AI in Catastrophe Response

Overview

AI in Catastrophe Response explores how artificial intelligence, drone imagery, and computer vision can enhance how industries prepare for, assess, and recover from large-scale catastrophe events. The program focuses on developing applied use cases that improve customer experience, increase safety, and streamline response operations when disasters strike.

Focus Areas

• Customer Loyalty: Use automation and AI-assisted communication to reduce uncertainty for policyholders during stressful events.
• Efficiency: Automate image analysis and damage classification to accelerate assessments and resource deployment.
• Public Safety and First Responder Support: Deploy drones and computer vision to minimize on-site exposure for claims specialists, engineers, and field teams while applying AI-driven mapping, aerial imagery, and computer vision to improve situational awareness, identify safe access routes, and support coordinated, life‑safety oriented response during emergencies.

Technology Approach

The program leverages applied AI methods in:

• Drone-based data collection for rapid aerial imaging after catastrophic events.
• Computer vision damage detection models to identify and classify structural impact automatically.
• Predictive AI modeling to prioritize high-risk areas and allocate resources efficiently.
• Resilient design research that integrates AI insights into architecture and construction practices to improve disaster readiness.

Industry Impact

AI in Catastrophe Response is part of Secure AI’s AI in Industry framework, demonstrating how applied AI can transform critical sectors. The initiative bridges insurance, architecture, and construction, exploring how technology can:

• Enhance post-disaster claim handling and response operations.
• Inform resilient building design to reduce future risk.
• Strengthen collaboration between insurers, engineers, and urban planners to improve community recovery.

Research Team

• Antione Stiles – Industry Advisor, Citizens Property Insurance Corporation
• T. Lee – Applied AI Research Assistant, National Center for Secure AI Education; Florida, Texas & Arizona State Licensed Insurance Adjuster and FAA Part 107 drone pilot
• Peyton Watson – Policy and Governance Lead, Texas A&M University–Texarkana
• Mazamesso Mebo – Computer Information Systems Major & AI Developer, University of North Florida
• Hanibal Grant – Architecture & Engineering Major, Florida A&M University
• Wally Charles – Construction Engineering Technology Major, Florida A&M University

Related Initiatives

• Rapid Prototyping Services – Engage with our team to build early-stage AI catastrophe assessment tools.
• Public Policy Research – Explore governance and regulatory frameworks informing responsible AI deployment in disaster contexts.
• AI Training – Develop talent pipelines for operationalizing catastrophe response tooling.

Contact

For collaboration or pilot inquiries, email keege.elliott@secuareaieducation.org.