LA Fire Department
AI-Powered Emergency
Response for Wildfires
Revolutionizing First Responder Coordination During LA Wildfires
The Challenge
First responders face extreme difficulties during wildfire emergencies, including delayed communication, inefficient resource allocation, and unpredictable fire behavior. These inefficiencies lead to slower response times and increased casualties.
Role
UX Researcher
Team
4 UX Researchers (Including me)
Timeline
Jan 2024 - May 2024
Mission
To equip first responders with AI-powered tools that improve real-time decision-making, speed up wildfire response, and reduce harm through smarter communication and resource use.
🔍 Research & Analysis
Understanding the Problem
During the January 2025 LA Wildfires, first responders encountered severe roadblocks:
🚨
Communication Barriers → Overloaded radio channels caused delays in relaying critical updates.
🔥
Unpredictable Fire Spread → Rapid changes in fire behavior made response planning difficult.
🚑
Inefficient Resource Deployment → Fire trucks and ambulances were often misallocated.
Key Research Insights
📊 200+
reports analyzed on past wildfire response inefficiencies.
🎤 10+
firefighter & EMT interviews to gather first-hand challenges.
📍3
emergency response systems studied to identify workflow gaps.
What First Responders are saying?
"By the time we get updates on fire spread, the situation has already changed. We need real-time insights to avoid getting trapped or wasting resources." - 👨🚒 Alex Rodriguez (Firefighter)
"We arrive at chaotic scenes with little to no information about patient conditions. It slows down triage and sometimes leads to wasted critical minutes." - 🚑 Emily Patterson (EMT)
"Coordinating with fire and medical teams is frustrating. Our radios are jammed, and there’s no central system to keep us all updated in real time." - 👮♂️ David Thompson (Police Officer)
User Pain Points
Alex Rodriguez
Fire Fighter
❌ Difficulty in tracking real-time fire spread & patient conditions.
Emily Patterson
EMT Professional
❌ Lack of seamless inter-agency communication.
David Thompson
Police Officer
❌ Limited predictive insights for proactive resource management.
Key Success Factors
👩🏻💻
Automated AI-driven dispatching → Optimize first responder allocation.
⏱️
Real-time situational awareness → Reduce guesswork for firefighters.
🔬
Seamless multi-agency collaboration → Improve decision-making and coordination.
How might we?
How might we enhance teamwork and collaboration among first responders at the scene of road accidents to optimize their efficiency and effectiveness in managing crises?
🎨 Research-Backed Solution Concepts
Based on our research, we proposed three AI-powered concepts to address the critical challenges:
Concept 1: AI-Driven Emergency Communication & Report Generation
📡 Real-time data feeds from satellites, IoT sensors & emergency units.
📍 AI-generated summaries & alerts to assist responders.
🔄 Automated dispatch notifications with real-time updates.
A wildfire erupts near Los Angeles County, spreading rapidly. Firefighters, EMTs, and police officers are dispatched, but conditions are changing too fast.
🚨 At the command center, AI processes real-time data from satellites, IoT sensors, and emergency units. Within seconds, it predicts fire movement and assigns resources.
📍 AI-generated alerts notify responders of high-risk areas. Firefighters receive real-time updates, and EMTs are guided to critical patients and safe routes.
🔄 Automated dispatch notifications ensure police officers manage traffic efficiently, preventing evacuation delays.
📑 AI continuously updates emergency teams, adapting response plans in real time. With precise coordination, responders act faster, saving lives and resources. 🚨🔥
Concept 2: Data Integration & Sharing for Enhanced Collaboration
📊 First responders tag & record patient data using AI-assisted tools.
🚑 Automated patient triage & hospital alerts to prepare emergency rooms in advance.
📡 Centralized data-sharing hub to enhance inter-agency coordination.
📢 AI-Powered Data Integration for Wildfire Response
A massive wildfire forces evacuations. First responders arrive at chaotic scenes, unsure of patient conditions or available hospital capacity.
📊 EMTs use AI-assisted tools to tag and record patient data. Key details—injuries, severity, and immediate needs—are logged instantly.
