Photo: The combine harvestor at work. Source:© InSensEPro

Efficient harvesting is a complex endeavor, with combine harvesters constantly adapting to field conditions and weather. Variations in plant size, spikes, grain count, and size, influenced by factors like soil quality, water distribution, and shading, eliminate any one-size-fits-all approach. This raises pivotal questions: How can we enhance monitoring during the harvesting process? How can we ease the operator’s workload?

These challenges drove an innovative collaboration between Bielefeld University’s Research Institute for Cognition and Robotics (CoR-Lab) and CLAAS, an agricultural machinery manufacturer in Harsewinkel. Their project, ‘Intelligent sensor network for determining process variables’ (InSensEPro), aimed to revolutionize combine harvesters.

The full text of the good practice is available to read and download in PDF format from the AgriSkills 4.0 e-Learning platform, section “Good practices”. You just need to search for it by name using the search box.

You will find additional 45 good practices, initiatives and use cases in the AgriSkills Reference Catalogue titled “AgriSkills Guidebook on Digitalization in Agriculture”.

Cover Photo: YouTube video “How a Combine Harvester Works” (EN). Link:

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them. 

Project number: 2021-1-DE02-KA220-VET-000034651

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