Increasing Europe’s competitiveness in cloud-edge Internet of Things platform solutions with Large Scale Pilots

Increasing Europe’s competitiveness in cloud-edge Internet of Things platform solutions with Large Scale Pilots

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​Brussels, 15 April 2025 – Edge computing as an alternative to centralised cloud services, as underlined in the Draghi report, is emerging as a cornerstone for Europe’s industrial digitalisation. Data localisation at the edge will be key to Europe’s industrial digitalisation. With their strength in industrial and business applications, industrial IoT systems, and 5G, Europe has its one-time opportunity to bring its actors back to playing a significant role in the data economy, thereby improving its strategic autonomy and competitiveness.

Imagine manufacturing enterprises where real-time data analytics predict equipment failures before they occur. As the EU builds highly automated manufacturing plants requiring low latency and significant data volumes steered by AI, edge computing for industrial applications could better enable performance and reduce latency for industrial connected robotics, keeping data transfers more secure.
 
These advancements are materialising through the integration of Cloud, Edge, and Internet of Things (IoT) technologies, as well as the introduction of Artificial Intelligence (AI). The convergence of Cloud, Edge, and IoT (CEI) creates a seamless network where data collected by IoT devices is processed, stored or analysed along the path between the edge and the cloud. Integrating AI into this continuum significantly amplifies its smart capabilities, such as predictive maintenance or personalisation.
 
Building on the foundational efforts of the EUCloudEdgeIoT initiative started in 2022, the EU has recently funded new projects under the Horizon Europe programme, dedicated to increasing innovation and collaboration in the CEI continuum. These pilots on IoT platforms and decentralised (edge) intelligence target breakthrough initiatives to revolutionise the use of edge paradigms and technologies in real-world environments in areas like electromobility, software-defined vehicles, logistics, smart agriculture and agri-food, smart urban environments and multiple electricity grids management. The cross-domain approach of the initiative is fully supporting a joint roadmap for decarbonisation and competitiveness as identified by the Competitiveness Compass.
 
By establishing best practices, the initiative seeks to accelerate the adoption and integration of clean energy technologies, such as electric vehicles (EV) chargers, heat pumps, solar panels, and residential batteries, through open IoT platforms and European CEI solutions. These efforts contribute to strengthening Europe’s competitiveness and strategic autonomy while driving the transition to a sustainable future for key industrial sectors.
 
The development of an open platform and European CEI technologies is instrumental in enhancing Europe’s competitiveness and strategic autonomy in this sector, recognising the global significance of open CEI. To this end, partners of the funded pilots will collectively develop solutions to link energy and European transport, for developing sustainable solutions in logistics, smart buildings, operation of ports and farm2fork systems. These efforts aim to foster consensus on interoperability and standards of distributed IoT-edge solutions bridging traditionally siloed domains. In particular, the EU-funded pilots will test cutting-edge solutions to drive cross-domain standards for flexible energy solutions by orchestrating cross-domain data sharing, minimising energy footprint, and promoting open standards for virtualisation and interoperability.

THE LARGE-SCALE PILOTS

Supported by the Coordination and Support Action CEI-Sphere, two major CEI  Large Scale Pilots (LSPs) have been funded, O-CEI and COP-PILOT.

The O-CEI project brings together 58 partners from 20 countries and aims to develop an open, interoperable, and sustainable platform, addressing key challenges in decentralised CEI networks, such as rising energy consumption, costs and carbon emissions.

Backed by over 20M€ of EU funding, O-CEI aims to imprint innovation in digital technologies across sectors relying on renewable energy sources in alignment with EU Strategies.

The project is implementing eight large-scale pilots across various sectors. These include optimising electricity grids with renewable energy integration, advancing software-defined vehicles, enhancing smart charging for electric postal fleets, and improving energy management in maritime ports. Additionally, the project focuses on sustainable dairy production, increasing efficiency in e-tractor operations for large-scale kiwi crops, deploying private 5G networks to enhance electric vehicle charging, and fostering social acceptance of energy flexibility in urban areas.

“O-CEI is dedicated to shaping an open, secure, and interoperable CEI platform that accelerates innovation and fosters a resilient digital future. By engaging key industries across six strategic verticals, we are laying the groundwork for scalable, energy-efficient solutions that drive sustainability and growth. Our collaboration with CEI-Sphere is instrumental in advancing these goals, with our first steps already taken through the jointly organised ‘Workshop on Digital ID Management and Data Governance.’ We look forward to further strengthening our partnership to drive the evolution of Europe’s Cloud-Edge-IoT ecosystems.”
Prof. Carlos Palau, O-CEI Coordinator

On the other hand, COP-PILOT and its consortium of 45 partners will create a Collaborative Open Platform (COP) that is standards-aligned and market-oriented, enabling end-to-end orchestration across service domains.

