A pilot study of occupant centric control stratum ventilation based on computer vision

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Article number01029
Journal / PublicationE3S Web of Conferences
Volume356
Online published31 Aug 2022
Publication statusPublished - 2022

Conference

Title16th ROOMVENT Conference (ROOMVENT 2022)
LocationVirtual
PlaceChina
CityXi'an
Period16 - 19 September 2022

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Abstract

Indoor occupant information has an obvious influence on operating parameters of heating ventilation and air conditioning (HVAC) system, which further affects occupants' thermal comfort and energy consumption. This pilot study proposes an occupant centric control (OCC) strategy for stratum ventilation (SV) to achieve demand control ventilation (DCV). Firstly, the computer vision sensing system and deep learning algorithm are used to detect the number of occupants in real time, and the accuracy of the number of occupants in the office environment was evaluated. Then, the occupant centric stratum ventilation control strategy is designed by the dynamic changes of cooling load. Finally, the thermal comfort and air quality of the thermal environment created by the OCC strategy were evaluated through subject experiment, and the energy consumption of the HVAC system was calculated in combination with the energy consumption simulation software. This study adjusts system setting values according to actual needs, so that the HVAC system responds to the dynamic changes of the indoor cooling load in real time, creating a comfortable and healthy indoor environment in an energy efficient manner. © The Authors, published by EDP Sciences.

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Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

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