Digital technologies

The Digital Technologies (DT) Sector investigates enabling solutions for digital transformation and technology transfer to SMEs and public administrations through the development of intelligent systems, IoT infrastructures, and interoperable data architectures. This integrated approach addresses real-world territorial needs by delivering advanced solutions for Smart Cities, sustainable and precision agriculture, and the digital enhancement of cultural heritage.

From a methodological perspective, research activities are organized around the following key areas:

Distributed Software Architectures and IIoT Systems

Design and development of decentralized computing infrastructures and intelligent sensor networks for the integrated acquisition of environmental and operational data. Activities focus on the orchestration of connected devices across industrial and territorial contexts (Industrial Internet of Things – IIoT) and on optimizing data processing at the source through edge computing paradigms. These solutions ensure secure, resilient, and low-latency data flows, providing the foundation for integrated digital ecosystems.

Keywords: Industrial Internet of Things (IIoT), edge intelligence, distributed architectures, sensor networks, cloud computing, integrated data flows.

Data Architectures for Digital Ecosystems

Design and management of data pipelines required to support secure and seamless digital ecosystems. Research activities focus on the development of data hubs and storage infrastructures capable of integrating heterogeneous data streams from IIoT networks and enterprise information systems. Particular attention is devoted to interoperability across platforms, efficient data governance, and secure data traceability mechanisms that safeguard the value and ownership of generated knowledge assets.

Keywords: Data pipelines, system interoperability, data governance, data architectures, secure data sharing, integrated information flows, knowledge protection.

Applied Artificial Intelligence and Decision Support Systems

Development and integration of machine learning models aimed at process optimization and intelligent automation. Activities focus on the design of Decision Support Systems (DSS) capable of interpreting heterogeneous data streams to generate predictive insights, optimize resource allocation, and transform data into actionable strategies that support both enterprises and public administrations.

Keywords: Artificial Intelligence (AI), Machine Learning, Decision Support Systems (DSS), process automation, predictive analytics, resource optimization.

Application Domains and Regional Impact

The sector’s methodological expertise is applied to strategic domains, translating research and innovation into sector-specific solutions for industry and institutions.

Territorial Hubs and Smart Cities Development of digital platforms for the coordinated management of urban infrastructures, mobility analytics, and territorial planning. This domain also integrates technologies derived from the aerospace sector, including satellite data processing and remote sensing techniques for advanced environmental monitoring and territorial resilience.

Smart Agriculture and Agritech Integration of advanced field sensing technologies, robotics, and predictive models to improve water and energy efficiency and optimize agricultural and livestock production processes. The incorporation of geospatial data and aerospace-derived positioning systems enables large-scale monitoring of soil conditions and crop health.

Energy Transition and Sustainability Application of machine learning and predictive analytics to optimize energy consumption, estimate thermal and electrical demand, and develop intelligent solutions that support decarbonization and sustainability in both industrial and civil sectors.

Media, Digital Content, and Creative Industries Technology transfer initiatives supporting the evolution of publishing, broadcasting, and cultural heritage value chains. Through the management of large-scale datasets and the integration of Generative Artificial Intelligence models, the sector develops digital ecosystems that optimize production workflows—including intelligent editing and archiving—and enable interactive solutions that combine personalized user experiences with operational efficiency for content providers and cultural institutions.