The loss of biodiversity on a global scale is accelerating, and the growing number of threatened species and degraded ecosystems requires increasingly more efficient monitoring tools. The use of new automated technologies, such as autonomous sound recording, camera traps, drones, etc., allied to the use of machine learning tools, provides an opportunity to improve monitoring and decision-making processes with regard to conservation.
This area of research and transfer aims to:
• Develop methodologies based on new technologies for monitoring biodiversity and measuring the impact of environmental and anthropic factors on biodiversity loss.
• Utilise the methods developed to respond to ecological issues and promote biodiversity conservation, particularly for species that are rare, threatened or hard to find.