Intelligence series: How can rail get value from Big Data?
Big data denotes data that has either a high velocity, a high variety or high volume. For instance, data collected from sensors in real time, data combining text, images and sounds on social media, and the dozen exabytes (10^18 bytes) of data contained in Google’s data centres, are typical examples of big data. The storage and processing of big data requires specific architectures, and advanced analytic techniques must be employed for their exploitation, enabling predictive analytics, the optimisation of complex systems, and the use of data mining to discover new trends and correlations.
Image author: Matt Howard, via Wikimedia Commons.
General Electric has a Movement Planner service that provides real-time train movement planning, route management and conflict resolution. In North America, the Movement Planner system has calculated, through predictive analytics and data collection, that $200m can be saved annually on operations by increasing the speed of a freight train on Class 1 Railroad by 1mph. Big data can also be used by the rail industry to optimise maintenance procedures through predictive maintenance. Conclusions can be drawn on how to improve the maintenance workflow through analysis of sensor data on components. Big data is also foreseen to become more used in the domain of risk analysis and safety management, as in aviation.