Bret Hull, Vladimir Bychkovsky, Yang Zhang, Kevin Chen, Michel Goraczko, Allen K. Miu, Eugene Shih, Hari Balakrishnan, Samuel Madden
4th ACM SenSys, Boulder, CO, November 2006
CarTel is a mobile sensor computing system designed to
collect, process, deliver, and visualize data from sensors located
on mobile units such as automobiles. A CarTel node
is a mobile embedded computer coupled to a set of sensors.
Each node gathers and processes sensor readings locally before
delivering them to a central portal, where the data is
stored in a database for further analysis and visualization. In
the automotive context, a variety of on-board and external
sensors collect data as users drive.
CarTel provides a simple query-oriented programming interface,
handles large amounts of heterogeneous data from
sensors, and handles intermittent and variable network connectivity.
CarTel nodes rely primarily on opportunistic wireless
(e.g., Wi-Fi, Bluetooth) connectivity—to the Internet,
or to “data mules” such as other CarTel nodes, mobile phone
flash memories, or USB keys—to communicate with the portal.
CarTel applications run on the portal, using a delay tolerant
continuous query processor, ICEDB, to specify how
the mobile nodes should summarize, filter, and dynamically
prioritize data. The portal and the mobile nodes use a delay tolerant
network stack, CafNet, to communicate.
CarTel has been deployed on six cars, running on a small
scale in Boston and Seattle for over a year. It has been used
to analyze commute times, analyze metropolitan Wi-Fi deployments,
and for automotive diagnostics.
[PDF (1951KB)]
Bibtex Entry:
@inproceedings{hull2006cartel,
author = "Bret Hull and Vladimir Bychkovsky and Yang Zhang and Kevin Chen and Michel Goraczko and Allen K. Miu and Eugene Shih and Hari Balakrishnan and Samuel Madden",
title = "{CarTel: A Distributed Mobile Sensor Computing System}",
booktitle = {4th ACM SenSys},
year = {2006},
month = {November},
address = {Boulder, CO}
}