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Special Issue "Wireless Sensor Network for Air Quality Monitoring and Control"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 15 July 2019

Special Issue Editors

Guest Editor
Dr. Jesús Lozano

Escuela de Ingenierías Industriales. Universidad de Extremadura. Av. Elvas s/n. Badajoz, Spain
E-Mail
Guest Editor
Dr. Saverio De Vito

ENEA - Agenzia per le nuove tecnologie, l' energía e lo sviluppo economico sostenibile. P.le E. Fermi, 1. Portici, Italy
Website | E-Mail
Interests: artificial olfaction, wireless and intelligent sensing, air quality monitoring, statistical pattern recognition, and computer-aided diagnosis
Guest Editor
Dr. José Pedro Santos

Nanosensors and Intelligent System group (NoySI), Instituto de Tecnologías Físicas y de la Información ITEFI-CSIC, 28006 Madrid, Spain
E-Mail
Interests: chemical sensors, nanotechnology, graphene; sensor networks; air quality; electronic noses

Special Issue Information

Dear Colleagues,

Air pollution is one of the most serious problems in the world. It refers to the contamination of the atmosphere by harmful chemicals or biological materials. There is a need to implement air quality management plans to ensure compliance with the pollution limits established by governments and institutions, so to improve air quality and reduce the severe health impacts causing millions of deaths worldwide. The task of air quality monitoring (AQM) are performed in most cases by reference stations in urban areas, which are costly, bulky and of complex operation and hence not suited for applications where ubiquity and low consumption are required. In addition, spatial and temporal resolution measurements of the order of one meter and one minute respectively are required to determine the actual exposure of each individual to pollution. Exposomics is currently a hot topic, and enhancing our knowledge of it will positively impact on the efficacy and efficiency of our public health systems.

In the field of odors and air quality, some citizens with simple and readily available equipment are increasingly engaged in collecting and processing heterogeneous data, which have traditionally been collected by authorized sources. The development of smart measuring devices with high accuracy, small size, low cost and high granularity can complement and/or in some cases replace official networks in their attempt to measure ambient air quality, but with a greater number of measuring points. In this sense, wireless sensor networks (WSN) play a fundamental role in this approach. The integration of low-cost detection capabilities, machine learning and wireless networking provides the core component of the WSN concept, which foresees a large number of autonomous sensors, known as "specks", working together to monitor different parameters. In its latest manifestation, the integration of WSNs into the emerging IoT and fog computing realm would move to the "Internet scale", with intelligent sensors from different WSNs collaborating to provide new services over networks that are in turn linked over large areas using the common Internet communications infrastructure.

In addition, novel gas sensors with improved features in terms of their ability to sense and sensitivity to pollutant gases, and other features, such as size and consumption, are required for their use in WSNs. In this sense, new materials and nanostructures are postulated as an important direction to explore. On the other hand, signal and data processing are essential elements in gas sensor-based detection systems and networks for the identification (classification) of chemical compounds and the estimation (regression) of the concentration and/or clustering of similar compounds (clustering). Methods should be developed to enhance drift compensation, changes in the measurement environment or sampling conditions, sensor switching or calibration between devices and compensation of the response due to moisture or other interferences.

The aim of this Special Issue is to contribute to the state-of-the-art and present current applications of wireless sensor networks for AQM. This Special Issue welcomes new research results from academia and industry. The Special Issue topics include, but are not limited to:

  • Architectures of gas sensor networks
  • Devices for citizen measurements
  • Electronics for sensor motes
  • Smart sensors
  • Novel gas sensors
  • Sensor data fusion
  • Artificial intelligence and deep learning for data processing
  • Prediction and classification from sensor data
  • Applications of sensor networks for air quality monitoring

Dr. Jesús Lozano
Dr. Saverio De Vito
Dr. José Pedro Santos
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Internet of Things
  • Air quality monitoring
  • Wireless sensor networks
  • Portable gas and particle detectors
  • Communications systems
  • Gas sensors
  • Data and signal processing

Published Papers (2 papers)

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Research

Open AccessArticle Wireless Sensor Network Combined with Cloud Computing for Air Quality Monitoring
Sensors 2019, 19(3), 691; https://doi.org/10.3390/s19030691
Received: 21 January 2019 / Revised: 2 February 2019 / Accepted: 4 February 2019 / Published: 8 February 2019
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Abstract
Low-cost air pollution wireless sensors are emerging in densely distributed networks that provide more spatial resolution than typical traditional systems for monitoring ambient air quality. This paper presents an air quality measurement system that is composed of a distributed sensor network connected to [...] Read more.
Low-cost air pollution wireless sensors are emerging in densely distributed networks that provide more spatial resolution than typical traditional systems for monitoring ambient air quality. This paper presents an air quality measurement system that is composed of a distributed sensor network connected to a cloud system forming a wireless sensor network (WSN). Sensor nodes are based on low-power ZigBee motes, and transmit field measurement data to the cloud through a gateway. An optimized cloud computing system has been implemented to store, monitor, process, and visualize the data received from the sensor network. Data processing and analysis is performed in the cloud by applying artificial intelligence techniques to optimize the detection of compounds and contaminants. This proposed system is a low-cost, low-size, and low-power consumption method that can greatly enhance the efficiency of air quality measurements, since a great number of nodes could be deployed and provide relevant information for air quality distribution in different areas. Finally, a laboratory case study demonstrates the applicability of the proposed system for the detection of some common volatile organic compounds, including: benzene, toluene, ethylbenzene, and xylene. Principal component analysis, a multilayer perceptron with backpropagation learning algorithm, and support vector machine have been applied for data processing. The results obtained suggest good performance in discriminating and quantifying the concentration of the volatile organic compounds. Full article
(This article belongs to the Special Issue Wireless Sensor Network for Air Quality Monitoring and Control)
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Open AccessArticle A Wireless Gas Sensor Network to Monitor Indoor Environmental Quality in Schools
Sensors 2018, 18(12), 4345; https://doi.org/10.3390/s18124345
Received: 6 November 2018 / Revised: 4 December 2018 / Accepted: 6 December 2018 / Published: 9 December 2018
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Abstract
Schools are amongst the most densely occupied indoor areas and at the same time children and young adults are the most vulnerable group with respect to adverse health effects as a result of poor environmental conditions. Health, performance and well-being of pupils crucially [...] Read more.
Schools are amongst the most densely occupied indoor areas and at the same time children and young adults are the most vulnerable group with respect to adverse health effects as a result of poor environmental conditions. Health, performance and well-being of pupils crucially depend on indoor environmental quality (IEQ) of which air quality and thermal comfort are central pillars. This makes the monitoring and control of environmental parameters in classes important. At the same time most school buildings do neither feature automated, intelligent heating, ventilation, and air conditioning (HVAC) systems nor suitable IEQ monitoring systems. In this contribution, we therefore investigate the capabilities of a novel wireless gas sensor network to determine carbon dioxide concentrations, along with temperature and humidity. The use of a photoacoustic detector enables the construction of long-term stable, miniaturized, LED-based non-dispersive infrared absorption spectrometers without the use of a reference channel. The data of the sensor nodes is transmitted via a Z-Wave protocol to a central gateway, which in turn sends the data to a web-based platform for online analysis. The results show that it is difficult to maintain adequate IEQ levels in class rooms even when ventilating frequently and that individual monitoring and control of rooms is necessary to combine energy savings and good IEQ. Full article
(This article belongs to the Special Issue Wireless Sensor Network for Air Quality Monitoring and Control)
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