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Time series forecasting methods in emergency contexts.

P Villoria Hernandez1, I Mariñas-Collado2, A Garcia Sipols3

  • 1Department of Electronics, Rey Juan Carlos University, Madrid, Spain.

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|September 26, 2023
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Summary
This summary is machine-generated.

HelpResponder detects fire hotspots in low-visibility conditions using sensor data. This system aids emergency intervention teams (EI) by improving fire response times and saving lives.

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Environmental Science

Background:

  • Fire emergencies present critical challenges in identifying hotspots, locating emergency teams, tracking fire spread, and planning evacuation routes.
  • Lack of visibility due to high temperatures complicates these critical tasks for emergency responders.

Purpose of the Study:

  • To develop and evaluate HelpResponder, a system for detecting areas of interest in fire environments with limited visibility.
  • To identify the most effective predictive model for environmental variables in fire scenarios.
  • To create an energy-efficient prediction system for battery conservation.

Main Methods:

  • Utilized sensor data including temperature, humidity, and air quality from a fire tower.
  • Applied statistical and machine learning models: ARIMAX, KNN, SVM, and TBATS for variable modeling.
  • Proposed an enhanced SVM model incorporating temporal structures and explored model combinations for improved forecasting.

Main Results:

  • Evaluated multiple predictive models to determine the best fit for measured environmental data.
  • Demonstrated that combining different forecasting models yielded the highest efficiency.
  • Validated the HelpResponder system in simulated real-world emergency scenarios within hostile building environments.

Conclusions:

  • The HelpResponder system effectively detects fire hotspots in challenging, low-visibility conditions.
  • The developed system enhances firefighter response speed by providing crucial real-time information.
  • This technology reduces risks associated with information gaps and optimizes tactical operations, potentially saving lives.