Title :
Estimation of occupancy level in indoor environment based on heterogeneous information fusion
Author :
Wang, Heng-Tao ; Jia, Qing-Shan ; Song, Chen ; Yuan, Ruixi ; Guan, Xiaohong
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
Monitoring the number of occupants in each zone of a building is important for energy-efficient control of the HVAC system and the lighting system under normal conditions and for fast evacuation under emergency conditions. There usually exist multiple systems for localizing and monitoring the occupants in a building such as the active RFID system and the video cameras. The accuracy of each system is affected by different factors. Further hardware investment is usually required to improve the accuracy of each system. It is thus of practical interest to combine multiple systems to achieve higher counting accuracy without further hardware investment. In this paper, this problem is formulated as an information fusion problem under the criterion of minimum mean square error. However, it is usually difficult to solve the problem optimally due to the lack of data on the joint distribution of the observation noises of multiple systems. Two approximation methods are developed following the independence assumption and heuristics, respectively. Experimental results show that the two methods improve the accuracy of the active RFID system and the video cameras by around 43% and 73%, respectively.
Keywords :
HVAC; approximation theory; least mean squares methods; lighting; radiofrequency identification; sensor fusion; video cameras; video signal processing; HVAC system; active RFID system; approximation method; building; emergency condition; energy-efficient control; hardware investment; heterogeneous information fusion; heuristics; indoor environment; lighting system; minimum mean square error; occupancy level estimation; occupancy monitoring; video camera; Accuracy; Approximation methods; Buildings; Cameras; Estimation; Noise; Radiofrequency identification; Information fusion; indoor localization; sensor network;
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-7745-6
DOI :
10.1109/CDC.2010.5717150