Abstract: Depending on the location of the air conditioner and the shape of a room, air-conditioning control may be inefficient resulting in temperature imbalance. When attempting to solve this problem, it is vital to understand the spatial structure of a room (including its size and shape) and the location of air conditioners and then automatically control the airflow and direction according to the structure. However, such a method for recognizing spatial structures has not yet been established. In this paper, we propose a spatial recognition method using stereo infrared array sensors (SIRA sensors) installed in an air conditioner. Our system detects objects in the obtained thermal images and estimates their distances using triangulation. In addition, the room's size and shape are estimated based on the assumption that the room size lies within the detection range. The distances to the front and left/right walls were estimated in one-meter-wide classes. The estimation accuracy was compared using two types of IRA sensors: thermopile array sensors and thermal diode infrared sensors. Regarding the distance estimation of persons from the captured stereo thermal images, the average error rate was 12.5% for both types. The distance to each wall was estimated within a 1 m error range for the thermal diode infrared sensor. Moreover, applications of the proposed spatial recognition to air-conditioning control were demonstrated. Specifically, we propose a method to control the airflow direction and volume by considering the room’s geometry. An L-shaped room was modeled and simulated. From the results, the spatial recognition reduced the unevenness in temperature by adjusting the airflow based on the room shape. These results indicate that the proposed method can be practically used for spatial recognition to efficiently improve user comfort by controlling air-conditioning based on the spatial structure and eliminating uneven temperature.
External IDs:dblp:conf/iecon/TakayamaSSN21
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