The INNOSETA project has come to an end. An overview is given of how the project has tried to bridge the innovation gap between research and developers of spraying technologies and end users.
Within this project, together with the flax sector, Inagro, VITO and ILVO, a digital, visual tool for monitoring the crop position of flax is being developed.
This project combines the potential of artificial intelligence with the use of camera technology for site-specific weed detection.
Within this project, a prototype of a robot and corresponding implements will be developed in co-creation with farmers and mechatronics companies.
This project investigates the application of semi-supervised learning for anomaly detection in potato cultivation as a decision support tool for farmers and advisors.
There is a range of innovations and good practices available for spraying crop protection products. In this project, all these are brought together in an orderly fashion in an online database.
In this project, several types of sensor data (soil scans, soil sensors, drone and satellite images) are combined for more intelligent fertilization of leek.