The aim of this joint project is the realization of an infrastructure to provide proactive support for agriculture processes, taking silage maize harvesting as an example of use. The key component is the integration of data from sources that are already available, yet unused in this application scenario so far. The data comes from farm management systems, as well as the machines themselves, public geo-information infrastructures (such as Copernicus) and other external sources (e.g., harvest forecasts).
The research department ASR contributes especially to logistics and to the usage of agent technologies in service-oriented architectures. This includes both the control of logistic processes as well as the interplay between technologies and process modelling and process execution tools. Specifically, the subproject “Predictive Planning” specifies, implements, and evaluates a system modeling logistics processes in corn harvesting based on maturation, biomass, reachability for vehicles, available resources, and distances.
CLAAS E-Systems KGaA mbH & Co KG, CLAAS Selbstfahrende Erntemaschinen GmbH, 365 Farmnet GmbH & Co KG, green spin GmbH, Hochschule Bochum, 52° North Initiative for Geospatial Open Source Software GmbH