FEIDS – FOAS Enabled Intruder Detection System
This project was one of the winners in the First Of A Kind 2022 competition run by Innovate UK.
In this document, this is said about the project.
Project No: 10038989
Project title: FEIDS – FOAS Enabled Intruder Detection System
Lead organisation: THALES GROUND TRANSPORTATION SYSTEMS LIMITED
Project grant: £223,660
Public description: Intruders in a railway environment and critical sites are a major problem for the rail industry, and
one that can cause severe delays if not prevented. Conventional monitoring technology is low
range, impractical and has a high deployment and operational cost. Instead, a system that can
monitor the perimeter of a large area with minimal human supervision and can be used to direct rail
staff to the correct location is required to introduce work efficiencies.
Thales’ subcontractor Focus Sensors have developed the technologies capable of delivering a
persistent perimeter detection system that can detect persons approaching a site before they reach
the perimeter boundary and alert railway staff to their precise location. This will support railway staff
to respond effectively and reduce delay minutes, insuring efficiency and cost benefits.
We propose to showcase a first-of-a-kind application of Focus Sensors’ next-generation Fibre Optic
Acoustic Sensing (FOAS) technology to deliver accurate and real-time information and alerts on
intruders or potential intruders in a rail environment using our lateral-positioning technology
developed for detection trains. This capability will enable security staff to rapidly respond to
incidents and ensure intruders can be dealt with quickly and efficiently.
The FOAS-Enabled Intrusion Detection System (FEIDS) will use FOAS to detect objects moving
near the fibre/perimeter, identify them and determine the distance from a boundary. This monitoring
is both real-time and persistent, enabling alerts to be sent when a person or vehicle gets too close
to or crosses a boundary. The high fidelity of the system means that an intruder’s location can be
determined to an accuracy of +/- 50cm, and this information is crucial to ensuring that on-site
security teams are able to quickly and efficiently deal with the intruder.
This technology can be utilised both along sections of the railway and at specific, sensitive sites.
Due to the long range and autonomous nature of the system, it drastically reduces the workload of
railway staff. Staff will be provided with an automatic alert that will provide them with information on
the nature of the intruder(s) and the exact location. This reduces the time for intervention, enabling
trains slowed due to the risk to resume at normal speed quicker, lowering the impact of trespass. It
also increases the likelihood of trespassers being stopped committing vandalism, which can disrupt
operations, and reduces the likelihood of reoffending.
My Thoughts And Conclusions
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