Project Information
In this minor project, students investigated how hyperspectral imaging combined with artificial intelligence can help in the automatic detection of quality defects in onions. The aim was to develop a system that enables automated quality control of onions, using a setup where hyperspectral technology is integrated. This contributes to smart agriculture and efficient food inspection.
What has been realised?
The students have developed a working demonstrator that scans, analyses, and classifies onions based on their spectral properties. By linking hyperspectral data to AI algorithms, the system can identify anomalies that are difficult to see with the naked eye. The demonstrator shows how technology can be used to assess food quality objectively and scalably.
What have they learned?
The project group has learned how hyperspectral technology and artificial intelligence can be combined in a practical application. They have gained experience in processing complex image data, training classification models, and building a physical setup for inspection. Furthermore, they have gained insight into how technological innovation can contribute to sustainability and automation within the agricultural sector.
