New data types and sources breed new traffic solutions.
Bike shares and dockless electric Scooters, no matter if they are human-powered or electric, they are still Internet of Things (IoT) devices. They and the smartphones used to activate them never stop generating data from integrated sensors which from there are transmitted to the systems of the companies where they come from. The information shared includes how long each ride takes, the location of each connected bicycle, which docks are full and which ones need to be restocked. All this happens in real time which somehow sounds futurists, does not it?
The system data of New York’s Citi Bike is publicly available for engineers, developers, and statisticians in case they want to use that information for development, analysis or they only want to visualize it. The decisions we make regarding municipal infrastructures and transportation will be influenced by the more open these data and technologies become.
Connected bikes and scooters provide data which can be continuously streamed and made into integral components of a fully responsive and functional interconnected grid which afterward process big data unprecedented in its variability, volume, and velocity.
The hub for similar mobility data types collected from sensors and hardware will also benefit from this especially the ones embedded within traditional and autonomous vehicles, law enforcement networks, public transit systems, healthcare facilities, transportation grids, weather monitors, and more.
More focused insights will be produced by this mobility data at its most functional level, most related to peak commute times, fleet management, heavily trafficked corridors, and other transit metrics that help to get the significant benefits of the “connected city” enhanced. Congestion cost $305 billion last year in the US alone, according to transportation consulting firm INRIX and it increased with $10 billion from 2016.
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