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HEASY Project

Technology and Science for Biodiversity in the Mediterranean

The project “HEASY – Reproductive health, biosensors and computer vision to conserve and protect the marine ecosystem” combines ecology, biotechnology and artificial intelligence for the protection of Mediterranean marine ecosystems.

Through innovative biosensors and advanced monitoring systems, we study the impact of anthropogenic stresses on biodiversity to develop concrete and sustainable solutions.
An EU-funded project – NextGenerationEU, under the NBFC – Spoke 1

The Project

HEASY is a multidisciplinary research initiative bringing together biologists, biotechnologists, engineers and data scientists from various Italian universities and research centres. The partnership includes academic institutions and specialised organisations committed to the development of innovative tools for the protection of marine biodiversity in the Mediterranean Sea.

A Commitment for the Mediterranean

The Mediterranean Sea is a fragile and unique ecosystem with an extraordinary biodiversity, but one that is severely threatened by pollution, climate change and human activity. HEASY focuses on specific areas of intervention, including:

  • Mar Piccolo di Taranto

    Monitoring the effects of industrial and urban pollution.

  • Golfo di Cagliari

    Studying the impact of emerging pollutants on benthic ecosystems.

  • Cilento’s areas

    Analysis of the health status of the coralligenous zone and associated biodiversity.

  • Stretto di Messina

    Development of metabolomic models for environmental monitoring.

As an official project partner, we are responsible for an artificial intelligence algorithm development for the recognition of marine species, with a special focus on corals.

The creation of image analysis software to determine the size, health and distribution of marine organisms, the integration of satellite data to estimate environmental parameters such as water temperature and oxygenation, are just two of the many aspects we will be involved in.

Another key aspect will be the optimisation of the algorithms to improve the accuracy of automatic recognition.

Other partners: