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.

Abstract :

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.

Keywords :

Precision Farming, Smart Farming, Planning, Maize Harvesting, Logistic Chains


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