AI-Driven Early Fire Detection Using CubeSats: Enhancing Real-Time Satellite Monitoring for Wildfire Prevention

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AI-Driven Early Fire Detection Using CubeSats: Enhancing Real-Time Satellite Monitoring for Wildfire Prevention

SmartSat is seeking applications for a hands-on project-based PhD looking at AI-Driven Early Fire Detection Using CubeSats: Enhancing Real-Time Satellite Monitoring for Wildfire Prevention.

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

The successful applicant is expected to study full-time and to be based at our Mawson Lakes campus in the north of Adelaide. Applicants are expected to start in a timely fashion upon receipt of an offer. Extended deferral periods are not available. Applications close Sunday, 1 December 2024.

For more information, contact Dr Stefan Peters, Senior Lecturer of Geospatial Science, at [email protected] or click here.

Apply for the PhD position here