Design and development of nEMoS, an all-in-one, low-cost, web-connected and 3D-printed device for environmental analysis

Effect of Three-Dimensional-Printed Thermoplastics Used in Sensor Housings on Common Atmospheric Trace Gasses

Low-cost air quality sensors (LCSs) are becoming more ubiquitous as individuals and communities seek to reduce their exposure to poor air quality. Compact, efficient, and aesthetically designed sensor housings that do not interfere with the target air quality measurements are a necessary component of a low-cost sensing system. The selection of appropriate housing material can be an important factor in air quality applications employing LCSs. Three-dimensional printing, specifically fused deposition modeling (FDM), is a standard for prototyping and small-scale custom plastics production because of its low cost and ability for rapid iteration. However, little information exists about whether FDM-printed thermoplastics affect measurements of trace atmospheric gasses. This study investigates how five different FDM-printed thermoplastics (ABS, PETG, PLA, PC, and PVDF) affect the concentration of five common atmospheric trace gasses (CO, CO2, NO, NO2, and VOCs). The laboratory results show that the thermoplastics, except for PVDF, exhibit VOC off-gassing. The results also indicate no to limited interaction between all of the thermoplastics and CO and CO2 and a small interaction between all of the thermoplastics and NO and NO2.

Environmental Quality bOX (EQ-OX): A Portable Device Embedding Low-Cost Sensors Tailored for Comprehensive Indoor Environmental Quality Monitoring

The continuous monitoring of indoor environmental quality (IEQ) plays a crucial role in improving our understanding of the prominent parameters affecting building users' health and perception of their environment. In field studies, indoor environment monitoring often does not go beyond the assessment of air temperature, relative humidity, and CO2 concentration, lacking consideration of other important parameters due to budget constraints and the complexity of multi-dimensional signal analyses. In this paper, we introduce the Environmental Quality bOX (EQ-OX) system, which was designed for the simultaneous monitoring of quantities of some of the main IEQs with a low level of uncertainty and an affordable cost. Up to 15 parameters can be acquired at a time. The system embeds only low-cost sensors (LCSs) within a compact case, enabling vast-scale monitoring campaigns in residential and office buildings. The results of our laboratory and field tests show that most of the selected LCSs can match the accuracy required for indoor campaigns. A lightweight data processing algorithm has been used for the benchmark. Our intent is to estimate the correlation achievable between the detected quantities and reference measurements when a linear correction is applied. Such an approach allows for a preliminary assessment of which LCSs are the most suitable for a cost-effective IEQ monitoring system.

Effects of 3D-printed bulking agent on microbial community succession and carbohydrate-active enzymes genes during swine manure composting

The bulking agent plays an important role in aerobic composting, but their shape, porosity, and homogeneity need to be optimized. In the present work, a bulking agent with a uniform shape was prepared by 3D printing to explore its influence on physicochemical parameters, microbial community succession, and gene abundance of carbohydrate-active enzymes (CAZymes) in swine manure aerobic composting. The results showed that adding 3D-printed bulking agents can increase maximum temperature, prolong the thermophilic period, and improve the degradation rate of volatile solids, which was attributed to ameliorative air permeability by the porous 3D-printed bulking agent. The abundances of some pathogenic bacteria decreased and CAZymes genes increased respectively in response to the addition of the 3D-printed bulking agent, implying it has a certain positive effect on improving the safety of compost products and promoting the degradation of organic matter. In summary, the 3D-printed bulking agent has good application potential in laboratory-scale aerobic composting.

A Low-Cost Sensor Network for Real-Time Thermal Stress Monitoring and Communication in Occupational Contexts

The MoBiMet (Mobile Biometeorology System) is a low-cost device for thermal comfort monitoring, designed for long-term deployment in indoor or semi-outdoor occupational contexts. It measures air temperature, humidity, globe temperature, brightness temperature, light intensity, and wind, and is capable of calculating thermal indices (e.g., physiologically equivalent temperature (PET)) on site. It visualizes its data on an integrated display and sends them continuously to a server, where web-based visualizations are available in real-time. Data from many MoBiMets deployed in real occupational settings were used to demonstrate their suitability for large-scale and continued monitoring of thermal comfort in various contexts (industrial, commercial, offices, agricultural). This article describes the design and the performance of the MoBiMet. Alternative methods to determine mean radiant temperature (T_mrt) using a light intensity sensor and a contactless infrared thermopile were tested next to a custom-made black globe thermometer. Performance was assessed by comparing the MoBiMet to an independent mid-cost thermal comfort sensor. It was demonstrated that networked MoBiMets can detect differences of thermal comfort at different workplaces within the same building, and between workplaces in different companies in the same city. The MoBiMets can capture spatial and temporal differences of thermal comfort over the diurnal cycle, as demonstrated in offices with different stories and with different solar irradiances in a single high-rise building. The strongest sustained heat stress was recorded at industrial workplaces with heavy machinery.

Development of IoT-Based Particulate Matter Monitoring System for Construction Sites

Particulate matters (PMs) generated on construction sites can pose serious health risks to field workers and residents living near construction sites. PMs are generated in a wide range of locations; therefore, they must be managed in real time at various locations within construction sites for practical management of the PMs. However, no such systems exist currently. Therefore, this study aims to develop a system that can manage PMs in real time at multiple locations in a construction site using the Internet of Things technology. Accordingly, measuring instrument, network, and program services were developed as system components, while considering the characteristics of construction sites, and the construction site PM monitoring system was developed by integrating these components. Finally, performance certification and field application tests were performed to verify the developed system. The construction site PM monitoring system (CPMS) achieved grade 1 for reproducibility, relative precision, and data acquisition rate, and grade 2 for accuracy and coefficient of determination. Thus, it received a performance certification of grade 2, in total. In particular, regarding accuracy, which is a shortcoming of the light-scattering method and represents the accuracy of measurements, the CPMS was found to have an accuracy of 74.2%.

Sensors for indoor air quality monitoring and assessment through Internet of Things: a systematic review

The growing populations around the world are closely associated with rising levels of air pollution. The impact is not restricted to outdoor areas. Moreover, the health of building occupants is also deteriorating due to poor indoor air quality. As per the World Health Organization, indoor air pollution is a leading cause of 1.6 million premature deaths annually. Therefore, numerous companies have started the development of low-cost sensors to monitor indoor air pollution with the Internet of Things-based applications. However, due to the close association of air pollution levels to the mortality and morbidity rates, communities face several limitations while selecting sensors to address this public health challenge. The main contribution of this systematic review is to present a qualitative and quantitative evaluation of low-cost sensors while providing deep insights into the selection criteria for adequate monitoring. The authors in this paper discussed studies published after the year 2015, and it includes an analysis of papers published in the English language only. Moreover, this study highlights crucial research questions, states answers, and provides recommendations for future research studies. The outcomes of this paper will be useful for students, researchers, and industry members concerning the upcoming research and manufacturing activities. The results show that 28 studies (70%) include indoor thermal comfort assessment, 26 (65%) and 12 (30%) studies include CO₂ and CO sensors, respectively. In total, 32 (45.7%) out of 71 sensors (whose prices are available) discussed in this study are available in a price below the US $20 over online marketplaces. Furthermore, the authors conclude that 77.5% of the analyzed literature does not include calibration details, and the accuracy specification is missing for 39.4% sensors.

Development of low-cost indoor air quality monitoring devices: Recent advancements

The use of low-cost sensor technology to monitor air pollution has made remarkable strides in the last decade. The development of low-cost devices to monitor air quality in indoor environments can be used to understand the behaviour of indoor air pollutants and potentially impact on the reduction of related health impacts. These user-friendly devices are portable, require low-maintenance, and can enable near real-time, continuous monitoring. They can also contribute to citizen science projects and community-driven science. However, low-cost sensors have often been associated with design compromises that hamper data reliability. Moreover, with the rapidly increasing number of studies, projects, and grey literature based on low-cost sensors, information got scattered. Intending to identify and review scientifically validated literature on this topic, this study critically summarizes the recent research pertinent to the development of indoor air quality monitoring devices using low-cost sensors. The method employed for this review was a thorough search of three scientific databases, namely: ScienceDirect, IEEE, and Scopus. A total of 891 titles published since 2012 were found and scanned for relevance. Finally, 41 research articles consisting of 35 unique device development projects were reviewed with a particular emphasis on device development: calibration and performance of sensors, the processor used, data storage and communication, and the availability of real-time remote access of sensor data. The most prominent finding of the study showed a lack of studies consisting of sensor performance as only 16 out of 35 projects performed calibration/validation of sensors. An even fewer number of studies conducted these tests with a reference instrument. Hence, a need for more studies with calibration, credible validation, and standardization of sensor performance and assessment is recommended for subsequent research.

Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review

Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is reported as one of the potential causes of several chronic health problems such as lung cancer, cardiovascular disease, and respiratory infections. Moreover, smart cities projects are promoting the use of real-time monitoring systems to detect unfavorable scenarios for enhanced living environments. The main objective of this work is to present a systematic review of the current state of the art on indoor air quality monitoring systems based on the Internet of Things. The document highlights design aspects for monitoring systems, including sensor types, microcontrollers, architecture, and connectivity along with implementation issues of the studies published in the previous five years (2015-2020). The main contribution of this paper is to present the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. The results show that 70%, 65%, and 27.5% of studies focused on monitoring thermal comfort parameters, CO₂, and PM levels, respectively. Additionally, there are 37.5% and 35% of systems based on Arduino and Raspberry Pi controllers. Only 22.5% of studies followed the calibration approach before system implementation, and 72.5% of systems claim energy efficiency.

Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review

Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is reported as one of the potential causes of several chronic health problems such as lung cancer, cardiovascular disease, and respiratory infections. Moreover, smart cities projects are promoting the use of real-time monitoring systems to detect unfavorable scenarios for enhanced living environments. The main objective of this work is to present a systematic review of the current state of the art on indoor air quality monitoring systems based on the Internet of Things. The document highlights design aspects for monitoring systems, including sensor types, microcontrollers, architecture, and connectivity along with implementation issues of the studies published in the previous five years (2015-2020). The main contribution of this paper is to present the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. The results show that 70%, 65%, and 27.5% of studies focused on monitoring thermal comfort parameters, CO2, and PM levels, respectively. Additionally, there are 37.5% and 35% of systems based on Arduino and Raspberry Pi controllers. Only 22.5% of studies followed the calibration approach before system implementation, and 72.5% of systems claim energy efficiency.

A Scoping Review of Technological Approaches to Environmental Monitoring

Indoor environment quality (IEQ) can negatively affect occupant health and wellbeing. Air quality, as well as thermal, visual and auditory conditions, can determine how comfortable occupants feel within buildings. Some can be measured objectively, but many are assessed by interpreting qualitative responses. Continuous monitoring by passive sensors may be useful to identify links between environmental and physiological changes. Few studies localise measurements to an occupant level perhaps due to many environmental monitoring solutions being large and expensive. Traditional models for occupant comfort analysis often exacerbate this by not differentiating between individual building occupants. This scoping review aims to understand IEQ and explore approaches as to how it is measured with various sensing technologies, identifying trends for monitoring occupant health and wellbeing. Twenty-seven studies were reviewed, and more than 60 state-of-the-art and low-cost IEQ sensors identified. Studies were found to focus on the home or workplace, but not both. This review also found how wearable technology could be used to augment IEQ measurements, creating personalised approaches to health and wellbeing. Opportunities exist to make individuals the primary unit of analysis. Future research should explore holistic personalised approaches to health monitoring in buildings that analyse the individual as they move between environments.

A review of 3D printing techniques for environmental applications

With a wide variety of techniques and compatible materials, three-dimensional (3D) printing is becoming increasingly useful in environmental applications in air, water, and energy. Through the advantages of quick production, cost-effectiveness, customizable design, the ability to produce complex geometries, and more, 3D printing has supported improvements to air quality monitors, filters, membranes, separation devices for water treatment, microbial fuel cells, solar cells, and wind turbines. It also supports sustainable manufacturing through reduced material waste, energy use, and carbon emissions. Applications of 3D printing within four environmental disciplines are described in this article: sustainable manufacturing, air quality, water and wastewater, and alternative energy sources.

