TY - JOUR
T1 - Online Indoor Fire Evacuation System
AU - Lee, An Fong
AU - Tsai, Pei Hsuan
N1 - Funding Information:
Thisworkwas supported in part by theMinistry of Science and Technology of Taiwan underGrant MOST 110-2221-E-006-008; and in part by the Higher Education Sprout Project, Ministry of Education to the Headquarters of University Advancement, National Cheng Kung University.
Publisher Copyright:
© 2023 IEEE.
PY - 2023/9/1
Y1 - 2023/9/1
N2 - Many methods for indoor fire escape evacuation have been proposed to assist victims in escaping. Greedy approaches focus on finding the closest exit and providing victims with the shortest evacuation path. However, they are time consuming to respond to a dynamic fire spread. Optimal approaches determine evacuation exits and routes based on the characteristics of indoor fires using probabilistic or gravitational algorithms. However, their disadvantage is the excessive amount of computation required. Compared with previous methods, this article provides a lightweight exit decision formulation paired with dynamic path planning. The experimental results indicate that our approach accelerates the computation time by approximately 1.5 times and achieves a victim survival rate higher than 90%.
AB - Many methods for indoor fire escape evacuation have been proposed to assist victims in escaping. Greedy approaches focus on finding the closest exit and providing victims with the shortest evacuation path. However, they are time consuming to respond to a dynamic fire spread. Optimal approaches determine evacuation exits and routes based on the characteristics of indoor fires using probabilistic or gravitational algorithms. However, their disadvantage is the excessive amount of computation required. Compared with previous methods, this article provides a lightweight exit decision formulation paired with dynamic path planning. The experimental results indicate that our approach accelerates the computation time by approximately 1.5 times and achieves a victim survival rate higher than 90%.
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U2 - 10.1109/JSYST.2023.3238348
DO - 10.1109/JSYST.2023.3238348
M3 - Article
AN - SCOPUS:85148427151
SN - 1932-8184
VL - 17
SP - 3584
EP - 3592
JO - IEEE Systems Journal
JF - IEEE Systems Journal
IS - 3
ER -