The smart city movement’s first wave brought tons of stationary sensors to our cities, especially in the context of transportation. These sensors are passively collecting valuable travel pattern information at traffic lights, parking lots, bus stops, sidewalks, and more. But if we want cities that are truly smart – if we want to solve the challenges exposed by our stationary sensors – we have to go beyond them. In this blog post, I will use New York City as a case study to explain why.
New York City's Department of Transportation (DOT) unfolded a plan to improve transportation data, which could considerably enhance the ability for NYC drivers to navigate the city safely. Referred to as the Drive Smart pilot program, it collects data directly from individual vehicles, accumulating the most accurate and up-to-date transportation data possible.
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The International Transport Forum Corporate Partnership Board's Workshop entitled “ITF Corporate Partnership Board Workshop: 21st Century Public Interest Data Sharing”, will be held on Nov 9 - 10 2015, at the OECD/IEA Conference Centre in Paris, France.
With the change in shopper travel patterns, retailers can no longer assume that trade areas are based on who lives nearby to a store or center. It’s time for them to change their thinking and use advanced analytics to make better-informed decisions.
A few weeks ago, we partnered up with INRIX for a webinar related to data-drive approaches to transportation demand management.
Here at StreetLight, we're constantly awed by the sheer magnitude of the Big Data Mobile Analytics that we do. We just passed the mark of processing trips representing nearly 50 billion vehicle miles traveled (VMT). This data comes from devices like connected cars, smart phones and commercial fleet management systems.