Internet of Things: Advance Learning in Networked Training

Project Information

IoTalentum

Grant agreement ID: 953442

DOI

10.3030/953442

Project closed

EC signature date 31 August 2020

Start date 1 October 2020

End date 30 June 2025

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 3 883 831,96

EU contribution

€ 3 883 831,96

Coordinated by

UNIVERSIDAD DE VALLADOLID
Spain

Periodic Reporting for period 2 - IoTalentum (Internet of Things: Advance Learning in Networked Training)

Reporting period: 2022-10-01 to 2025-06-30

Summary of the context and overall objectives of the project

IoTalentum is a Horizon 2020 Marie Skłodowska-Curie European Training Network focused on the Internet of Things (IoT). Its primary objective is to deliver interdisciplinary research and training in key IoT areas: infrastructure, cybersecurity, and applications. To this end, it established a balanced and innovative network of nine beneficiaries—six leading European universities and three prominent companies from five EU Member States—with complementary and internationally recognized expertise.

The project has trained 15 Early-Stage Researchers (ESRs) through an outstanding and integrative training programme, combining cutting-edge research with high-impact training modules. This comprehensive initiative has equipped ESRs with both advanced technical knowledge and transferable skills, supporting careers in academia and industry. The programme included hands-on research, secondments in non-academic sectors, and an extensive array of courses and workshops on both scientific topics and soft skills. The academic–industrial composition of the consortium was key to achieving this holistic training approach.

The global research objective of IoTalentum is to develop the next generation of IoT by achieving coordinated advances in infrastructure and cybersecurity, and to apply these developments to a wide range of next-generation IoT applications—particularly in the field of smart grids.

The IoTalentum project is of great importance to society, as it has addressed critical challenges related to IoT. By developing intelligent and adaptive network infrastructures, the project has contributed to the creation of more efficient environments for IoT-based services. Its strong emphasis on security ensures the protection of sensitive data and systems in an increasingly connected world, while its application to smart grids promotes sustainable energy management. Furthermore, by training a new generation of skilled researchers through a multidisciplinary, industry-integrated approach, IoTalentum has helped build a workforce capable of driving innovation for the benefit of society.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The research objectives of IoTalentum are being realized through its three technical work packages (WP1–WP3), each aligned with a strategic pillar of next-generation IoT development.

Work Package 1 (WP1) focused on developing the foundational infrastructure for next-generation IoT systems, emphasizing scalability, intelligence, and resilience. Research activities advanced key technologies such as Multi-Access Edge Computing (MEC), Software-Defined Networking (SDN), and Network Function Virtualization (NFV), enabling efficient resource orchestration and dynamic service provisioning. AI techniques, including Machine Learning and Quantum Machine Learning, were applied to optimize traffic management and resource allocation. Efforts also addressed optical backhaul planning, network survivability, and privacy-preserving data handling. The integration of Quantum Key Distribution (QKD) reinforced infrastructure security, aligning WP1 with broader cybersecurity goals.

WP2 focused on developing trusted communication mechanisms for IoT by integrating hardware-based security, quantum-secured networking, and blockchain technologies. Research addressed key cybersecurity challenges, including post-quantum resilience through QKD and Post-Quantum Cryptography (PQC), lightweight authentication using Physical Unclonable Functions (PUFs), and privacy protection in virtualized environments. Blockchain-based solutions were optimized for scalability and efficiency, incorporating novel consensus mechanisms and AI-driven anomaly detection to enhance trust and resilience across distributed IoT systems.

WP3 advanced smart grid development within the IoT ecosystem by leveraging distributed data center architectures and integrating strong cybersecurity measures. Research addressed energy management in smart homes, collaborative energy usage, and automated systems for consumption tracking and billing. Novel aggregation models and business strategies were proposed to enhance cooperation among consumers and buildings, enabling active participation in Demand Response programs. These efforts support secure, efficient, and intelligent energy infrastructures.

In addition, three work packages were considered transversal to the entire project:

WP4 focused on training. The ESRs received high-level instruction in the IoT field through a unique program comprising 33 courses that integrated both scientific and complementary soft skills. The project also facilitated extensive secondments, offering ESRs exposure to industrial, academic, and research center environments. This comprehensive approach enabled high-impact research and supported the achievement of the project’s objectives.

WP5 addressed communication, dissemination, exploitation, and data management, enhancing IoTalentum’s visibility and impact across academia, industry, and society. Participation in over 40 academic and professional events supported outreach and collaboration. ESRs achieved an average of 2.1 journal publications and 5.3 conference papers, with three receiving Best Student Paper or Honourable Mention Awards, underscoring the project’s scientific excellence.

Finally, WP6 was devoted to project coordination.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The Early-Stage Researchers (ESRs) in the infrastructure domain significantly advanced the foundational technologies for next-generation IoT systems. Their work integrated Multi-access Edge Computing (MEC), a 5G-based network, and an optical backhaul-to-backbone architecture. Within Work Package 1 (WP1), the ESRs proposed novel techniques for the intelligent management and control of the IoTalentum infrastructure, employing advanced methods such as Software-Defined Networking (SDN), Network Function Virtualization (NFV), network slicing, survivability strategies, and Artificial Intelligence tools—including Machine Learning (ML), Quantum Machine Learning (QML), and Quantum Key Distribution (QKD). These contributions laid the groundwork for a scalable, resilient, and intelligent IoT infrastructure.

In cybersecurity (WP2), ESRs tackled key challenges by exploring hardware-level security, particularly through Physical Unclonable Functions (PUFs), and deploying subcarrier wave quantum cryptography for secure data transmission. They also developed a hardware-free identification tool to enhance inter-data center security. Their work optimized blockchain consensus mechanisms by balancing cost and complexity, leveraging IoTalentum’s distributed architecture. These advancements contribute meaningfully to the evolution of post-quantum and distributed security frameworks.

For WP3 (Applications: Smart Grids), ESRs applied the IoTalentum infrastructure to design advanced smart grid systems. Their research enabled secure energy management in smart homes, orchestration of energy in connected neighborhoods, and novel aggregation models for grid optimization. They also proposed collaborative consumer-building energy strategies and business models to support active demand-response participation, aligning technological development with societal energy needs.

IoTalentum ESRs

IoTalentum consortium