Elemental: An Open-Source Wireless Hardware and Software Platform for Building Energy and Indoor Environmental Monitoring and Control

This work demonstrates an open-source hardware and software platform for monitoring the performance of buildings, called Elemental, that is designed to provide data on indoor environmental quality, energy usage, HVAC operation, and other factors to its users. It combines: (i) custom printed circuit boards (PCBs) with RFM69 frequency shift keying (FSK) radio frequency (RF) transceivers for wireless sensors, control nodes, and USB gateway, (ii) a Raspberry Pi 3B with custom firmware acting as either a centralized or distributed backhaul, and (iii) a custom dockerized application for the backend called Brood that serves as the director software managing message brokering via Message Queuing Telemetry Transport (MQTT) protocol using VerneMQ, database storage using InfluxDB, and data visualization using Grafana. The platform is built around the idea of a private, secure, and open technology for the built environment. Among its many applications, the platform allows occupants to investigate anomalies in energy usage, environmental quality, and thermal performance via a comprehensive dashboard with rich querying capabilities. It also includes multiple frontends to view and analyze building activity data, which can be used directly in building controls or to provide recommendations on how to increase operational efficiency or improve operating conditions. Here, we demonstrate three distinct applications of the Elemental platform, including: (1) deployment in a research lab for long-term data collection and automated analysis, (2) use as a full-home energy and environmental monitoring solution, and (3) fault and anomaly detection and diagnostics of individual building systems at the zone-level. Through these applications we demonstrate that the platform allows easy and virtually unlimited datalogging, monitoring, and analysis of real-time sensor data with low setup costs. Low-power sensor nodes placed in abundance in a building can also provide precise and immediate fault-detection, allowing for tuning equipment for more efficient operation and faster maintenance during the lifetime of the building.

mHealth: Indoor Environmental Quality Measuring System for Enhanced Health and Well-Being Based on Internet of Things

Mobile health research field aims to provide access to healthcare anytime and anywhere through mobile computing technologies while using a cost-effective approach. Mobile health is closely related to ambient assisted living as both research fields address independence in elderly adults. Aging has become a relevant challenge, as it is anticipated that 20% of world population will be aged 60 years and older in 2050. Most people spend more than 90% of their time indoors, therefore the indoor environmental quality has a relevant impact on occupant’s health and well-being. We intended to provide real-time indoor quality monitoring for enhanced living environments and occupational health. This paper presents the AirPlus real-time indoor environmental quality monitoring system, which incorporates several advantages when compared to other systems, such as scalability, flexibility, modularity, easy installation, and configuration, as well as mobile computing software for data consulting and notifications. The results that were obtained are promising and present a significant contribution to the monitoring solutions available in the literature. AirPlus provides a rich dataset to plan interventions for enhanced indoor quality, but also to support clinical diagnostics and correlate occupant’s health problems with their living environment conditions.

Development and field testing of low-cost, quantal microbial assays with volunteer reporting as scalable means of drinking water safety estimation

AIMS

To evaluate a low-cost water quality test for at-scale drinking water safety estimation in rural India.

METHODS AND RESULTS

Within a longitudinal study to characterize variability in household drinking water safety in rural Maharashtra, we piloted a low-cost presence-absence (LCPA) microbial test designed to be used by volunteer residents in rural areas. In comparing the LCPA results with standard laboratory methods for enumeration of Escherichia coli, we found that LCPA tests using modified mTec media were highly sensitive in detecting drinking water of moderate risk (88% of tests were positive at E. coli counts of 11-100 CFU per 100 ml) and high risk (96% of tests were positive at E. coli counts of 101 + CFU per 100 ml). The LCPA tests demonstrated low specificity for E. coli specifically, due to concurrent detection of Klebsiella: 38% of LCPA tests were positive even when E. coli was not detected in a 100 ml sample by membrane filtration, suggesting the test would be conservative in risk estimation. We also found that 47% of participants in rural villages in India were willing to conduct tests and return results after a brief training, with 45% of active participants sending their water testing results via short message service.

