Social signal processing: Detecting human interactions using wireless sensor networks

Authors: Angelopoulos, C.M., Mouskos, C. and Nikoletseas, S.E.

http://doi.acm.org/10.1145/2069131.2069163

Journal: Proceedings of the 9th ACM International Workshop on Mobility Management & Wireless Access, MOBIWAC 2011, October 31- November 4, 2011, Miami Beach, FL, USA

Pages: 171-174

DOI: 10.1145/2069131.2069163

This data was imported from Scopus:

Authors: Angelopoulos, C.M., Mouskos, C. and Nikoletseas, S.

Journal: MobiWac'11 - Proceedings of the 9th ACM International Symposium on Mobility Management and Wireless Access, Co-located with MSWiM'11

Pages: 171-174

ISBN: 9781450309011

DOI: 10.1145/2069131.2069163

In this paper we address the problem of capturing and processing certain spatiotemporal, social characteristics of human interactions with the use of Wireless Sensor Networks. Using TelosB motes, we basically monitor the binary proximity within a group of people. The collected data give an insight of how people interact with each other (how often, for how much time, in which room) and provide a novel tool (which can be further enhanced) to study (quantitatively, in an automated manner) human social networks. Copyright 2011 ACM.

This data was imported from Web of Science (Lite):

Authors: Angelopoulos, C.M., Mouskos, C., Nikoletseas, S. and ACM

Journal: MOBIWAC 11: PROCEEDINGS OF THE NINTH ACM INTERNATIONAL SYMPOSIUM ON MOBILITY MANAGEMENT AND WIRELESS ACCESS

Pages: 171-174

ISBN: 978-1-4503-0901-1

ISSN: 1947-8151

The data on this page was last updated at 05:16 on February 19, 2020.