This paper describes our experiences with building and deploying a low-cost participatory system for urban air pollution monitoring in Sydney. Though air pollution imposes significant health costs on the urban community globally, today's published data on pollution concentrations is spatially too sparse, and does not allow for sufficiently accurate estimation of exposures for (potentially mobile) individuals in order to make medical inferences. The HazeWatch project described in this paper uses several low-cost mobile sensor units attached to vehicles to measure air pollution concentrations, and users' mobile phones to tag and upload the data in real time. The greater spatial granularity of data thus collected enables creation of pollution maps of metropolitan Sydney viewable in real-time over the web, as well as personalized apps that show the individual's exposure history and allow for route planning to reduce future exposure. We share the insights we obtained from building and trialling such a system in Sydney, and highlight challenges that can be addressed collaboratively by groups developing similar systems world-wide.
%0 Conference Paper
%1 6758498
%A Sivaraman, V.
%A Carrapetta, J.
%A Hu, Ke
%A Luxan, B.G.
%B Local Computer Networks Workshops (LCN Workshops), 2013 IEEE 38th Conference on
%D 2013
%K air airprobe android eva everyaware framework hardware
%P 56-64
%R 10.1109/LCNW.2013.6758498
%T HazeWatch: A participatory sensor system for monitoring air pollution in Sydney
%U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6758498
%X This paper describes our experiences with building and deploying a low-cost participatory system for urban air pollution monitoring in Sydney. Though air pollution imposes significant health costs on the urban community globally, today's published data on pollution concentrations is spatially too sparse, and does not allow for sufficiently accurate estimation of exposures for (potentially mobile) individuals in order to make medical inferences. The HazeWatch project described in this paper uses several low-cost mobile sensor units attached to vehicles to measure air pollution concentrations, and users' mobile phones to tag and upload the data in real time. The greater spatial granularity of data thus collected enables creation of pollution maps of metropolitan Sydney viewable in real-time over the web, as well as personalized apps that show the individual's exposure history and allow for route planning to reduce future exposure. We share the insights we obtained from building and trialling such a system in Sydney, and highlight challenges that can be addressed collaboratively by groups developing similar systems world-wide.
@inproceedings{6758498,
abstract = {This paper describes our experiences with building and deploying a low-cost participatory system for urban air pollution monitoring in Sydney. Though air pollution imposes significant health costs on the urban community globally, today's published data on pollution concentrations is spatially too sparse, and does not allow for sufficiently accurate estimation of exposures for (potentially mobile) individuals in order to make medical inferences. The HazeWatch project described in this paper uses several low-cost mobile sensor units attached to vehicles to measure air pollution concentrations, and users' mobile phones to tag and upload the data in real time. The greater spatial granularity of data thus collected enables creation of pollution maps of metropolitan Sydney viewable in real-time over the web, as well as personalized apps that show the individual's exposure history and allow for route planning to reduce future exposure. We share the insights we obtained from building and trialling such a system in Sydney, and highlight challenges that can be addressed collaboratively by groups developing similar systems world-wide.},
added-at = {2016-01-11T14:48:49.000+0100},
author = {Sivaraman, V. and Carrapetta, J. and Hu, Ke and Luxan, B.G.},
biburl = {https://www.bibsonomy.org/bibtex/2b35d09f0cf03d6c30cee5e4f165a45c3/becker},
booktitle = {Local Computer Networks Workshops (LCN Workshops), 2013 IEEE 38th Conference on},
doi = {10.1109/LCNW.2013.6758498},
interhash = {59fd4a09fb269f38127909a9ba593738},
intrahash = {b35d09f0cf03d6c30cee5e4f165a45c3},
keywords = {air airprobe android eva everyaware framework hardware},
month = oct,
pages = {56-64},
timestamp = {2016-01-11T14:48:49.000+0100},
title = {HazeWatch: A participatory sensor system for monitoring air pollution in Sydney},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6758498},
year = 2013
}