Elderly monitoring system based on multisensor information fusion

Yajiang Chen; Shuwang Chen; Yifei Ma

doi:10.1117/12.3035780

20 November 2024 Elderly monitoring system based on multisensor information fusion

Yajiang Chen, Shuwang Chen, Yifei Ma

Author Affiliations +

Proceedings Volume 13243, Advanced Sensor Systems and Applications XIV; 132430S (2024) https://doi.org/10.1117/12.3035780
Event: SPIE/COS Photonics Asia, 2024, Nantong, Jiangsu, China

Conference Poster

Abstract

Traditional monitoring systems for older adults typically rely on a single type of sensor, resulting in limited data sources that limit the comprehensiveness and diversity of monitoring. This limitation makes it difficult for the system to effectively and comprehensively identify complex abnormal behaviors, thus failing to provide sufficient data support for decision-making. To address this problem, this study proposes a multi-sensor information fusion-based monitoring system for the elderly. The system employs an advanced fusion algorithm to fuse data from visible, infrared and other sensors. To further improve the accuracy and coverage of the system monitoring, this study introduces a fusion genetic wolf pack algorithm to optimize the sensor layout and ensure the optimal configuration of sensors in the monitoring environment. By combining multi-sensor information fusion with optimal layout, the system not only monitors the multidimensional living environment and physiological state of the elderly more accurately, and provides comprehensive and accurate monitoring of the elderly's daily activities and health status, but also provides a solid data base for the detection and processing of abnormal behaviors.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yajiang Chen, Shuwang Chen, and Yifei Ma "Elderly monitoring system based on multisensor information fusion", Proc. SPIE 13243, Advanced Sensor Systems and Applications XIV, 132430S (20 November 2024); https://doi.org/10.1117/12.3035780

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