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Christopher Hooi is the Deputy Director of Communications & Sensors at the Land Transport Authority of Singapore. He is passionate about harnessing big data innovations to address complex land transport issues. Since 2010, he has embarked on a long term digital strategy with the main aim of achieving smart urban mobility in a fast changing digital world. Central to this strategy is to build and sustain a land transport digital ecosystem through an extensive network of sensor feeds, analytical processes and commuter outreach channels, synergistically put together to deliver a people-centred land transport system.

Sessions

  • June 11: UITP Awards 2019 Finalists Poster Session 4

    Early Incident Detection using Fusion Analytics of Commuter-Centric Data Sources

    In Singapore, over 7.2 million public transport journeys occur daily. The Land Transport Operations Centre (LTOC) is responsible for monitoring 24/7 operations and relies on alerts from Public Transport Operators (PTO) to manually co-ordinate incident response in the past. As ridership increases and the network expands, the complexity of LTOC’s tasks also increased. Today, LTOC is equipped with FASTER (Fusion Analytics for Public Transport Event Response), a big data AI platform which mines real-time IoT sensor sources such as WiFi, cellular, farecard, train, bus, taxi and CCTV, for early warning of potential anomalies to reduce impact to commuters through timely activation of contingency plans (Figure 1). Using fusion analytics, FASTER provides round-the-clock visibility of public transport operations, crowd levels and commuting patterns. It detects unusual network events, and provides automatic alerts in advance when service levels fall below the acceptable range.
  • June 11: Artificial intelligence and smart technology in public transport

    Early Incident Detection using Fusion Analytics of Commuter-centric Data Sources

    The Fusion Analytics for Public Transport Event Response (FASTER) system provides a real-time advanced analytics solution to provide early warning of potential train incidents for the early activation of contingency plans to reduce impact to commuters. Using novel fusion analytics of multiple data sources such as WiFi, cellular, farecard, train, bus, taxi and CCTV, FASTER harnesses the use of engineering and commuter-centric IoT data sources for the early detection of operational anomalies to enhance incident responses. FASTER supports both real-time and planning analysis through its simulation and optimisation modules. With these, FASTER is able to present alternative scenarios and evaluate effectiveness of incident response measures such as the impact of train turn-arounds and optimal routes for bus bridging.
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