Timely daily activity recognition from headmost sensor events
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Updated: Jan 25, 2026

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
Published on: December 11, 2015
Yaqing Liu1, Xiangxin Wang2, Zhengguo Zhai2
1School of Information Science & Technology, Dalian Maritime University, Dalian 116026, China; College of Computer Science and Technology, Jilin University, Changchun 130012, China; Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong 643000, China.
Abstract:
Smart homes are designed to promote safe and comfortable living for inhabitants without any manual intervention. The performance of approaches for daily activity recognition is therefore crucial, but current real-time approaches have to wait until a daily activity ends before performing recognition. We present an approach for timely daily activity recognition from an incomplete stream of sensor events, by which the recognition process can start as soon as a daily activity begins. Activity features are generated from several headmost sensor events rather than from all sensor events that a daily activity activated. A public dataset was utilized to evaluate the presented method. Experimental findings show its effectiveness for timely daily activity recognition in terms of precision, recall, average saved time, and saved time proportion.
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