AI4ESOPP: Artificial Intelligence for Environment

The platform can be described as the integration of five conceptually distinct modules:

1- Data collection and integration

A module designed to collect, aggregate and make available data from enterprise systems, machinery, distributed plant sensors and external sources. Activities include Data Fusion, acquisition, ingestion, storage, metadata management and ETL, creating a common and governed data foundation.

2- Plant analysis and monitoring

An analysis and visualisation module that makes operational and environmental information available through dashboards and monitoring tools. Depending on the type of plant, it can support the analysis of energy and water consumption, performance, anomalies and other indicators useful for understanding production-system behaviour.

3- Forecasting, planning and optimisation

A module based on mathematical models and artificial intelligence techniques to represent plant behaviour, simulate scenarios and support forecasting, scheduling and optimisation. Machine Learning, Deep Learning and reinforcement learning are investigated to identify inefficiencies, critical points and improvement opportunities and to compare possible operational alternatives. The resulting recommendations remain a decision-support tool for operators and management.

4- Environment, ESG and certifications

A reporting module that structures data and indicators for the periodic assessment of environmental impact and supports the export of information for ESG processes and certification pathways. The project considers standards and schemes such as LEED, ISO 50001, ISO 14001 and EMAS, linking collected data to the evidence required.

5- LLM-based virtual assistant

An interaction module based on Large Language Models that simplifies access to the platform. The assistant allows users to query data, reports and documentation in natural language and obtain textual explanations of results, making technical, environmental and certification-related

The project is centred in Sicily and contributes to the development of technological capabilities in one of the less developed regions covered by the funding programme. Implementing AI4ESOPP in Palermo strengthens research and development activities in artificial intelligence, data management and sustainable manufacturing, while also encouraging dialogue with universities and the research ecosystem.

The project’s applied dimension is strengthened by the involvement of D’Amico – D&D Italia S.p.A. Società Benefit as an industrial partner for validating the platform in a real production environment.

From an environmental perspective, AI4ESOPP is consistent with objectives related to emissions reduction, efficient use of resources, circular economy and climate-change adaptation. The integration of industrial data, models and AI makes it possible to assess production performance and environmental impact within the same information framework, considering energy consumption, water resources and other relevant indicators.
 

AI4ESOPP is part of the digital transformation of industry that connects production efficiency with sustainability. In line with the priorities referenced by the EUSAIR strategy and the Blue Economy, the project applies digital technologies and artificial intelligence to improve resource use, reduce waste and impact, and support production processes that are more aware of their environmental performance.

The platform therefore brings together data management, monitoring, modelling, forecasting and optimisation, environmental reporting and LLM-based interaction within a single architecture. The expected result is a modular tool that makes it easier to understand plant operation and assess operational and environmental choices on the basis of data and verifiable evidence.
 

Purpose and expected results

AI4ESOPP aims to develop an Artificial Intelligence-based platform for the management, efficiency and environmental sustainability of production plants. The project integrates methodologies and software components for the acquisition and management of heterogeneous data, plant monitoring, process modelling and simulation, production forecasting and optimisation, environmental-impact assessment support, and user interaction through Large Language Model-based virtual assistants.

Funding

AI4ESOPP is a Research and Development project implemented by Mashfrog Group S.r.l. under the Fondo per la Crescita Sostenibile - “Scoperta imprenditoriale”, within the Italian National Programme “Research, Innovation and Competitiveness for the Green and Digital Transition 2021-2027”, Action 1.1.4 “Collaborative Research”. The project is co-funded by the European Union.

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