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Enabling Remote Elderly Care: Design and Implementation of a Smart Energy Data System with Activity Recognition
Patricia Franco1, Felipe Condon1, José M Martínez1
1Department of Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile.
Sensors (Basel, Switzerland)
|September 28, 2023
Summary
Smart energy data from home appliances can monitor seniors living alone, detecting health changes through activity patterns. This system supports remote healthcare and telehealth adoption, especially where smart meters are scarce.
Area of Science:
- Gerontology and Health Informatics
- Machine Learning Applications in Healthcare
- Smart Home Technology
Background:
- Aging populations face challenges like cognitive decline and sensory impairments, increasing the need for effective remote care solutions.
- The shift towards home-centric healthcare services aims to reduce costs and improve patient recovery experiences.
- Smart energy data from home appliances offers a novel approach to continuous remote health monitoring by correlating energy usage with daily activities.
Purpose of the Study:
- To develop and deploy a Smart Energy Data with Activity Recognition (SEDAR) system for monitoring older adults living alone.
- To utilize machine learning techniques for identifying appliance usage and behavioral patterns indicative of health status.
- To explore the potential of energy data analytics for enhancing remote healthcare and telehealth services.
Main Methods:
- Collecting smart energy data from electrical home appliances.
- Applying machine learning algorithms to recognize appliance usage and activity patterns.
- Analyzing deviations from normal routines to infer potential health anomalies.
Main Results:
- The SEDAR system successfully identifies appliance usage and behavior patterns in older adults.
- Deviations in routine activities, detected through energy data, can signal potential health issues like sleep disturbances or confusion.
- The system demonstrates the feasibility of using non-invasive energy data for remote health monitoring.
Conclusions:
- Smart energy data analytics provides a viable method for the remote monitoring of elderly individuals living independently.
- The SEDAR system can support telehealth initiatives by offering insights into seniors' daily routines and health conditions.
- This approach has significant implications for healthcare accessibility in regions with limited smart meter infrastructure.
