The importance of educational buildings’ Indoor Environmental Quality (IEQ) is critically increased due to the COVID-19 pandemic. The need to protect occupants and preserve educational spaces where learning activities could proceed in attendance promotes the development of strategies to monitor and correct the indoor conditions on a real-time basis. The adaptability of building spaces aimed at optimizing comfort and users’ health and safety may be connected to a Digital Twin (DT) and a Building Management System (BMS), enabling data collection and diagnostic to trigger corrective actions on indoor air conditions. A soft DT, i.e., one based on a Building Information Model (BIM) with a low Level of Geometry (LOG) coupled with an IoT network, is proposed to collect results from IEQ monitoring in educational spaces. The DT is aimed to measure the CO2 emissions and Particulate Matter (PM) pollutants, balancing the need for increased ventilation rates to dilute contaminants and thus reduce the infection risk and the control of comfort conditions. Besides the DT, a stand-alone particulate matter sensor has been used to verify the possible inverse influence of the increased ventilation on indoor pollutants coming from outside. This approach enables pupils to learn in a healthy and protected environment.

Soft Digital Twin for IEQ enabling the COVID risk mitigation in educational spaces

F. Re Cecconi;E. De Angelis;
2021

Abstract

The importance of educational buildings’ Indoor Environmental Quality (IEQ) is critically increased due to the COVID-19 pandemic. The need to protect occupants and preserve educational spaces where learning activities could proceed in attendance promotes the development of strategies to monitor and correct the indoor conditions on a real-time basis. The adaptability of building spaces aimed at optimizing comfort and users’ health and safety may be connected to a Digital Twin (DT) and a Building Management System (BMS), enabling data collection and diagnostic to trigger corrective actions on indoor air conditions. A soft DT, i.e., one based on a Building Information Model (BIM) with a low Level of Geometry (LOG) coupled with an IoT network, is proposed to collect results from IEQ monitoring in educational spaces. The DT is aimed to measure the CO2 emissions and Particulate Matter (PM) pollutants, balancing the need for increased ventilation rates to dilute contaminants and thus reduce the infection risk and the control of comfort conditions. Besides the DT, a stand-alone particulate matter sensor has been used to verify the possible inverse influence of the increased ventilation on indoor pollutants coming from outside. This approach enables pupils to learn in a healthy and protected environment.
16 SDEWES Conference digital proceedings
18477178
Digital Twin, Indoor Environment Quality, Educational Buildings, Internet of Things, Environmental sensors, Building Management System, SARS-CoV-2infection
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1187733
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