Intelligent and Scalable Air Quality Monitoring with 5G Edge

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Su , X , Liu , X , Hossein Motlagh , N , Cao , J , Su , P , Pellikka , P , Liu , Y , Petäjä , T , Kulmala , M , Hui , P & Tarkoma , S 2021 , ' Intelligent and Scalable Air Quality Monitoring with 5G Edge ' , IEEE Internet Computing , vol. 25 , no. 2 , pp. 35-43 . https://doi.org/10.1109/MIC.2021.3059189

Title: Intelligent and Scalable Air Quality Monitoring with 5G Edge
Author: Su, Xiang; Liu, Xiaoli; Hossein Motlagh, Naser; Cao, Jacky; Su, Peifeng; Pellikka, Petri; Liu, Yongchun; Petäjä, Tuukka; Kulmala, Markku; Hui, Pan; Tarkoma, Sasu
Contributor organization: Department of Computer Science
Department of Geosciences and Geography
Institute for Atmospheric and Earth System Research (INAR)
Department of Physics
Content-Centric Structures and Networking research group / Sasu Tarkoma
Helsinki Institute for Information Technology
Date: 2021
Language: eng
Number of pages: 9
Belongs to series: IEEE Internet Computing
ISSN: 1089-7801
DOI: https://doi.org/10.1109/MIC.2021.3059189
URI: http://hdl.handle.net/10138/331666
Abstract: Air pollution introduces a major challenge for societies, where it leads to the premature deaths of millions of people each year globally. Massive deployment of air quality sensing devices and data analysis for the resultant data will pave the way for the development of real-time intelligent applications and services, e.g., minimization of exposure to poor air quality either on an individual or city scale. 5G and edge computing supports dense deployments of sensors at high resolution with ubiquitous connectivity, high bandwidth, high-speed gigabit connections, and ultralow latency analysis. This article conceptualizes AI-powered scalable air quality monitoring and presents two systems of calibrating low-cost air quality sensors and the image processing of pictures captured by hyperspectral cameras to better detect air quality. We develop and deploy different AI algorithms in these two systems on a 5G edge testbed and perform a detailed analytics regarding to 1) the performance of AI algorithms and 2) the required communication and computation resources.
Subject: 5G
5G mobile communication
Air quality
Calibration
Cameras
Hyperspectral imaging
Real-time systems
Sensors
air quality monitoring
edge computing
hyperspectral images processing
sensor calibration
113 Computer and information sciences
1172 Environmental sciences
Peer reviewed: Yes
Usage restriction: openAccess
Self-archived version: acceptedVersion


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