A shared language for greenhouse horticulture
Within the greenhouse horticulture sector, there is a lack of standardized methods for exchanging data between autonomous systems, robots, and operators. This use case focuses on developing a collective data infrastructure that enables secure and efficient data exchange. It enhances collaboration between companies and accelerates the adoption of technological innovations.
Background of Use Case 10
From fragmentation to a standardized data platform
The use of autonomous systems is causing an explosive growth of data within the greenhouse horticulture sector. The key challenge is to efficiently connect this data, ensuring that all systems involved—from autonomous vehicles to climate control systems—can communicate seamlessly. This use case focuses on developing standards and protocols for data quality, positioning, and co-learning. As a result, both humans and machines know exactly what to expect, creating a solid foundation for further innovation.
The platform is based on the Common Greenhouse Ontology (CGO), which provides a unified language for all connected systems. CGO enables seamless interoperability between technologies such as harvesting robots, climate control, and irrigation systems. By integrating machine learning and AI, the platform can automatically adapt to changing greenhouse conditions, making production more efficient and increasing the predictability of the cultivation process.
"By developing a shared data language, we improve collaboration and accelerate innovation in greenhouse horticulture."
Public summaries of Use Case 10
Validatie Hortivationpoint
Contribution to the ecosystem and the sector
Faster innovation through better collaboration
This use case enables systems from different manufacturers to work together more efficiently through standardized data exchange. It reduces development and maintenance costs and ensures that new technologies are adopted and implemented more quickly. The use of a unified data language allows systems to communicate directly and consistently, accelerating innovation within the sector.
The project also fosters strategic collaboration across the industry. By making data accessible to various stakeholders, new opportunities for optimization and innovation emerge. This leads not only to cost savings but also to higher quality in the final product.
Deliverables Use Case 10
Standardized data exchange for faster innovation
Development of a collective data infrastructure for greenhouse horticulture
Creation of standards for positioning and data quality
Faster adoption of new technologies through unified system communication
Reduction of development and maintenance costs through improved system integration
Implementation of CGO as the standard for data linkage between various systems
Added value for Human Capital
More knowledge about data infrastructure requires additional expertise and training
The implementation of a collective data infrastructure requires new skills that are not yet widely available in the sector. Growers and technology companies will need to upskill in data analysis, data management, and system integration within a unified data language. Additional expertise in data integration and systems administration is essential to ensure smooth collaboration between autonomous systems, robots, and operators. This calls for targeted training and education across the sector.
In addition, the use of AI and machine learning demands new insights into data processing and system management. Growers must learn how to interpret data and use it to automatically adjust greenhouse processes. This project encourages the development of digital skills, which accelerates the adoption of autonomous systems and boosts efficiency throughout the sector.
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