the world's most visited architecture website
i

Sign up now and start saving and organizing your favorite architecture projects and photos

Sign up now to save and organize your favorite architecture projects

i

Find the most inspiring products for your projects in our Product Catalog.

Find the most inspiring products in our Product Catalog.

i

Get the ArchDaily Chrome Extension and be inspired with every new tab. Install here »

i

All over the world, architects are finding cool ways to re-use run-down old buildings. Click here to see the best in Refurbishment Architecture.

Want to see the coolest refurbishment projects? Click here.

i

Immerse yourself in inspiring buildings with our selection of 360 videos. Click here.

See our immersive, inspiring 360 videos. Click here.

All
Projects
Products
Events
Competitions
Navigate articles using your keyboard
  1. ArchDaily
  2. News
  3. NYU and Hudson Yards to Use Big Data to Improve Cities

NYU and Hudson Yards to Use Big Data to Improve Cities

NYU and Hudson Yards to Use Big Data to Improve Cities
NYU and Hudson Yards to Use Big Data to Improve Cities, Phase One Visualisation © Nelson Byrd Woltz; Courtesy of Hudson Yards
Phase One Visualisation © Nelson Byrd Woltz; Courtesy of Hudson Yards

New York University’s Center for Urban Science and Progress has teamed up with the developers of Hudson Yards to transform the future 28-acre mixed-use neighborhood into the nations first “quantified community.” As Crain’s New York reports, the aim is to “use big data to make cities better places to live.” Information, from pedestrian traffic to energy production and resident activity levels, will be collected in order to study how cities can run efficiently and improve quality of living. You can read more on the subject, here.

About this author
Karissa Rosenfield
Author
Cite: Karissa Rosenfield. "NYU and Hudson Yards to Use Big Data to Improve Cities" 16 Apr 2014. ArchDaily. Accessed . <https://www.archdaily.com/497515/nyu-and-hudson-yards-to-use-big-data-to-improve-cities/> ISSN 0719-8884