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 five-tier 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.
Bibliographical noteFunding Information:
This work was supported by Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government ( MOTIE ) ( 20202020800030 , Development of Smart Hybrid Envelope Systems for Zero Energy Buildings through Holistic Performance Test and Evaluation Methods and Fields Verifications).
© 2021 Elsevier Ltd
All Science Journal Classification (ASJC) codes
- Environmental Engineering
- Civil and Structural Engineering
- Geography, Planning and Development
- Building and Construction