Project description

INVASOR-ES project aims to develop advanced technological solutions against invasive alien species (IAS) in hydraulic infrastructures, especially irrigation systems. These species, such as the zebra mussel, apple snail, and bryozoans, cause severe infrastructure problems, including blockages, failures, high maintenance costs, also reducing the agricultural productivity.

The project development promotes the implementation of new technologies that combine advanced sensors for monitoring, computer vision, and deep learning, enabling the accurate identification and calcification of different invasive species larvae. The project’s main result is the creation of artificial intelligence-based monitoring stations for the real-time detection of Invasive Alien Species (IAS) at larvae and adult stages through automatic sample collection and computer vision. This disruptive technology will facilitate more efficient preventive monitoring by reducing the dependence on traditional chemical treatments, which are expensive and harmful to the environment.

Besides, the project will develop specific strategies for emerging IAS without any preventive and efficient methodology already developed. These solutions will be customised to the real needs of each infrastructure, integrating sustainable methods and being environmentally friendly while reducing operative costs and minimising economic impact risks.