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Moreair: A low-cost urban air pollution monitoring system

TitreMoreair: A low-cost urban air pollution monitoring system
Publication TypeJournal Article
Year of Publication2020
AuthorsGryech, I, Ben-Aboud, Y, Guermah, B, Sbihi, N, Ghogho, M, Kobbane, A
JournalSensors (Switzerland)
Volume20
Mots-clésAgile deployments, Agile manufacturing systems, Air quality, Costs, Decision trees, Geographic information systems, Information systems, Information use, Learning systems, Machine learning, Mobile sensing, Monitoring, Particles (particulate matter), Particulate Matter, Pollution detection, Pollution monitoring, Random forests, Real-time information, Sensor deployment, Urban air pollution, Urban pollutions
Abstract

MoreAir is a low-cost and agile urban air pollution monitoring system. This paper describes the methodology used in the development of this system along with some preliminary data analysis results. A key feature of MoreAir is its innovative sensor deployment strategy which is based on mobile and nomadic sensors as well as on medical data collected at a children’s hospital, used to identify urban areas of high prevalence of respiratory diseases. Another key feature is the use of machine learning to perform prediction. In this paper, Moroccan cities are taken as case studies. Using the agile deployment strategy of MoreAir, it is shown that in many Moroccan neighborhoods, road traffic has a smaller impact on the concentrations of particulate matters (PM) than other sources, such as public baths, public ovens, open-air street food vendors and thrift shops. A geographical information system has been developed to provide real-time information to the citizens about the air quality in different neighborhoods and thus raise awareness about urban pollution. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85079609813&doi=10.3390%2fs20040998&partnerID=40&md5=dc90b4357fcdc64d82d12f57a45f971f
DOI10.3390/s20040998
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