CONCLUSIONS

Given their low cost (~US$0.50 as piloted) and open-source format, such tests may provide a compelling alternative to standard methods for rapid water quality assessments, especially in resource-limited settings.

SIGNIFICANCE AND IMPACT OF THE STUDY

The lack of availability of water quality data constrains efforts to monitor, evaluate and improve the safety of water and sanitation infrastructure in underserved settings. Current water testing methods are not scalable because of laboratory and cost constraints. Our findings indicate the LCPA or similar low-cost microbial tests could be useful in rapid water safety estimation, including via crowdsourcing.

Indoor Air Quality Assessment Using a CO2 Monitoring System Based on Internet of Things

Indoor air quality (IAQ) parameters are not only directly related to occupational health but also have a significant impact on quality of life as people typically spend more than 90% of their time in indoor environments. Although IAQ is not usually monitored, it must be perceived as a relevant issue to follow up for the inhabitants' well-being and comfort for enhanced living environments and occupational health. Carbon dioxide (CO₂) has a substantial influence on public health and can be used as an essential index of IAQ. CO₂ levels over 1000 ppm, indicates an indoor air potential problem. Monitoring CO₂ concentration in real-time is essential to detect IAQ issues to quickly intervene in the building. The continuous technological advances in several areas such as Ambient Assisted Living and the Internet of Things (IoT) make it possible to build smart objects with significant capabilities for sensing and connecting. This paper presents the iAirCO₂ system, a solution for CO₂ real-time monitoring based on IoT architecture. The iAirCO₂ is composed of a hardware prototype for ambient data collection and a Web and smartphone software for data consulting. In future, it is planned that these data can be accessed by doctors in order to support medical diagnostics. Compared to other solutions, the iAirCO₂ is based on open-source technologies, providing a total Wi-Fi system, with several advantages such as its modularity, scalability, low-cost, and easy installation. The results reveal that the system can generate a viable IAQ appraisal, allowing to anticipate technical interventions that contribute to a healthier living environment.

A Cost-Effective Air Quality Supervision Solution for Enhanced Living Environments through the Internet of Things

We spend about 90% of our lives in indoor living environments. Thus, it is essential to provide indoor air quality monitoring for enhanced living environments. Advances in networking, sensors, and embedded devices have made monitoring and supply of assistance possible to people in their homes. Technological advancements have made possible the building of smart devices with significant capabilities for sensing and connecting, but also provide several improvements in ambient assisted living system architectures. Indoor air quality assumes an important role in building productive and healthy indoor environments. In this paper, the authors present an Internet of Things system for real-time indoor air quality monitoring named iAir. This system is composed by an ESP8266 as the communication and processing unit and a MICS-6814 sensor as the sensing unit. The MICS-6814 is a metal oxide semiconductor sensor capable of detecting several gases such as carbon monoxide, nitrogen dioxide, ethanol, methane, and propane. The iAir system also provides a smartphone application for data consulting and real-time notifications. Compared to other solutions, the iAir system is based on open-source technologies and operates as a totally Wi-Fi system, with several advantages such as its modularity, scalability, low cost, and easy installation. The results obtained are very promising, representing a meaningful contribution for enhanced living environments as iAir provides real-time monitoring for enhanced ambient assisted living and occupational health.

An Internet of Things-Based Environmental Quality Management System to Supervise the Indoor Laboratory Conditions

Indoor air quality (IAQ) is not only a determinant of occupational health but also influences all indoor human behaviours. In most university establishments, laboratories are also used as classrooms. On one hand, indoor environment quality (IEQ) conditions supervision in laboratories is relevant for experimental activities. On the other hand, it is also crucial to provide a healthy and productive workplace for learning activities. The proliferation of cost-effective sensors and microcontrollers along with the Internet of Things (IoT) architectures enhancements, enables the development of automatic solutions to supervise the Laboratory Environmental Conditions (LEC). This paper aims to present a real-time IEQ-laboratory data collection system-based IoT architecture named iAQ Plus (iAQ+). The iAQ+ incorporates an integrated Web management system along with a smartphone application to provide a historical analysis of the LEC. The iAQ+ collects IAQ index, temperature, relative humidity and barometric pressure. The results obtained are promising, representing a meaningful contribution for IEQ supervision solutions based on IoT. iAQ+ supports push notifications to alert people in a timely way for enhanced living environments and occupational health, as well as a work mode feature, so the user can configure setpoints for laboratory mode and schoolroom mode. Using the iAQ+, it is possible to provide an integrated management of data information of the spatio-temporal variations of LEC parameters which are particularly significant not only for enhanced living environments but also for laboratory experiments.

A Comprehensive IoT Node Proposal Using Open Hardware. A Smart Farming Use Case to Monitor Vineyards

The last decade has witnessed a significant reduction in prices and an increased performance of electronic components, coupled with the influence of the shift towards the generation of open resources, both in terms of knowledge (open access), programs (open-source software), and components (open hardware). This situation has produced different effects in today’s society, among which is the empowerment of citizens, called makers, who are themselves able to generate citizen science or build assembly developments. Situated in the context described above, the current study follows a Do-It-Yourself (DIY) approach. In this way, it attempts to define a conceptual design of an Internet of Things (IoT) node, which is reproducible at both physical and behavioral levels, to build IoT nodes which can cover any scenario. To test this conceptual design, this study proposes a sensorization node to monitor meteorological phenomena. The node is called SEnviro (node) and features different improvements such as: the possibility of remote updates using Over-the-Air (OTA) updates; autonomy, using 3G connectivity, a solar panel, and applied energy strategies to prolong its life; and replicability, because it is made up of open hardware and other elements such as 3D-printed pieces. The node is validated in the field of smart agriculture, with the aim of monitoring different meteorological phenomena, which will be used as input to disease detection models to detect possible diseases within vineyards.

Integrated Method for Personal Thermal Comfort Assessment and Optimization through Users' Feedback, IoT and Machine Learning: A Case Study †

Thermal comfort has become a topic issue in building performance assessment as well as energy efficiency. Three methods are mainly recognized for its assessment. Two of them based on standardized methodologies, face the problem by considering the indoor environment in steady-state conditions (PMV and PPD) and users as active subjects whose thermal perception is influenced by outdoor climatic conditions (adaptive approach). The latter method is the starting point to investigate thermal comfort from an overall perspective by considering endogenous variables besides the traditional physical and environmental ones. Following this perspective, the paper describes the results of an in-field investigation of thermal conditions through the use of nearable and wearable solutions, parametric models and machine learning techniques. The aim of the research is the exploration of the reliability of IoT-based solutions combined with advanced algorithms, in order to create a replicable framework for the assessment and improvement of user thermal satisfaction. For this purpose, an experimental test in real offices was carried out involving eight workers. Parametric models are applied for the assessment of thermal comfort; IoT solutions are used to monitor the environmental variables and the users’ parameters; the machine learning CART method allows to predict the users’ profile and the thermal comfort perception respect to the indoor environment.

A System Based on the Internet of Things for Real-Time Particle Monitoring in Buildings

Occupational health can be strongly influenced by the indoor environment as people spend 90% of their time indoors. Although indoor air quality (IAQ) is not typically monitored, IAQ parameters could be in many instances very different from those defined as healthy values. Particulate matter (PM), a complex mixture of solid and liquid particles of organic and inorganic substances suspended in the air, is considered the pollutant that affects more people. The most health-damaging particles are the ≤PM₁₀ (diameter of 10 microns or less), which can penetrate and lodge deep inside the lungs, contributing to the risk of developing cardiovascular and respiratory diseases, as well as of lung cancer. This paper presents an Internet of Things (IoT) system for real-time PM monitoring named iDust. This system is based on a WEMOS D1 mini microcontroller and a PMS5003 PM sensor that incorporates scattering principle to measure the value of particles suspended in the air (PM₁₀, PM_2.5, and PM_1.0). Through a Web dashboard for data visualization and remote notifications, the building manager can plan interventions for enhanced IAQ and ambient assisted living (AAL). Compared to other solutions the iDust is based on open-source technologies, providing a total Wi-Fi system, with several advantages such as its modularity, scalability, low cost, and easy installation. The results obtained are very promising, representing a meaningful tool on the contribution to IAQ and occupational health.

