SPHCFeb 13, 2020

Augmenting an Assisted Living Lab with Non-Intrusive Load Monitoring

arXiv:2002.05593v116 citationsHas Code
AI Analysis

This addresses energy efficiency and safety monitoring for aging populations in assisted living, but it is incremental as it applies existing methods to a new domain.

The paper tackled the problem of managing energy consumption and monitoring occupants in assisted living by using Non-Intrusive Load Monitoring to break down aggregate power into device-level data without intrusive equipment, and demonstrated detection of abnormal behavior in a case study with common household devices.

The need for reducing our energy consumption footprint and the increasing number of electric devices in today's homes is calling for new solutions that allow users to efficiently manage their energy consumption. Real-time feedback at device level would be of a significant benefit for this application. In addition, the aging population and their wish to be more autonomous have motivated the use of this same real-time data to indirectly monitor the household's occupants for their safety. By breaking down aggregate power consumption into its components, Non-Intrusive Load Monitoring provides information on individual appliances and their current state of operation. Since no additional metering equipment is required, residents are not confronted with intrusion into their familiar environment. Our work aims to depict an architecture supporting non-intrusive measurement with a smart electricity meter and the handling of these data using an open-source platform that allows to visualize and process real-time data about the total energy consumed. As a case study, we describe a series of measurements from common household devices and show how abnormal behavior can be detected.

Foundations

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