Ermis Project
ERMIS_Project
ERMIS – AdvancemEnts in 3D IndooR Positioning Methods and ApplicatIons for Next-Gen Communication Systems
ERMIS is a 24-month research initiative aiming to push the boundaries of 3D indoor positioning using state-of-the-art wireless technologies and AI-driven methods. The project integrates Machine Learning, Reconfigurable Intelligent Surfaces (RIS), mmWave radar sensing, and IEEE 802.11az-based Fine Time Measurement (FTM) to achieve sub-meter positioning accuracy in complex environments.
The project develops and validates techniques in lab settings and demonstrates their applicability to use cases such as jamming attack localization, beam management, and emergency response localization. A key output is an open-source Positioning Toolbox and curated open datasets for the research community.
✅ Project Summary
Project ID: EXCELLENCE/0524/0218
Duration: 1st May 2025 – 30th April 2027 (24 months)
Funding Received: €249,930.33
- INSPIRE: €171,770.67
- CYENS: €78,159.67
Funded by: Research and Innovation Foundation (RIF), Cyprus
Programme: RESTART 2016–2020 (co-funded by the EU under THALIA 2021–2027)
Coordinator: Dr Marios Raspopoulos
Dissemination & IPR Manager: Dr Iacovos Ioannou
🎯 Objectives
Scientific Objectives
- SO1: Design and evaluate ML-, RIS-, mmWave-, and FTM-based 3D positioning techniques with decimeter-level accuracy.
- SO2: Demonstrate positioning-enhanced use cases:
- IoT jammer localization
- RIS-aided beamforming
- Auto-calibration for first responders
Technological Objectives
- TO1: Validate techniques through simulations and lab testing
- TO2: Release open datasets and a reusable Positioning Toolbox on GitHub
🔧 Work Packages
| WP | Title | Lead | Duration | Description |
|---|---|---|---|---|
| WP1 | Project Management | INSPIRE | M1–M24 | Coordination, reporting, risk mitigation |
| WP2 | Dissemination and Exploitation | CYENS | M1–M24 | Outreach, IPR, open science, community engagement |
| WP3 | System Engineering | INSPIRE | M1–M24 | Technical concept, KPIs, performance analysis, open tools |
| WP4 | Novel 3D Positioning Methods | INSPIRE | M2–M24 | ML/RIS, mmWave, FTM-based 3D positioning methods |
| WP5 | Position-Based Applications and Processes | CYENS | M2–M24 | Use cases: IoT, RIS beamforming, emergency localization |
📦 Deliverables (Key Outputs)
D3.4: Open Dataset & Toolbox (M24)D3.3: Critical Evaluation Report (M24)D4.2: Final Report on Novel 3D Positioning Methods (M23)D5.2: Final Report on Position-Based Applications (M23)D2.3: Dissemination, Communication & Exploitation Report (M24)
📺 Project Videos
Video Title
📚 Publications
Journal Papers
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I. Ioannou, V. Vassiliou, and M. Raspopoulos, “Adaptive Multi-Stage Hybrid Localization for RIS-Aided 6G Indoor Positioning Systems: Combining Fingerprinting and Geometric Methods with Condition-Aware Fusion,” Sensors, vol. 26, no. 4, p. 1084, Feb. 2026. DOI: 10.3390/s26041084
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I. Ioannou, V. Vassiliou, C. Christophorou, A. Gregoriades, M. Raspopoulos, P. Nagaradjane, and V. Vassiliou, “Access Point Selection and Localization for Cluster-Based Realization of a Device-to-Device Cell-Free 6G Communications Network,” IET Communications, Oct. 2025. DOI: 10.1049/cmu2.70096
Conference Papers
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M. Raspopoulos, A. Sesyuk, and I. Ioannou, “3D millimeter-Wave Multi-Target Sensing,” in Proc. 2025 International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp. 1–6, 2025, IEEE.
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I. Ioannou, P. Nagaradjane, M. Raspopoulos, V. Papadopoulou-Lesta, C. Christophorou, A. Khalifeh, and V. Vassiliou, “Topology-Aware Deep Reinforcement Learning for RIS Beamforming: A GNN-PPO and Risk-Sensitive Evaluation,” in Proc. 2025 Asian Conference on Communication and Networks (ASIANComNet), 2025, IEEE.
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M. Raspopoulos, I. Ioannou, and L. Nisiotis, “mmWave-Based Crowd Sensing for Metaverse Applications,” in Proc. 2025 IEEE International Symposium on Emerging Metaverse (ISEMV), pp. 46–54, 2025, IEEE.
🌐 Consortium
- INSPIRE (Coordinator) – Expertise in radio propagation, mmWave, indoor localization
- CYENS Centre of Excellence – Expertise in IoT, security, ML, RIS, jamming detection
🔓 Open Science & IPR
- All final datasets and source code will be available via:
- 🔗 [GitHub Repository – Coming Soon]
- 🌍 [Project Website – Coming Soon]
- IPR managed through the Central Knowledge Transfer Office (CKTO) in line with RIF regulations.
📣 Contact
For more information, please contact the coordinator:
Dr. Marios Raspopoulos
InSPIRE Research Centre
📧 mraspopoulos@inspirecenter.org
🌐 http://inspirecenter.org/