Monitoring Indoor Activity of Daily Living Using Thermal Imaging: A Case Study
Hassan M. Ahmed, Bessam Abdulrazak (AMI-Lab Faculte des sciences,, Universite de Sherbrooke)

TL;DR
This paper presents an IoT-based thermal imaging system for monitoring indoor activities of daily living, accurately identifying activity types, estimating temperature, and locating individuals while preserving privacy.
Contribution
It introduces a thermal sensor array system for indoor ADL monitoring, including activity classification, temperature estimation, and spatial localization without compromising privacy.
Findings
Successful identification of three activity classes
Accurate estimation of person's average temperature
Effective spatial location determination
Abstract
Monitoring indoor activities of daily living (ADLs) of a person is neither an easy nor an accurate process. It is subjected to dependency on sensor type, power supply stability, and connectivity stability without mentioning artifacts introduced by the person himself. Multiple challenges have to be overcome in this field, such as; monitoring the precise spatial location of the person, and estimating vital signs like an individuals average temperature. Privacy is another domain of the problem to be thought of with care. Identifying the persons posture without a camera is another challenge. Posture identification assists in the persons fall detection. Thermal imaging could be a proper solution for most of the mentioned challenges. It provides monitoring both the persons average temperature and spatial location while maintaining privacy. In this research, we propose an IoT system for…
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