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| Funder | European Commission |
|---|---|
| Recipient Organization | Aston University |
| Country | United Kingdom |
| Start Date | Feb 01, 2025 |
| End Date | Jul 31, 2028 |
| Duration | 1,276 days |
| Number of Grantees | 14 |
| Roles | Participant; Associated Partner; Coordinator |
| Data Source | European Commission |
| Grant ID | 101189595 |
The 5+ Bn km of currently installed data communications optical fibre cable provides an opportunity to create a globe-spanning network of fibre sensors, without laying any new fibres.
These traverse the seas and oceans, where conventional sensors are practically non-extent, and major infrastructures, offering potential for smart structural health monitoring.ECSTATIC will develop novel interferometry and polarisation-based sensing approaches for vibration and acoustic fibre-optic sensing technologies.
New possibilities will be defined for sensitivity, distance range and localization, offering a range of solutions for different use cases, while ensuring the coexistence of the sensing signal with live data traffic.A new compact photonic chip-based dual-microcomb engine will enable enhanced range, resolution, and bandwidth of distributed acoustic sensing together with fundamental new knowledge on the physics of physical stimuli in relation to state-of-polarisation sensing.
Simultaneous interrogation of multiple transmitted comb lines in the microwave domain with multi-wavelength interferometry and novel state-of-polarisation millisecond field programmable gate array-based transceivers will be developed and characterised to improve the sensitivity, spatial resolution, and dynamic range of distributed fiber sensors.To address the limited data storage and processing capabilities of communication networks new digital signal processing algorithms based on edge devices and artificial intelligence/machine learning will be developed and used to extract information via data-compression techniques.
Solutions will aim to minimise algorithm complexity while realising real-time sensing of events and network condition with high classification accuracy.These technologies and algorithms will be tested in real-world submarine, metropolitan and infrastructure networks to validate their potential for early warning of seismic events, predictive maintenance, and network integrity.
Universitat Jaume I de Castellon; Telecom Italia Sparkle Spa; Panepistimio Dytikis Attikis; Modus Research and Innovation Limited; Network Rail Infrastructure Limited; Coriant R&D Gmbh; Universita Degli Studi Di Padova; Organismos Tilepikoinonion Tis Ellados Ote Ae; Universita Degli Studi Dell'Aquila; Universidad de Alcala; Enlightra Sarl; Ethniko Asteroskopeio Athinon; Aston University; Chalmers Tekniska Hogskola Ab
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