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PEIR: the personal environmental impact report, as a platform for participatory sensing systems research (2009)
| Venue: | in Proc. ACM/USENIX Int. Conf. Mobile Systems, Applications, and Services (MobiSys) Krakow |
| Citations: | 98 - 3 self |
BibTeX
@INPROCEEDINGS{Mun09peir:the,
author = {Min Mun and Sasank Reddy and Katie Shilton and Nathan Yau and Jeff Burke and Deborah Estrin and Mark Hansen and Eric Howard and Ruth West and Péter Boda},
title = {PEIR: the personal environmental impact report, as a platform for participatory sensing systems research},
booktitle = {in Proc. ACM/USENIX Int. Conf. Mobile Systems, Applications, and Services (MobiSys) Krakow},
year = {2009}
}
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Abstract
PEIR, the Personal Environmental Impact Report, is a participatory sensing application that uses location data sampled from everyday mobile phones to calculate personalized estimates of environmental impact and exposure. It is an example of an important class of emerging mobile systems that combine the distributed processing capacity of the web with the personal reach of mobile technology. This paper documents and evaluates the running PEIR system, which includes mobile handset based GPS location data collection, and server-side processing stages such as HMM-based activity classification (to determine transportation mode); automatic location data segmentation into “trips”; lookup of traffic, weather, and other context data needed by the models; and environmental impact and exposure calculation using efficient implementations of established models. Additionally, we describe the user interface components of PEIR and present usage statistics from a two month snapshot of system use. The paper also outlines new algorithmic components developed based on experience with the system and undergoing testing for integration into PEIR, including: new map-matching and GSM-augmented activity classification techniques, and a selective hiding mechanism that generates believable proxy traces for times a user does not want their real location revealed.
Keyphrases
personal environmental impact report system research environmental impact efficient implementation hmm-based activity classification personal reach everyday mobile phone participatory sensing application undergoing testing new algorithmic component exposure calculation important class real location peir system mobile handset selective hiding mechanism system use personalized estimate distributed processing capacity automatic location data segmentation gsm-augmented activity classification technique server-side processing stage mobile technology context data user interface component gps location data collection transportation mode month snapshot present usage statistic believable proxy trace paper document mobile system location data
