Department of Electrical and Computer Engineering

Aarhus University – Dept. of Electrical and Computer Engineering (AU-ECE) is a world-leading research institution with expertise in artificial intelligence, computer vision, and agentic systems for agriculture. AU-ECE will utilize their participation in this project to pioneer a Context-Aware and Agentic AI framework that bridges the gap between advanced in-field sensing and legacy decision support systems. This project allows their theoretical machine learning research to be expanded into an applied, closed-loop precision agriculture ecosystem. The novel architectural patterns and AI models to be developed are believed to be generalizable to other complex integration challenges, and will hopefully be positive assets for future scientific advancements and the green transition

Department of Agroecology

Aarhus University – Dept. of Agroecology (AU-AGRO) is a premier research institution with deep agronomic expertise in weed science, integrated pest management (IPM), and the scientific validation of environmental impacts. AU-AGRO will utilize their participation in this project to generate unique, high-resolution longitudinal datasets to scientifically quantify the link between precision pesticide reduction and in-field biodiversity. This project allows their agroecological research methods to be expanded to include automated, AI-driven field diagnostics and monitoring. The resulting data and validated economic and environmental impact models will inform national and EU agricultural policy, and will hopefully be positive assets to the broader scientific and agricultural communities.

AG Precision ApS (AGP) is a commercialization and integration company with extensive practical experience in the integration, sale, and on-farm support of precision agriculture hardware, operating with an established dealer and customer network. AG Precision will utilize their participation in this project to transition from a technology reseller to a proprietary product owner by commercializing the robust CropCareCam system. This project allows their expertise in machinery integration to be expanded to include the physical mounting and support of intelligent sensor hardware. The resulting proprietary product line will drive significant business growth, and will hopefully be a highly valuable asset to their existing and future farming customers

I•GIS is a specialized GIS and geoscience software and service provider, with an international client base.
I•GIS will utilize their participation in this project to continue building state-of-the-art applications for automatic analysis of non-crop and crop plants and improving the RoboWeedMaps mapping service. This project allows their set of modelling and data management solutions to be expanded to include modelling and decision support tools in the special case of plant mapping. Many of the new features to be developed are believed to be general and applicable in other use-cases, and will hopefully be positive assets to already existing and future customers.

AI Lab ApS (AILab) is a specialized high-tech engineering company with core expertise in developing and deploying robust, embedded AI and camera systems for harsh, real-world environments. AI Lab will utilize their participation in this project to develop, validate, and showcase their core intelligent optical sensor technology in a large-scale agricultural application. This project allows their edge computing and hardware solutions to be expanded into a comprehensive cloud-based data hub for raw field imagery and AI-derived insights. The technologies and embedded software developed will serve as a critical commercial proof-point, and will hopefully be positive assets applicable to future industrial machine vision clients.

Perplant ApS (PerPlant) is an innovative ag-tech startup focused on democratizing access to AI for sustainable farming through user-centric, API-driven Farm Management System (FMS) cloud platforms. PerPlant will utilize their participation in this project to solve the “last mile” problem of ag-tech adoption by ensuring that their GUI (the PerPlant FMS cloud platform) serves as the ultimate digital endpoint for the farmer. This project allows their existing FMS platform to be expanded to include real-time, high-resolution data streams and context-aware herbicide prescriptions. By translating complex Agentic AI insights into simple, actionable agronomic recommendations delivered directly to the farmer’s screen, the seamless API integrations and premium GUI developed will provide a significant competitive advantage, and will hopefully be positive assets to already existing and future users

Sigridshøj Jordbrug & Landskabspleje is an innovative, tech-savvy farming enterprise that provides practical agronomic expertise and serves as an essential real-world testbed for agricultural technologies. Sigridshøj will utilize their participation in this project to gain early access to cutting-edge tools, providing crucial daily operational feedback to optimize the system’s usability and agronomic value. This project allows their conventional farming operations to be expanded to include advanced AI-driven decision support for reduced pesticide use and improved sustainability. The resulting insights and validated workflows are believed to be highly applicable to other modern farms, and will hopefully serve as a demonstrator for the broader agricultural community.