Scientific publications
See the scientific impact of our work. Discover the scientific papers supported by COP-PILOT
COP-PILOT as a Pan-European, Open, and Interoperable Platform of Open Standardised Platforms
Abstract
The open-source software and related communities behind COP-PILOT have been systematically developing software and open implementations of standards since 2019, providing solid platforms to several EU projects since then. COP-PILOT is an excellent opportunity for these communities to meet and collaborate under the umbrella of one of the largest high Technology Readiness Level (TRL) projects to date. The scale of COP-PILOT, both by means of number of vertical sectors (Mining, Smart Cities, Agriculture & Logistics, Energy, and Manufacturing) and geographical span across the entire Europe (from the mines of northern Sweden to South European business domains in Greece, Spain, and Portugal) creates a perfect Pan-European environment where these communities could develop integrated solutions for close-to-market deployments and validations through large-scale pilots.
For this reason, this document puts all these communities under a common perspective and attempts to highlight how they jointly contribute to the realisation of a platform-of-platforms to facilitate stakeholders from heterogeneous vertical business domains, but also 3rd parties as COP-PILOT employs two rounds of open calls that will bring many more stakeholders aboard.
Relevance of the Paper to the COP-PILOT Project:
This document aims at presenting COP-PILOT Horizon as an ecosystem of open-source assets that establish a solid foundation with (i) long-living open-source communities in Europe, (ii) global standards that matter for the Cloud Edge IoT (CEI) ecosystem, and (iii) five business sectors across Europe.
Authors
- Georgios P. Katsikas (UBITECH) – ETSI SDG OpenSlice TSC member & HypO MDG Co-leader
- Kostis Trantzas (UOP) – ETSI SDG OpenSlice TSC Leader & BSS MDG Leader
- Christos Tranoris (PNET) – ETSI SDG OpenSlice Chair
- Philip Griffiths (TATA) – OpenZiti Main Contributor, ETSI HypO MDG Contributor
- Konstantinos Fragkos (NETC) – COP-PILOT Platform Integration co-leader
- Panos Mantzakos (NETC) – COP-PILOT Platform Integration co-leader
- Jesus Iglesias Maqueda (TID) – ETSI SDG OpenSlice BSS contributor
- Emilio Garrido (TID) – ETSI SDG OpenSlice BSS contributor
- Benjamin Ertl (AGE) – ETSI SDG OpenSlice BSS contributor
- Luis Ferreira (ONE) – ETSI SDG OpenSlice BSS contributor
- Sergio Figueiredo (IPN) – ETSI SDG OpenSlice BSS contributor
- Spyros Kousouris (SUITE5) – ETSI SDG OpenSlice BSS contributor
- Jerker Desling (LTU) – Eclipse Arrowhead Leader
- Johan Kristiansson (LTU) – ColonyOS Leader
- Theodoros Rokkas (INC) – COP-PILOT exploitation leader
- Christos Tselempis (D4P) – Visual Identity & Design
AI in the evolution of Autonomous Networks
Abstract
Autonomous Networks (AN) are a key enabler of digital transformation in modern communications,
leveraging real-time data, automation, and AI to enhance efficiency, reduce costs, and enable new
services. While AN concepts are not inherently dependent on AI, artificial intelligence significantly
accelerates progress toward higher autonomy levels, particularly AN Level 4 and beyond. This paper
highlights AI-driven innovations such as network digital twins, agent-based architectures, generative
AI, and advanced data models, alongside their architectural and business impacts. It also addresses
critical challenges related to security and privacy, emphasizing the need for robust frameworks and
privacy-preserving techniques. Drawing on ETSI contributions, proof-of-concepts, and industry
collaboration, the paper outlines how AI-powered AN will shape the evolution of 5G, future 6G
systems, and the broader ICT ecosystem.
