The CarTel mobile sensor computing system
Proceedings of the 4th international conference on Embedded networked sensor systems
Surface street traffic estimation
Proceedings of the 5th international conference on Mobile systems, applications and services
The pothole patrol: using a mobile sensor network for road surface monitoring
Proceedings of the 6th international conference on Mobile systems, applications, and services
Nericell: rich monitoring of road and traffic conditions using mobile smartphones
Proceedings of the 6th ACM conference on Embedded network sensor systems
SignalGuru: leveraging mobile phones for collaborative traffic signal schedule advisory
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
LEAP: a low energy assisted GPS for trajectory-based services
Proceedings of the 13th international conference on Ubiquitous computing
MARVEL: multiple antenna based relative vehicle localizer
Proceedings of the 18th annual international conference on Mobile computing and networking
Auditeur: a mobile-cloud service platform for acoustic event detection on smartphones
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
A survey on smartphone-based systems for opportunistic user context recognition
ACM Computing Surveys (CSUR)
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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.