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European Research & Innovation Projects

Cloud4Business actively takes part in European projects funded by the Horizon Europe programme, applying artificial intelligence to complex environmental challenges and climate resilience goals.

Cloud4Business actively takes part in European projects funded by the Horizon Europe programme, applying artificial intelligence to complex environmental challenges and climate resilience goals.

Cloud4Business actively takes part in European research and innovation programmes, bringing its expertise in software development, artificial intelligence and secure on-premise architectures to the service of the green and digital transition.

AQUAI-MED — PRIMA 2025

“AI-powered Nature-Based Solutions for Water Resilience in Mediterranean Landscapes”

Programme: PRIMA (Partnership for Research and Innovation in the Mediterranean Area)
C4B role: development of the on-premise AI platform for the monitoring and assessment of Nature-Based Solutions applied to water resource management
International multi-partner consortium (Italy, Greece, Spain, Cyprus)
Key technologies: artificial intelligence, IoT, edge computing, secure environmental data processing

Related Open Access outputs (2 records co-authored with Ingenium Rise): PREVIO-SICILIA Extended Dataset (DOI 10.5281/zenodo.19284247) and working paper Advanced simulation of climate risk scenarios (DOI 10.5281/zenodo.16895362).

NEURO-NBS — Horizon Europe (in preparation)

“Sovereign AI Infrastructure for Evidence-Based Nature-Based Solutions”

Programme: Horizon Europe — Cluster 6 Biodiversity & Ecosystem Services
Call: HORIZON-CL6-2026-01-BIODIV-04-two-stage
C4B role: development of the sovereign software infrastructure for the integration of Earth Observation data, IoT and predictive AI models for the assessment of NbS at landscape scale
Focus: digital sovereignty, GDPR compliance, on-premise processing of sensitive environmental and financial data

Related Open Access outputs (4 C4B records): software C4B-NbS-Pipeline v0.1.0 (DOI 10.5281/zenodo.19278318), working paper Sovereign Economic Case Builder for NbS (DOI 10.5281/zenodo.19277454), technical report On-Premise AI Architectures (DOI 10.5281/zenodo.19261999), specification Edge-Computing AI Nodes for NbS (DOI 10.5281/zenodo.19262587).

QualiAgro 4.0

QualiAgro 4.0 – “Digital platform for predictive monitoring and quality management in agri-food systems”

Programme: PO FESR Sicilia 2014–2020 – Action 1.1.5
C4B role: design and development of a digital platform aimed at SMEs in the agri-food sector, based on the integration of predictive Artificial Intelligence models, IoT sensors and interactive dashboards to optimise decision-making processes, increase operational efficiency and ensure quality control, supply chain traceability and full regulatory compliance

Related Open Access output (co-authored with Ingenium Rise): working paper Qualiagro 4.0: an open platform for agri-food data (DOI 10.5281/zenodo.16925267).

SmartBlue

SmartBlue – “Digital platform for sustainable water management in urban areas”

Programme: Action 1.1.1 “Promotion of collaborative research and technology transfer” – PR FESR Sicilia 2021/2027
C4B role: development of the SmartBlue platform, which integrates Artificial Intelligence, predictive Digital Twins and IoT sensors to monitor water systems, anticipate anomalies and support timely decisions. The project helps tackle drought, flooding and water emergencies, promoting urban resilience, sustainability and European digital sovereignty

i-Mosys

i-Mosys – “Intelligent System Transfer Learning Modeler”

Programme: Research, development and innovation projects geared to the development of Artificial Intelligence, Blockchain and Internet of Things technologies and applications
C4B role: development of the platform for an Artificial Intelligence project that aims to make the creation and use of customised neural network models accessible to SMEs and non-specialist users too, significantly reducing the cost and complexity of adoption
Key technologies: Artificial Intelligence, Machine Learning