Implementation and Evaluation of Four Interoperable Open Standards for the Internet of Things

An Interoperable Architecture for the Internet of COVID-19 Things (IoCT) Using Open Geospatial Standards-Case Study: Workplace Reopening

To safely protect workplaces and the workforce during and after the COVID-19 pandemic, a scalable integrated sensing solution is required in order to offer real-time situational awareness and early warnings for decision-makers. However, an information-based solution for industry reopening is ineffective when the necessary operational information is locked up in disparate real-time data silos. There is a lot of ongoing effort to combat the COVID-19 pandemic using different combinations of low-cost, location-based contact tracing, and sensing technologies. These ad hoc Internet of Things (IoT) solutions for COVID-19 were developed using different data models and protocols without an interoperable way to interconnect these heterogeneous systems and exchange data on people and place interactions. This research aims to design and develop an interoperable Internet of COVID-19 Things (IoCT) architecture that is able to exchange, aggregate, and reuse disparate IoT sensor data sources in order for informed decisions to be made after understanding the real-time risks in workplaces based on person-to-place interactions. The IoCT architecture is based on the Sensor Web paradigm that connects various Things, Sensors, and Datastreams with an indoor geospatial data model. This paper presents a study of what, to the best of our knowledge, is the first real-world integrated implementation of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) and IndoorGML standards to calculate the risk of COVID-19 online using a workplace reopening case study. The proposed IoCT offers a new open standard-based information model, architecture, methodologies, and software tools that enable the interoperability of disparate COVID-19 monitoring systems with finer spatial-temporal granularity. A workplace cleaning use case was developed in order to demonstrate the capabilities of this proposed IoCT architecture. The implemented IoCT architecture included proximity-based contact tracing, people density sensors, a COVID-19 risky behavior monitoring system, and the contextual building geospatial data.

GRAFT: A Model for Evaluating Actuator Systems in terms of Force Production

In the scope of evaluation methodologies for Internet of Things (IoT) systems, some approaches concern security, while others latency. However, some methodologies evaluate systems that contain active entities, so-called actuators. In this paper, we propose a novel methodology for evaluating such systems with actuator components using Graph Representation of the Angle of the Force and Time (GRAFT). GRAFT facilitates easy computation of the net force produced by physical or mechanical acts occurring on a daily basis on Earth. We use laws and definitions of physics describing the relations between Speed, Distance, and Time (SDT), apply them in a heliocentric system, and model the considered systems with a graph. The continuous movement of the Earth was shown to be weakening the total produced net force in some systems. We considered this weakening issue a problem, and we propose two possible solutions to overcome it by using restoration values, or reordering actuator sessions, in GRAFT to arrive to a more force-efficient system. We compared our default GRAFT algorithm to a special implementation using the Clock-Angle-Problem (CAP) for sessions. We also study and discuss an IoT-focused case for validating our approach, and we present a detailed explanation of the proposed GRAFT algorithm. The experimental results show the ability of GRAFT to provide highly accurate results, which also exemplifies that our GRAFT approach is programmable, hence deployable in real life scenarios.

An Internet of Things-Based Low-Power Integrated Beekeeping Safety and Conditions Monitoring System

This paper proposes a holistic management and control system for the apiculture industry (Integrated Beekeeping System of holistic Management and Control – IBSMC). This integrated beehive array system mainly focuses on the regulation of bees living conditions, targeting both minimizing bee swarm mortality and maximizing productivity. Within the proposed IBSMC system architecture, additional security functionalities are implemented for bee monitoring, low energy consumption and incidents response. As a complete unit, the proposed IBSMC system is both a hive conditions monitoring and safety system. It communicates with the outer world using low power RF data transmission and the LoRaWAN transceivers. This paper presents the proposed IBSMC architecture consisting of new beehive cells embedded with functionalities for integrated conditions regulation and security provisions, as well as the communication protocols used for facility-conditions management, incidents’ acquisition and incidents’ response.

IoT in Healthcare: Achieving Interoperability of High-Quality Data Acquired by IoT Medical Devices

It is an undeniable fact that Internet of Things (IoT) technologies have become a milestone advancement in the digital healthcare domain, since the number of IoT medical devices is grown exponentially, and it is now anticipated that by 2020 there will be over 161 million of them connected worldwide. Therefore, in an era of continuous growth, IoT healthcare faces various challenges, such as the collection, the quality estimation, as well as the interpretation and the harmonization of the data that derive from the existing huge amounts of heterogeneous IoT medical devices. Even though various approaches have been developed so far for solving each one of these challenges, none of these proposes a holistic approach for successfully achieving data interoperability between high-quality data that derive from heterogeneous devices. For that reason, in this manuscript a mechanism is produced for effectively addressing the intersection of these challenges. Through this mechanism, initially, the collection of the different devices’ datasets occurs, followed by the cleaning of them. In sequel, the produced cleaning results are used in order to capture the levels of the overall data quality of each dataset, in combination with the measurements of the availability of each device that produced each dataset, and the reliability of it. Consequently, only the high-quality data is kept and translated into a common format, being able to be used for further utilization. The proposed mechanism is evaluated through a specific scenario, producing reliable results, achieving data interoperability of 100% accuracy, and data quality of more than 90% accuracy.

