# Real-Time Egress Model for Multiplex Buildings under Fire Based on Artificial Neural Network
## 5 Conclusions  
This study developed a model capable of deriving the optimized evacuation route in the event of fire for general multiplex buildings. The correlations between fire temperature and visibility distance, and between fire temperature and gas concentration, were examined through fire simulations. Based on this, an artificial neural network (ANN) model was proposed, which can estimate the available safe egress time (ASET) for the fire compartment and nonfire compartment in multiplex buildings under fire. The proposed ANN model was then used to develop an egress model that considers not only ASET but also the movement time of occupants. The rationality of the proposed model was verified through the application to the simulated fire scenario. Based on this study, the following conclusions can be drawn.  
1. The fire simulation results showed that temperature and visibility are the most influential factors on the safety of occupants under fire and the concentrations of oxygen (O\({}_{2}\)) and carbon dioxide (CO\({}_{2}\)) are relatively less influential.
2. The ANN model was developed based on the normalized correlations between fire simulation variables, and it estimated the ASET derived from the simulation results very accurately. In addition, this study examined whether the proposed ANN model can be used to obtain the ASET of another multiplex building that was not used in the development of the model, and it was confirmed that the proposed ANN model also provided a good estimation of the ASET for the building.
3. Based on the ANN model, an egress model was proposed to ensure the safety of occupants under fire, and it provided optimal evacuation routes with the highest margin of safety in consideration of both ASET and the movement time of occupants..
4. In this study, however, the application of the proposed ANN algorithm and egress model was limited to multiplex buildings. Therefore, there is a need to secure fire simulation data of various types of buildings, such as apartment houses and underground structures, to further expand the application ranges of the proposed model in the future.  
Investigation, H.-C.C.; verification, I.H. and S.-J.H.; writing--original draft, K.D.; writing--review and editing, K.S.K. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 21 RMP-C163162-01).  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Path**} & \multirow{2}{*}{**Distance (m)**} & \multicolumn{2}{c}{**Available Safe Egress**} & \multirow{2}{*}{**Movement Time (sec.)**} & \multirow{2}{*}{**Margin of Safety (sec.)**} & \multirow{2}{*}{**Result \({}^{*}\)**} \\  & & **Time (sec.)** & & & **Safe = 1** \\  & **D** & **ASET** & & & **USafe = 0** \\ \hline \(1\to 2\) & 8 & 12 & 6.29 & 5.71 & 1 \\ \(2\to 4\) & 18 & 35 & 14.15 & 20.85 & 0 \\ \(2\to 3\) & 8 & 29 & 6.29 & 22.71 & 1 \\ \(3\to 5\) & 18 & 42 & 14.15 & 27.85 & 1 \\ \(4\to 6\) & 20 & 51 & 15.72 & 35.28 & 0 \\ \(5\to 7\) & 20 & 63 & 15.72 & 47.28 & 1 \\ \(6\to 7\) & 8 & 63 & 6.29 & 56.71 & 0 \\ \(6\to\) Exit 1 & 6 & 51 & 4.72 & 46.28 & 0 \\ \(7\to\) Exit 2 & 6 & 63 & 4.72 & 58.28 & 1 \\ \hline \hline \end{tabular}  
* The safest route = \(1\to 2\to 3\to 5\to 7\to\) Exit 2.  
\end{table}
Table 12: Application results.