Real-Time Energy Measurement for Non-Intrusive Well-Being Monitoring of Elderly People -- a Case Study
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866917709160120320 |
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| author | Brzozowski, Mateusz Janicki, Artur |
| author_facet | Brzozowski, Mateusz Janicki, Artur |
| contents | This article presents a case study demonstrating a non-intrusive method for the well-being monitoring of elderly people. It is based on our real-time energy measurement system, which uses tiny beacons attached to electricity meters. Four participants aged 67-82 years took part in our study. We observed their electric power consumption for approx. a month, and then we analyzed them, taking into account the participants' notes on their activities. We created typical daily usage profiles for each participant and used anomaly detection to find unusual energy consumption. We found out that real-time energy measurement can give significant insight into someone's daily activities and, consequently, bring invaluable information to caregivers about the well-being of an elderly person, while being discreet and entirely non-intrusive. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_00524 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Real-Time Energy Measurement for Non-Intrusive Well-Being Monitoring of Elderly People -- a Case Study Brzozowski, Mateusz Janicki, Artur Computers and Society Machine Learning Signal Processing J.3; I.5.3 This article presents a case study demonstrating a non-intrusive method for the well-being monitoring of elderly people. It is based on our real-time energy measurement system, which uses tiny beacons attached to electricity meters. Four participants aged 67-82 years took part in our study. We observed their electric power consumption for approx. a month, and then we analyzed them, taking into account the participants' notes on their activities. We created typical daily usage profiles for each participant and used anomaly detection to find unusual energy consumption. We found out that real-time energy measurement can give significant insight into someone's daily activities and, consequently, bring invaluable information to caregivers about the well-being of an elderly person, while being discreet and entirely non-intrusive. |
| title | Real-Time Energy Measurement for Non-Intrusive Well-Being Monitoring of Elderly People -- a Case Study |
| topic | Computers and Society Machine Learning Signal Processing J.3; I.5.3 |
| url | https://arxiv.org/abs/2407.00524 |