Sensor-based adaptive activity recognition with dynamically available sensors

Wen, Jiahui and Wang, Zhiying (2016) Sensor-based adaptive activity recognition with dynamically available sensors. Neurocomputing, 218 9: 307-317. doi:10.1016/j.neucom.2016.08.077

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Author Wen, Jiahui
Wang, Zhiying
Title Sensor-based adaptive activity recognition with dynamically available sensors
Journal name Neurocomputing   Check publisher's open access policy
ISSN 1872-8286
Publication date 2016-12-19
Year available 1997
Sub-type Article (original research)
DOI 10.1016/j.neucom.2016.08.077
Open Access Status File (Author Post-print)
Volume 218
Issue 9
Start page 307
End page 317
Total pages 11
Place of publication Amsterdam, Netherlands
Publisher Elsevier BV
Language eng
Subject 1706 Computer Science Applications
2805 Cognitive Neuroscience
1702 Artificial Intelligence
Abstract An activity recognition system essentially processes raw sensor data and maps them into latent activity classes. Most of the previous systems are built with supervised learning techniques and pre-defined data sources, and result in static models. However, in realistic and dynamic environments, original data sources may fail and new data sources become available, a robust activity recognition system should be able to perform evolution automatically with dynamic sensor availability in dynamic environments. In this paper, we propose methods that automatically incorporate dynamically available data sources to adapt and refine the recognition system at run-time. The system is built upon ensemble classifiers which can automatically choose the features with the most discriminative power. Extensive experimental results with publicly available datasets demonstrate the effectiveness of our methods.
Keyword Activity adaptation
Activity recognition
Extra context
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 2 times in Scopus Article | Citations
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