Journal of the Korean Solar Energy Society (한국태양에너지학회 논문집)

The Korean Solar Energy Society (한국태양에너지학회)
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A Study on Occupancy Estimation Method of a Private Room Using IoT Sensor Data Based Decision Tree Algorithm

IoT 센서 데이터를 이용한 단위실의 재실추정을 위한 Decision Tree 알고리즘 성능분석

  • Kim, Seok-Ho (Department of Architectural Engineering, Chungbuk National University) ;
  • Seo, Dong-Hyun (Department of Architectural Engineering, Chungbuk National University)
  • 김석호 (충북대학교 건축공학과) ;
  • 서동현 (충북대학교 건축공학과)
  • Received : 2017.02.06
  • Accepted : 2017.04.25
  • Published : 2017.04.30
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Abstract

Accurate prediction of stochastic behavior of occupants is a well known problem for improving prediction performance of building energy use. Many researchers have been tried various sensors that have information on the status of occupant such as $CO_2$ sensor, infrared motion detector, RFID etc. to predict occupants, while others have been developed some algorithm to find occupancy probability with those sensors or some indirect monitoring data such as energy consumption in spaces. In this research, various sensor data and energy consumption data are utilized for decision tree algorithms (C4.5 & CART) for estimation of sub-hourly occupancy status. Although the experiment is limited by space (private room) and period (cooling season), the prediction result shows good agreement of above 95% accuracy when energy consumption data are used instead of measured $CO_2$ value. This result indicates potential of IoT data for awareness of indoor environmental status.

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