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      From occupants to occupants: A review of the occupant information understanding for building HVAC occupant-centric control

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          Abstract

          Occupants are the core of the built environment. Traditional heating, ventilation, and air-conditioning (HVAC) systems operate with predefined schedules and maximum occupancy assumptions with no consideration of specific occupant information. These generalized assumptions usually do not align with the actual demand and result in over-conditioning and occupant discomfort. In recent years, with the aid of Information & Communication Technology (ICT) and Computer Science (CS), it is possible to acquire real-time and accurate occupant information to satisfy the exact thermal requirement through specific HVAC control in one particular built environment. This mechanism is called HVAC “Occupant-centric Control (OCC).” HVAC OCC strategy starts with collecting the occupant’s information (e.g., presence/absence) and then applies it to meet the occupant’s requirement (e.g., thermal comfort). However, even though some research studies and field pilot demonstrations have been devoted to the field of OCC, there is a lack of systematic knowledge about occupant data, which is the principal component of OCC for HVAC researchers and practitioners. To fill this gap, this review paper discusses OCC with a particular emphasis on occupant information and investigates how this information can assist HVAC operation in providing an acceptable built environment in required spaces during the required time. We provide a fine-grained, comprehensive picture of occupant information, discuss its features, the modalities of information feed-in into the HVAC control, and the application of commonly utilized occupant information for OCC.

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          Most cited references104

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          Association of the infection probability of COVID-19 with ventilation rates in confined spaces

          A growing number of cases have proved the possibility of airborne transmission of the coronavirus disease 2019 (COVID-19). Ensuring an adequate ventilation rate is essential to reduce the risk of infection in confined spaces. In this study, we estimated the association between the infection probability and ventilation rates with the Wells-Riley equation, where the quantum generation rate (q) by a COVID-19 infector was obtained using a reproductive number-based fitting approach. The estimated q value of COVID-19 is 14–48 h−1. To ensure an infection probability of less than 1%, a ventilation rate larger than common values (100–350 m3/h per infector and 1200–4000 m3/h per infector for 0.25 h and 3 h of exposure, respectively) is required. If the infector and susceptible person wear masks, then the ventilation rate ensuring a less than 1% infection probability can be reduced to a quarter respectively, which is easier to achieve by the normal ventilation mode applied in typical scenarios, including offices, classrooms, buses, and aircraft cabins. Strict preventive measures (e.g., wearing masks and preventing asymptomatic infectors from entering public spaces using tests) that have been widely adopted should be effective in reducing the risk of infection in confined spaces.
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            Use of model predictive control and weather forecasts for energy efficient building climate control

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              Occupant behavior modeling for building performance simulation: Current state and future challenges

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                Author and article information

                Contributors
                Zoneill@tamu.edu
                Journal
                Build Simul
                Build Simul
                Building Simulation
                Tsinghua University Press (Beijing )
                1996-3599
                1996-8744
                7 December 2021
                : 1-20
                Affiliations
                [1 ]GRID grid.264756.4, ISNI 0000 0004 4687 2082, J. Mike Walker’ 66 Department of Mechanical Engineering, , Texas A&M University, ; College Station, TX 77843 USA
                [2 ]GRID grid.166341.7, ISNI 0000 0001 2181 3113, Department of Civil, Architectural & Environmental Engineering, , Drexel University, ; Philadelphia, PA 19104 USA
                [3 ]GRID grid.264484.8, ISNI 0000 0001 2189 1568, Department of Mechanical and Aerospace Engineering, , Syracuse University, ; Syracuse, NY 13244 USA
                Article
                861
                10.1007/s12273-021-0861-0
                8654494
                86beb557-d796-4224-9816-5441ba3f974b
                © Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2021

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 7 September 2021
                : 25 October 2021
                : 27 October 2021
                Categories
                Review Article

                occupant information,occupant-centric control,smart building,hvac,energy efficiency

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