Periodic Reporting for period 1 - ELIXIRION (rEaLIzing healthcare 4.0 eXploIting the 6G netwoRk evolutION)
Reporting period: 2023-11-01 to 2025-10-31
ELIXIRION will create the first fully-integrated, inter- and multi-disciplinary, highly-innovative training and research network that will set the foundations of the emerging H4.0 paradigm by leveraging, developing, and advancing 6G technologies targeting to:
i) provide all citizens/patients with a wide range of services of different requirements, such as low latency for latency-critical applications, high speed for data hungry services and ubiquitous secure access to healthcare resources, anytime, anywhere, respecting all privacy aspects, and
ii) ensure a secure, effective, and democratized healthcare ecosystem to all involved stakeholders, while creating a sustainable open H4.0 market facilitating access to innovators. The motivation behind the Elixirion project is rooted in the potential of merging healthcare and 6G technologies. Recognizing the rapid advancements in
communication networks, our goal is to harness these cutting-edge technologies for the improvement of healthcare systems.
This vision will be realized through three core objectives:
1. Leverage a range of 6G technologies towards a powerful interconnected network for ubiquitous ultra-high performance access to the H4.0 ecosystem targeting at up to 99.99999% reliability, 100% coverage, up to 1 Tbps capacity, ~2x higher energy efficiency and ~55% Total Cost of Ownership (TCO) reduction compared to current networks.
2. Design edge-aware platforms leveraging diverse computing capabilities of the network offering down to sub-ms task execution through parallelization, serverless and distributed computing by intra- and inter-edge node AI-enabled orchestration techniques offering 99.99999% service continuity for real-time H4.0 applications. Leverage
robust AI/Machine Learning (ML) techniques combined with MEC capabilities to perform data analytics, and allow fast algorithm execution and decision making, while ensuring General Data Protection Regulation (GDPR) compliance and trusted role-based data sharing among the involved entities.
3. Create a unified, sustainable, democratized and ubiquitous (always-on) H4.0 ecosystem promoting the secure collaboration of the involved stakeholders (e.g. network operators, infrastructure, MEC and cloud providers, healthcare facilities (e.g. hospitals) and healthcare technology providers (e.g. SW and IoMT solutions)) through
blockchain-based incentive engineering, while devising new business models and easing access to new players. Ensure secure and efficient information handling for a massive number of connections, supported by fully-automated E2E slicing and zero-touch orchestration optimizing network performance. Perform XAI-enabled big data
analytics across the network, resulting in transparent and interpretable outputs that facilitate decision-making in the H4.0 ecosystem (e.g. XAI analytics on glucose monitoring data from wearables could reliably predict hypoglycemic events and anticipate hospital service overloads, while making the results interpretable).
The above objectives are divided into 10 research challenges to be addressed by the 10 DCs hired by the consortium members. All DCs will be recruited by the consortium for 36 months and they will be enrolled in PhD programs. Moreover, they will receive training through:
Research and their successful accomplishment of their individual projects.
Network wide training activities, i.e. related to their work schools and courses in transferable skills.
Secondment, i.e. they will perform two 3-month secondments: one inter-sectoral (academia-industry) and one interdisciplinary (to a healthcare partner) secondment.
Industrial Dissemination Days, i.e. The DCs will get feedback from industry experts.
Interaction with structured research teams either in the academic or the industrial environment.
Participation to international conferences/workshops.
i) provide all citizens/patients with a wide range of services of different requirements, such as low latency for latency-critical applications, high speed for data hungry services and ubiquitous secure access to healthcare resources, anytime, anywhere, respecting all privacy aspects, and
ii) ensure a secure, effective, and democratized healthcare ecosystem to all involved stakeholders, while creating a sustainable open H4.0 market facilitating access to innovators. The motivation behind the Elixirion project is rooted in the potential of merging healthcare and 6G technologies. Recognizing the rapid advancements in
communication networks, our goal is to harness these cutting-edge technologies for the improvement of healthcare systems.
