DATA from video footage in train stations, telecommunications and fare cards will be used in combination to help the authorities manage train breakdowns more effectively down the road.
The Land Transport Authority of Singapore (LTA), SMRT Corporation (SMRT), StarHub and IBM have banded together for a two-year research project aimed at developing more rapid response times and better crowd management during train breakdowns.
The study, announced yesterday at the World Cities Summit, has been named Faster, which stands for Fusion AnalyticS for public Transport Emergency Response.
Under this, SMRT will provide video data from selected MRT stations to help with crowd counting on trains and in areas within and without the stations. SMRT will also provide fare card data, which gives mobility insights - such as the start and end points of the journey and the mode of public transport - to derive patterns in travel movements.
StarHub will pitch in with anonymised telecommunications data to refine journey patterns by pinpointing true origins and destinations of commuters before reaching or after leaving the train stations and bus stops.
The three data sets will be integrated and analysed using IBM's Intelligent Operations Centre software, which was created for cities to deliver better citizen services by tapping into available information. Merging these data sets will give transport operators real-time situational awareness of the transport network.
LTA chief executive Chew Hock Yong said that the agency uses data analytics, but lacks exhaustive data and knowledge, so it is getting on board this research collaboration, which may take on new partners.
Laura Wynter, the director of IBM Research Collaboratory in Singapore, said: "It means knowing at any point in time what the crowd levels are in stations and on trains, and what the delays to the trains are if there's an incident."
Predictive models can be applied to fare card data to see how people will move in the future; with telecommunications data to complete the mobility pattern, combining these with video analytics allow predictions to be made about crowd levels as a function of time, day and special events.
The system can also predict the impact of an incident in terms of expected delays and passengers affected, and recommend actions the operator can take to respond to the incident.
SMRT president and chief executive officer Desmond Kuek said of Faster: "We expect to enhance our ability to sense-make and act in the dynamic environment that typifies emergency situations."

DATA from video footage in train stations, telecommunications and fare cards will be used in combination to help the authorities manage train breakdowns more effectively down the road.

The Land Transport Authority of Singapore (LTA), SMRT Corporation (SMRT), StarHub and IBM have banded together for a two-year research project aimed at developing more rapid response times and better crowd management during train breakdowns.

The study, announced yesterday at the World Cities Summit, has been named Faster, which stands for Fusion AnalyticS for public Transport Emergency Response.

Under this, SMRT will provide video data from selected MRT stations to help with crowd counting on trains and in areas within and without the stations. SMRT will also provide fare card data, which gives mobility insights - such as the start and end points of the journey and the mode of public transport - to derive patterns in travel movements.

StarHub will pitch in with anonymised telecommunications data to refine journey patterns by pinpointing true origins and destinations of commuters before reaching or after leaving the train stations and bus stops.

The three data sets will be integrated and analysed using IBM's Intelligent Operations Centre software, which was created for cities to deliver better citizen services by tapping into available information. Merging these data sets will give transport operators real-time situational awareness of the transport network.

LTA chief executive Chew Hock Yong said that the agency uses data analytics, but lacks exhaustive data and knowledge, so it is getting on board this research collaboration, which may take on new partners.

Laura Wynter, the director of IBM Research Collaboratory in Singapore, said: "It means knowing at any point in time what the crowd levels are in stations and on trains, and what the delays to the trains are if there's an incident."

Predictive models can be applied to fare card data to see how people will move in the future; with telecommunications data to complete the mobility pattern, combining these with video analytics allow predictions to be made about crowd levels as a function of time, day and special events.

The system can also predict the impact of an incident in terms of expected delays and passengers affected, and recommend actions the operator can take to respond to the incident.

SMRT president and chief executive officer Desmond Kuek said of Faster: "We expect to enhance our ability to sense-make and act in the dynamic environment that typifies emergency situations."