Towards Establishing Cross-Platform Interoperability for Sensors in Smart Cities

Typically, smart city projects involve complex distributed systems having multiple stakeholders and diverse applications. These applications involve a multitude of sensor and IoT platforms for managing different types of timeseries observations. In many scenarios, timeseries data is the result of specific simulations and is stored in databases and even simple files. To make well-informed decisions, it is essential to have a proper data integration strategy, which must allow working with heterogeneous data sources and platforms in interoperable ways. In this paper, we present a new lightweight web service called InterSensor Service allowing to simply connect to multiple IoT platforms, simulation specific data, databases, and simple files and retrieving their observations without worrying about data storage and the multitude of different APIs. The service encodes these observations “on-the-fly” according to the standardized external interfaces such as the OGC Sensor Observation Service and OGC SensorThings API. In this way, the heterogeneous observations can be analyzed and visualized in a unified way. The service can be deployed not only by the users to connect to different sources but also by providers and stakeholders to simply add further interfaces to their platforms realizing interoperability according to international standards. We have developed a Java-based implementation of the InterSensor Service, which is being offered free as open source software. The service is already being used in smart city projects and one application for the district Queen Elizabeth Olympic Park in London is shown in this paper.

Development of Virtual Resource Based IoT Proxy for Bridging Heterogeneous Web Services in IoT Networks

The Internet of Things is comprised of heterogeneous devices, applications, and platforms using multiple communication technologies to connect the Internet for providing seamless services ubiquitously. With the requirement of developing Internet of Things products, many protocols, program libraries, frameworks, and standard specifications have been proposed. Therefore, providing a consistent interface to access services from those environments is difficult. Moreover, bridging the existing web services to sensor and actuator networks is also important for providing Internet of Things services in various industry domains. In this paper, an Internet of Things proxy is proposed that is based on virtual resources to bridge heterogeneous web services from the Internet to the Internet of Things network. The proxy enables clients to have transparent access to Internet of Things devices and web services in the network. The proxy is comprised of server and client to forward messages for different communication environments using the virtual resources which include the server for the message sender and the client for the message receiver. We design the proxy for the Open Connectivity Foundation network where the virtual resources are discovered by the clients as Open Connectivity Foundation resources. The virtual resources represent the resources which expose services in the Internet by web service providers. Although the services are provided by web service providers from the Internet, the client can access services using the consistent communication protocol in the Open Connectivity Foundation network. For discovering the resources to access services, the client also uses the consistent discovery interface to discover the Open Connectivity Foundation devices and virtual resources.

Middleware for Plug and Play Integration of Heterogeneous Sensor Resources into the Sensor Web

The study of global phenomena requires the combination of a considerable amount of data coming from different sources, acquired by different observation platforms and managed by institutions working in different scientific fields. Merging this data to provide extensive and complete data sets to monitor the long-term, global changes of our oceans is a major challenge. The data acquisition and data archival procedures usually vary significantly depending on the acquisition platform. This lack of standardization ultimately leads to information silos, preventing the data to be effectively shared across different scientific communities. In the past years, important steps have been taken in order to improve both standardization and interoperability, such as the Open Geospatial Consortium's Sensor Web Enablement (SWE) framework. Within this framework, standardized models and interfaces to archive, access and visualize the data from heterogeneous sensor resources have been proposed. However, due to the wide variety of software and hardware architectures presented by marine sensors and marine observation platforms, there is still a lack of uniform procedures to integrate sensors into existing SWE-based data infrastructures. In this work, a framework aimed to enable sensor plug and play integration into existing SWE-based data infrastructures is presented. First, an analysis of the operations required to automatically identify, configure and operate a sensor are analysed. Then, the metadata required for these operations is structured in a standard way. Afterwards, a modular, plug and play, SWE-based acquisition chain is proposed. Finally different use cases for this framework are presented.

Tracking the Evolution of the Internet of Things Concept Across Different Application Domains

Both the idea and technology for connecting sensors and actuators to a network to remotely monitor and control physical systems have been known for many years and developed accordingly. However, a little more than a decade ago the concept of the Internet of Things (IoT) was coined and used to integrate such approaches into a common framework. Technology has been constantly evolving and so has the concept of the Internet of Things, incorporating new terminology appropriate to technological advances and different application domains. This paper presents the changes that the IoT has undertaken since its conception and research on how technological advances have shaped it and fostered the arising of derived names suitable to specific domains. A two-step literature review through major publishers and indexing databases was conducted; first by searching for proposals on the Internet of Things concept and analyzing them to find similarities, differences, and technological features that allow us to create a timeline showing its development; in the second step the most mentioned names given to the IoT for specific domains, as well as closely related concepts were identified and briefly analyzed. The study confirms the claim that a consensus on the IoT definition has not yet been reached, as enabling technology keeps evolving and new application domains are being proposed. However, recent changes have been relatively moderated, and its variations on application domains are clearly differentiated, with data and data technologies playing an important role in the IoT landscape.