Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.3
3.4
Journals
Sensors
Special Issues
Intelligent Sensor Systems and Networks for Air Quality Monitoring
sensors-logo
Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Intelligent Sensor Systems and Networks for Air Quality Monitoring

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

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 4919

Special Issue Editor

Dr. Núria Castell

E-Mail Website
Guest Editor
NILU-Norwegian Institute for Air Research, 2007 Kjeller, Norway
Interests: air quality; sustainability; sensor systems; sensor networks; smart cities; citizen engagement; citizen science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The increase of the commercial availability of low-cost sensor technology to monitor atmospheric composition is contributing to the rapid adoption of such technology by academy, public authorities and self-organized initiatives (e.g. grass root movements, citizen science, etc.). Low-cost sensors (LCS) can provide real time measurements, in principle at lower cost than traditional monitoring reference stations, allowing higher spatial coverage than the current reference methods. However, data quality from LCS is lower than the one provided by reference methods. 

This Special Issue addresses the fit for purpose and usefulness of sensor systems and networks in purposes such as indoor and outdoor pollution assessment, smart cities, citizen science, wildfires monitoring and exposure assessment, among others. We welcome review papers, as well as research papers.

Dr. Nuria Castell
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 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.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 11845 KiB  
Article
Calibration of CO, NO2, and O3 Using Airify: A Low-Cost Sensor Cluster for Air Quality Monitoring
by Marian-Emanuel Ionascu, Nuria Castell, Oana Boncalo, Philipp Schneider, Marius Darie and Marius Marcu
Sensors 2021, 21(23), 7977; https://doi.org/10.3390/s21237977 - 29 Nov 2021
Cited by 27 | Viewed by 4198
Abstract
During the last decade, extensive research has been carried out on the subject of low-cost sensor platforms for air quality monitoring. A key aspect when deploying such systems is the quality of the measured data. Calibration is especially important to improve the data [...] Read more.
During the last decade, extensive research has been carried out on the subject of low-cost sensor platforms for air quality monitoring. A key aspect when deploying such systems is the quality of the measured data. Calibration is especially important to improve the data quality of low-cost air monitoring devices. The measured data quality must comply with regulations issued by national or international authorities in order to be used for regulatory purposes. This work discusses the challenges and methods suitable for calibrating a low-cost sensor platform developed by our group, Airify, that has a unit cost five times less expensive than the state-of-the-art solutions (approximately €1000). The evaluated platform can integrate a wide variety of sensors capable of measuring up to 12 parameters, including the regulatory pollutants defined in the European Directive. In this work, we developed new calibration models (multivariate linear regression and random forest) and evaluated their effectiveness in meeting the data quality objective (DQO) for the following parameters: carbon monoxide (CO), ozone (O3), and nitrogen dioxide (NO2). The experimental results show that the proposed calibration managed an improvement of 12% for the CO and O3 gases and a similar accuracy for the NO2 gas compared to similar state-of-the-art studies. The evaluated parameters had different calibration accuracies due to the non-identical levels of gas concentration at which the sensors were exposed during the model’s training phase. After the calibration algorithms were applied to the evaluated platform, its performance met the DQO criteria despite the overall low price level of the platform. Full article
(This article belongs to the Special Issue Intelligent Sensor Systems and Networks for Air Quality Monitoring)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop