AI-Powered Tools for Safe Evacuation of Individuals During Emergencies

Emergency evacuation via transportation systems and infrastructure is a critical component of public safety, particularly in scenarios involving fires, transportation incidents, wildfires, and tsunamis. Studies have demonstrated the potential of artificial intelligence (AI) and machine learning to enhance evacuation efficiency. The first research need is to investigate and create personalized evacuation plans that consider various factors such as mobility limitations, communication needs, and access to resources. The second research need is to explore methods for integrating real-time data from IoT (internet of things) devices into AI-powered evacuation tools. First, the research team will assemble comprehensive datasets from multiple sources, focusing on evacuation scenarios involving fires, transportation incidents, wildfires, and tsunamis. Second, the team will employ a range of advanced analytical methods to synthesize and analyze the collected data, ensuring the development of effective AI-powered evacuation tools. This research is expected to yield significant advancements in the modeling, practices, and procedures for emergency evacuations, particularly for vulnerable populations.

• Record URL:
  https://www.ctips.org/projects/details.php?id=628

Language

• English

Project

• Status: Active
• Funding: $178273
• Contract Numbers:

  69A3552348308

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Transformative Infrastructure Preservation and Sustainability

  North Dakota State University
  Fargo, North Dakota  United States  58108-6050
• Project Managers:

  Tolliver, Denver

• Performing Organizations:

  Utah State University

  Civil and Environmental Engineering Department
  Logan, UT  United States 
• Principal Investigators:

  Singleton, Patrick

• Start Date: 20240915
• Expected Completion Date: 20260914
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program
• Source Data: CTIPS-030

Subject/Index Terms

• TRT Terms: Artificial intelligence; Disasters and emergency operations; Evacuation; Internet of things; Real time information
• Subject Areas: Data and Information Technology; Safety and Human Factors; Security and Emergencies; Transportation (General);

Filing Info

• Accession Number: 01931551
• Record Type: Research project
• Source Agency: Center for Transformative Infrastructure Preservation and Sustainability
• Contract Numbers: 69A3552348308
• Files: UTC, RIP
• Created Date: Sep 21 2024 3:31PM