BiodivKI Projects

Research projects of the guideline “Methods of Artificial Intelligence as a Tool for Biodiversity Research” (BiodivKI) started

Biodiversity is the basis for the economy, global food security and quality of life. It provides key ecosystem services and important resources. However, the condition of these ecosystems is deteriorating rapidly – with serious consequences for the core areas of supply, value creation and quality of life for entire countries. AI and digitalization have the potential to make a significant contribution to safeguarding biodiversity and open up new avenues that could not be explored without them.

With the funding measure “Methods of Artificial Intelligence as an Instrument of Biodiversity Research” (BiodivKI), the BMBF is pursuing the goal of using AI and digitalization to increase understanding of the highly complex and highly dynamic relationships of biological diversity and ecosystems and thus achieve progress in species conservation. Particular attention is paid to the networking of computer science and biodiversity, AI-supported analysis of biodiversity loss and AI-based monitoring. The funding measure also aims to encourage public participation (citizen science) in order to give researchers access to new data, perspectives and impetus.

14 projects have now entered a one-year conception phase within this guideline. They are looking for innovative solutions based on digitalization and AI for the challenges in biodiversity research. In addition to automated species recording, the integration of additional data sets, the analysis of long time series and spatial dynamics as well as comprehensive network analyses of future application areas and objectives are of great importance.

The scientific projects funded in the FEdA flagship initiative are listed below.
Please note that the links that are mentioned here will be forwarded to pages that are currently available in German only.

AI4WildLIVE
Citizen portal, archive and analysis tool for multimodal monitoring data

Bi-O-Ton
Biodiversity assessment of biotope types through machine learning based on citizen science sound recordings and satellite images

BiodivKI-LEPMON
Recording the biodiversity of moths (Lepidoptera) with automated camera traps and artificial intelligence

BioIntAkt
Biodiversity factor measurement with intelligent acoustic sensors

BioMLAgrar
Biodiversity, machine learning and agriculture

BioWaWiKI
Potentials of using artificial intelligence to safeguard biodiversity and ecosystem services in protected areas of water management

FluBioKI
Airborne monitoring of insects using fluorescence and AI image processing

GEBIKI
Linking genomics and remote sensing through AI to efficiently capture the entirety of biodiversity

iForest
AI-based integration of remote sensing and citizen science data to derive biodiversity in forests

IQ-Wasser
AI-supported recording and forecasting of biodiversity and water quality in drinking water reservoirs

KICS-Zert
AI and citizen science-supported monitoring of certified biodiversity projects

MikroKIez
Observation and prediction of microbial diversity and its interactions with the environment using artificial intelligence

NatureAI
Automatic detection of biodiversity in national natural landscapes using deep learning methods

SmartPatrol
More efficiency against poaching through AI – dynamic real-time optimization of protected area patrols

An overview of the funding measure can be found on the website of the framework program “Research for Sustainable Development – FONA”, the text of the official funding guideline on the website of the Federal Ministry of Education and Research (BMBF).