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Air Quality Internet of Things Devices
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Air Quality Internet of Things Devices

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

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 7887

Special Issue Editors

Dr. Philip J. Basford

E-Mail Website
Guest Editor
School of Engineering, University of Southampton, SO17 1BJ, UK
Interests: Internet of Things; environmental monitoring; sensor networks; data management; edge computing
Dr. Florentin Bulot

E-Mail Website
Guest Editor
School of Engineering, University of Southampton, SO17 1BJ, UK
Interests: Air quality; Internet of Things; environmental monitoring; sensor networks
Prof. Dr. Simon J. Cox

E-Mail Website
Guest Editor
School of Engineering, University of Southampton, Southampton SO17 1BJ, UK
Interests: Internet of Things; high performance computing; data science; algorithms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Air quality affects us all, and the dangers poor air quality can pose are still being understood. Technological advances in Internet of Things (IoT) research have recently been transferred to the air quality monitoring community. These IoT advances have led to the development of richer datasets potentially furthering the understanding of air quality within varied environments. Sensing systems of lower cost than traditional air pollution monitoring instruments have been deployed in various settings for different applications. 

In this special issue we are interested in articles that demonstrate and share results of how these IoT developments are being applied in new and novel ways to facilitate research into air quality.  We are also interested in results from all areas of air quality monitoring where IoT devices have been used, including but not limited to: 

  • Long term air quality monitoring studies
  • City-scale monitoring 
  • Application of network of sensors for air quality monitoring
  • Indoor and ambient air quality monitoring
  • Urban and rural areas monitoring
  • Calibration, correction and validation of network of sensors
  • Data presentation/useability
  • Mobile sensing
  • Integration of data from different sources
  • Data aggregation and visualisation
  • Intervention monitoring, real time mitigation

Internet of Things topics of interest include: 

  • Hardware / Software design for reusability / modularity
  • Sensor evaluation and testing
  • Efficient data collection techniques
  • Security / Integrity / Privacy
  • Deployment experiences & systems at scale
  • Use of Artificial Intelligence and Machine Learning 
  • Edge computing / architectures
  • Communication protocols and technologies
  • Data storage, management, processing, validation and visualisation
  • Designs for inhospitable environments

Dr. Philip J. Basford
Dr. Florentin Bulot
Prof. Dr. Simon J. Cox
Guest Editors

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 submissions that pass pre-check are 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 2600 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 
  • Data handling 
  • Long term studies 
  • Air Quality 
  • Air Pollution 
  • Particulate Matter 
  • Gas sensing 
  • Low cost sensing 
  • Air monitoring

Published Papers (2 papers)

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Research

18 pages, 1270 KiB  
Article
Sampling Trade-Offs in Duty-Cycled Systems for Air Quality Low-Cost Sensors
by Pau Ferrer-Cid, Julio Garcia-Calvete, Aina Main-Nadal, Zhe Ye, Jose M. Barcelo-Ordinas and Jorge Garcia-Vidal
Sensors 2022, 22(10), 3964; https://0-doi-org.brum.beds.ac.uk/10.3390/s22103964 - 23 May 2022
Cited by 6 | Viewed by 2219
Abstract
The use of low-cost sensors in conjunction with high-precision instrumentation for air pollution monitoring has shown promising results in recent years. One of the main challenges for these sensors has been the quality of their data, which is why the main efforts have [...] Read more.
The use of low-cost sensors in conjunction with high-precision instrumentation for air pollution monitoring has shown promising results in recent years. One of the main challenges for these sensors has been the quality of their data, which is why the main efforts have focused on calibrating the sensors using machine learning techniques to improve the data quality. However, there is one aspect that has been overlooked, that is, these sensors are mounted on nodes that may have energy consumption restrictions if they are battery-powered. In this paper, we show the usual sensor data gathering process and we study the existing trade-offs between the sampling of such sensors, the quality of the sensor calibration, and the power consumption involved. To this end, we conduct experiments on prototype nodes measuring tropospheric ozone, nitrogen dioxide, and nitrogen monoxide at high frequency. The results show that the sensor sampling strategy directly affects the quality of the air pollution estimation and that each type of sensor may require different sampling strategies. In addition, duty cycles of 0.1 can be achieved when the sensors have response times in the order of two minutes, and duty cycles between 0.01 and 0.02 can be achieved when the sensor response times are negligible, calibrating with hourly reference values and maintaining a quality of calibrated data similar to when the node is connected to an uninterruptible power supply. Full article
(This article belongs to the Special Issue Air Quality Internet of Things Devices)
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19 pages, 9620 KiB  
Article
AirKit: A Citizen-Sensing Toolkit for Monitoring Air Quality
by Sachit Mahajan, Jennifer Gabrys and Joanne Armitage
Sensors 2021, 21(12), 4044; https://0-doi-org.brum.beds.ac.uk/10.3390/s21124044 - 11 Jun 2021
Cited by 11 | Viewed by 4423
Abstract
Increasing urbanisation and a better understanding of the negative health effects of air pollution have accelerated the use of Internet of Things (IoT)-based air quality sensors. Low-cost and low-power sensors are now readily available and commonly deployed by individuals and community groups. However, [...] Read more.
Increasing urbanisation and a better understanding of the negative health effects of air pollution have accelerated the use of Internet of Things (IoT)-based air quality sensors. Low-cost and low-power sensors are now readily available and commonly deployed by individuals and community groups. However, there are a wide range of such IoT devices in circulation that differently focus on problems of sensor validation, data reliability, or accessibility. In this paper, we present AirKit, which was developed as an integrated and open source “social IoT technology”. AirKit enables a comprehensive approach to citizen-sensing air quality through several integrated components: (1) the Dustbox 2.0, a particulate matter sensor; (2) Airsift, a data analysis platform; (3) a reliable and automatic remote firmware update system; (4) a “Data Stories” method and tool for communicating citizen data; and (5) an AirKit logbook that provides a guide for designing and running air quality projects, along with instructions for building and using AirKit components. Developed as a social technology toolkit to foster open processes of research co-creation and environmental action, Airkit has the potential to generate expanded engagements with IoT and air quality by improving the accuracy, legibility and use of sensors, data analysis and data communication. Full article
(This article belongs to the Special Issue Air Quality Internet of Things Devices)
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