🚑 AI triages patients and alerts hospitals, ensuring the nearest facilities are prepared with the right resources.
📡 A centralized data-sharing hub updates firefighters, EMTs, and police officers in real time, improving coordination and reducing miscommunication in critical moments.
🔥 With seamless data integration, emergency teams work faster and more efficiently, saving lives. 🚨
Concept 3: Predictive Analytics for Proactive Resource Allocation
🔹 AI models identify high-risk fire zones based on real-time & historical data.
🚒 Optimized fire truck & ambulance distribution based on severity & needs.
📍 Early warning alerts for at-risk areas to prevent delayed response.
🤖 Predictive AI for Wildfire Resource Allocation
🔥 A wildfire spreads unpredictably, forcing responders to make critical decisions under uncertainty.
🔹 AI models analyze real-time satellite data and historical fire patterns, predicting high-risk zones before flames reach them.
🚒 Emergency units are dispatched proactively—fire trucks are sent to the most vulnerable areas, and ambulances position near expected casualty zones.
📍 Early warning alerts notify responders of shifting fire behavior, ensuring rapid adjustments to evacuation and containment strategies.
🚨 With predictive analytics, responders stay ahead of the crisis, preventing delays and maximizing safety. 🔥
👩🏻👨🏻Stakeholder Feedback & Validation
To validate our research findings and recommendations, we conducted think-aloud sessions and qualitative testing with 6 participants (3 firefighters, 2 EMTs, and 1 incident commander). Here’s what we found:
Key Research Insights
📈 85%
of first responders agreed that AI-powered coordination could improve response times.
🔍 Firefighters
emphasized the need for seamless, low-effort integration into their existing systems.
🚑 EMTs
highlighted AI’s potential to optimize patient triage and hospital readiness.
User Pain Points
Alex Rodriguez
Fire Fighter
❌ Difficulty in tracking real-time fire spread & patient conditions.
Emily Patterson
EMT Professional
❌ Lack of seamless inter-agency communication.
David Thompson
Police Officer
❌ Limited predictive insights for proactive resource management.
Key Success Factors
👩🏻💻
Automated AI-driven dispatching → Optimize first responder allocation.
⏱️
Real-time situational awareness → Reduce guesswork for firefighters.
🔬
Seamless multi-agency collaboration → Improve decision-making and coordination.
Key Adjustments Post-Testing
✔ Simplified AI data presentation → Ensuring insights are actionable without overwhelming users.
✔ Voice-enabled support for firefighters → Addressing hands-free interaction needs.
✔ Scalable integration models → Ensuring compatibility with existing emergency response systems.
📊 Expected Impact Based on Research
📡 40% Potential Improvement in Response Time → AI-powered dispatching could optimize emergency unit allocation.
🔥 30% Reduction in False Alarms → AI-enhanced situational awareness could improve decision-making accuracy.
🚑 Higher Emergency Preparedness → Hospitals could anticipate and prepare for incoming patients in real-time.
💡 Future Research & Considerations
🚀 Pilot Testing & Real-World Deployment → Partnering with first responder units for live field tests.
🚀 Enhanced Human-AI Collaboration → Exploring intuitive AI interfaces for real-time firefighting operations.
🚀 Cross-Agency Policy Integration → Ensuring AI adoption aligns with regulatory and operational guidelines.
🔮 Learnings & Takeaways
🛠 Research is key – Groundwork ensures problem-solving accuracy and stakeholder buy-in.
🧠 Iterate based on real-world feedback – Practical usability validation is crucial in high-stakes scenarios.
💰 Adoption matters – AI solutions must be user-friendly and align with operational needs to gain traction.
📩 Interested in learning more? Let’s connect!
Looks like you've reached the end. Here's a medal
Got a wild idea, a shower thought, or UX crisis at 2 a.m.? I'm all ears for it ✨
My calendar's open and the form’s shorter than a tweet. Let’s jam on it with some sticky notes 📝
San Francisco, CA, USA