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Identifying and facilitating social interaction with a wearable wireless sensor network

by: Joseph Paradiso, Jonathan Gips, Mathew Laibowitz, Sajid Sadi, David Merrill, Ryan Aylward, Pattie Maes, and Alex Pentland

In: Personal and Ubiquitous Computing, Vol. 14, Nr. 2 (February 2010) , p. 137--152.

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URL:	http://dx.doi.org/10.1007/s00779-009-0239-2

Abstract  We have designed a highly versatile badge system to facilitate a variety of interaction at large professional or social events and serve as a platform for conducting research into human dynamics. The badges are equipped with a large LED display, wirelessinfrared and radio frequency networking, and a host of sensors to collect data that we have used to develop features and algorithmsaimed at classifying and predicting individual and group behavior. This paper overviews our badge system, describes the interactionsand capabilities that it enabled for the wearers, and presents data collected over several large deployments. This data isanalyzed to track and socially classify the attendees, predict their interest in other people and demonstration installations,profile the restlessness of a crowd in an auditorium, and otherwise track the evolution and dynamics of the events at whichthe badges were run.

Description

SpringerLink - Zeitschriftenbeitrag

BibTeX record

@article{joseph2010identifying,
  abstract = {Abstract&nbsp;&nbsp;We have designed a highly versatile badge system to facilitate a variety of interaction at large professional or social events
and serve as a platform for conducting research into human dynamics. The badges are equipped with a large LED display, wirelessinfrared and radio frequency networking, and a host of sensors to collect data that we have used to develop features and algorithmsaimed at classifying and predicting individual and group behavior. This paper overviews our badge system, describes the interactionsand capabilities that it enabled for the wearers, and presents data collected over several large deployments. This data isanalyzed to track and socially classify the attendees, predict their interest in other people and demonstration installations,profile the restlessness of a crowd in an auditorium, and otherwise track the evolution and dynamics of the events at whichthe badges were run.},
  added-at = {2010-02-19T13:49:58.000+0100},
  author = {Paradiso, Joseph and Gips, Jonathan and Laibowitz, Mathew and Sadi, Sajid and Merrill, David and Aylward, Ryan and Maes, Pattie and Pentland, Alex},
  biburl = {http://www.bibsonomy.org/bibtex/237b13a9085306104ac242a9595cb76bd/hotho},
  description = {SpringerLink - Zeitschriftenbeitrag},
  interhash = {2147daa8d319533a06f0b0eb0b3c4a54},
  intrahash = {37b13a9085306104ac242a9595cb76bd},
  journal = {Personal and Ubiquitous Computing},
  keywords = {network rfid toread},
  month = {#feb#},
  number = 2,
  pages = {137--152},
  timestamp = {2010-02-19T13:49:58.000+0100},
  title = {Identifying and facilitating social interaction with a wearable wireless sensor network},
  url = {http://dx.doi.org/10.1007/s00779-009-0239-2},
  volume = 14,
  year = 2010
}

Endnote record

%0 Journal Article
%1 joseph2010identifying
%A Paradiso, Joseph
%A Gips, Jonathan
%A Laibowitz, Mathew
%A Sadi, Sajid
%A Merrill, David
%A Aylward, Ryan
%A Maes, Pattie
%A Pentland, Alex
%D 2010
%J Personal and Ubiquitous Computing
%K 
%N 2
%P 137--152
%T Identifying and facilitating social interaction with a wearable wireless sensor network
%U http://dx.doi.org/10.1007/s00779-009-0239-2
%V 14
%X Abstract&nbsp;&nbsp;We have designed a highly versatile badge system to facilitate a variety of interaction at large professional or social events
and serve as a platform for conducting research into human dynamics. The badges are equipped with a large LED display, wirelessinfrared and radio frequency networking, and a host of sensors to collect data that we have used to develop features and algorithmsaimed at classifying and predicting individual and group behavior. This paper overviews our badge system, describes the interactionsand capabilities that it enabled for the wearers, and presents data collected over several large deployments. This data isanalyzed to track and socially classify the attendees, predict their interest in other people and demonstration installations,profile the restlessness of a crowd in an auditorium, and otherwise track the evolution and dynamics of the events at whichthe badges were run.