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Real-life Experimental Data Acquisition in Smart Home and Data Analysis Tool Development
Tatsuya Yamazaki,Tetsuo Toyomura 한국과학기술원 인간친화 복지 로봇 시스템 연구센터 2008 International Journal of Assistive Robotics and Me Vol.9 No.4
Collecting smart environment experimental data in a real situation and sharing the data are necessary to make the technologies used in the smart environment more practical. We have developed a data analysis tool for the real-life experiment data collected in a smart home environment. the subjects of the 16-day experimental data were a couple of husband and wife in their sixties. the data analysis tool as well as the collected data with the consent of the subjects is open for the purpose of research and development. In this paper, we introduce how the data were collected and the outline of the data analysis tool to promote interdisciplinary research and standardization activities in the field of smart environments.
Real-life Experimental Data Acquisition in Smart Home and Data Analysis Tool Development
Tatsuya Yamazaki,Tetsuo Toyomura 동국대학교 정보융합기술원 2008 International Journal of Assistive Robotics and Sy Vol.9 No.4
Collecting smart environment experimental data in a real situation and sharing the data are necessary to make the technologies used in the smart environment more practical. We have developed a data analysis tool for the real-life experiment data collected in a smart home environment. The subjects of the 16-day experimental data were a couple of husband and wife in their sixties. The data analysis tool as well as the collected data with the consent of the subjects is open for the purpose of research and development. In this paper, we introduce how the data were collected and the outline of the data analysis tool to promote interdisciplinary research and standardization activities in the field of smart environments.
Takekazu Kato,Hyun Sang Cho,Dongwook Lee,Tetsuo Toyomura,Tatsuya Yamazaki 동국대학교 정보융합기술원 2009 International Journal of Assistive Robotics and Sy Vol.10 No.4
We are developing a novel home network system based upon the integration of information and energy. The system aims to analyze user behavior with a power-sensing network and provide various life-support services to manage power and electric appliances according to user behavior and preferences. This paper describes an electric appliance recognition method using power-sensing data measured by CECU (Communication and Energy Care Unit) which is an intelligent outlet with voltage and current sensors to integrate legacy appliances (which are incompatible with a communication network) within the home network. Furthermore, we demonstrate a prototype home energy management system and examples of services based upon appliance recognition.