• Title/Summary/Keyword: human adaptive appliance

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Estimation of Metabolic Rate Estimation for Location-based Human Adaptive Air-conditioner in Smart Home (스마트 홈에서 위치 기반 인간 적응형 냉난방기를 위한 신체 활동량 추정)

  • Kim, Hyun-Hee;Lee, Suk;Lee, Kyung-Chang
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.1
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    • pp.83-89
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    • 2010
  • If an appliance perceives the location or health condition of a resident in the smart home, it can provide more intelligent service actively. That is, while the conventional appliance is operated by manual input of a resident, the location-based human adaptive appliance detects the resident's information such as location, activity pattern, or health condition by itself and provides the most suitable living condition for the resident autonomously. This paper presents the real-time location-based metabolic rate estimation method that measures the amount of physical activity (metabolic rate) for location-based human adaptive air-conditioner. And, the feasibility of the algorithm is evaluated experimentally on a test bed using the pyroelectric infrared sensor-based indoor location aware system (PILAS) that is a non-terminal-based location-aware system.

Metabolic Rate Estimation for ECG-based Human Adaptive Appliance in Smart Homes (인간 적응형 가전기기를 위한 거주자 심박동 기반 신체활동량 추정)

  • Kim, Hyun-Hee;Lee, Kyoung-Chang;Lee, Suk
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.5
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    • pp.486-494
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    • 2014
  • Intelligent homes consist of ubiquitous sensors, home networks, and a context-aware computing system. These homes are expected to offer many services such as intelligent air-conditioning, lighting control, health monitoring, and home security. In order to realize these services, many researchers have worked on various research topics including smart sensors with low power consumption, home network protocols, resident and location detection, context-awareness, and scenario and service control. This paper presents the real-time metabolic rate estimation method that is based on measured heart rate for human adaptive appliance (air-conditioner, lighting etc.). This estimation results can provide valuable information to control smart appliances so that they can adjust themselves according to the status of residents. The heart rate based method has been experimentally compared with the location-based method on a test bed.