Transport for London: Using data to keep London moving

Transport for London (TfL) and WSO2 have been working together on broader integration projects focused on getting the most efficient use out of London transport. Roland Major and Sriskandarajah Suhothayan explain how TfL and WSO2 bring together a wide range of data from multiple disconnected systems to understand current and predicted transport network status.

Transport for London (TfL) moves people and things around London. As the city grows, it is increasingly important to get the most efficient use of its transportation networks, safely, while keeping them moving. TfL uses a wide range of data for operational purposes, but the underlying data is typically held in multiple disconnected systems. Freedom of Information requests have helped prove the value of sharing this data. TfL is embarking on a journey to make more of this data open and available in real time. TfL and WSO2 have been working together on broader integration projects. Roland Major and Sriskandarajah Suhothayan share the evolving big data and IoT architectures and services TfL is building to pull together these diverse datasets to better support operational teams and accelerate the identification and classification of disruption to improve response times for incidents. In particular, they explore WSO2’s solution, which emerged from the Data in Motion hackathon organized by TfL, AWS, and Geovation. The solution innovates TfL’s heterogeneous data sources through the combination of the TfL Unified API and its operational data sources, including traffic sensor, air quality, and passenger flow data, to provide better travel time and transit suggestions for Londoners and tourists using the WSO2 Data Analytics Server, WSO2 Complex Event Processor, and WSO2 API Manager, bringing together IoT and big data techniques to feed a real-time dashboard of current and predicted transport network status.