NeMeA Sistemi achieves ISO/IEC 42001 certification: a step forward in the responsible management of Artificial Intelligence

The certification of the Artificial Intelligence management system reinforces an approach that combines Earth observation, knowledge of the territory and environmental monitoring.

A satellite image can reveal a great deal: changes to the landscape, a variation that warrants further investigation, or signs from a marine ecosystem that require close observation. To promptly transform this data into useful information and address critical issues, we need technologies capable of interpreting it and a method that allows us to verify the results.

NeMeA Sistemi operates along this two-pronged approach, having secured the ISO/IEC 42001:2023 certification, the international standard relating to Artificial Intelligence management systems. A milestone that reinforces the way in which the company develops and utilises AI in its solutions for the local area and the environment.

The starting point is to make large amounts of data understandable and to derive insights from it that can inform effective decision-making. This process also requires attention to be paid to what lies behind a result – from the origin of the data to the checks carried out, and from the limitations of the models to the ability to reconstruct the analysis process.

Understanding the landscape, observing the sea

This approach takes shape in 3xA®, the patented NeMeA technology which uses SAR radar satellite data and analysis algorithms to identify and map changes in the landscape.

The mechanism is that of the Change Detection: compare satellite images taken at different times to detect changes and anomalies. The results are converted into geographical information layers that can be viewed in the GIS and WebGIS systems, incorporating satellite analysis into planning and management tools.

From the land to the sea, the question remains the same: how can we translate what we observe into a clearer understanding of what is happening?

An answer comes from EMAMI – IoT-based Marine Environmental Monitoring Ecosystem, as part of which NeMeA is developing Artificial Intelligence models for process optical and multispectral satellite data. The aim is to highlight changes and potential issues affecting marine communities, with a particular focus on Posidonia oceanica seagrass beds.

Two different fields, one common thread: providing public administrations and bodies responsible for the protection of natural resources with analytical tools to help them interpret changes and guide decision-making.

Innovation also depends on the method

When information can help inform a decision concerning the local area or the environment, the process by which it was produced takes on particular significance. This is where the ISO/IEC 42001, providing a structured framework for managing Artificial Intelligence throughout its life cycle, from defining objectives to assessing risks, from verifying outcomes to continuous improvement.

The certification relates to the management system adopted by NeMeA and reinforces the procedures through which the company supports the development of its technologies. Data quality, traceability and an awareness of limitations are integral to the day-to-day work on AI.

‘Artificial Intelligence thus becomes a tool for moving from the availability of data to its interpretation: it does not replace the decision-maker, but helps to provide them with more timely and accessible information’, says Michele Boella, CEO and Founder of NeMeA Sistemi.

For NeMeA, achieving ISO/IEC 42001 means further strengthening this vision. AI is integrated into a process that begins with data collection and extends to its geographical representation, integrating Earth observation, GIS, IoT and marine robotics.

Value lies in the knowledge it provides and in the ability to decipher the dynamics of a place, understand a change, and recognise a sign that warrants further investigation. And it enables decision-makers to make decisions with greater awareness.

English (UK)