Real-Time Egress Model for Multiplex Buildings under Fire Based on Artificial Neural Network

Abstract

When fire occurs in a large multiplex building, the direction of smoke and flames is often similar to that of the evacuation of building occupants. This causes evacuation bottlenecks in a specific compartment, especially when the occupant density is very high, which unfortunately often leads to many fatalities and injuries. Thus, the development of an egress model that can ensure the safe evacuation of occupants is required to minimize the number of casualties. In this study, the correlations between fire temperature with visibility and toxic gas concentration were investigated through a fire simulation on a multiplex building, from which databases for training of artificial neural networks (ANN) were created. Based on this, an ANN model that can predict the available safe egress time was developed, and it estimated the available safe egress time (ASET) very accurately. In addition, an egress model that can guide rapid and safe evacuation routes for occupants was proposed, and the rationality of the proposed model was verified in detail through an application example. The proposed model provided the optimal evacuation route with the longest margin of safety in consideration of both ASET and the movement time of occupants under fire.

A review of the contributions of Artificial Intelligence in fire engineering, in a world rapidly realising the need for sustainable design

“…On the management front, ANNs have been used to help researchers determine the required evacuation time from multiplex buildings under fire conditions, based on temperature, visibility and toxic gas concentration figures. CFD analysis offered the required data for training the AI algorithms [42]. Instead of CFD analysis, fire scenarios from previous disasters in large residential buildings can also be used to train ANNs to assist with the assessment of proposed fire strategy plans [43].…”

Egress Safety Criteria for Nursing Hospitals

“…Abdelghany et al [11], Cho et al [12], and Xie et al [13] performed research on the improvement of egress models considering way-finding guidance. In addition, there have been many other studies on fire or egress simulation to estimate fire safety [14][15][16][17][18][19][20][21][22][23][24][25][26].…”