Life-log Data-based Window Opening and Closing for Individual Customized Services in Symbiosis Houses

Abstract

Smart residential spaces designed for residents departs from simply providing conventional standardized services, to go beyond and provide personalized experiences that take individual circumstances into account. Such services play a key role in enhancing the residents’ quality of life. This study looks into such personalized services that reflect different characteristics of a diverse range of residents who have different behavior patterns. Such services can increase the satisfaction of the residents by providing flexible services that take into account the lifestyle and circumstances of each resident. A problem with offering customized services, however, is that there is a dearth of data on individuals. Sufficient amount of data must be collected in order to determine what a proper service for an individual is. As such, this study explains the life-log data and discusses its collection method. The life-log data collected serves as crucial grounds for decision-making. How decisions are made using the life log data is an intriguing research topic. This study proposes and discusses logics and processes of various decision-making methods that can be executed using the life log-data. In their homes, residents tend to regularly display certain behaviors in patterns, which allows for identifying the residents’ behavior patterns, as well as the predicting the residents’ future behavior. In this aspect, the residents’ location, needs, and current behavior must be recognized in order to provide personalized services. As such, this study proposes decision-making method by verifying in-house behavior of Korean elderly with companion dogs in symbiosis homes. Such dog's hair and foul smells cause indoor pollutions that damage elderly heath. This study proposes an automatic personalized window opening and closing service by using life-log data of the resident.