Harvesting more efficiently with autonomous technology
The agricultural sector faces the challenge of producing more food with fewer resources and less environmental impact. This project focuses on the development of smart autonomous harvesting machines for open-field vegetables, designed for both selective and non-selective harvesting.
Background of Use Case 6
Autonomous harvesting machines for sustainable production
The project develops automated and autonomous harvesting machines that not only harvest more efficiently but are also lighter in weight. This reduces soil compaction and minimizes damage to soil structure. By using data-intensive models and digital twins, processes are optimized and harvest quality is improved. The technology supports sustainable food production and responds to the growing demand for plant-based products.
"Smart harvesting machines increase efficiency and reduce environmental impact."
Contribution to the ecosystem and the sector
Less soil compaction and higher yields
The use of smaller, autonomous machines reduces the impact of heavy equipment on the soil, leading to healthier crops and higher yields. This technology enables more efficient operations and reduces the need for manual labor. By leveraging data and digital models, processes can be continuously optimized, resulting in a more sustainable production process.
Deliverables Use Case 6
Practical applications for autonomous harvesting
Development and validation of autonomous harvesting machines for open-field vegetables
Reduction of soil compaction through lighter machinery
Implementation of digital models and data-intensive solutions for harvest optimization
Testing and scaling up the technology in real-world conditions
Added value for Human Capital
Less physical labor, more technical knowledge
The use of autonomous harvesting machines reduces the need for physical labor. Growers require fewer workers for harvesting and pruning, making them less dependent on seasonal labor. At the same time, working with autonomous technology requires new skills. Growers must learn how to calibrate machines, analyze data, and optimize harvesting processes. This combination of reduced manual labor and increased technological expertise leads to a more efficient and sustainable harvesting process.
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