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Nericell: using mobile smartphones for rich monitoring of road and traffic conditions
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Conference On Embedded Networked Sensor Systems archive
Proceedings of the 6th ACM conference on Embedded network sensor systems table of contents
Raleigh, NC, USA
DEMONSTRATION SESSION: Demonstrations table of contents
Pages: 357-358  
Year of Publication: 2008
ISBN:978-1-59593-990-6
Authors
Prashanth Mohan  Microsoft Research India, Bangalore, India
Venkata N. Padmanabhan  Microsoft Research India, Bangalore, India
Ramachandran Ramjee  Microsoft Research India, Bangalore, India
Sponsors
SIGCOMM: ACM Special Interest Group on Data Communication
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
SIGOPS: ACM Special Interest Group on Operating Systems
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
ACM: Association for Computing Machinery
SIGARCH: ACM Special Interest Group on Computer Architecture
SIGBED: ACM Special Interest Group on Embedded Systems
Publisher
ACM  New York, NY, USA
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ABSTRACT

We consider the problem of monitoring road and traffic conditions in a city. Prior work in this area has required the deployment of dedicated sensors on vehicles and/or on the roadside, or the tracking of mobile phones by service providers. Furthermore, prior work has largely focused on the developed world, with its relatively simple traffic flow patterns. In fact, traffic flow in cities of the developing regions, which comprise much of the world, tends to be much more complex owing to varied road conditions (e.g., potholed roads), chaotic traffic (e.g., a lot of braking and honking), and a heterogeneous mix of vehicles (2-wheelers, 3-wheelers, cars, buses, etc.).

To monitor road and traffic conditions in such a setting, we present Nericell, a system that performs rich sensing by piggybacking on smartphones that users carry around with them. In this demo, we show the use of accelerometer to detect bumps and braking. We also use the microphone to enable honk detection. Nericell addresses several challenges including virtually reorienting the accelerometer on a phone that is at an arbitrary orientation, and performing honk detection and localization in an energy efficient manner.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Intelligent Transportation Systems. http://www.its.dot.gov/.
 
2
OnStar by GM. http://www.onstar.com/.
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Collaborative Colleagues:
Prashanth Mohan: colleagues
Venkata N. Padmanabhan: colleagues
Ramachandran Ramjee: colleagues