Activities are organised into four piloting clusters related to emerging vertical sectors, such as Industry (mining, manufacturing, recycling), Smart buildings/Smart city, Agriculture, and Energy Management, with cross-sector scenarios focusing on mobility and logistics. Each piloting cluster is composed of several piloting use cases that capture key sector processes as well as the interactions across sectors. This structure is designed to showcase enhanced industrial cooperation, cross-sector applications, supply chain interactions, and the practical use of the platform framework across all clusters. COP-PILOT plans to develop an architectural framework that will facilitate the different needs of these pilots.

At each site, COP-PILOT services will manage data flows to applications and repositories while software components will enable configuration and resource orchestration across different infrastructures. Finally, COP-PILOT platform services will provide end-to-end service orchestration across geo-distributed domains.

“As we step into a new era of industrial innovation powered by AI, automation, and seamless connectivity, COP-PILOT is committed to fostering a collaborative platform that drives interoperability and transformative impact service domains. We highly appreciate CEI-Sphere’s collaboration and guidance in aligning our efforts with broader goals. Their expertise in standardisation, interoperability, and certification will be instrumental in ensuring that COP-PILOT achieves its vision of a cohesive, standards-aligned computing environment that evolves with market demands.”
Ioanna Drigkopoulou, COP-PILOT Coordinator

Project representatives at the workshop ‘Advancing Cross-Domain Standardisation for IoT and Edge and Edge Computing’, held in Brussels

Project representatives at the workshop ‘Advancing Cross-Domain Standardisation for IoT and Edge and Edge Computing’, held in Brussels

CEI-Sphere works with the LSPs and European industry players to translate use cases into business models, promoting replicability and scalability of the developed solutions.

“The investment in the CEI LSPs presents a massive market opportunity. The future competitiveness of European industry and the mass adoption of AI-driven solutions that are responsible for decarbonising our energy through flexibility and transforming our manufacturing models rely on a strong, secure and diverse digital CEI ecosystem. This can only be achieved by delivering market value and making an unavoidable investment case for companies to build on the EU CEI.” Tanya Suárez, CEI-Sphere Coordinator

CEI-Sphere supports the LSPs by mapping pilots and actors, developing a use-case catalogue, promoting interoperability through a defined Minimum Interoperability Mechanisms (MiMs) approach. It also supports the development of secure and compliant CEI systems.

To maintain market focus, CEI-Sphere will engage networks of industry actors surrounding the LSPs through events like Hackathons and conferences, and through its CEI Tech Backbone Toolkit. To maintain the quality, security, and interoperability of cloud-edge infrastructures throughout Europe and promote the adoption of these diverse and complex systems, CEI-Sphere will work towards a trust label framework.

Pilot 8

Heightened social engagement and acceptability of energy flexibility in urban areas

Summary

Domain
Urban

Partners
Polygones, CLEMAP, HES-SO, Val D’Anniviers

Goal
The aim is to showcase how innovative Smart IoT solutions, already deployed within networks of prosumers, can be integrated into the O-CEI platform to enhance user acceptance and engagement.

Pilot Scenarios

The aim is to develop new Smart Energy Services (SES) based on an enhanced solution.

1

Democratization of energy demand forecasting for e-vehicle charging SES

This scenario focuses on residential buildings from Meyrin, which have local grids and charging stations for electric vehicles (EVs). It enables EV owners and software vendors to optimize vehicle charging through grid insights, integrating unidirectional power flow (V1G) as well as more extended Vehicle-to-X (V2X) for energy network enhancement, with O-CEI monitoring, Smart Contracts, and new business models.

2

Advanced graph data processing and LLM for energy prediction

O-CEI Data Fabric will be employed as an information graph containing energy data and results from previous scenario, and will integrate energy data, user inputs, and AI models to forecast energy consumption and production, using edge computing, LLM models, and serverless functions for efficient data processing and collaboration.

3

Self-adaptive energy and computation continuum in distributed tourism area

Edge equipment in Val D’Anniviers will use O-CEI orchestration, cybersecurity, and Machine Learning Operations for context-aware energy forecasting, improving efficiency in villages and ski stations through decentralized analytics and continuous updates.

In all scenarios, social acceptance by design will be driven by a combination of qualitative surveys, conjoint analysis, and discrete choice experiments (DCE) optimized on edge devices.

Pilot 7

Trustworthy and secure EV charging upon reliable 5G networks

Summary

Domain
Telecom

Partners
GAP, Nova, CERTH, Ares2T

Goal
The goal of this pilot is to leverage a private 5G network and cybersecurity measures to optimize the EV charging ecosystem, improving resource balancing, reducing costs, and enabling data-driven services

Pilot Scenarios

Pilot 7 presents two complementary scenarios focused on 5G-driven EV charging.

