PMDS improves pollinator-friendly agriculture through AI-driven biodiversity monitoring. The system integrates satellite, drone, and IoT sensor data to track pollinator populations, assess plant-pollinator interactions, and guide policymakers and farmers in promoting sustainable farming practices for biodiversity preservation.
The PMDS aims to stimulate the transition towards more sustainable and pollinator-friendly agriculture by improving the understanding and identification of pollinator-friendly cultivars through a system for monitoring pollinator and plant diversity. The monitoring will be based on multiple combined data sources. Impact Monitoring pollinator populations and biodiversity is crucial for effective conservation. Current methods are often invasive, time-consuming, resource-intensive, and biased. New technologies in remote sensing and machine vision offer potential solutions, enabling 24-hour monitoring and remote viewing. However, existing digital insect tracking stations mainly focus on pest species and are unsuitable for studying plant-pollinator interactions.
By deploying a digital toolset for monitoring pollinator diversity, we can monitor the impact of agricultural practices on pollinator diversity, supporting a decision support system for pollinator friendly agriculture. We can also objectively assess the effects of different crop varieties on pollinators over time, surpassing traditional methods like traps and visual estimates, and better validate assumptions about crop traits such as nectar production.
For farmers, this toolset enables monitoring of pollinator presence and its impact on crop yield. Realtime data aids in making informed, pollinator-friendly decisions. Integration with farm management systems streamlines and automates recommendations.
For industry, this toolset aids agricultural businesses in gathering data on the biodiversity impact of various practices, benefiting food and biomaterial companies in meeting EU obligations.
GDDS interdependency AI models will detect key pollinator species using acoustic, visual, and photonic data, while also monitoring floristic diversity and functional traits through imaging methods. These data will be fused to estimate pollinator and floristic diversity, integrating auxiliary data for habitat quality and flower pollinator interactions. Interoperability and the availability of datasets for AI model training are pivotal, with GDDS playing a key role.
AI models and data will be integrated as a data source for the national eDwin platform. eDwin is a public service provided free of charge to all Polish farmers, assisting with field and crop management, hazard and pest reporting, and plant protection management.
The SAGE (Sustainable Green Europe Data Space) project targets the four strategic pillars in the European Green Deal— Zero Pollution, Climate Adaptation, Biodiversity, and the Circular Economy Action Plan, by implementing a rich portfolio of use cases in each of them.
The project demonstrates a total of 10 pilot use cases to foster data-driven sustainability solutions across biodiversity, climate, circular economy, and pollution monitoring. Below you can read about one of these pilots.
The overview of all use cases can be found here: Use-cases
Use case objective
The PMDS use case aims to stimulate the transition towards more sustainable and pollinator-friendly agriculture by improving the understanding and identification of pollinator-friendly cultivars through a system for monitoring pollinator and plant diversity. The monitoring is based on multiple combined data sources, and supports secure, interoperable data exchange between farm systems, biodiversity databases, weather services, and policy frameworks.
End users
Primary end users include farmers, who will use the pilot decision support system to optimize crop protection practices with pollinator safety in mind. Beekeepers will contribute data on apiary locations and benefit from improved protection of pollinators. The scientific community is also a key user group—contributing monitoring data and using the harmonized datasets for biodiversity modeling and AI training.
Objectives/Benefits
The use case will provide many benefits to a wide audience, such as:
- farmers: access to actionable treatment recommendations that reduce risk to pollinators and improve sustainability,
- beekeepers: better protection of apiaries through visibility of nearby treatments and pollinator-safe practices,
- advisors: use of decision support data to guide farm-level biodiversity strategies and improve compliance with environmental schemes,
- policymakers: insight into how farm-level and environmental data can support biodiversity goals under the Common Agricultural Policy and EU Biodiversity Strategy,
- researchers: integration and reuse of structured monitoring data to support ecological modeling and machine learning,
- technology providers: validation of federated, semantically interoperable systems using Green Deal Data Space infrastructure.
Tech provider
The use case is technically led by the Poznan Supercomputing and Networking Center (PSNC), which is responsible for integrating pollinator-friendly services with the Green Deal Data Space infrastructure. PSNC oversees the use of the SAGE GDDS Connector, manages identity and access, ensures semantic interoperability, and enforces data exchange policies within a secure, federated environment.
Participants
- Research Institute of Horticulture – National Research Institute (INHORT)
INHORT provides expert knowledge on pollinator behavior, melliferous plant phenology, and biodiversity monitoring in horticultural landscapes. The institute supports the development of pollinator behavior models and contributes domain validation for decision support logic related to treatment timing and ecological risk assessment.
- Institute of Soil Science and Plant Cultivation – State Research Institute (IUNG)
IUNG contributes expertise in crop modeling, agri-environmental policy, and data harmonization. It supports integration of spatial and farm-level data, validates the ecological compliance of tool outputs, and helps align recommendations with CAP eco-schemes and EU biodiversity strategy frameworks.
- In Pollinator Monitoring Data Space use case we are inviting farmers and beekeepers as external users to test provided data and tools.
Expected results
The Pollinator Monitoring Data Space use case will deliver a functional tools like pollinator-friendly decision support system, integrated with the Green Deal Data Space infrastructure through the SAGE GDDS Connector. This system will enable secure and interoperable data exchange between farm-level systems, biodiversity sources, and weather services. Its core outputs will include expert-validated recommendations for pollinator-safe treatment practices and ecological compliance. In addition, the pilot will demonstrate a matchmaking platform that connects beekeepers with nearby farmers to coordinate protection zones and reduce pesticide exposure. It will also result in the creation of semantically enriched data repositories suitable for machine learning applications in pollinator and habitat modeling, developed in alignment with FAIR principles. The use case engages farmers, beekeepers, and researchers in a co-design approach and contributes to broader EU policy goals on biodiversity, agriculture, and sustainable innovation.
In conclusion, the expected results include improved decision support for sustainable agriculture, new service markets for pollination coordination, enhanced public policy capabilities, and a major leap forward in biodiversity monitoring and AI readiness. These directly respond to the weaknesses identified in the present scenario, including fragmented systems, insufficient data updates, and poor usability for non-technical users. PMDS will thus serve as a durable and expandable foundation for long-term pollinator protection across Europe.
Contact
Marcin Plociennik – marcinp@man.poznan.pl