An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH₄, CO, SO₂, and H₂S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R² and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality.

Design and Development of a Nearable Wireless System to Control Indoor Air Quality and Indoor Lighting Quality

The article describes the results of the project “open source smart lamp” aimed at designing and developing a smart object able to manage and control the indoor environmental quality (IEQ) of the built environment. A first version of this smart object, built following a do-it-yourself (DIY) approach using a microcontroller, an integrated temperature and relative humidity sensor, and techniques of additive manufacturing, allows the adjustment of the indoor thermal comfort quality (ICQ), by interacting directly with the air conditioner. As is well known, the IEQ is a holistic concept including indoor air quality (IAQ), indoor lighting quality (ILQ) and acoustic comfort, besides thermal comfort. The upgrade of the smart lamp bridges the gap of the first version of the device providing the possibility of interaction with the air exchange unit and lighting system in order to get an overview of the potential of a nearable device in the management of the IEQ. The upgraded version was tested in a real office equipped with mechanical ventilation and an air conditioning system. This office was occupied by four workers. The experiment is compared with a baseline scenario and the results show how the application of the nearable device effectively optimizes both IAQ and ILQ.

A Low-Cost Environmental Monitoring System: How to Prevent Systematic Errors in the Design Phase through the Combined Use of Additive Manufacturing and Thermographic Techniques

nEMoS (nano Environmental Monitoring System) is a 3D-printed device built following the Do-It-Yourself (DIY) approach. It can be connected to the web and it can be used to assess indoor environmental quality (IEQ). It is built using some low-cost sensors connected to an Arduino microcontroller board. The device is assembled in a small-sized case and both thermohygrometric sensors used to measure the air temperature and relative humidity, and the globe thermometer used to measure the radiant temperature, can be subject to thermal effects due to overheating of some nearby components. A thermographic analysis was made to rule out this possibility. The paper shows how the pervasive technique of additive manufacturing can be combined with the more traditional thermographic techniques to redesign the case and to verify the accuracy of the optimized system in order to prevent instrumental systematic errors in terms of the difference between experimental and actual values of the above-mentioned environmental parameters.

An Open Source "Smart Lamp" for the Optimization of Plant Systems and Thermal Comfort of Offices

The article describes the design phase, development and practical application of a smart object integrated in a desk lamp and called “Smart Lamp”, useful to optimize the indoor thermal comfort and energy savings that are two important workplace issues where the comfort of the workers and the consumption of the building strongly affect the economic balance of a company. The Smart Lamp was built using a microcontroller, an integrated temperature and relative humidity sensor, some other modules and a 3D printer. This smart device is similar to the desk lamps that are usually found in offices but it allows one to adjust the indoor thermal comfort, by interacting directly with the air conditioner. After the construction phase, the Smart Lamp was installed in an office normally occupied by four workers to evaluate the indoor thermal comfort and the cooling consumption in summer. The results showed how the application of the Smart Lamp effectively reduced the energy consumption, optimizing the thermal comfort. The use of DIY approach combined with read-write functionality of websites, blog and social platforms, also allowed to customize, improve, share, reproduce and interconnect technologies so that anybody could use them in any occupied environment.

An Open Source Low-Cost Wireless Control System for a Forced Circulation Solar Plant

The article describes the design phase, development and practical application of a low-cost control system for a forced circulation solar plant in an outdoor test cell located near Milan. Such a system provides for the use of an electric pump for the circulation of heat transfer fluid connecting the solar thermal panel to the storage tank. The running plant temperatures are the fundamental parameter to evaluate the system performance such as proper operation, and the control and management system has to consider these parameters. A solar energy-powered wireless-based smart object was developed, able to monitor the running temperatures of a solar thermal system and aimed at moving beyond standard monitoring approaches to achieve a low-cost and customizable device, even in terms of installation in different environmental conditions. To this end, two types of communications were used: the first is a low-cost communication based on the ZigBee protocol used for control purposes, so that it can be customized according to specific needs, while the second is based on a Bluetooth protocol used for data display.