Review on occupancy detection and prediction in building simulation

作     者：Yan Ding Shuxue Han Zhe Tian Jian Yao Wanyue Chen Qiang Zhang Yan Ding;Shuxue Han;Zhe Tian;Jian Yao;Wanyue Chen;Qiang Zhang

作者机构：School of Environmental Science and EngineeringTianjin Key Laboratory of Built Environment and Energy ApplicationTianjin UniversityTianjin300072 Department of ArchitectureNingbo UniversityNingboChina 

出 版 物：《Building Simulation》 (建筑模拟（英文）)

年 卷 期：2022年第15卷第3期

页      面：333-356页

核心收录：

学科分类：12[管理学] 02[经济学] 0202[经济学-应用经济学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 020205[经济学-产业经济学] 0807[工学-动力工程及工程热物理] 0813[工学-建筑学] 0814[工学-土木工程] 

基　　金：This work is supported by the Nature Science Foundation of Tianjin(No.19JCQNJC07000) the National Nature Science Foundation of China(No.51678396) 

主　　题：occupancy rate monitoring occupancy model occupancy prediction occupancy verification 

摘      要：Energy simulation results for buildings have significantly deviated from actual consumption because of the uncertainty and randomness of occupant *** differences are mainly caused by the inaccurate estimation of occupancy in ***,the error between reality and prediction could be largely reduced by improving the accuracy level of occupancy *** various studies on occupancy have been conducted,there are still many differences in the approaches to detection,prediction,and *** published within this domain are reviewed in this article to discover the advantages and limitations of previous studies,and gaps in the research are identified for future *** methods of monitoring and their combinations are analyzed to provide effective guidance in choosing and applying a *** advantages of deterministic schedules,stochastic schedules,and machine-learning methods for occupancy prediction are summarized and discussed to improve prediction accuracy in future ***,three applications of occupancy models—improving building simulation software,facilitating building operation control,and managing building energy use—are *** review provides theoretical guidance for building design and makes contributions to building energy conservation and thermal comfort through the implementation of intelligent control strategies based on occupancy monitoring and prediction.