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Publikation

prospective.HARVEST - Optimizing Planning of Agricultural Harvest Logistic Chains

Arne de Wall; Christian Danowski-Buhren; Andreas-Wytzisk-Arens; Kai Lingemann; Santiago Focke Martínez
In: Lecture Notes in Informatics (LNI). Gesellschaft für Informatik in der Land-, Forst- und Ernährungswirtschaft (GIL-2020), February 17-18, Weihenstephan, Germany, Köllen Druck & Verlag GmbH, 2020.

Zusammenfassung

The research and development project “prospective.HARVEST” aims at optimizing the process chain of silo maize harvesting, based on a predictive approach using prognosis data. New methods and tools have been developed in order to enable farmers to optimize their logistic chains.

Projekte