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Ways of Knowing in HCI pp 291–321Cite as

Sensor Data Streams

Abstract

It is possible today to collect streams of data from sensors in the environment (e.g., on walls of buildings) or attached to individuals (e.g., badges that record location and with whom one is speaking). The data from these sensors allows researchers to trace people’s behavior with and without various technology interventions or incentives intended to change behavior. These traces can also be used inside technologies, for example to sense when it is a good time to interrupt a person with a message.

Keywords

  • Data Stream
  • Sensor Data
  • Ubiquitous Computing
  • Gesture Recognition
  • Experience Sampling Method

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Authors and Affiliations

  1. Indiana University School of Informatics and Computing, Indianapolis (IUPUI), 535 W. Michigan St., IT 475, Indianapolis, IN, 46205, USA

    Stephen Voida

  2. Donald Bren School of Information and Computer Sciences, University of California, Irvine, 5084 Donald Bren Hall, Irvine, CA, 92797-3440, USA

    Donald J. Patterson

  3. Department of Computer Science and Engineering, University of Washington, 352350, Seattle, WA, 98195-2350, USA

    Shwetak N. Patel

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  1. Stephen Voida
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  1. University of California, Irvine, Irvine, California, USA

    Judith S. Olson

  2. Group Social Computing, IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Wendy A. Kellogg

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Voida, S., Patterson, D.J., Patel, S.N. (2014). Sensor Data Streams. In: Olson, J., Kellogg, W. (eds) Ways of Knowing in HCI. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0378-8_12

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