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Dr Steve Gwynne, alongside co-authors, recently published a paper regarding A Framework for Intelligent Fire Detection and Evacuation System
Fire incidents in large buildings pose challenges for occupants and first responders. Occupants need to find safe evacuation routes while first responders need to maneuver their way into the building. Fire conditions can become uncontrollable without warning to those located in remote sections of the building. Application of Artificial Intelligence (AI) could help guide occupants to safe evacuation routes and first responders into the building. Here, we propose an integrated trained AI and data collection system that can make short-term predictions on fire behaviour, structural integrity and optimal egress path(s). The system can distribute guidance to users via mobile devices or public address systems.
Several studies have explored intelligent evacuation guidance systems consisting of various sub-components such as fire detection, monitoring building conditions, locating occupants, crowd management and guiding evacuation routes [1,2,3]. A notable example is the “Understanding Data through Reasoning, Extraction, and sYnthesis (AUDREY)” system [4]. AUDREY utilizes the concept of Artificial General Intelligence (AGI) to provide a Human Like Reasoning (HLR) to extract useful information from sensors and provide it to firefighters on a head up display.
Reference:
Gomaa, I., Adelzadeh, M., Gwynne, S. et al. A Framework for Intelligent Fire Detection and Evacuation System. Fire Technol57, 3179–3185 (2021). https://doi.org/10.1007/s10694-021-01157-3