Review of vision-based occupant information sensing systems for occupant-centric control

被引:46
作者
Choi, Haneul [1 ]
Um, Chai Yoon [1 ]
Kang, Kyungmo [1 ]
Kim, Hyungkeun [1 ]
Kim, Taeyeon [1 ]
机构
[1] Yonsei Univ, Dept Architecture & Architectural Engn, Seoul 03722, South Korea
基金
新加坡国家研究基金会;
关键词
Vision-based system; Computer vision; Building control; Occupant information; Thermal comfort; Occupant-centric control; REAL-TIME; THERMAL COMFORT; PREDICTIVE CONTROL; SKIN TEMPERATURE; TRACKING; RECOGNITION; PEOPLE; ALGORITHM; MODEL;
D O I
10.1016/j.buildenv.2021.108064
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Vision-based (camera-based) systems, which can effectively sense occupant information, have garnered attention as a core technology in the Fourth Industrial Revolution. A detailed understanding of vision-based sensing systems is required to detect occupant information based on vision and use it for occupant-centric control. Therefore, in this study, we performed a comprehensive and structural literature review of vision-based occupant information systems. The contributions of this review can be summarized in the following six points: (1) a fivetier taxonomy of vision-based occupant information is proposed, (2) a systematic summary of vision-based occupant information is presented, (3) the quantitative and qualitative performance of sensing systems is reviewed, (4) an analysis of the applicability of deep-learning-based computer vision techniques is presented, (5) a summary of privacy-preserving techniques is included, and (6) a summary of vision-based control strategies and energy saving potential analysis is provided. The analysis in this review is an important contribution toward addressing the challenges in the field of research.
引用
收藏
页数:19
相关论文
共 131 条
  • [1] A. ASHRAE, 2019, ASHRAE 621 2019 VENT
  • [2] Automatic HVAC control with real-time occupancy recognition and simulation-guided model predictive control in low-cost embedded system
    Aftab, Muhammad
    Chen, Chien
    Chau, Chi-Kin
    Rahwan, Talal
    [J]. ENERGY AND BUILDINGS, 2017, 154 : 141 - 156
  • [3] Ahmad J., 2018, P P SAI INTELLIGENT, P957
  • [4] 2D Human Pose Estimation: New Benchmark and State of the Art Analysis
    Andriluka, Mykhaylo
    Pishchulin, Leonid
    Gehler, Peter
    Schiele, Bernt
    [J]. 2014 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2014, : 3686 - 3693
  • [5] [Anonymous], 2004, ANSI/ASHRAE Standard 62.1
  • [6] [Anonymous], 2019, AS901
  • [7] [Anonymous], 2019, APPL SCI
  • [8] A comparative study of predicting individual thermal sensation and satisfaction using wrist-worn temperature sensor, thermal camera and ambient temperature sensor
    Aryal, Ashrant
    Becerik-Gerber, Burcin
    [J]. BUILDING AND ENVIRONMENT, 2019, 160
  • [9] ASHRAE, 2018, ASHRAE HDB HVAC APPL
  • [10] Speeded-Up Robust Features (SURF)
    Bay, Herbert
    Ess, Andreas
    Tuytelaars, Tinne
    Van Gool, Luc
    [J]. COMPUTER VISION AND IMAGE UNDERSTANDING, 2008, 110 (03) : 346 - 359