Communities around the world continue to rely on trains to transport people and goods, with railways playing a critical role in most regional economies. Getting those goods and people where they need to be, safely, quickly and without disruption, is of paramount concern for railway operators. Their ability to accomplish this goal is limited by one primary factor – risk.
Railways operate in a wide range of geographies (rural and urban), with differing geological and topographical features and distinct weather patterns – all of which can introduce hazards. Depending on the route and its length, conditions can change dramatically over the course of a journey. Predicting, preparing for and mitigating the range of possible hazards and their associated risks is an understandable preoccupation for many railway operators.
Amongst the biggest challenges they face are weather issues, with water events being chief among them. The simple reality is that railway lines are invariably subject to ground hazards, namely erosion and flooding, both of which can negatively impact track conditions and contribute to derailments and other kinds of accidents. Worse yet, instances of these hazards are on the rise, in line with the ever-increasing occurrence of extreme weather events such as hurricanes, typhoons and record-breaking spring snow melts.
Historically, risk management strategies have been built on a reactive approach where responses to risk are determined while the risk is underway, which naturally limits the effectiveness of mitigation efforts. By gathering real-time information on hydrologic conditions, and coupling it with historical data, railway operators can more effectively predict and avoid hazards, and be more targeted with efforts to maintain and manage railway infrastructure.
Increasingly, advanced analytics are transforming railway operations and the passenger experience. By continually monitoring the track environment, operators can detect and rectify issues before they lead to failure and disruption.
This capability is at the heart of Nokia’s Water Events Prediction solution. Nokia, through its recent acquisition of SpaceTime Insight, now offers advanced analytics applications for asset-intensive industries. These tools support real-time collection and correlation of data to predict asset condition and operation and optimize and automate networks of people and assets. This is particularly valuable in the context of railways and mitigation of hazards.
Nokia Water Events Prediction is an analytics solution – based on an advanced machine learning engine - that provides actionable data to enable railway maintenance and risk management/mitigation professionals to identify rail washout failures before they happen. This unique solution enables railway operators to protect their rolling stock, avoid possible spills of hazardous material and keep rail personnel and passengers safe.
As powerful as this solution is, it represents just one of the many ways that Nokia is helping railway operators modernize their railway infrastructure, and enabling them to ensure safe, on-time, connected journeys for their customers.
Every day, Nokia’s mission-critical communications systems, cybersecurity capabilities and IoT solutions are working for railway operators around the world to improve safety and efficiency, and to maximize reliability. Whether you’re a mainline railway operator looking to modernize your signaling and communications system, a metro or urban transit system looking to enhance the passenger experience, a station operator looking to optimize efficiency and economics or an operations department looking to improve rolling stock and trackside maintenance, we can help you on your way.
Nokia’s solutions for railways will be on display next week at InnoTrans 2018 which is the leading international trade fair for transport technology. We will be exhibiting in Hall #4.1, in Stand #219. Meet us at the show, or at our railway solutions homepage to find out more.
Share your thoughts on this topic by joining the Twitter discussion with @nokia and @nokianetworks using #railway #trains #analytics