1

Edge optimization of power flow to EV needs

This scenario transforms chargers into “intelligent” bidirectional elements, optimizing grid power flow through O-CEI microservices, data management, and 5G’s low-latency, ensuring efficient load balancing and reduced environmental impact.

2

Increasing trustworthiness and security in EV charging data exchange

The O-CEI blueprint will incorporate security measures, data sovereignty, and auditing to ensure trustworthy data flow from sensors and EVs, supporting energy balance decisions with continuous monitoring and response to cyber threats.

Pilot 6

Smart re-charging and efficiency of robot tractors in large fruit production fields

Summary

Domain
Agrifood

Partners
Garaia, Innovalia, Zettrack, Agrimac

Goal
This pilot uses O-CEI’s monitoring, data integration, and decentralized computing to optimize energy management of electric tractors in kiwi farming, reducing emissions, energy use, and addressing travel and battery cost challenges.

Pilot Scenarios

P6 introduces three scenarios aimed at enhancing the energy efficiency of agricultural operations of electric tractors.

1

Real-time energy consumption aid for agricultural decision

The O-CEI platform will provide farmers with energy optimization suggestions, managing fleet, climate, and location data. It will propose action plans for efficient area coverage and extended charging downtime, using real-time services.

2

Remote route optimization and task planning of robot tractors

The O-CEI AI-block will optimize agricultural tasks in kiwi plantations, using state-of-the-art models for efficient operations and route planning, with real-time data storage and semi-autonomic management.

3

Autonomous tractor re-charging strategy

The tractors in this pilot will optimize battery charging through edge analytics and AI predictions, either autonomously or via a farmer-controlled app, minimizing battery use, extending lifespan, and reducing costs for improved sustainability.

Pilot 5

Energetically and environmentally sustainable Halloumi cheese production

Summary

Domain
Agrifood

Partners
Green Supply Chain, Embio Diagnostics, Charalambides Christis

Goal
The pilot uses O-CEI technologies for IoT-based monitoring and energy optimization, aiming to reduce the energy footprint per kilogram of dairy product in Cyprus, promoting sustainable farming despite challenging climates.

Pilot Scenarios

Livestock farming and the dairy industry are vital to Cyprus’s economy but face significant challenges from rising energy costs and the unstable agro-environmental conditions affected by climate change.

1

IoT-Assisted Livestock Management based on Edge Intelligence and automation

The pilot optimizes energy use in stables while reducing animal heat stress, using IoT sensors and cameras for behavior classification, edge computing for HVAC control, and forecasting for efficient milk production.

2

Controlled sharing of data from various stables to the dairy production factory

O-CEI mechanisms and marketplace will securely share trusted stable data on milk quality, feed mix, and energy footprint, using AI to forecast parameters, optimize energy consumption, and improve production practices with secure data management.

3

Intelligent selection of energy mix for dairy production

This scenario optimizes cheese production’s energy sources (grid, solar, biofuel) based on demand, availability, and price, using O-CEI models and Decision Support System (DSS) to reduce costs, environmental impact, and optimize operations.

4

Calculation of energy footprint of dairy (halloumi) products

This scenario aggregates energy consumption data across the production chain, using O-CEI orchestration and IoT-edge-cloud elements to optimize energy use, enhance trustworthiness, and audit halloumi production’s sustainability.

Pilot 4

Variable demand in challenging maritime terminal landscape

Summary

Domain
Logistics

Partners
CMA CGM, Prodevelop, Awake.ai, Enemalta, Schneider

Goal
This pilot aims to optimize energy usage in Malta’s port operations by aligning demand with capacity, using edge-optimized control systems for real-time adjustments based on vessel schedules, container handling equipment (CHE) usage, and the island grid data.

Pilot Scenarios

The Malta pilot focuses on three interconnected scenarios that leverage O-CEI technologies for monitoring, prioritization, and AI-driven predictions. These scenarios demonstrate how O-CEI technologies can handle simultaneously energy management across vessels, port terminals, and residential settings to achieve a sustainable and efficient energy ecosystem.

1

Vessel Energy Management

The O-CEI platform will integrate energy flows from berthed vessels, using decentralized monitoring, IoT, and cybersecurity utilities to minimize blackouts and optimize energy control through orchestration and real-time dashboards.

2

Terminal Energy Management

This scenario integrates terminal asset energy data with O-CEI orchestration, coordinating peak power demands from Container Handling Equipment (CHE), and reefers to avoid unnecessary peaks, with individual control systems.

3

Home Consumers

This scenario replaces home electricity meters with an O-CEI orchestrated control system, managing device priorities for critical services and appliances through secure data governance and pub/sub-models of the project.