Relevance of the Paper to the COP-PILOT Project:
The ETSI White Paper “AI in the evolution of Autonomous Networks” highlights SDG OpenSlice (OSL) as a reference implementation for AI-enhanced, intent-driven service orchestration. The paper describes how OpenSlice supports Autonomous Network evolution by exposing standardized catalogues, lifecycle management, and multi-domain orchestration capabilities, which directly align with COP-PILOT’s architectural choices. In COP-PILOT, SDG OpenSlice acts as a core orchestration engine, while the Business Management Portal provides the business-facing entry point for onboarding domains, defining service offerings, and managing pilots. The white paper’s discussion of LLM-based and agentic interfaces on top of OpenSlice offers concrete patterns for how the COP-PILOT portal can capture high-level, business-oriented intents and translate them into deployable configurations. Furthermore, the emphasis on data models, APIs, and AI-assisted operations in OpenSlice provides guidance for the portal’s integration design, enabling closed-loop monitoring, SLA tracking, and policy-based automation. By following these recommendations, COP-PILOT can ensure that its Business Management Portal remains aligned with state-of-the-art AN practices and contributes feedback to the evolution of SDG OpenSlice and related ETSI activities.
Authors
- Raymond Forbes (Forbes Ltd.)
- Luigi Licciardi
- Yoshihiro Nakajima (NTTdocomo)
- Nick Sampson (Orange)
- Faraz Naim (Accenture)
- Benoit Radier (Orange)
- Aldo Artigiani (Huawei)
- Olivier Ferveur (Post Luxemburg)
- Marcus Brunner (Huawei)
- Yuan Xie (Huawei)
- Fernando Camacho (Huawei)
- Yu Zeng (China Telecom)
- Ricard Vilalta (CTTC)
- Massimo Banzi (TIM)
- Christos Tranoris (University of Patras),
- Kostis Trantzas (University of Patras)
- Muslim Elkotob (Vodafone)
- Scott Cadzow (Cadzow Consulting)
- Shahar Steiff (Esthertech)
- Giulio Maggiore (Fibercop)
- Xueli An (Huawei)
- Haitao Xia (Huawei)
- DongJin Lee (SK Telecom)
An Agentic Framework for Intent Co-Creation in 6G NaaS: Architecture and Open-Source Model Evaluation
Abstract
6G network complexity necessitates high levels of autonomy, yet current intent-based systems struggle with ambiguous or incomplete human requests. This paper introduces an agent-based, intent-driven end-to-end (E2E) orchestration framework designed for Network-as-a-Service (NaaS) delivery through collaborative intent co-creation. The proposed system leverages a pool of Domain Expert Agents and a TM Forum-aligned Body-of-Knowledge (BoK) to iteratively refine user requests into deterministic, machine-readable actions. A fundamental design principle is the decoupling of cognition and actuation, where AI-driven reasoning is isolated from standardized execution controllers to ensure safety and operational trust. The framework includes a dual-layer memory system to maintain coherence during multi-step collaborations. The presented prototype, built on ETSI OpenSlice and the Model Context Protocol (MCP), evaluates across several open-source Large Language Models (LLMs). While these models demonstrate high instruction compliance, results reveal a significant gap in translating high-resolution intents into valid, catalog-backed orders without hallucinations.
Relevance of the Paper to the COP-PILOT Project:
The concept of intent refinement can be effectively applied to the COP-PILOT architectural components. In particular, the COP-PILOT Business Portal is designed to capture stakeholders’ intent and translate it into appropriate specifications for the End-to-End Service Orchestrator. This approach is especially valuable in complex scenarios where a single intent must be mapped to multiple specifications.
