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Collaborative project: Resource-efficient AI for Embedded Systems in Agricultural Machines - subproject D (resKIL)
Project
Project code: 28DK102D20
Contract period: 01.01.2021
- 30.06.2024
Budget: 341,321 Euro
Purpose of research: Applied research
Keywords: data management, crop production, knowledge transfer, networking, AI Artificial Intelligence, agricultural engineering, information-communicationtechnology, digital world
The use of AI methods is particularly useful in agriculture, since the environment is characterized by a high dynamic, is not completely known and cannot be comprehensively controlled. First AI applications have shown significant process improvements, especially in the agricultural domain. However, the implementation of AI-based applications on mobile machines (on the edge) and specialized and high-performance hardware systems result in major consequences.Wireless, reliable and broadband cloud connectivity is not available in rural areas. These restrictions may hinder the introduction of a technology that has proved useful for farmers in various cases. Therefore a distributed approach appears to be sensible, which is minimally invasive on the machine-side and uses a specialized environment on the cloud-side.In the project resKIL, modern approaches of artificial intelligence (especially deep learning) are made suitable despite the limiting hardware on agricultural machines by the precise analysis and optimization of the required resources. Scientific results in the areas of experimental planning, evaluation of data quality, annotation and use of multivariate and resource-efficient ML and AI methods are sought.A software architecture and an AI toolchain are developed that meet the requirements of the mobile working environment. These are integrated and evaluated as prototypes in agricultural practice.
Section overview
Subjects
- Crop Production
Framework programme
Funding programme
Excutive institution
German Research Center for Artificial Intelligence GmbH (DFKI)
Funding institution
Project management agencies
Associated projects: resKIL
- Collaborative project: Resource-efficient AI for Embedded Systems in Agricultural Machines - subproject A
- Collaborative project: Resource-efficient AI for Embedded Systems in Agricultural Machines - subproject B
- Collaborative project: Resource-efficient AI for Embedded Systems in Agricultural Machines - subproject C
- Collaborative project: Resource-efficient AI for Embedded Systems in Agricultural Machines - subproject E
- Collaborative project: Resource-efficient AI for Embedded Systems in Agricultural Machines - subproject F
