At the MDEC-Alibaba Cloud announcement of their collaboration to implement the Malaysia City Brain, Dr. Min Wanli gave a quick overview of the ET City Brain and the Tianchi platform for crowd intelligence.
Who Is Dr. Min Wanli?
Dr. Min Wanli (also known as Dr. Wanli Min) is the Chief Scientist of Machine Intelligence at Alibaba Cloud.
He holds a Ph.D in statistics from the University of Chicago, was a researcher at IBM’s T.J. Watson Research Center and a senior statistician at Google. He now oversees Alibaba Cloud’s artificial intelligence projects.
ET City Brain & The Tianchi Platform
ET is an Alibaba Cloud designation that refers to artificial intelligence services that “can be broadly applied to different areas in society”. It accomplishes this by leveraging the crowd intelligence capabilities of the Tianchi platform.
Dr. Min Wanli showcased how the Hangzhou City Brain master plan eases traffic congestion in the city, using an ambulance as an example. The Hangzhou City Brain will predict the traffic conditions for the next 30-60 minutes and determine the most efficient route for the ambulance.
It also synchronises the traffic signals so that they will turn green 10 seconds before the ambulance arrives, allowing it to pass without stopping. This not only cuts the ambulance’s arrival time, it also reduces risk of accidents.
The Malaysia City Brain
Dr. Min Wanli was here as part of the Alibaba Cloud delegation to announce their collaboration with the Malaysia Digital Economy Corporation (MDEC) to introduce the Malaysia City Brain.
In the first phase of implementation, the Malaysia City Brain will be used in Kuala Lumpur’s traffic management. It will begin with a base of 382 cameras, and input from 281 traffic light junctions – all located in central Kuala Lumpur.
Using cloud computing and big data processing capabilities, the Malaysia City Brain will be able to optimise the flow of vehicles and timing of traffic signals.
It will also be able to generate structured summaries of data like traffic volume, and speed according to lanes, which can be used to facilitate other tasks, including traffic accident detection.