Authors
Kostis Trantzas, Besiana Agko, Christos Tranoris, Irene Denazi
Towards Agentic Test-Driven Quality Assurance for 6G Networks
Abstract
This work proposes an agentic, intent-driven end-to-end (E2E) orchestration framework that integrates intent co-creation with a Test-Driven Quality Assurance paradigm. In this framework, autonomous agents iteratively refine a user’s initial intent into a confirmed, auditable specification. Furthermore, the system automatically derives validation tests from these intents before provisioning, directly mirroring the Test-Driven Development workflow in software engineering to ensure proactive Service Level Agreement (SLA) compliance. The architecture is grounded in a standards-aligned knowledge representation using TM Forum (TMF) information models and catalogs. This enables deterministic graph traversal from high-level Product Offerings down to granular Service/Resource and Test specifications. We prototyped this architecture by extending OpenSlice with a message-driven, multi-agent pattern and integrating MCP-enabled (Model Context Protocol) tool access for real-time knowledge retrieval. Currently, our evaluation of the agents targets the intent co-creation phase as a baseline toward full-scale orchestration. Building on experiments with multiple open-source Large Language Model (LLM) backends integrated with the TMF-based knowledge base, we observe substantial variability in tool-use reliability and hallucination patterns, underscoring the critical importance of robust knowledge integration in agentic 6G systems.
Relevance of the Paper to the COP-PILOT Project:
The concepts of intent refinement and test-driven quality assurance presented in this paper can be effectively applied to the COP-PILOT architectural components. In particular, the COP-PILOT Business Portal aims to capture stakeholders’ intent and translate it into appropriate specifications for the End-to-End Service Orchestrator. These approaches are especially valuable in complex scenarios where a single intent must be mapped to multiple specifications. Additionally, when supported, test-driven quality assurance can enhance the Domain Orchestration layer by enabling systematic validation of deployed platform services.
Authors
Christos Tranoris, Besiana Agko, Kostis Trantzas, Irene Denazi
Abstract
Relevance of the Paper to the COP-PILOT Project:
Authors
Maria Crespo-Aguado, Lucía Martínez-Palomo, Nuria Molner, Arturo-José Torrealba-Ferrer, Jose-Miguel Higón-Sorribes, Carlos Blasco, Carlos Ravelo and David Gomez-Barquero
From the siloed operation to multi-domain orchestration for resilient V2G Services through cloud-edge collaboration and edge intelligence in EV Fast charging networks: The COP-PILOT Cluster 3E showcase.
Abstract
EV fast charging infrastructure is traditionally deployed and operated as a standalone, siloed asset, with limited visibility into component health and no structured interaction with the surrounding grid. This restricts both operational reliability and the potential for charging stations to contribute to grid flexibility. This work presents the architecture and early results of the COP-PILOT Cluster 3E (CL3E) showcase for Vehicle-to-Grid (V2G) readiness, demonstrated on DC fast charging stations in Patras, Greece. The approach embeds edge intelligence directly at the charging station to enable predictive maintenance and demand forecasting from high-resolution voltage and current measurements, while a cloud orchestration layer connects charging decisions to broader grid objectives through standardized, FIWARE-based communication (MQTT, OPC-UA, HTTPS). A Secure Integration Fabric links this EV domain with the cluster’s other use cases, including biogas plant monitoring, supporting multi-domain orchestration across the pilot. The result is a transition from passive, standalone chargers to grid-interactive nodes capable of local decision-making and collaboration with Distribution System Operators and aggregators on real-time flexibility harvesting. This architecture provides a replicable foundation for scalable, interoperable V2G deployment in support of EU e-mobility and grid resilience objectives.
Relevance of the Paper to the COP-PILOT Project:
This poster presents a concrete instantiation of COP-PILOT’s core objective: secure, intelligent orchestration of services across IoT, edge, and cloud computing environments, applied to the energy and e-mobility domain. It demonstrates Cluster 3E’s UC#3E.2 (EV DC Fast Charger Predictive Maintenance & Demand Forecasting), showing how the project’s edge-to-cloud architecture, Secure Integration Fabric (SIF), and FIWARE-based data management translate into operational value for a real pilot site (PPC Blue/DEI, Patras). It validates COP-PILOT’s cross-domain orchestration model by situating the EV use case alongside the cluster’s biogas and grid flexibility use cases under a common orchestration and data management layer, illustrating how the platform supports multiple verticals through shared architectural patterns rather than bespoke integrations per domain. The poster also speaks directly to COP-PILOT’s interoperability and resilience goals, showing standardized communication protocols (MQTT, OPC-UA, HTTPS) enabling multi-vendor operation, and edge-based intelligence reducing reliance on constant cloud connectivity. Finally, it supports the project’s exploitation and policy ambitions, framing the pilot as a replicable model for grid-aware, interoperable e-mobility infrastructure across the EU, and laying groundwork for future V2G-based business models such as ancillary services offered by fleet or charging operators.
