Robots and machines integrated within farming processes host numerous specialized sensors and measurement devices and generate large amounts of data that combined with data, coming from external sources, could provide a basis for better process understanding and process optimization. One serious roadblock to this vision is that the equipment of different vendors is often not interoperable and cannot exchange data. Another pitfall of current solutions is that the process knowledge is not modelled in a standardized machine readable form. On the other hand, such process model can be flexibly used to support process-specific integration of machines, and could also enable context-sensitive automatic process optimization.
The project agriOpenLink (Adaptive Agricultural Processes via Open Interfaces and Linked Services) will provide an extendible interface model for agricultural machines via an open-source library and a design methodology for adaptive process control based on linked semantic services and data, and will verify and popularize these results in a user study targeting developers of ICT applications for smart farming.
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