A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Review of vision-based occupant information sensing systems for occupant-centric control
https://orcid.org/0000-0003-2519-6348
https://orcid.org/0000-0003-2984-5739
Abstract 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.
Highlights Trend of vision-based research for occupant-centric building control was analyzed. Systematic taxonomy of vision-based occupant information was proposed. Sensing performance of vision-based systems was quantitatively and qualitatively reviewed. Sensing techniques for occupant information were reviewed focusing on deep learning and privacy preservation. Control strategy and energy saving potential of vision-based building control were reviewed.
Review of vision-based occupant information sensing systems for occupant-centric control
https://orcid.org/0000-0003-2519-6348
https://orcid.org/0000-0003-2984-5739
Abstract 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.
Highlights Trend of vision-based research for occupant-centric building control was analyzed. Systematic taxonomy of vision-based occupant information was proposed. Sensing performance of vision-based systems was quantitatively and qualitatively reviewed. Sensing techniques for occupant information were reviewed focusing on deep learning and privacy preservation. Control strategy and energy saving potential of vision-based building control were reviewed.
Review of vision-based occupant information sensing systems for occupant-centric control
https://orcid.org/0000-0003-2519-6348
https://orcid.org/0000-0003-2984-5739
Abstract 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.
Highlights Trend of vision-based research for occupant-centric building control was analyzed. Systematic taxonomy of vision-based occupant information was proposed. Sensing performance of vision-based systems was quantitatively and qualitatively reviewed. Sensing techniques for occupant information were reviewed focusing on deep learning and privacy preservation. Control strategy and energy saving potential of vision-based building control were reviewed.
Review of vision-based occupant information sensing systems for occupant-centric control
Choi, Haneul (author) / Um, Chai Yoon (author) / Kang, Kyungmo (author) / Kim, Hyungkeun (author) / Kim, Taeyeon (author)
Building and Environment ; 203
2021-06-16
Article (Journal)
Electronic Resource
English