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), (GIL-2020), 17.2.-18.2.2020, Weihenstephan, Köllen Druck & Verlag GmbH, 2020.
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.
Precision Farming, Smart Farming, Planning, Maize Harvesting, Logistic Chains