Over half the world’s population live in cities and urban areas, and over the next thirty years, 2 billion more people are expected to become urban residents. Cities are thinking carefully about the challenges associated with such rapid growth - like avoiding over-stressed public transit infrastructure and reducing traffic congestion. We’re interested in these questions too: we’ve been helping people navigate urban areas and route around traffic jams for many years. KTH Royal Institute of Technology to reduce the number of tunnel closures on the Södra Länken, the second longest urban motorway tunnel in Europe, to improve travel times for citizens. Netherlands Organization for Applied Scientific Research (TNO) to see whether it’s possible to reduce their reliance on expensive physical road sensors for information about traffic flows. The aim is to reduce infrastructure costs without compromising on traffic safety. We’re also working with the Amsterdam Institute for Advanced Metropolitan Solutions on related questions. Technical University of Denmark ) and in the US (the Rudin Center for Transportation at New York University Wagner School of Public Service, San Francisco County Transportation Authority , and the University of Chicago Harris School of Public Policy ).My Account ). This is the same data we use in Google Now to notify users of disruptions to their commute due to traffic, and tell them about the best time to visit their favourite museum in Google Maps. differential privacy , which intentionally adds “noise” to the data in a way that maintains both users' privacy and the data's accuracy. The technique has also been successfully tried and tested in Chrome.please get in touch .Posted by Andrew Eland, Engineering Director
Great job, nerds do good!
ReplyDeleteYou said "It's still early days, but preliminary results have been positive."
ReplyDeleteI've been following the intelligent transport systems and services market for many years and I'm encouraged by the potential for Internet of Things (IoT) technology use cases. I anticipate that we'll see many more interesting new proof-of-concept experiments in 2016.