The project aims to investigate the potential of using drones for bioacoustics monitoring and detecting acoustically active species, e.g. birds and bats, for biodiversity and wildlife population monitoring. To this aim, the project will develop a low-cost prototype system, and the corresponding wildlife detection and identification algorithm based on the sound recorded from drones. The candidate will apply signal processing and machine learning techniques in the biology domain.
 Lan, Yun Long, Ahmed Sony Kamal, Carlo Lopez-Tello, Ali Pour Yazdanpanah, Emma E. Regentova, and Venkatesan Muthukumar. “Evaluation of Audio Denoising Algorithms for Application of Unmanned Aerial Vehicles in Wildlife Monitoring.” Information Technology-New Generations (2018): 759-766.
 Michez, Adrien, Stéphane Broset, and Philippe Lejeune. “Ears in the Sky: Potential of Drones for the Bioacoustic Monitoring of Birds and Bats.” Drones 5, no. 1 (2021): 9.
 Wang, Lin, and Andrea Cavallaro. “Acoustic sensing from a multi-rotor drone.” IEEE Sensors Journal 18, no. 11 (2018): 4570-4582.
 Rossberg, Axel, Food Webs and Biodiversity: Foundations, Models, Data. John Wiley & Sons, 2013.