10038989FEIDS - FOAS Enabled Intruder Detection SystemClosedCollaborative R&DInnovate UKIntruders 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.