RailView

Guiding the Future of Rail Maintenance

What is RailView?

Step into the world of RailView, where Remote Condition Monitoring reaches new heights. Developed by our in-house experts, this cutting-edge package offers a comprehensive framework that effortlessly manages the entire analytics and RCM workflow. From gathering on-field data, parsing information, to delivering insightful trends to your frontline maintainers – RailView has it covered

Comprehensive Analytics Portal

RailView's powerful engine brings context driven datasets to the end users allowing for quick, reliable and effective data dives. RailViewWeb is designed for users ranging from data scientists all the way to front line maintainers

RailView and RailViewWeb has been proven in the field over numerous years having successfully predicted and prevented countless real-world failures, provided critical data for maintenance schedules, and ensuring client system up-time and high service levels

Bespoke API Suite

RailView makes ingesting data easy. Utilising our suite of API's developed to interface with new systems, old legacy devices, IoT sensors and anything in-between

Written speficically for Rail applications, our comprehensive API suite is easily extenedable allowing for seamless integration, adaptability, authentication / security and remote device control

RailView Parsing Engine

The RailView parsing engine is a core element to the system. These modules combined take the ingested data (via API, Raw log and others) and interpret these, perform complex analysis and algorithms across the datasets and store this data for use by the end users whilst also being utilised by the RailView reporting & alarming tiers

The sensor and log data can have intricate connections to other data sources and metrics. The RailView engine is context aware of these intricacies and correlates this for use in its proprietary algorithms and machine learning functions to provide detailed insight and analysis across multiple sources which would not otherwise be possible

RailView Datasets

  • TBTC / CBTC
  • Axle Counters
  • Points
  • Track Circuits
  • UPS
  • Track Temperature / Vibration
  • Point Heaters
  • Control Systems
  • Bespoke IoT device design and deployment service
  • Specialists in integration to any dataset / existing system

Trigger Based Alarming

The alarming tier is directly integrated into RailView's reporting, parsing and analytics models. Utilising the full functionality of our machine learning and suite of proprietary algorithms, RailView is able to generate accurate and comprehensive alarms direct to end users via numerous methods, for example; SMS, Email & CSV file

RailView can be configured to send graded levels of degradation alerts as well as a range of warnings, prioritised alarms (Low, Medium & High), and imminent failure alarms

Customisable Reporting Engine

RailView's proprietary reporting engine allows user defined and configurable reports to be sent to recipients on a trigger, schedule or Ad-Hoc basis

Reports can be generated in PDF or CSV format and sent to users via Email, FTP, API, SMS and direct integration. Our highly configurable engine is integrated into our dynamic and complex data algorithms allowing the alerts tier to warn users of degrading assets, failure hotspots, daily summary reports

Geographical Analysis

RailView correlates geographical datasets with its bespoke algorithms to accurately predict and analyse data sources allowing users to review identified trends, highlight degrading assets, and understand geographically linked issues

Third Party Integrations

RailView can be integrated into any third-party system by utilising our full suite of API's. This enables RailView customers to be able to push and pull data in both directions, provide alarming and asset condition data to be transferred into asset management systems therefore allowing automated scheduling of maintenance & detailed asset reporting

RailView currently integrates into Maximo as part of our TFL analytics deployment. This enables TFL to automatically raise work orders and fault reports within their asset management system allowing them to have all of their asset data in one place

RailView Embedded Framework

RailView offers a flexible built-in datalogger framework that enables clients to easily deploy standard dataloggers with IoT capabilities directly to the RailView APIs

  • Using RailView's proprietary embedded framework (REF), users can download, configure and deploy implementation specific datalogger code directly to the hardware, remotely from RailView’s servers
  • Firmware as a service
  • Caters for most datalogger requirements (Current, Voltage, Serial, Ethernet, USB, Modbus)
  • Allows for rapid time to market
  • Generic (COTS) hardware supporting many protocols
  • Simple installation by the client & configurable data endpoints
  • Maintenance free data loggers
  • Reporting Engine Integration
  • Alerts Tier Integration

Scalable Infrastructure

RailView’s ecosystem is forever growing. AWS industry leading services are utilised to seamlessly handle the rapidly expanding datasets which are being processed and consumed by the RailView system

  • Multiple Data Centre Redundancy
  • Automated differential backups
  • On-Demand hardware scaling
  • Automated hardware scaling based upon utilisation
  • Near immediately available services and hardware provisioning for new implementations
  • Rapid time to market and deployment turnaround

On-Premise Deployment

We understand that it's not always possible to use Cloud Infrastructure. RailView can also be intalled on-premise. We work with our clients and their IT departments to ensure that the correct solution is provided, each and every time

Transport for London

TFL use RailView as their primary analytics and Remote Condition Monitoring platform for all of their signalling assets, also utilising RailView's direct integration into Maximo for their Asset Management

Assets Currently Monitored for TFL

  • CBTC
  • TBTC
  • Point Monitoring
  • Axle Counters
  • UPS Monitoring
  • Piccadilly Control System
  • Track Temperature
  • Point Heaters
  • AZLM

What can RailView do?

  • Reduced Maintenance Costs

    • Predictive maintenance helps identify issues before they lead to major failures, reducing the need for costly emergency repairs
    • Scheduled maintenance based on data-driven insights optimizes resource allocation and reduces unnecessary expenses
  • Improved Safety

    • Reduce the need for trackside maintenance and investigation, keeping workers off the track as much as possible
  • Minimised Downtime

    • Early detection of potential failures allows for proactive maintenance, minimising unplanned downtime
    • Operational disruptions and revenue losses due to unexpected breakdowns are significantly reduced
  • Extended Asset Lifespan

    • By addressing issues before they escalate, RailView helps extend the lifespan of critical rail assets
    • Avoid premature replacements and capital investments, leading to long-term cost savings
  • Optimised Resource Allocation & Costs

    • RailView's analytics and reporting assist in optimizing resource allocation, ensuring that maintenance efforts are focused on areas that need them the most
    • Maintenance teams can work more efficiently, focusing on preventive measures and higher-value tasks
  • Improved Inventory Management

    • With RailView's insights, you can better manage spare parts and inventory levels
    • Avoid overstocking or shortages, leading to cost savings in procurement and storage
  • Data-Driven Decision-Making

    • Informed decisions based on real-time data reduce the likelihood of costly errors
    • Prioritize investments and allocate resources strategically, minimizing waste
  • Reduced Regulatory Non-Compliance Risks

    • By maintaining assets in optimal condition, RailView helps ensure compliance with industry regulations and safety standards
    • Avoid fines, penalties, and reputational damage associated with non-compliance
  • High Return on Investment (ROI)

    • Cost savings achieved through reduced maintenance costs, improved uptime, and optimized operations