Pilot 3

Energy consumption and emission reductions in postal service fleet operation via intelligent BEV charging strategies

Summary

Domain
Mobility

Partners
Austrian Postal Service, Energie Steiermark, AVL

Goal
This pilot optimizes electric fleet operations by integrating intelligent charging, V2G, and renewable energy utilization, reducing emissions, energy consumption, costs, and enhancing grid stability.

Pilot Scenarios

The Austrian Postal Service (POST) operates 5000 electric trucks that connect to EV charging stations owned by POST or Energie Steiermark. Both the vehicles and charging stations can share data through O-CEI software services, helping to speed up the adoption of smart, sustainable energy and mobility strategies.

P3 introduces three innovative use cases designed to optimize energy consumption, enhance grid stability, and reduce emissions through the integration of O-CEI technologies. These use cases highlight how advanced energy strategies and O-CEI technologies can transform electric fleet operations and grid management, driving sustainability and efficiency.

1

Infrastructure analysis to optimize Storage Battery Systems

For this use case, we analyse the power infrastructure (PV panels, batteries, charging infrastructure), the control and communication infrastructure, and the various communication protocols. This knowledge will then be used to optimize the location and operation of stationary storage battery systems.

2

Vehicle-to-Grid (V2G) – Vehicles as Mobile Energy Storage Units

Building on the first scenario, this use case optimizes EVs as mobile storage units, utilizing O-CEI for intelligent charging, discharging, and fleet route planning, enhancing fleet resilience and battery autonomy. Among others, we will assess the economic balance of the state of health degradation of the EV battery vs. revenue generation by providing energy to the grid at market price.

3

Smart and Innovative Energy Management Systems

O-CEI will evaluate mobile storage systems, such as trucks, supporting grid peak shaving and reactive power management. A virtual power plant integrates energy delivery, billing, and regulatory data for interventions.

Pilot 2

Electricity Grid - Software Defined Vehicle for VaS in Urban Areas

Summary

Domain
Electricity Grid

Partners
Continental, FENIX2.0, ERTICO

Goal
P2 scales Continental’s innovations by integrating a Software Defined Vehicle (SDV), transforming it into an active hub for computation, data exchange, and context-aware connectivity.

Pilot Scenarios

P2 introduces four SDV scenarios, each focusing on Vehicle-as-a-Service (VaS) to address key areas of urban mobility through O-CEI-enabled technologies. These scenarios demonstrate the transformative role of SDVs as active infrastructure elements, revolutionizing safety, sustainability, energy integration, and grid optimization in urban mobility.

1

VaS for Vehicle Safety

This scenario enhances vehicle safety with AI-driven system monitoring, OTA updates, advanced cybersecurity, and real-time technologies for the reliable, secure, and dynamic operation of embedded systems (e.g., engine management, braking, steering, infotainment)

2

VaS for Sustainability

This scenario leverages AI utilities from the O-CEI marketplace to optimize EV powertrain efficiency, minimize carbon footprints, and ensure driver engagement with sustainable, real-time feedback and seamless integration.

3

VaS for Fleet V2G Integration

It uses AI to optimize EV charging and energy return via Vehicle-to-Grid (V2G) capabilities, with edge and cloud software supporting fleet-wide data analysis and operations.

4

VaS for Grid Optimization

This scenario uses V2G, smart grids, and AI to optimize energy use, schedule charging during off-peak hours, utilize dynamic pricing, and grid balancing for sustainable vehicle interactions.

Pilot 1

Electric Grid performance optimization upon RES integration

Summary

Domain
Energy grid

Partners
UCC, EDF, MDU, Powerledger, Smart MPower, Eko Kvarner

Goal
The pilot aims to transition towards a greener, more efficient, and resilient energy system, paving the way for a sustainable and robust energy future.

Pilot Scenarios

1

Community-Driven Renewable Energy Integration

The O-CEI project empowers prosumers/flexumers to trade energy, optimize usage, and store excess via AI-driven tools, boosting grid stability and renewable energy use.

2

Smart Thermal Load Management

Sensor data and smart controls dynamically manage heating for energy efficiency using edge computing.

3

Wide Smart Grid Optimization

Seasonal demand patterns are optimized with renewable integration and decentralized learning models.

4

EV and Heat Pump Synchronization

Synchronizing renewable energy for household appliances and EVs ensures comfort and charging availability.

5

Residential Energy Management

IoT gateways and secure O-CEI utilities empower users to monitor energy use and promote grid flexibility.

6

Advanced Load Scheduling

Proactive scheduling for appliances like electric water heaters and space heaters, will enhance grid capacity and user comfort using edge computing and robust connectivity.

Each of these scenarios highlights the role of O-CEI in creating innovative, sustainable, and resilient energy solutions tailored to specific community needs and environments.