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Automatic Wildfire Detection and Simulation using Optical Information from Unmanned Aerial Systems
Technical Paper
2015-01-2474
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
In many parts of the world, uncontrolled fires in sparsely populated areas are a major concern as they can quickly grow into large and destructive conflagrations in short time spans. Detecting these fires has traditionally been a job for trained humans on the ground, or in the air. In many cases, these manned solutions are simply not able to survey the amount of area necessary to maintain sufficient vigilance and coverage. This paper investigates the use of unmanned aerial systems (UAS) for automated wildfire detection. The proposed system uses low-cost, consumer-grade electronics and sensors combined with various airframes to create a system suitable for automatic detection of wildfires. The system employs automatic image processing techniques to analyze captured images and autonomously detect fire-related features such as fire lines, burnt regions, and flammable material. This image recognition algorithm is designed to cope with environmental occlusions such as shadows, smoke and obstructions. Once the fire is identified and classified, it is used to initialize a spatial/temporal fire simulation. This simulation is based on occupancy maps whose fidelity can be varied to include stochastic elements, various types of vegetation, weather conditions, and unique terrain. The simulations can be used to predict the effects of optimized firefighting methods to prevent the future propagation of the fires and greatly reduce time to detection of wildfires, thereby greatly minimizing the ensuing damage. This paper also documents experimental flight tests using a SenseFly Swinglet UAS conducted in Brisbane, Australia as well as modifications for custom UAS.
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Citation
Lum, C., Summers, A., Carpenter, B., Rodriguez, A. et al., "Automatic Wildfire Detection and Simulation using Optical Information from Unmanned Aerial Systems," SAE Technical Paper 2015-01-2474, 2015, https://doi.org/10.4271/2015-01-2474.Also In
References
- Australian Government - Attorney General's Department Bushfire Arson Prevention
- Australian Government Sentinel Geoscience Australia
- Harrington J. D. , Barnstorff K. and Lowie C. NASA Aeronautics Research Tests New Tool for Early Wildfire Detection NASA 2014
- Merino L. , Caballero F. , Martinez De Dios L. M. , Maza I. and Ollero A. Automatic Forest Fire Monitoring and Measurement Using Unmanned Aerial Vehicles International Conference on Fire Research
- Atherton K. D. Why Don't We Have More Drones Monitoring Wildfires? Popular Science 2013
- SenseFly SwingletCAM https://www.sensefly.com/drones/swinglet-cam.html 27 August 2014
- SenseFly EMotion https://www.sensefly.com/drones/emotion.html 20 August 2014
- Queensland University of Technology Samford Ecological Research Facility 15 March 2015 http://www.serf.qut.edu.au/ 25 August 2014
- Singh S. P. , Jain K. and Mandla V. Image Based 3D City Modeling: Comparative Study
- Lum C. W. and Rysdyk R. T. Feature Extraction of Low Dimensional Sensor Returns for Autonomous Target Identification Proceedings of the AIAA Guidance, Navigation, and Control Conference Honolulu 2008
- Alberto E. Using Occupancy Grids for Mobile Robot Perception and Navigation Carnegie Mellon University
- Lum C. W. , Rysdyk R. T. and Pongpunwattana A. Occupancy Based Map Searching Using Heterogeneous Teams of Autonomous Vehicles Proceedings of the AIAA Guidance, Navigation, and Control Conference Keystone 2006
- Lum C. W. , Vagners J. and Rysdyk R. T. Search Algorithms for Teams of Heterogeneous Agents with Coverage Guarantees AIAA Journal of Aerospace Computing, Information, and Communication 7 1 1 31 2010
- Lum C. W. , Rysdyk R. T. and Pongpunwattana A. Autonomous Airborne Geomagnetic Surveying and Target Identification Proceedings of the AIAA Infotech@Aerospace Conference Arlington 2005
- Rysdyk R. T. , Lum C. W. and Vagners J. Autonomous Orbit Coordination for Two Unmanned Aerial Vehicles Proceedings of the AIAA Guidance, Navigation, and Control Conference San Francisco 2005
- Lum C. W. and Waggoner B. A Risk Based Paradigm and Model for Unmanned Aerial Systems in the National Airspace Proceedings of the AIAA Infotech@Aerospace Conference St. Louis 2011
- Lum C. W. and Rysdyk R. T. Time Constrained Randomized Path Planning Using Spatial Networks Proceedings of the IEEE American Control Conference Seattle 2008
- Lum C. W. and Vagners J. A Modular Algorithm for Exhaustive Map Searching Using Occupancy Based Maps Proceedings of the AIAA Infotech@Aerospace Conference Seattle 2009
- Hoover A. and Olsen B. A Real-time Occupancy Map from Multiple Video Streams Detroit IEEE International Conference 1999
- Lum C. W. , Vagners J. , Jang J.-S. and Vian J. Partioned Searching and Deconfliction: Analysis and Flight Tests Proceedings of the IEEE American Control Conference Seattle 2010
- Lum C. W. , Vagners J. , Vavrina M. and Vian J. Formation Flight of Swarms of Autonomous Vehicles In Obstructed Environments Using Vector Field Navigation Proceedings of the International Conference on Unmanned Aircraft Systems 2012
- Lum C. W. , Rowland M. L. and Rysdyk R. T. Human-in-the-Loop Distributed Simulation and Validation of Strategic Autonomous Algorithms Proceedings of the AIAA Aerodynamic Measurement Technology and Ground Testing Conference Seattle 2008
- Ueunten K. , Lum C. W. , Creigh A. A. and Tsujita K. Conservative Algorithms for Automated Collision Awareness for Multiple Unmanned Aerial Systems Proceedings of the IEEE Aerospace Conference Big Sky 2015
- Lum C. W. , Gauksheim K. R. , Vagners J. and McGeer T. Assessing and Estimating Risk of Operating Unmanned Aerial Systems in Populated Areas Proceedings of the AIAA Aviation Technology, Integration, and Operations Conference 2011