Home Education Study With Us CLOSED: AI-Driven Early Fire Detection Using CubeSats: Enhancing Real-Time Satellite Monitoring for Wildfire Prevention
CLOSED: AI-Driven Early Fire Detection Using CubeSats: Enhancing Real-Time Satellite Monitoring for Wildfire Prevention
Applications for this internship opportunity are now closed. For more information, please contact [email protected].
This PhD will be facilitated through SmartSat and Uni SA STEM, in partnership with the European Space Agency (ESA) Phi-lab, Green Triangle Forest Industry Hub/Green Triangle Fire Alliance, South Australian Country Fire Service and the Victorian Country Fire Authority.
The successful applicant will undertake several significant stages of research, enhancing existing AI models and onboard processing systems for CubeSats, focusing on segmentation-based detection and integrating advanced deep learning techniques. The applicant will also help develop solutions that integrate thermal information, visible fire scars, fire smoke aerosols, and additional factors such as fuel and fire risk to achieve a comprehensive onboard wildfire detection system.
This project provides extensive opportunities to collaborate with academic and industry partners, engaging through workshops, live demonstrations, and conferences. Research may involve travel, particularly to ESA’s Phi-lab in Frascati, Italy for research cooperation and technical knowledge exchange.
Applicants must meet the eligibility criteria for entrance into a PhD. All applications that meet the eligibility and selection criteria will be considered for this project.
This project is open to applications from both Domestic and International applicants, provided they meet the project selection criteria:
- Educational background in Remote Sensing or Machine Learning
- Excellent programming skills
PHD CANDIDATES FROM THE UNIVERSITY OF SOUTH AUSTRALIA
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