GreenGPS-MobiSys10 - GreenGPS: A Participatory Sensing...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon
GreenGPS: A Participatory Sensing Fuel-Efficient Maps Application Raghu K. Ganti, Nam Pham, Hossein Ahmadi, Saurabh Nangia, and Tarek F. Abdelzaher Department of Computer Science, University of Illinois, Urbana-Champaign rganti2, nampham2, hahmadi2, nangia1, ABSTRACT This paper develops a navigation service, called GreenGPS , that uses participatory sensing data to map fuel consump- tion on city streets, allowing drivers to find the most fuel- efficient routes for their vehicles between arbitrary end-points. The service exploits measurements of vehicular fuel con- sumption sensors, available via the OBD-II interface stan- dardized in all vehicles sold in the US since 1996. The in- terface gives access to most gauges and engine instrumenta- tion. The most fuel-efficient route does not always coincide with the shortest or fastest routes, and may be a function of vehicle type. Our experimental study shows that a par- ticipatory sensing system can influence routing decisions of individual users and also answers two questions related to the viability of the new service. First, can it survive condi- tions of sparse deployment? Second, how much fuel can it save? A challenge in participatory sensing is to generalize from sparse sampling of high-dimensional spaces to produce compact descriptions of complex phenomena. We illustrate this by developing models that can predict fuel consumption of a set of sixteen different cars on the streets of the city of Urbana-Champaign. We provide experimental results from data collection suggesting that a 1% average prediction error is attainable and that an average 10% savings in fuel can be achieved by choosing the right route. Categories and Subject Descriptors J.0 [ Computer Applications ]: General; K.4 [ Computing Milieux ]: Computers and Society General Terms Experimentation, Measurement Keywords Participatory sensing, green navigation, green GPS, model clustering Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. MobiSys’10, June 15–18, 2010, San Francisco, California, USA. Copyright 2010 ACM 978-1-60558-985-5/10/06 . ..$10.00. 1. INTRODUCTION In this paper, we develop a novel GPS-based navigation service, called GreenGPS , that gives drivers the most fuel- efficient route for their vehicle as opposed to the shortest or fastest route. GreenGPS relies on data collected by indi- viduals from their vehicles and a generalization framework that predicts the fuel consumption of an arbitrary car on an arbitrary street. The service is an example of an emerging category of sensing applications, called participatory sens- ing [2, 9, 12, 23, 24], that rely on voluntary data collection and sharing within a community for common purposes such
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 2
This is the end of the preview. Sign up to access the rest of the document.

Page1 / 14

GreenGPS-MobiSys10 - GreenGPS: A Participatory Sensing...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online