Using Sound Source Localization to Monitor and Infer Activities in the Home

Abstract

Recent research in ubiquitous computing has focused both on how to infer human activity from a variety of signals sensed in the environment as well as how to use that information to support interactions. In this paper, we examine the feasibility and usefulness of sound source localization (SSL) in a home environment, which is an implicit location system to support monitoring of a remote space as well as to infer key activities, such as face-to-face conversations. We present a microphone array system that covers a significant portion of the public space in a realistic home setting and discuss monitoring and automated inferring applications that are made possible with this technology in a domestic setting.