Publication
- November 2025
V2G Leaders Europe 2025, 20 November 2025
Authors
Dimitrios Brodimas, Apostolos Chouliaras, Evangelos Paidas, Rafael Rodrigues, Alex Birbas, Nikos Tzanis
Abstract
The monitoring of oxygen in food packaging during storage and transportation is crucial in food quality surveillance, warning users regarding food spoiling, happening through compound oxidation and aerobic microorganism proliferation. In this overall scenario, we report the development of a
flexible, cost-effective, and Bluetooth-assisted electrochemical sensor for oxygen detection in food packaging. The device encompasses three layers, namely a zinc sheet as an anode, a conductive silver
ink printed on an oriented polypropylene sheet serving as a cathode, and a deep eutectic solvent deposited on a paper-based substrate sandwiched between both electrodes. The sensing tool provided a wide linear range for oxygen detection up to 20.9 O 2 % v/v with good intra-electrode
repeatability (RSD % = 0.02 %). Finally, the developed device was integrated with a 3D printed holder and tested for oxygen detection in packages containing mushrooms, tomatoes, and broccoli samples,
obtaining a good correlation with the reference method. This study opens noticeable possibilities for employing paper-based metal-air batteries in the detection of specific target analytes, by integrating
paper substrate and metal-based batteries delivering smart and self-powered instruments as reliable and accurate analytical tools.
Relevance of the Paper to the COP-PILOT Project:
The study carried out in this paper provides valuable insight into the use of Bluetooth-based and wireless sensing platforms. Specifically, this technology will be utilized in the framework of the COP-PILOT project to develop a Bluetooth-assisted electrochemical sensor for plant health monitoring.
Furthermore, with the investigation performed during this work, we dealt with the agrifood field, and specifically with the monitoring of parameters related to vegetables, laying the groundwork for the development of a wearable electrochemical sensor for monitoring (anti)nutrients in plants. This is strictly related to the COP-PILOT project, following the Use Cases, and to fulfill the Expected Outcomes related to Cluster 3A.
This is an open access article under the CC BY license http://creativecommons.org/
Authors
Achref Chebil, Vincenzo Mazzaracchio, Leonardo Duranti, Ludovica Gullo, Fabiana Arduini
Model Optimization pipeline for hardware-aware trustworthy edge- residing AI: a grid reliability case study
Abstract
This paper presents a hardware-aware optimization pipeline for deploying trustworthy edge AI on resource-constrained devices, demonstrated through an automated fault inspection system for electrical insulators in grid infrastructure. The approach combines flat minima training methods with hardware-specific quantization and a hierarchical inference paradigm, where a calibrated far-edge model handles high-confidence classifications on-device while offloading uncertain samples to a more powerful edge server. Experimental results across multiple embedded platforms demonstrate 98% cooperative accuracy with power consumption as low as 11.5 mJ per inference, supporting reliable real-time operation in safety-critical energy environments.
Relevance of the Paper to the COP-PILOT Project:
The paper addresses automated fault inspection of electrical insulators running on resource-constrained far-edge devices — a challenge that maps directly onto Cluster 3E’s core mission of enhancing energy system resilience and efficiency through edge intelligence deployed across distributed grid infrastructure in Western Greece.
Cluster 3E explicitly targets the transition from reactive to predictive maintenance paradigms across all three use cases (UC#3E.1–3E.3). The paper’s insulator fault detection system embodies precisely this transition: rather than waiting for infrastructure failures, it enables real-time, on-device classification of faults before they escalate.
