Activity Recognition on Streaming Sensor Data

Narayanan C Krishnan; Diane J Cook

doi:10.1016/j.pmcj.2012.07.003

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Activity Recognition on Streaming Sensor Data

Journal article

Open access

Peer reviewed

Activity Recognition on Streaming Sensor Data

Narayanan C Krishnan and Diane J Cook

Pervasive and mobile computing, Vol.10(Pt B), pp.138-154

02/01/2014

DOI: https://doi.org/10.1016/j.pmcj.2012.07.003

Handle:

https://hdl.handle.net/2376/113951

PMCID: PMC3979570

PMID: 24729780

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Abstract

online

streaming

mutual information

real-time

activity recognition

Many real-world applications that focus on addressing needs of a human, require information about the activities being performed by the human in real-time. While advances in pervasive computing have lead to the development of wireless and non-intrusive sensors that can capture the necessary activity information, current activity recognition approaches have so far experimented on either a scripted or pre-segmented sequence of sensor events related to activities. In this paper we propose and evaluate a sliding window based approach to perform activity recognition in an on line or streaming fashion; recognizing activities as and when new sensor events are recorded. To account for the fact that different activities can be best characterized by different window lengths of sensor events, we incorporate the time decay and mutual information based weighting of sensor events within a window. Additional contextual information in the form of the previous activity and the activity of the previous window is also appended to the feature describing a sensor window. The experiments conducted to evaluate these techniques on real-world smart home datasets suggests that combining mutual information based weighting of sensor events and adding past contextual information into the feature leads to best performance for streaming activity recognition.

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Title: Activity Recognition on Streaming Sensor Data
Creators: Narayanan C Krishnan - School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164-2752, USA
Diane J Cook - School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164-2752, USA
Publication Details: Pervasive and mobile computing, Vol.10(Pt B), pp.138-154
Academic Unit: Electrical Engineering and Computer Science, School of
Publisher: Netherlands
Grant note: R01 EB009675 / NIBIB NIH HHS R01 EB015853 / NIBIB NIH HHS
Identifiers: 99900548493701842
Language: English
Resource Type: Journal article