MATLAB and Simulink Seminars

Drones and Fire Hazards: Where There’s Smoke There’s Fire!


Join us for first event in the webinar series: Fire and Ice, Earth and Oceans: Tools and Techniques for Researching Our Changing Climate with MATLAB.

In this session, you will hear from a researcher at UC Davis and one of MathWorks’ own engineers discussing how MATLAB can support the work being done in wildfire analysis using autonomous aerial systems.

Who Should Attend

Anyone interested in learning about how MATLAB is supporting climate change research in North America.

About the Presenters

Dr. Zhaodan Kong is an Associate Professor in Mechanical and Aerospace Engineering at University of California, Davis. He is also affiliated with  the Center for Spaceflight Research and the Center for Neuroengineering and Medicine at UC Davis.

Dr. Shadi Mohagheghi is a Senior Application Engineer at MathWorks focusing on supporting Aerospace and Wireless Communications applications, based in Southern California. Prior to joining MathWorks, Shadi worked on positioning, navigation, and timing of GPS satellites at The Aerospace Corporation. 



Autonomous Aerial Systems for Early Wildfire Detection
Zhaodan Kong, University of California Davis

Due to an expanding wildland-urban interface (WUI), and climate change, wildfires are becoming one of the most significant natural hazards threatening the world. Damage caused by wildfires, in terms of total area burned, firefighting costs, and lives lost, either directly by the wildfires or indirectly by the resulting air pollution, have increased significantly over the past two decades. For example, economic losses associated with the health impacts of wildfire smoke are estimated to range from $88 billion to $142 billion per year, with most of the losses due to premature human mortality. Once a wildfire is ignited, during severe burn conditions, it can spread at a rate of roughly 10% of the open wind speed. Therefore, timely response and management of wildfires depend critically on how quickly ignitions are identified and confirmed. Early detection often leads to a smaller fire size at the initial attack, a greater probability of containment, and the prevention of loss of life and property. Accordingly, there is an urgent need to develop an economical and easily scalable solution that can detect wildfires early.

This talk will describe the team’s idea of developing an economical, scalable, integrated ground-air Cyber-Physical System (CPS) framework that can autonomously, effectively, and rapidly predict and detect wildfires within a large geographical area. The team will also show some of our preliminary results of using uncrewed aerial systems (UAS) as a potential candidate for early wildfire detection.

Catching Fire: Autonomous Drones for Wildfire Detection and Tracking
Shadi Mohagheghi, MathWorks

Can drones help prevent natural disasters? Wildfires have become highly destructive in recent years, ravaging the environment and human lives. In this seminar, we will learn about wildfire detection systems using autonomous drones. We will explore cutting-edge methods to detect fire outbreaks and analyze their spread. We cover simulation and AI techniques that can be applied to life-saving problems in MATLAB and Simulink. These include:

  • Designing and simulating a wildfire detection system using autonomous drones
  • Processing drone-captured images to detect fire outbreak using deep learning models
  • Real-time tracking of the spread using hyperspectral images from sensors.

In this talk, learn how simulations and other computational techniques to demonstrate how to solve interdisciplinary engineering problems with MATLAB and Simulink.

This event is part of a series of related topics. View the full list of events in this series.

Drones and Fire Hazards: Where There’s Smoke There’s Fire!

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