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The scorching wildfires of 2017 and 2018 cast California into a devastating inferno, seizing national attention and leaving entire communities in ruins. The ferocious Thomas fire, tearing through Ventura and Santa Barbara Counties, and the relentless Tubbs fire, laying waste to Napa, Sonoma, and Lake Counties, unleashed destruction upon more than 7,200 structures and devoured a staggering 318,000 acres in 2017. Then, in 2018, the Woolsey fire's unforgiving blaze scarred 1,990 structures across nearly 97,000 acres in Los Angeles and Ventura Counties. The state faced a historic wildfire season in 2020, including the August Complex Fire, which surpassed the Mendocino Complex as the largest recorded wildfire in California's history.
These wildfires not only resulted in substantial property damage and loss of life but also had severe environmental impacts, affecting air quality, wildlife, and ecosystems across the state. The scale and frequency of these wildfires highlight the urgency for innovative approaches to wildfire prevention, early detection, and efficient response strategies to mitigate future catastrophes.
Several research works have been conducted on wildfire detection, spread estimation, wildfire evacuation, and search and rescue operations. However, to the best of our knowledge, there is no unified framework that tries to address several of those important issues simultaneously in a single framework. We are confident that implementing our proposed framework would significantly benefit wildfire control authorities.
In this project, we propose to develop a unified framework for wildfire emergency response and evacuation that includes:
• Dynamic Environment Modeling: Utilizing machine learning algorithms coupled with infrared sensors, visible cameras, and weather sensors including temperature, wind direction, and speed detection mounted on a drone to predict forest fires before they occur.
• Evacuation Route Optimization: Leveraging a drone equipped with machine learning algorithms to optimize path planning during wildfire emergencies, enabling efficient and safe evacuation routes while aiding first responders in containment efforts.
• Search and Rescue Operations: Employing the framework to identify and locate firefighters trapped in wildfire, especially when communication links with the base station are lost.
California State University, Fresno
The anticipated outputs from this research project encompass technological advancements, innovative processes, and valuable datasets contributing to the development of a comprehensive wildfire response system. These outputs aim to significantly benefit wildfire control authorities by enhancing their capabilities in prevention, early detection, and efficient emergency response strategies, ultimately mitigating the impact of future wildfire catastrophes.
The implementation of the proposed unified framework for wildfire emergency response and evacuation is expected to bring about significant positive impacts on the transportation system, regulatory frameworks, and overall wildfire management practices. The anticipated benefits include:
In the subsequent phase of this project, our goal is to deploy the system within wildfire emergency protocols. This deployment involves seamless integration with emergency communication systems and collaboration with local authorities. Our next steps include engaging with fire authorities to coordinate real-time testing and drone operations, ensuring the system's practical implementation and effectiveness.
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SJSU Research Foundation 210 N. 4th Street, 4th Floor, San Jose, CA 95112 Phone: 408-924-7560 Email: mineta-institute@sjsu.edu