PRECISION: Advanced Machine Learning for Drone-Based Precision Agriculture

Overview

PRECISION is a collaborative research project coordinated by the University of Luxembourg and co-lead by Technical University of Munich, focusing on enhancing sustainability in wheat farming. The project aims to develop advanced machine learning models that utilize drone-based remote sensing data to optimize nitrogen fertilization and weed control strategies.

Objective

• Enhance crop yield and Reduce environmental impact: Utilize high-resolution data collected during the growing season to inform precise application of fertilizers and herbicides, thus optimizing resource use efficiency.

Methodology

The project integrates expertise from geospatial engineering, remote sensing, and agronomy to:

• Collect high-resolution data: Employ drones equipped with LiDAR and hyperspectral imaging sensors to gather detailed information on crop health and field conditions.
• Develop AI models: Create machine learning algorithms capable of analyzing collected data to provide actionable insights for farmers.
• Field testing: Implement and validate the developed technologies at test fields, including those of the Institute for Organic Agriculture and Agroecology Luxembourg (IBLA), Luxembourg and Technical University of Munich.

Collaboration and Funding

PRECISION is a joint effort involving:

• University of Luxembourg
• Technical University of Munich
• Institute for Organic Agriculture and Agroecology Luxembourg (IBLA), Luxembourg
• Lycée Technique Agricole

The project is funded by the Luxembourg National Research Fund (FNR) and the Ministry of Agriculture, Viticulture and Rural Development (MAVDR).

Also check out the PRECISION project at UniLux.