Monitoring and Assessment of Indoor Environmental Conditions in Educational Building Using Building Information Modelling Methodology
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AuthorAguilar Aguilera, Antonio Jesús; De la Hoz Torres, María Luisa; Ruiz Padillo, Diego Pablo; Martínez Aires, María Dolores
Building information modellingCOVID-19Educational buildingIndoor environmental qualitySensor monitoring
Aguilar, A.J... [et al.]. Monitoring and Assessment of Indoor Environmental Conditions in Educational Building Using Building Information Modelling Methodology. Int. J. Environ. Res. Public Health 2022, 19, 13756. [https://doi.org/10.3390/ijerph192113756]
SponsorshipConsejo General de la Arquitectura Tecnica (CGATE) (2018); State Research Agency (SRA) of Spain; European Commission PID2019-108761RB-I00
Managing indoor environmental quality (IEQ) is a challenge in educational buildings in the wake of the COVID-19 pandemic. Adequate indoor air quality is essential to ensure that indoor spaces are safe for students and teachers. In fact, poor IEQ can affect academic performance and student comfort. This study proposes a framework for integrating occupants’ feedback into the building information modelling (BIM) methodology to assess indoor environmental conditions (thermal, acoustic and lighting) and the individual airborne virus transmission risk during teaching activities. The information contained in the parametric 3D BIM model and the algorithmic environment of Dynamo were used to develop the framework. The IEQ evaluation is based on sensor monitoring and a daily schedule, so the results show real problems of occupants’ dissatisfaction. The output of the framework shows in which range the indoor environmental variables were (optimal, acceptable and unacceptable) and the probability of infection during each lecture class (whether or not 1% is exceeded). A case study was proposed to illustrate its application and validate it. The outcomes provide key information to support the decision-making process for managing IEQ and controlling individual airborne virus transmission risks. Long-term application could provide data that support the management of ventilation strategies and protocol redesign.