MegaSense: Cyber-Physical System for Real-time Urban Air Quality Monitoring

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http://hdl.handle.net/10138/321750

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Rebeiro-Hargrave , A , Hossein Motlagh , N , Varjonen , S , Lagerspetz , E , Nurmi , P & Tarkoma , S 2020 , MegaSense: Cyber-Physical System for Real-time Urban Air Quality Monitoring . in 15th IEEE Conference on Industrial Electronics and Applications (ICIEA2020) . IEEE , IEEE Conference on Industrial Electronics and Applications , Kristiansand , Norway , 09/11/2020 . https://doi.org/10.1109/ICIEA48937.2020.9248143

Title: MegaSense: Cyber-Physical System for Real-time Urban Air Quality Monitoring
Author: Rebeiro-Hargrave, Andrew; Hossein Motlagh, Naser; Varjonen, Samu; Lagerspetz, Eemil; Nurmi, Petteri; Tarkoma, Sasu
Other contributor: University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
University of Helsinki, Department of Computer Science
University of Helsinki, Content-Centric Structures and Networking research group / Sasu Tarkoma


Publisher: IEEE
Date: 2020-11-09
Language: eng
Number of pages: 6
Belongs to series: 15th IEEE Conference on Industrial Electronics and Applications (ICIEA2020)
ISBN: 978-1-7281-5169-4
DOI: https://doi.org/10.1109/ICIEA48937.2020.9248143
URI: http://hdl.handle.net/10138/321750
Abstract: Air pollution is a contributor to approximately one in every nine deaths annually. To counteract health issues resulting from air pollution, air quality monitoring is being carried out extensively in urban environments. Currently, however, city air quality monitoring stations are expensive to maintain, resulting in sparse coverage. In this paper, we introduce the design and development of the MegaSense Cyber-Physical System (CPS) for spatially distributed IoT-based monitoring of urban air quality. MegaSense is able to produce aggregated, privacy-aware maps and history graphs of collected pollution data. It provides a feedback loop in the form of personal outdoor and indoor air pollution exposure information, allowing citizens to take measures to avoid future exposure. We present a battery-powered, portable low-cost air quality sensor design for sampling PM2.5 and air pollutant gases in different micro-environments. We validate the approach with a use case in Helsinki, deploying MegaSense with citizens carrying low-maintenance portable sensors, and using smart phone exposure apps. We demonstrate daily air pollution exposure profiles and the air pollution hot-spot profile of a district. Our contributions have applications in policy intervention management mechanisms and design of clean air routing and healthier navigation applications to reduce pollution exposure.
Subject: 113 Computer and information sciences
Air quality
Cyber-physical Systems
Internet of Things
Low-cost sensors
Data integration and visualisation
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