This vision will be realized through three core objectives:
1. Leverage a range of 6G technologies towards a powerful interconnected network for ubiquitous ultra-high performance access to the H4.0 ecosystem targeting at up to 99.99999% reliability, 100% coverage, up to 1 Tbps capacity, ~2x higher energy efficiency and ~55% Total Cost of Ownership (TCO) reduction compared to current networks.
2. Design edge-aware platforms leveraging diverse computing capabilities of the network offering down to sub-ms task execution through parallelization, serverless and distributed computing by intra- and inter-edge node AI-enabled orchestration techniques offering 99.99999% service continuity for real-time H4.0 applications. Leverage
robust AI/Machine Learning (ML) techniques combined with MEC capabilities to perform data analytics, and allow fast algorithm execution and decision making, while ensuring General Data Protection Regulation (GDPR) compliance and trusted role-based data sharing among the involved entities.
3. Create a unified, sustainable, democratized and ubiquitous (always-on) H4.0 ecosystem promoting the secure collaboration of the involved stakeholders (e.g. network operators, infrastructure, MEC and cloud providers, healthcare facilities (e.g. hospitals) and healthcare technology providers (e.g. SW and IoMT solutions)) through
blockchain-based incentive engineering, while devising new business models and easing access to new players. Ensure secure and efficient information handling for a massive number of connections, supported by fully-automated E2E slicing and zero-touch orchestration optimizing network performance. Perform XAI-enabled big data
analytics across the network, resulting in transparent and interpretable outputs that facilitate decision-making in the H4.0 ecosystem (e.g. XAI analytics on glucose monitoring data from wearables could reliably predict hypoglycemic events and anticipate hospital service overloads, while making the results interpretable).
The above objectives are divided into 10 research challenges to be addressed by the 10 DCs hired by the consortium members. All DCs will be recruited by the consortium for 36 months and they will be enrolled in PhD programs. Moreover, they will receive training through:
Research and their successful accomplishment of their individual projects.
Network wide training activities, i.e. related to their work schools and courses in transferable skills.
Secondment, i.e. they will perform two 3-month secondments: one inter-sectoral (academia-industry) and one interdisciplinary (to a healthcare partner) secondment.
Industrial Dissemination Days, i.e. The DCs will get feedback from industry experts.
Interaction with structured research teams either in the academic or the industrial environment.
Participation to international conferences/workshops.
ELIXIRION research efforts are organized into the following three areas (one per objective) that reflect the three technical Work Packages (WPs):
Research Area 1:
High reliability and high capacity green 6G infrastructures, where the research effort are focusing on leveraging a gamut of future-proof 6G technologies., i.e. (i) NTNs (Unmanned Aerial Vehicles (UAVs), satellites and High Altitude Platform Stations (HAPS)), (ii) Joint access and X-haul, and (iii) Multi-GHz bands (mmWave, sub-THz, THz), to complement the TN services, e.g. on remote areas or in case of TN failures due to natural disasters, in an energy/cost-efficient fashion, while improving the autonomy of the employed IoMT devices.
Research Area 2:
Fully-distributed compute continuum for low latency healthcare applications, where disruptive new optimization techniques will be devised towards distributed and fully parallelized computing and E2E orchestration, all tailored to the healthcare vertical, and especially targeting at real-time mission critical healthcare applications, such as motion prediction during telesurgery or real-time representation of a healthcare digital twin. To that end, the research effort are focusing on the development of efficient compute (both intra- and inter-edge node) orchestration solutions. The aforementioned framework will enable real-time data analytics execution, e.g. for real-time stroke detection in acute care. Given the importance of secure information handling in the H4.0 ecosystem, trusted data sharing techniques will be also explored in combination with the aforementioned techniques.
