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Time-Aware and Temperature-Aware Fire Evacuation Path Algorithm in IoT-Enabled Multi-Story Multi-Exit Buildings.

Hong-Hsu Yen1, Cheng-Han Lin1, Hung-Wei Tsao1

  • 1Department of Information Management, Shih Hsin University, Taipei 116, Taiwan.

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|December 30, 2020
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Summary
This summary is machine-generated.

This study introduces intelligent algorithms for dynamic fire evacuation paths, considering time and temperature in multi-story buildings. The developed algorithms efficiently guide evacuees, even in extreme scenarios with limited time.

Keywords:
evacuation pathmulti-story multi-exit buildingmulti-time-slots planningoptimizationtemperature sensors

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Area of Science:

  • Computer Science
  • Operations Research
  • Emergency Management

Background:

  • Traditional fire evacuation methods are static and fail to adapt to real-time conditions.
  • Temperature fluctuations and time constraints are critical factors in multi-story building evacuations.
  • Existing approaches do not adequately address human temperature limitations during emergencies.

Purpose of the Study:

  • To develop intelligent algorithms for identifying time-aware and temperature-aware fire evacuation paths.
  • To model multi-story, multi-exit buildings as a 2D graph for efficient pathfinding.
  • To propose mathematical optimization models for dynamic evacuation planning.

Main Methods:

  • Mapping 3D multi-story buildings to a 2D graph representation.
  • Developing a mathematical optimization model for time-aware and temperature-aware evacuation.
  • Proposing and evaluating six evacuation algorithms: BFS, SP, DBFS, TABFS, TASP, and TADBFS.

Main Results:

  • Algorithms TABFS, TASP, and TADBFS showed similar pathfinding in tested buildings.
  • BFS, SP, and DBFS offered marginally better results for evacuation time and temperature.
  • TABFS and TADBFS proved effective for large-scale evacuations (e.g., 1200 people in Taipei 101) within critical timeframes.

Conclusions:

  • Intelligent algorithms (TABFS, TADBFS) are crucial for efficient, real-time fire evacuations in complex buildings.
  • Algorithm selection (TADBFS vs. TABFS) depends on building occupancy and capacity.
  • The study also provides insights into optimal sensor deployment for enhanced building safety.