Open Source Technologies for Forest Biodiversity Monitoring

This contribution presents an open source-based approach to the automated monitoring of forest biodiversity, focusing on saproxylic arthropods as ecological indicators. The system integrates open hardware and software components to enable continuous, non-invasive field data collection with minimal human intervention.
At the center of the setup is an IoT device designed for temporary insect capture, high-resolution image acquisition, and automated release. The hardware architecture is built from off-the-shelf, openly documented components, while image analysis is performed via open source AI algorithms for species detection and classification.
The data pipeline adheres to Open FAIR principles, ensuring that sensor readings, images, metadata, and processed outputs are structured, accessible, and reusable. All collected information is organized within a scalable digital infrastructure and made available through a user-facing web interface, allowing access to a wide range of stakeholders, including researchers, land managers, and public agencies.
Remote sensing data—multispectral and radar—are also integrated into the system to map habitat features such as deadwood presence and microhabitat density, providing complementary spatial context to in situ observations.
This case highlights how open source technologies can support biodiversity monitoring by improving reproducibility, reducing costs, and facilitating wider adoption across contexts and user communities.