Research Area 3:
AI-driven E2E Healthcare service provisioning over 6G, delivering robust AI models and techniques for the energy- and cost-efficient placement of the multitude of healthcare applications and network components towards credible, secure, and fully automated healthcare provisioning with minimum human intervention (zero-touch). AI-enabled service management techniques will be developed leveraging AoI and Value of Information (VoI) for cost-efficient, scalable, and secure massive IoMT. Big data analytics will be also performed leveraging robust and trustworthy, privacy by design enabled XAI models aiming at easing the decision-making process while being characterized by transparency and interpretability for results comprehension. Finally, blockchain-based mechanisms as well as new business models will be developed promoting the incentivized and secure collaboration of the involved H4.0 stakeholders
The ELIXIRION project made significant progress over the first 18 months. The main achievements include:
- Delivered three consolidated SoA review on:
o 6G infrastructures and methodological tools (D1.1)
o The compute continuum and methodological tools (D2.1)
o E2E healthcare-oriented network management and methodological tools (D3.1)
- Training activities during the first 18 months include:
o 1st and 2nd Complementary Courses (organized at Thessaloniki on 1st -4th of Oct. 2024 and evaluated),
o 1st and 2nd Schools (organized at Amsterdam on 18th -22nd of Nov. 2024 and evaluated),
o 5th and 6th Schools (organized at Athens on 17th -21st of Feb. 2025 and evaluated),
o E-learning platform was established hosted at AUTH Server.
Research Area 1:
High reliability and high capacity green 6G infrastructures, where the research effort are focusing on leveraging a gamut of future-proof 6G technologies., i.e. (i) NTNs (Unmanned Aerial Vehicles (UAVs), satellites and High Altitude Platform Stations (HAPS)), (ii) Joint access and X-haul, and (iii) Multi-GHz bands (mmWave, sub-THz, THz), to complement the TN services, e.g. on remote areas or in case of TN failures due to natural disasters, in an energy/cost-efficient fashion, while improving the autonomy of the employed IoMT devices.
Research Area 2:
Fully-distributed compute continuum for low latency healthcare applications, where disruptive new optimization techniques will be devised towards distributed and fully parallelized computing and E2E orchestration, all tailored to the healthcare vertical, and especially targeting at real-time mission critical healthcare applications, such as motion prediction during telesurgery or real-time representation of a healthcare digital twin. To that end, the research effort are focusing on the development of efficient compute (both intra- and inter-edge node) orchestration solutions. The aforementioned framework will enable real-time data analytics execution, e.g. for real-time stroke detection in acute care. Given the importance of secure information handling in the H4.0 ecosystem, trusted data sharing techniques will be also explored in combination with the aforementioned techniques.
Research Area 3:
AI-driven E2E Healthcare service provisioning over 6G, delivering robust AI models and techniques for the energy- and cost-efficient placement of the multitude of healthcare applications and network components towards credible, secure, and fully automated healthcare provisioning with minimum human intervention (zero-touch). AI-enabled service management techniques will be developed leveraging AoI and Value of Information (VoI) for cost-efficient, scalable, and secure massive IoMT. Big data analytics will be also performed leveraging robust and trustworthy, privacy by design enabled XAI models aiming at easing the decision-making process while being characterized by transparency and interpretability for results comprehension. Finally, blockchain-based mechanisms as well as new business models will be developed promoting the incentivized and secure collaboration of the involved H4.0 stakeholders
The ELIXIRION project made significant progress over the first 18 months. The main achievements include:
- Delivered three consolidated SoA review on:
o 6G infrastructures and methodological tools (D1.1)
o The compute continuum and methodological tools (D2.1)
o E2E healthcare-oriented network management and methodological tools (D3.1)
- Training activities during the first 18 months include:
o 1st and 2nd Complementary Courses (organized at Thessaloniki on 1st -4th of Oct. 2024 and evaluated),
o 1st and 2nd Schools (organized at Amsterdam on 18th -22nd of Nov. 2024 and evaluated),
o 5th and 6th Schools (organized at Athens on 17th -21st of Feb. 2025 and evaluated),
o E-learning platform was established hosted at AUTH Server.
Not applicable at this point of the project.