New facility to explore technology in Electric buses

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Singapore (Commonwealth Union) – Electric buses have been seen as a natural solution to blocking the effects of environmental pollution. However, its implementation has not been immediately feasible across the world for a variety of reasons, such as economic factors and difficulty in re-constructing road infrastructures to accommodate electric buses.

A new facility was opened for the Nanyang Technological University (NTU) community and the public to gain knowledge on the technology solutions implemented for the campus electric shuttle bus service. The launch was done together with ComfortDelGro Bus, the new Smart Mobility Experience Centre (SMEC) at the NTU Smart Campus, the very 1st center accessible for members of the public.

The Centre has the the latest systems able to monitor real-time ridership, the location of the buses, together with the electrification progress of the fleet. Visitors can expect to engage and interact via touchscreen panels. This gives them a chance to educate themselves on smart fleet management systems, and ways the tech-enabled solutions such as bus ridership can impact outcomes impacting them as commuters.

A display of the NTU Omnibus app, which is a mobile app that is a simplified app powered together by ComfortDelGro Bus and NTU, gives the opportunity for commuters to have their trip well organized.

The new electric buses will contain a host of telematic equipment, such as a GPS, battery management hardware, while providing powerful data gathering capabilities. This will also include a passenger information display system permitting commuters to gain information on the bus route and the coming bus stop.

The ability to get to a location with options on the mode of transport such as train or bus and the arrival time used to be available in most parts of the world via phone. However, in recent years it has been increasingly replaced with technology with limited phone support. Data gathered via the electric bus fleet is set to be analyzed for ridership patterns in predicting interventions for a smoother journey.

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