Intelligent Agriculture refers to the application of advanced Information and Communication Technologies (ICT) in the agricultural sector, combined with the development of specialised, intelligent computing methodologies and tools. Machine learning algorithms and other Artificial Intelligence (AI) techniques are developed and applied to wireless sensor and actuator systems, autonomous agricultural vehicles, robotic systems and other precision equipment, as well as plant disease and weed detection systems, and agricultural data analysis tools. In particular:
- Plant disease and weed detection
Development of deep learning models for the automated identification of plant diseases and weeds.
- Developing intelligent methods for the detection of diseases and diseases of plant diseases, including the development of advanced techniques for the diagnosis and diagnosis of diseases in the field of plant diseases.
Design and energy optimisation of WSNs for precision and intelligent agriculture and their integration into IoT applications.
- Autonomous vehicles
Heuristic and intelligent algorithms for optimal path planning of autonomous agricultural vehicles in various field applications.
In addition, research related to agricultural engineering and environmental protection will be carried out, focusing on agricultural equipment, technologies and pesticide application methodologies, with the aim of optimising the quality of spraying equipment and techniques applied to minimise the impact on human health and the environment.