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A novel occupant-centric stratum ventilation system using computer vision : Occupant detection, thermal comfort, air quality, and energy savings

Yang, Bin (författare)
Xian Univ Architecture & Technol, Sch Bldg Serv Sci & Engn, Xian 710055, Peoples R China.;Tianjin Chengjian Univ, Sch Energy & Safety Engn, Tianjin 300384, Peoples R China.
Liu, Yihang (författare)
Xian Univ Architecture & Technol, Sch Bldg Serv Sci & Engn, Xian 710055, Peoples R China.
Liu, Pengju (författare)
Xian Univ Architecture & Technol, Sch Bldg Serv Sci & Engn, Xian 710055, Peoples R China.
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Wang, Faming (författare)
Katholieke Univ Leuven, Dept Biosyst, B-3001 Leuven, Belgium.
Cheng, Xiaogang (författare)
Nanjing Univ Posts & Telecommun, Coll Telecommun & Informat Engn, Nanjing 210042, Peoples R China.
Lv, Zhihan, Dr. 1984- (författare)
Uppsala universitet,Institutionen för speldesign
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Xian Univ Architecture & Technol, Sch Bldg Serv Sci & Engn, Xian 710055, Peoples R China;Tianjin Chengjian Univ, Sch Energy & Safety Engn, Tianjin 300384, Peoples R China. Xian Univ Architecture & Technol, Sch Bldg Serv Sci & Engn, Xian 710055, Peoples R China. (creator_code:org_t)
Elsevier, 2023
2023
Engelska.
Ingår i: Building and Environment. - : Elsevier. - 0360-1323 .- 1873-684X. ; 237
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Traditional ventilation and air conditioning systems typically operate on a predetermined schedule with fixed operating parameters. Occupant-centric control (OCC) strategies have been proposed to reduce system operation energy consumption without sacrificing thermal comfort. Indoor occupancy detection in real time is a critical step in successfully implementing the OCC strategy. Thus, the deep learning-based computer vision method was adopted in the first step of the study, and the detection performance and camera position were analyzed in an office scenario. Next, the proposed OCC strategy was used to regulate the supply air parameters and outdoor air volume in stratum ventilation based on the monitored occupant number. The traditional static control strategy was then compared to two control strategies: constant air volume and variable air volume. Occupant detection performance results showed the mean NRMSD for the five most common relative positions of the occupants and camera was 0.1109, with sitting back to camera having the lowest accuracy. Subjective response results demonstrated that, when compared to the traditional control strategy, thermal comfort was improved by 43%-73%, perceived air quality was maintained at an acceptable level, CO2 concentration was less than 700 ppm, and energy could be saved by 2.3%-8.1%. Furthermore, the lower the occupancy, the greater the improvement in comfort and the greater the energy savings. This research focused on how the stratum ventilation system responds to dynamic changes in occupancy and provided insights into reducing unnecessary energy waste while maintaining comfort.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Husbyggnad (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Building Technologies (hsv//eng)

Nyckelord

Occupant-centric control strategy
Occupant detection
Stratum ventilation
Thermal comfort
Energy savings
Computer vision

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