prospective.HARVEST – Optimizing Planning of Agricultural Harvest Logistic Chains
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ISSN der Zeitschrift
40. GIL-Jahrestagung, Digitalisierung für Mensch, Umwelt und Tier
Gesellschaft für Informatik e.V.
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 utilizing remote and in-situ (geo-) data from a variety of data sources in order to enable farmers to optimize their logistic chains. Optimizations are computed as recommendations on several layers of the harvest process, from monitoring the crop over planning the inter-field and in-field coordination of harvesters and transport vehicles up to the surveillance and dynamic replanning of the ongoing harvest execution.