Publication Type

Blog Post

Version

acceptedVersion

Publication Date

5-2021

Abstract

There is no widely agreed upon definition of a supposed “Smart City.” Yet, when you see city employees — in this case city-state employees — working in what are obviously smarter ways, “you know it when you see it.” One such example of a smarter way to work in a smart city setting is the way that employees of the Land Transport Authority (LTA) in Singapore are using a new generation of data driven, AI-enabled support systems to manage the city’s urban rail network. We spoke to LTA officers Kong Wai, Ho (Director of Integrated Operations and Planning) and Chris Hooi (Deputy Director for Communications & Sensors, a unit within LTA’s IT, Cybersecurity & Digital Services Group) to find out more about their roles in implementing the FASTER system, and to Meng Fai, Leow (Deputy Group Director in the Rail Asset, Operations & Maintenance Group) and Christine Wee (Principal Manager for Asset Management Data and Analytics under LTA’s Rail Asset, Operations and Maintenance Group) about the usefulness of the Rail Enterprise Asset Management System.

Keywords

Transportation, Land Transport Authority, artificial intelligence

Discipline

Artificial Intelligence and Robotics | Asian Studies | Data Science | Transportation

Research Areas

Information Systems and Management

Publication

AI Singapore

First Page

1

Last Page

5

Publisher

National Research Foundation

City or Country

Singapore

Embargo Period

5-30-2021

Copyright Owner and License

Authors

Additional URL

https://aisingapore.org/2021/05/a-smarter-way-to-manage-mass-transit-in-a-smart-city-rail-network-management-at-singapores-land-transport-authority/

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