Leveraging AI and IoT for Improved Management of Educational Buildings: Fid-Bau Portal

Leveraging AI and IoT for Improved Management of Educational Buildings

Manga, Ashvin / Allen, Christopher

As countries around the world gradually return to life before the Covid-19 pandemic, it is important for facility management divisions across education sectors to use innovative technology and unique solutions to provide healthy and safe learning environments. This research aimed to improve the management of educational buildings by leveraging innovative technologies. The first objective was to develop a system for real-time occupancy levels within lecture venues. To achieve this, a branch of artificial intelligence known as computer vision was combined with existing CCTV cameras to count occupants in real-time. This was achieved by training a convoluted neural network on a dataset of 15 000 images of ‘human bodies’ extracted from Googles Open Images v6. The second objective was to measure indoor air quality. A medical grade air quality device was placed within the assessed lecture venues and real-time occupant count was correlated against real-time indoor air quality data. The results from this study demonstrate the successful use of computer vision combined with existing CCTV cameras to accurately count occupants in real-time. The study utilised open-source AI resources and provides a method for further computer vision research. Regarding indoor air quality within the assessed educational buildings, the results of this study indicate that even under significantly reduced occupancy levels, carbon dioxide accumulated within assessed venues, indicating inadequate ventilation. The Covid-19 pandemic will not be the last pandemic we encounter. However, facility management can utilise innovative technologies to ensure educational buildings are managed using data-driven strategies that ensure learning environments remain safe and accessible spaces for students.