Demo: Automatically generating interesting events with LifeJoin

Author(s)
Cheung, Alvin K.; Thiagarajan, Arvind; Madden, Samuel R.
Thumbnail
DownloadMadden_Demo automatically.pdf (182.0Kb)
OPEN_ACCESS_POLICY
Terms of use
Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/
Metadata
Show full item record
Abstract
This demo will showcase LifeJoin, a system that collects raw sensor data from phones and laptop computers to generate interesting events. Given the raw sensor data, LifeJoin implements a number of activity recognition algorithms to generate higher-level events. Furthermore, it uses supervised learning techniques to learn from users' feedback to generate only events of interest. In this demo, the audience will get to interact with the LifeJoin system and be able to examine the internals of LifeJoin.
Date issued
2011-11
URI
http://hdl.handle.net/1721.1/72550
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems (SenSys '11)
Publisher
Association for Computing Machinery (ACM)
Citation
Alvin Cheung, Arvind Thiagarajan, and Samuel Madden. 2011. Demo: Automatically generating interesting events with LifeJoin. In Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems (SenSys '11). ACM, New York, NY, USA, 411-412.
Version: Author's final manuscript
ISBN
978-1-4503-0718-5
Collections