Estimation of metabolic rate for location-based human adaptive air-conditioner in smart home

Abstract

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.