Research Axes
Drone Imagery for crops health - Computer Vision
Drone imagery is a widely used technique for observing agricultural plantations. Equipped with specific sensors, the imaging makes it possible to capture areas of the field and make detailed reports in record time. Our focus will be on disease detection, plant and soil health using artificial intelligence techniques, including computer vision. In particular, we will use the colors from the ndvi with comparative methods such as the cosine of similarity and the machine vector support based on Opencv libraries.
Smart irrigation via robotics and tractors - Deep Learning
Automatic irrigation is an advanced method of bringing substantial water resources to agricultural land as needed. This automatic irrigation can be carried out on ground-based systems or on mobile supports such as semi-autonomous tractors for agriculture. Our study will focus on the use of deep learning techniques for the auto-steering of semi-autonomous vehicles as well as the regulation of irrigation valves according to the needs of the soil. We will use many simulations based on Numpy and Tensorflow libraries.
Algae based nutrition for livestock - Indoor farming
Our study will focus on the cultivation and indoor production of algae plants for livestock nutrition. The algae plant has the essential characteristics to promote livestock health - the production of quality and quantity of milk but also the reduction of the rate of CO2 emission into the atmosphere. We will go from the simulation of the installations to the setting up of the production unit.
