With a rapidly growing population and the pursuit of a car-lite Singapore and Hong Kong, there is a need to improve the efficiency and responsiveness of public transportation. Zhihao Lin explores how telco-enabled data analytics empower day-to-day operational effectiveness and forward planning of public transport networks in Singapore.
The real-time tracking of train arrivals, incident detection, and people flow are essential for day-to-day monitoring of the performance of urban transport networks, to allow for timely intervention and enable commuter-centric decision making. However, for densely populated Singapore, important questions remain: Where should next train station be built to improve accessibility and convenience? And is the transport network able to cope with future growth?
So how can transport authorities access insights into end-to-end commuter movement, journey time, and the transport network’s ability to allow people to commute? With its volume and richness of information, telco data presents a great potential as a source of mobility insights. Zhihao explains how telco data along with a combination of data science methodologies and high-level architecture can provide the answer to transportation issues. Along the way, Zhihao illustrates transport performance indicators visualized on interactive dashboards and the spatial-temporal technology underlying people mobility insights.
Zhihao Lin started Teralytics’s Asia business and is currently the company’s head of Asia, where he is responsible for data science, software engineering, and business development. Previously, Zhihao worked for cybersecurity and advanced analytics companies in Switzerland, Singapore, and India. He holds an MS in computer science from Eidgenössische Technische Hochschule Zürich (ETH Zürich) and a BE in computer engineering (with first-class honors) from the National University of Singapore.
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