Cities are expanding and more and more citizens are exposed to air pollutants both indoors and outdoors. This may have adverse effects on citizens' health. In this paper, we present AirSense, an opportunistic crowd-sensing based air quality monitoring system, aimed at collecting and aggregating sensor data to monitor air pollution in the vicinity (building/neighbourhood) and the city. We introduce a light weight, low power and low cost air quality monitoring device (AQMD) and demonstrate how AQMD and smartphones in a crowd collaboratively gather and share data of interest to the cloud. In cloud, collected data are analyzed and an aggregate view is generated from data collected from various sensors and from different users for providing an air pollution heat map of the city. Unlike previous works, both micro and macro level air quality monitoring is possible with Airsense. End user can view his/her pollution footprint for the whole day, the neighborhood (local) air quality and AQImap (air quality index map) of the city on his/her smartphone. The system is implemented and the prototype is also evaluated.
%0 Conference Paper
%1 Dutta:2017:TSC:3007748.3018286
%A Dutta, Joy
%A Chowdhury, Chandreyee
%A Roy, Sarbani
%A Middya, Asif Iqbal
%A Gazi, Firoj
%B Proceedings of the 18th International Conference on Distributed Computing and Networking
%C New York, NY, USA
%D 2017
%I ACM
%K air airprobe collection eva everyaware framework pollution quality relatedwork system ubicon
%P 42:1--42:6
%R 10.1145/3007748.3018286
%T Towards Smart City: Sensing Air Quality in City Based on Opportunistic Crowd-sensing
%U http://doi.acm.org/10.1145/3007748.3018286
%X Cities are expanding and more and more citizens are exposed to air pollutants both indoors and outdoors. This may have adverse effects on citizens' health. In this paper, we present AirSense, an opportunistic crowd-sensing based air quality monitoring system, aimed at collecting and aggregating sensor data to monitor air pollution in the vicinity (building/neighbourhood) and the city. We introduce a light weight, low power and low cost air quality monitoring device (AQMD) and demonstrate how AQMD and smartphones in a crowd collaboratively gather and share data of interest to the cloud. In cloud, collected data are analyzed and an aggregate view is generated from data collected from various sensors and from different users for providing an air pollution heat map of the city. Unlike previous works, both micro and macro level air quality monitoring is possible with Airsense. End user can view his/her pollution footprint for the whole day, the neighborhood (local) air quality and AQImap (air quality index map) of the city on his/her smartphone. The system is implemented and the prototype is also evaluated.
%@ 978-1-4503-4839-3
@inproceedings{Dutta:2017:TSC:3007748.3018286,
abstract = {Cities are expanding and more and more citizens are exposed to air pollutants both indoors and outdoors. This may have adverse effects on citizens' health. In this paper, we present AirSense, an opportunistic crowd-sensing based air quality monitoring system, aimed at collecting and aggregating sensor data to monitor air pollution in the vicinity (building/neighbourhood) and the city. We introduce a light weight, low power and low cost air quality monitoring device (AQMD) and demonstrate how AQMD and smartphones in a crowd collaboratively gather and share data of interest to the cloud. In cloud, collected data are analyzed and an aggregate view is generated from data collected from various sensors and from different users for providing an air pollution heat map of the city. Unlike previous works, both micro and macro level air quality monitoring is possible with Airsense. End user can view his/her pollution footprint for the whole day, the neighborhood (local) air quality and AQImap (air quality index map) of the city on his/her smartphone. The system is implemented and the prototype is also evaluated.},
acmid = {3018286},
added-at = {2017-01-16T11:07:49.000+0100},
address = {New York, NY, USA},
articleno = {42},
author = {Dutta, Joy and Chowdhury, Chandreyee and Roy, Sarbani and Middya, Asif Iqbal and Gazi, Firoj},
biburl = {https://www.bibsonomy.org/bibtex/24414aee70b8bd7bd9ea63cb79cc2bb65/becker},
booktitle = {Proceedings of the 18th International Conference on Distributed Computing and Networking},
description = {Towards Smart City},
doi = {10.1145/3007748.3018286},
interhash = {24aecc2c0804c4ac9e0241a7d88f61f6},
intrahash = {4414aee70b8bd7bd9ea63cb79cc2bb65},
isbn = {978-1-4503-4839-3},
keywords = {air airprobe collection eva everyaware framework pollution quality relatedwork system ubicon},
location = {Hyderabad, India},
numpages = {6},
pages = {42:1--42:6},
publisher = {ACM},
series = {ICDCN '17},
timestamp = {2017-01-16T11:07:49.000+0100},
title = {Towards Smart City: Sensing Air Quality in City Based on Opportunistic Crowd-sensing},
url = {http://doi.acm.org/10.1145/3007748.3018286},
year = 2017
}