Technology Assessment Of AI-Based Computer Vision For Harvesters In Industrial Mixed Crop Production
- Conventional agriculture faces escalating environmental and economic challenges. Intensive monoculture farming and the extensive use of chemical additives, such as fertilizers and pesticides, contribute to environmental pollution, biodiversity loss, and soil and water degradation, threatening both natural resources and the long-term resilience of agricultural systems. Mixed cropping, the cultivation of multiple crop species together, presents a promising alternative by optimizing resource use, enhancing soil and water quality, and reducing dependency on chemical inputs. However, its industrial application remains limited due to complexities and the lack of technical solutions, particularly in harvesting. Computer vision technology holds great potential to address these technical limitations. This paper supports agricultural machinery manufacturers by presenting a technology assessment of computer vision applications in harvesting machines for industrial mixed crop cultivation. Functional capabilities of computer vision were categorized and matched against the requirements of various functions within industrial mixed-crop harvesting, creating impact matrices that evaluate the relevance of computer vision per function. The results demonstrate the substantial potential of computer vision to facilitate, or even enable, the harvesting of mixed cropping systems at an industrial scale. The findings offer a technological foundation for developing mixed crop harvesters, informing evaluation and selection processes for final design solutions.
| Author: | Tim WalterORCiD, Günther SchuhORCiDGND |
|---|---|
| DOI: | https://doi.org/10.1109/ICCAR64901.2025.11073058 |
| ISBN: | 979-8-3315-2026-7 |
| ISBN: | 979-8-3315-2025-0 |
| ISSN: | 2251-2454 |
| Parent Title (English): | 11th International Conference on Control, Automation and Robotics (ICCAR) 2025, Proceedings (IEEE ICCAR '25) |
| Publisher: | IEEE |
| Place of publication: | Piscataway (NJ) |
| Document Type: | Conference Proceeding |
| Language: | English |
| Date of Publication (online): | 2025/08/10 |
| Date of first Publication: | 2025/08/01 |
| Release Date: | 2025/08/10 |
| Tag: | 03 Computer Vision; Product development; Smart farming; Sustainability; Technology assessment |
| First Page: | 445 |
| Last Page: | 451 |
| Note: | SAAT Project:
Duration: 01.05.2023 – 30.04.2026
Funding no.: 01MN23012B
Project homepage: projekt-saat.de
Funding: Federal Ministry for Economic Affairs and Energy (BMWE)
Promoters: Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
Acknowledgment: Funded as DLR project no. 01MN23012B by the Federal Ministry for Economic Affairs and Climate Action (BMWK) due to a decision of the German Parliament.
SAAT:
Sustainable Agriculture through Artificial Intelligence and Digital Technologies
The aim of the research project 'SAAT' is to demonstrate the technical and economic feasibility of sustainable mixed crops in agriculture. For this purpose, a field planning tool based on explainable AI as well as an AI-controlled sorting robotics module for field crop sorting on autonomous harvesting systems will be developed and the economic efficiency and sustainability of mixed crops compared to monocultures will be measured by means of multidimensional monitoring.
Benefits for the target group:
The results are intended to serve as an incentive and basis for agricultural machinery manufacturers to develop and sell systems suitable for mixed cropping, and to encourage farms to demand and use these systems. If used successfully, higher yields can be achieved in arable farming on more climate-sensitive fields, CO2-intensive fertilizers and pesticides can be saved, and biodiversity as well as soil and water quality can be increased as a result.
Project partners:
Bürgershof Familie Blomenkamp, Duisburg
Grimme Landmaschinenfabrik GmbH & Co. KG, Damme
Günther Claas Vermögensverwaltungs-GmbH & Co. KG, Bohmte
Gutsverwaltung Wittlaer Hof, Düsseldorf
Nature Robots GmbH, Osnabrück
Schmiede.one GmbH & Co. KG, Düsseldorf
SeedForward GmbH, Osnabrück |
| Name of the conference: | 11th International Conference on Control, Automation and Robotics (ICCAR) 2025 |
| place of the conference: | Kyoto |
| Date of the conference: | 18.04.2025-20.05.2025 |
| Institute / Department: | FIR e. V. an der RWTH Aachen |
| Informationsmanagement | |
| Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften |
