and Engineering, Hodeidah University, Al Hodeidah P.O. Box 3114, Yemen
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49
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Jara Ochoa HJ, Peña R, Ledo Mezquita Y, Gonzalez E, Camacho-Leon S. Comparative Analysis of Power Consumption between MQTT and HTTP Protocols in an IoT Platform Designed and Implemented for Remote Real-Time Monitoring of Long-Term Cold Chain Transport Operations. Sensors (Basel) 2023; 23:4896. [PMID: 37430809 DOI: 10.3390/s23104896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/05/2023] [Accepted: 05/12/2023] [Indexed: 07/12/2023]
Abstract
IoT platforms for the transportation industry are portable with limited battery life and need real-time and long-term monitoring operations. Since MQTT and HTTP are widely used as the main communication protocols in the IoT, it is imperative to analyze their power consumption to provide quantitative results that help maximize battery life in IoT transportation systems. Although is well known that MQTT consumes less power than HTTP, a comparative analysis of their power consumption with long-time tests and different conditions has not yet been conducted. In this sense, a design and validation of an electronic cost-efficient platform system for remote real-time monitoring is proposed using a NodeMCU module, in which experimentation is carried out for HTTP and MQTT with different QoS levels to make a comparison and demonstrate the differences in power consumption. Furthermore, we characterize the behavior of the batteries in the systems and compare the theoretical analysis with real long-time test results. The experimentation using the MQTT protocol with QoS 0 and 1 was successful, resulting in power savings of 6.03% and 8.33%, respectively, compared with HTTP, demonstrating many more hours in the duration of the batteries, which could be very useful in technological solutions for the transport industry.
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Affiliation(s)
- Heriberto J Jara Ochoa
- Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico
| | - Raul Peña
- Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico
| | - Yoel Ledo Mezquita
- Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico
| | - Enrique Gonzalez
- Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico
| | - Sergio Camacho-Leon
- Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico
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50
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Wang D, Lin Y, Hu J, Zhang C, Zhong Q. FPGA Implementation for Elliptic Curve Cryptography Algorithm and Circuit with High Efficiency and Low Delay for IoT Applications. Micromachines (Basel) 2023; 14:mi14051037. [PMID: 37241660 DOI: 10.3390/mi14051037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 05/08/2023] [Accepted: 05/09/2023] [Indexed: 05/28/2023]
Abstract
The Internet of Things requires greater attention to the security and privacy of the network. Compared to other public-key cryptosystems, elliptic curve cryptography can provide better security and lower latency with shorter keys, rendering it more suitable for IoT security. This paper presents a high-efficiency and low-delay elliptic curve cryptographic architecture based on the NIST-p256 prime field for IoT security applications. A modular square unit utilizes a fast partial Montgomery reduction algorithm, demanding just a mere four clock cycles to complete a modular square operation. The modular square unit can be computed simultaneously with the modular multiplication unit, consequently improving the speed of point multiplication operations. Synthesized on the Xilinx Virtex-7 FPGA platform, the proposed architecture completes one PM operation in 0.08 ms using 23.1 k LUTs at 105.3 MHz. These results show significantly better performance compared to that in previous works.
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Affiliation(s)
- Deming Wang
- School of Electronics and Information Engineering, South China Normal University, Foshan 528225, China
- Development Research Institute of Guangzhou Smart City, Guangzhou 510805, China
| | - Yuhang Lin
- School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou 510006, China
| | - Jianguo Hu
- Development Research Institute of Guangzhou Smart City, Guangzhou 510805, China
- School of Microelectronics Science and Technology, Sun Yat-sen University, Zhuhai 519082, China
| | - Chong Zhang
- School of Microelectronics Science and Technology, Sun Yat-sen University, Zhuhai 519082, China
| | - Qinghua Zhong
- School of Electronics and Information Engineering, South China Normal University, Foshan 528225, China
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