OPeRAte - Orchestration of Process Chains for data-driven Resource Optimization in Agricultural Business and Engineering
Environmentally sustainable and economically efficient operation of agricultural processes depends heavily on farm management and controlling systems. However, practical usage of these systems suffers from diverse, non-compatible implementations across collaboration machinery. Systems are often bound to static operation in centralised environments. This is where OPeRAte (Orchestration of Process Chains for data-driven Resource Optimization in Agricultural Business and Engineering) comes in place: OPeRAte's vision is to explore mechanisms for an automatic creation und utilisation of dynamically adaptable agricultural processes in distributed environments. OPeRAte employs Big Data techniques to automatically optimise resource usage in agriculture. During resource optimisation, OPeRAte considers the privacy of process chain members at all times.
The project investigates reusable components, which can be easily combined for the realisation of complex agricultural process chains. A big challenge is the dynamic nature of agricultural processes. Mechanisms for monitoring and adaption are researched. Support of dynamic process chain optimisation at runtime is supposed to take effect on process-, data-, and device-level as follows:
- Dynamic orchestration of process chains by combination of services for a fleet management (e.g. calculation of application maps for liquid manure, navigation of manure trailers / harvesters / tractor-trailer combinations, nutrient balance).
- Efficient and privacy-guaranteeing data analysis of large, heterogeneous data sources for real-time optimisation of distributed agricultural processes.
- Autonomous discovery, authentication and network integration of physical resources (devices, sensors, actors, data-servers, etc.).
Cooperation between different agricultural actors (farmers, agricultural contractors, precision farming providers, authorities, etc.) is supported by providing data analysis equipped with a flexible definition of data access rights. In regards to privacy concerns, every actor can only access data based on his given access rights by other actors. OPeRAte implements and prototypes the core concepts using two use cases (application of liquid manure, harvest logistics).
Project partners: 365FarmNet, ANEDO Ltd., FARMsystem, Hochschule Osnabrück, Kotte Landtechnik
Project funding: Federal Ministry of Food and Agriculture (Bundesministerium für Ernährung und Landwirtschaft, BMEL)
Project Runtime: May 2016 to January 2020
Project website: http://operate.edvsz.hs-osnabrueck.de