Situative Space Tracking within Smart Environments
- Dipak Surie,
- Florian Jäckel,
- Lars-Erik Janlert,
- Thomas Pederson
- Umeå University
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review
Open access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPages from-to (Number of pages)
Pages 152-157 (6 pages)Publication milestones
- Published - 19/07/2010
Publication status
Published - 19/07/2010
Publisher
IEEE, United StatesISBN (Print)
978-0-7695-4149-5ISBN (Electronic)
978-0-7695-4149-5Publication IDs
- Scopus: 78751661804
Host publication title
Proceedings of the 6th International Conference on Intelligent EnvironmentsAbstract
This paper describes our efforts in modeling and
tracking a human agent’s situation based on his/her possibilities
to perceive and act upon objects (both physical and virtual)
within smart environments. A Situative Space Model is proposed.
WLAN signal-strength-based situative space tracking system that
positions objects within individual situative spaces (without
tracking their absolute positions) distributed across multiple
modalities like vision, audio, and touch is presented. As a proofof-
concept, a preliminary evaluation of the tracking system was
performed by two subjects within a living-laboratory smart home
environment where a global precision of 83.4% and a global
recall of 88.6% were obtained.
tracking a human agent’s situation based on his/her possibilities
to perceive and act upon objects (both physical and virtual)
within smart environments. A Situative Space Model is proposed.
WLAN signal-strength-based situative space tracking system that
positions objects within individual situative spaces (without
tracking their absolute positions) distributed across multiple
modalities like vision, audio, and touch is presented. As a proofof-
concept, a preliminary evaluation of the tracking system was
performed by two subjects within a living-laboratory smart home
environment where a global precision of 83.4% and a global
recall of 88.6% were obtained.
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