Abstract
Identifying ways of monitoring this aging population in their home environment is very important. Sensor-based human activity recognition has proven to be a valid candidate in order to estimate the human activity. This paper proposes a human activity behavior recognition technology based on indoor positioning. Firstly, a location fingerprinted database is constructed by collecting RSSI values and each AP name. The relationship between the feature parameters and the activity was established based on the acceleration values. Secondly, the wearable device captures the RSSI values and acceleration when older people are indoors. Then the system given the corresponding position and action through support vector machine. The probability of positioning accuracy within 2 m is more than 90%, which meets the requirement of indoor positioning accuracy. The action recognition rate is 100%.
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Acknowledgements
This work is partially supported by the Key Research and Development Program of Shaanxi (2019GY-107), Natural Science Foundation of Shaanxi Province (2019JQ-859) and the Scientific Research Program of Shaanxi Provincial Education Committee (18JK0715).
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Pan, Z., Wei, C. Human activity monitoring based on indoor map positioning. Microsyst Technol 27, 2919–2923 (2021). https://doi.org/10.1007/s00542-020-05124-w
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DOI: https://doi.org/10.1007/s00542-020-05124-w