Abstract:
Abstract: Fires in large buildings can have tragic consequences, including the loss of human lives.
Despite the advancements in building construction and fire safety technologies, the unpredictable
nature of fires, particularly in large buildings, remains an enormous challenge. Acknowledging the
paramount importance of prioritising human safety, the academic community has been focusing
consistently on enhancing the efficiency of building evacuation. While previous studies have inte-
grated evacuation simulation models, aiding in aspects such as the design of evacuation routes and
emergency signalling, modelling human behaviour during a fire emergency remains challenging due
to cognitive complexities. Moreover, behavioural differences from country to country add another
layer of complexity, hindering the creation of a universal behaviour model. Instead of centring on
modelling the occupant behaviour, this paper proposes an innovative approach aimed at enhancing
the occupants’ behaviour predictability by providing real-time information to the occupants regarding
the most suitable evacuation routes. The proposed models use a building’s environmental conditions
to generate contextual information, aiding in developing solutions to make the occupants’ behaviour
more predictable by providing them with real-time information on the most appropriate and efficient
evacuation routes at each moment, guiding the occupants to safety during a fire emergency. The
models were incorporated into a context-aware recommender system for testing purposes. The
simulation results indicate that such a system, coupled with hazard and congestion models, positively
influences the occupants’ behaviour, fostering faster adaptation to the environmental conditions and
ultimately enhancing the efficiency of building evacuations.