Authors
Alexandros Machairas, Nikolaos Tzanis, Athanasios Bachoumis
Abstract
In 2023, the World Economic Forum selected wearable plant sensors as one of the Top 10 Emerging Technologies, demonstrating that these smart analytical tools will be relevant in the next generation of agrifood practices. Considering the robustness, accuracy, and miniaturisation of electrochemical (bio)sensing tools, electrochemical-based plant sensors could be suitable devices to address the requirements for their advanced applications in the agrifood sector. This review deals with electrochemical (bio)sensors for monitoring agrochemicals , phytohormones, growth precursors, and stress biomarkers, using wearable and implantable configurations. The design and type of biocomponent and/or nanomaterial(s) used are reported, highlighting the analytical performances obtained on plants. The ongoing application of these analytical tools is discussed, and the future applications combined with Internet of Thing and Artificial Intelligence are envisioned, with the overriding aim to give an overall scenario related to plant electrochemical (bio)sensors for the next technologies in the agrifood sector.
Relevance of the Paper to the COP-PILOT Project:
This review paper focuses on the state-of-the-art in wearable and implantable electrochemical biosensors for monitoring plant health, including agrochemicals, phytohormones, and stress biomarkers. The insights from this research are crucial for one of COP-PILOT’s key objectives in Cluster 3A, which is to develop a wearable electrochemical sensor for monitoring antinutrients in leaves. The study provides essential knowledge for the development of our sensing device, including its implementation and integration with our cluster partners, enabling us to create a reliable and innovative analytical tool for plant health monitoring.
This is an open access article under the CC BY license http://creativecommons.org/
Authors
Narjiss Seddaoui, Fabiana Arduini
Abstract
Relevance of the Paper to the COP-PILOT Project:
This paper is directly relevant to COP-PILOT because ColonyOS constitutes a core technology for the implementation of the computing continuum in Cluster 1. The paper presents the architecture, design principles, and industrial validation of ColonyOS as a meta-operating system capable of orchestrating workloads across heterogeneous edge, cloud, HPC, and on-premises computing environments.
The work contributes to several COP-PILOT objectives related to computing continuum management, including heterogeneous resource integration, automated workload placement, orchestration, resilience, and hybrid execution across distributed infrastructures. The presented architecture provides the foundation for managing applications and services across the edge-to-cloud continuum that is being developed and validated within Cluster 1.
The industrial use cases presented in the paper demonstrate practical deployment and operation of ColonyOS in real-world environments, including real-time seismic monitoring and HPC integration. These experiences provide valuable insights for the implementation and evaluation of COP-PILOT use cases that require scalable, resilient, and interoperable orchestration across multiple computing domains.
Furthermore, the paper discusses support for advanced workload management strategies, including carbon-aware scheduling and hybrid orchestration, which align with COP-PILOT’s goals of developing efficient, sustainable, and intelligent computing continuum solutions. The results therefore contribute directly to the technical foundation and validation of the Cluster 1 testbed and its associated KPIs related to heterogeneous compute infrastructures, automated workload placement, and continuum orchestration.
This paper was awarded the Best Industry Paper Award at the 2025 IEEE International Conference on Cloud Engineering (IC2E).
Authors
Johan Kristiansson; Ulf Bodin; Carl Borngrund; Jerker Delsing; Jesper Martinsson
Relevance of the Paper to the COP-PILOT Project:
The paper focuses on developing an analytical platform that combines sample treatment with an electrochemical biosensor to measure phytic acid in spinach leaves. It strictly aligns with the COP-PILOT project (Cluster 3A), providing insights into creating a sensor to quantify a nutritional marker for assessing crop health and quality (Use Cases #3A). Additionally, the use of a wireless portable system enables integration with IoT technology for real-time environmental and crop health monitoring.
