A lifestyle monitoring system for older adults living independently using low-resolution smart meter data
B. M. Mathunjwa, Y. F. Chen, T. C. Tsai, Y. L. Hsu
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AbstractThere are three types of technologies commonly used in home monitoring services: (1) Wearable devices, which can be uncomfortable and intrusive to users; (2) Ambient sensors, which require extra installation; and (3) household meters, such as smart electricity and water meters. Smart household meters are becoming an essential part of the smart city infrastructure. Previous research focused on applying NIALM techniques to identify specific appliance usage using high-resolution smart meter data (one data every 10 seconds) [Delvin and Hayes, 2019]. This approach employs supervised learning, which is difficult to implement in practical situations and may cause privacy concerns. Japanese power companies have used low-resolution smart-meter data (one data every 30 minutes) to monitor the lifestyle of older adults living independently. Their approach relies entirely on power consumption data and does not map to appliance usage. In this study, we aim to develop a lifestyle monitoring system using low-resolution smart meter data (one data every 15 minutes) for older adults living independently at home. Power consumption data is mapped to appliance usage (0/1), which often relates to the elder’s activities of daily living (ADL). Indices of “activity” and “regularity” of appliance usage based on comparison with the pattern of the past 28 days are calculated.Keywords: lifestyle monitoring, older adults, independent living, smart meter data, remote monitoring
B. M. Mathunjwa, Y. F. Chen, T. C. Tsai, Y. L. Hsu (2024). A lifestyle monitoring system for older adults living independently using low-resolution smart meter data. Gerontechnology, 23(2), 1-1
https://doi.org/10.4017/gt.2024.23.s.966.opp