Application of Smart Meters for Detecting Human Activity: Concept and Case Study

Kijun Kim, Noboru Koshizuka, Shota Narisawa

Abstract: With the widespread implementation of smart meter infrastructure, various applications have been proposed and implemented beyond energy usage monitoring and savings. In particular, there has been a growing interest in using smart meter data for daily life monitoring and remote care systems by visualizing human activities based on electricity, gas, and water usage. Previous research has demonstrated the feasibility of activity detection using an individual smart meter dataset. However, research on the effectiveness of using multiple smart meter datasets is limited. This paper proposes a model for Activities of Daily Living (ADLs) detection using multiple smart meter datasets (i.e., gas and electricity). To evaluate the performance of the proposed approach, a case study was conducted with 47 households for one month, collecting electricity data, gas data, and ground truth data about ADLs. The case study results showed that our proposed approach, which uses multiple smart meter datasets, enables more accurate activity detection.