Navigating With AI And Big Data
SG Nautilus|SN46
Maritime Singapore’s aim to double its port capacity by 2030 has stirred interest in traffic management along the narrow Singapore Strait. Jon White learns how a multi-party industry collaboration keeps this dream afloat
Jon White
Navigating With AI And Big Data

From smart traffic lights to predictive flight paths, multi-agent technologies have been used extensively in coordinating the movements of unmanned vehicles in the air and on the ground. In 2015, transport researcher Professor Lau Hoong Chuin of the Singapore Management University (SMU) mooted Singapore Strait. Jon White learns how a multi-party industry collaboration keeps this dream afloat the idea of extending the use of artificial intelligence (AI) to enhance safety and efficiency on the seas.

Sharing his dream, Prof Lau reveals, “While optimisation models have been successfully deployed for coordinating land and air traffic, my wishful thinking was, in an age of maritime digitalisation and automation, wouldn’t it be nice if similar models can be applied to coordinate maritime traffic to enhance safety and efficiency?”

Prof Lau’s thought comes against the backdrop of a booming maritime scene. Singapore is one of the world’s busiest ports, with about a thousand ships anchored in its waters at any one time and a ship arriving or departing every two to three minutes. Vessel traffic — comprising cruise ships, regional ferries, container ships, barges, and tugs — is only expected to grow, making narrow channels even more complex to manoeuvre and navigate. Ensuring navigation safety and efficiency in Singapore’s waters is, thus, of utmost importance.

MAXIMISING PROGRESS

Building on his research on AI planning and scheduling, Prof Lau reached out to industry partners to build an AI solution. “It’s almost obvious that no single party can claim that they have the full know-how and solutions,” he ventures. “So I always advocate collaboration.”

This story is from the SN46 edition of SG Nautilus.

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