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

Author(s)

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

Volume

33

Issue

5

Key words

UAV, Environmental Monitoring, Image Processing, Machine Learning

Abstract

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.

Scholarly Commons Citation

Gonzalez Nunez, J. A., Gonzalez Nunez, J. G., Akbas, M. I., Currier, P., & Macchiarella, N. D. (2024). Real-Time Detection of Sea Turtles Using UAV and Neural Networks on Edge Devices. Journal of Aviation/Aerospace Education & Research, 33(5). DOI: https://doi.org/10.58940/2329-258X.2060