Real-Time Detection of Sea Turtles Using UAV and Neural Networks on Edge Devices

Abstract

Verbatim from Embry-Riddle Scholarly Commons. Not paraphrased, not summarized.

Sea turtle populations continue to diminish around the globe for various reasons. Therefore, the need for innovative solutions to monitor sea turtles has been increasing. This research paper focuses on an innovative application of artificial intelligence (AI) and machine learning (ML) together with unmanned aerial vehicles (UAV) to improve sea turtle conservation efforts. We outline the design, implementation, and evaluation of a system that deploys UAVs equipped with high-resolution cameras, coupled with a purpose-built neural network to recognize, classify, and monitor sea turtles. This project thus serves as a platform for understanding the wider applicability and limitations of this technology in the realm of wildlife conservation, while placing particular emphasis on the protection of sea turtles.

Authors

• Gonzalez Nunez, Jose A Embry-Riddle Aeronautical University
• Gonzalez Nunez, Jose G Embry-Riddle Aeronautical University
• Akbas, Mustafa I Embry-Riddle Aeronautical University
• Currier, Patrick Embry-Riddle Aeronautical University
• Macchiarella, Nickolas D. Embry-Riddle Aeronautical University

Keywords

• UAV
• Environmental Monitoring
• Image Processing
• Machine Learning
• Aviation and Space Education
• Computer Engineering
• Robotics