IMPROVING OPERATIONAL MANAGEMENT OF UK RAIL INFRASTRUCTURE
Through the unique processing and visualisation of real-time weather, mobile phone and train data, Emu Analytics’ Flo.w platform is being purposed to monitor, understand and predict the impacts of day-to-day and extreme weather on the network.
Flo.w generates actionable insights against rail networks, weather and population movements in real-time, driving enhanced operational efficiency
REDUCED DELAYS AND RISK
Flo.w gives operators a unique historical and real-time insight into the impact of weather events on the network, enabling better planning and risk mitigation
Flo.w's unique insights allows operators to plan more effectively, potentially reducing financial penalty across both customer and infrastructure
A COMPLEX, HIGH VOLUME RAIL NETWORK
The UK rail network is a complex and high volume operating environment with 1.759 billion rail journeys undertaken across 28 operators in 2018-19(1). This represents the movements of millions of people on a daily basis and any disruption within the network can cause thousands of people to be impacted. Lost hours due to delayed trains in 2018 were estimated at 4 million, costing operators £81 million in compensation claims(2).
A growing number of issues within the network are caused by severe weather events and Network Rail have in place a ‘Weather Resilience and Climate Change Adaption Strategy’ to recognise this.
However there is no current system in place to monitor the real-time impact to the rail network from weather events and to see the actual impact on population movement. As a result, mitigating actions are limited and analysis on the numerous data sets is a costly, time consuming overhead.
(1) Passenger and freight rail performance 2018-19 Q4 - Office of Rail and Road
(2) Which? Consumer Report 2018
REAL-TIME LOCATION ANALYTICS & VISUALISATION
Working with Amey, University of Birmingham and BT, Emu Analytics have deployed their cloud-based Flo.w platform, capable of ingesting thousands of location-based points a second, to capture, analyse and visualise weather, mobile phone and rail data in real-time. This is called WeatherSense+.
Through cutting edge location analytics and data science, Emu Analytics is able to provide unique insights into the impact of rail delays on population movements and those caused by weather events.
This will allow network and rail operators to mitigate risk to infrastructure and delays to passengers. This will reduce their exposure to financial penalties and ultimately improve the resilience of local economies, negatively impacted by severe weather events.
Hyper-local weather can cause far-reaching impacts across the wider transport network. Weathersense+ can provide the insights to help planning for extreme and everyday events.
Professor Lee Chapman - University of Birmingham
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