Sensor networks for social networks
Name
78624571-MIT.pdf
Description
Full printable version
Size
4.06 MB
Format
Adobe PDF
Checksum (MD5)
b7a227bc0eece921ec26eecf1ece5556
Author(s)
Farry, Michael P. (Michael Patrick)
Advisor(s)
Samuel Madden.
Date Issued
2006
Publisher
Massachusetts Institute of Technology
Abstract
This thesis outlines the development of software that makes use of Bayesian belief networks and signal processing techniques to make meaningful inferences about real-world phenomena using data obtained from sensor networks. The effectiveness of the software is validated by applying it to the problem of detecting face-to-face social interactions between groups of people, given data readings from sensors that record light, temperature, acceleration, sound, and proximity. This application represents a novel method for social network construction which is potentially more accurate and less intrusive than traditional methods, but also more meaningful than newer methods that analyze digitally mediated communication.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
Includes bibliographical references (p. 51-55).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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