Project: Developing a semi-automatic and publicly available biodiversity monitoring system for Ukrainian protected areas.

This initiative aims to establish a modern technological foundation for wildlife observation under current challenges. Traditional monitoring methods in Ukraine are often labor-intensive and require significant human resources, which are currently critically scarce. Our solution focuses on the automation of data collection and analysis.

Core Project Objectives:

• Remote Sensing: Expanding the network of camera traps (UOVision) and acoustic recorders (Song Meter Micro) within the Roztochya Strict Nature Reserve and Yavoriv National Nature Park.
• Artificial Intelligence: Utilizing neural networks for automated identification of mammals (Deepfaune) and birds (BirdNET).
• Data Transparency: Building a public portal where all monitoring results are accessible to scientists and the general public in real-time.

Technical Infrastructure:
The system is powered by cloud computing (Hetzner Cloud) using open-source Python/Flask software and PostgreSQL/PostGIS spatial databases. This architecture ensures scalability and allows other Ukrainian protected areas to join the platform free of charge.

This project is implemented with the financial support of the German Federal Environmental Foundation (Deutsche Bundesstiftung Umwelt - DBU) as part of the funding initiative for Ukrainian scientists.

Project repositories:

• Main app
• PAM module
• Camera traps module