Appliance Recognition from Electric Current Signals for Information-Energy Integrated Network in Home Environments. Kato, T., Cho, Sang, H., Lee, D., Toyomura, T., & Yamazaki, T. In Mokhtari, M., Khalil, I., Bauchet, J., Zhang, D., & Nugent, C., editors, Ambient Assistive Health and Wellness Management in the Heart of the City, of Lecture Notes in Computer Science, pages 150--157. Springer Berlin Heidelberg, January, 2009.
Appliance Recognition from Electric Current Signals for Information-Energy Integrated Network in Home Environments [link]Paper  abstract   bibtex   
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 communications network) with the home network. Furthermore, we demonstrate a prototype home energy management system and examples of services based upon appliance recognition.
@incollection{ kato_appliance_2009,
  series = {Lecture Notes in Computer Science},
  title = {Appliance Recognition from Electric Current Signals for Information-Energy Integrated Network in Home Environments},
  copyright = {©2009 Springer Berlin Heidelberg},
  isbn = {978-3-642-02867-0, 978-3-642-02868-7},
  url = {http://link.springer.com/chapter/10.1007/978-3-642-02868-7_19},
  abstract = {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 communications network) with the home network. Furthermore, we demonstrate a prototype home energy management system and examples of services based upon appliance recognition.},
  language = {en},
  number = {5597},
  urldate = {2014-09-12TZ},
  booktitle = {Ambient Assistive Health and Wellness Management in the Heart of the City},
  publisher = {Springer Berlin Heidelberg},
  author = {Kato, Takekazu and Cho, Hyun Sang and Lee, Dongwook and Toyomura, Tetsuo and Yamazaki, Tatsuya},
  editor = {Mokhtari, Mounir and Khalil, Ismail and Bauchet, Jérémy and Zhang, Daqing and Nugent, Chris},
  month = {January},
  year = {2009},
  keywords = {Appliance Recognition, Computational Biology/Bioinformatics, Computers and Society, Geriatrics/Gerontology, Home Energy Management System ({HEMS}), Home Network, Image Processing and Computer Vision, Power Sensing Network, Special Purpose and Application-Based Systems, pattern recognition},
  pages = {150--157}
}

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