Authors
Ludovica Gullo, Igor Gabriel Silva Oliveira, Achref Chebil, Luca Fiore, Silvia Maria Martelli, Willyam Róger Padilha Barros, Fabiana Arduini
Abstract
Abstract—Cyber-Physical Systems (CPS) powered by Artificial Intelligence (AI) have the potential to revolutionize industries by enabling advanced analytics and autonomous decision-making. To support resource-intensive applications, there is often a need to dynamically allocate additional compute resources. The Edge-Cloud Continuum enables allocation and deployment of workloads across platforms, including IoT devices, edge clusters, and cloud environments. However, the growing computational demands of these systems can unfortunately result in increased energy consumption and higher carbon emissions.
This paper investigates the development of a carbon-aware scheduler for the Edge-Cloud Continuum, designed to optimize workload placement by balancing energy consumption, temporal variations in carbon intensity, and resource availability. Key contributions of the paper include a spatiotemporal scheduling algorithm, a discrete-event simulator capable of replaying realistic workloads from the MIT SuperCloud dataset, and a comprehensive empirical evaluation.
Findings from the paper show substantial reductions in carbon emissions by prioritizing renewable energy sources and time shifting workloads to periods of lower carbon intensity. However, when clusters operate under high utilization, time-shifting can inadvertently result in significantly higher emissions. In such scenarios, simpler greedy algorithms can be more effective.
Relevance of the Paper to the COP-PILOT Project:
This paper directly contributes to the objectives of COP-PILOT Cluster 1 by addressing automated workload placement across the Edge-Cloud Continuum. The work investigates how AI-enabled Cyber-Physical Systems can dynamically allocate workloads between edge, on-premises, and cloud computing resources while minimizing carbon emissions and efficiently utilizing available infrastructure.
The proposed carbon-aware scheduling algorithm is particularly relevant to KPI-VSS-CL1-4.5 (Automated Workload Placement), as it explores mechanisms for selecting execution locations and execution times based on resource availability and environmental impact. The paper provides both a practical scheduling approach and a simulation framework for evaluating placement strategies in heterogeneous computing environments.
The work is also aligned with the Cluster 1 vision of a unified computing continuum based on ColonyOS and Arrowhead. The long-term goal of the research is to integrate the proposed scheduler with these technologies, enabling intelligent and sustainable orchestration of workloads across distributed edge, on-premises, and cloud infrastructures.
By demonstrating how workload orchestration policies can reduce carbon emissions while
maintaining operational requirements, the paper contributes to COP-PILOT’s objectives of developing efficient, scalable, and sustainable computing continuum solutions for industrial Cyber-Physical Systems.
Publication
- 30 July 2025
Authors
Johan Kristiansson, Jerker Delsing, Thomas Ohlson Timoudas
Abstract
Cloud-native computing has transformed modern application development, deployment, and management by enabling scalability and flexibility. However, the increasing complexity of workloads and the dynamic resource demands challenge traditional scheduling and resource provisioning techniques, often leading to inefficiencies. This paper explores AI-driven approaches to optimizing cloud-native scheduling and resource provisioning. By leveraging machine learning, deep reinforcement learning, and predictive analytics, AI enhances decision-making, automates scaling, and improves workload distribution. We present a comprehensive review of recent AI techniques applied to container orchestration and Kubernetes-based scheduling, analysing their impact on cost
reduction, performance optimization, and resource efficiency. Additionally, we discuss key challenges
such as model interpretability, real-time adaptability, and integration with existing cloud and edge infrastructures. Ultimately, this paper provides insights into the future of intelligent cloud and edge resource management, emphasizing the necessity of AI-augmented strategies to meet the growing demands of next-generation applications.
Relevance of the Paper to the COP-PILOT Project:
The paper provides a comprehensive survey of how artificial intelligence (AI) is being integrated into cloud-native systems, highlighting its role in enhancing automation, scalability, and decision-making in complex distributed environments. This paper helps COP-PILOT gain insight into current trends, key challenges, and emerging research directions for applying AI to optimise cloud-native, multi-domain architectures.
Publication
- 23 June 2025
Authors
Tomás Dias, Luís Ferreira, Diogo Fevereiro, Luis Rosa
