Activity Strength Recognition Using a Binary Infrared Sensor Array

Abstract

Smart environments such as smart homes and smart offices have attracted great attention in recent years. Smart home is one solution for senior care in a super–aging society like Japan. Since smart home is a private space, devices like video camera and voice recorder cannot be used. The objective of this research is to investigate technologies for constructing privacypreserving smart home systems. In this paper, we try to use an array of binary infrared sensors to recognize the activity strengths. By activity strength here we mean the speed of a certain action. Because daily–life activities (DLAs) can be considered time sequences of different activity strengths, results obtained in this paper can provide insights about sensor–based DLA recognition. Experimental results show that an array consisting of 15 sensors can provide information for a machine learner to recognize activity strengths well, and the accuracy does not depend on the location of the subject.