BoniKI
AI-based scoring system for plant-accurate, autonomous plant evaluation
Start: 05/2021
End: 04/2024
The BoniKI project was concerned with the automation of plant evaluation. Plant evaluation – for example, the assessment of pest infestation in crops – is time-consuming, cost-intensive and requires many years of experience. Currently, a manual process is necessary, in which plants are randomly inspected and overall assessments are determined via statistical analyses.
Automated plant evaluation with Artificial Intelligence (AI) and classical computer vision algorithms was supposed to increase sustainability, transparency, and efficiency in agriculture. The potentials of algorithms and neural networks were tested regarding opening up new potentials and relevant assessment parameters. They could enable a larger circle of users to determine protection and maintenance measures.
The tasks and responsibilities of the FZI were specifically in the field of AI. High-resolution data were recorded with an Unmanned Aerial System (UAS) for a plant-specific evaluation and AI methods were used to separate the crop plant from weeds and background before an automatic evaluation is carried out with further AI methods. At the end of the project, the goal was to create a holistic, easy-to-use solution that can automate the evaluation process.
The results from the BoniKI project were taken up for a follow-up project by an industrial partner.
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