SENSEable study uses network data to show communication patterns and social divisions

Dec 19, 2013. Posted by Ezra Glenn

Many residents of Britain, Italy, and Belgium imagine there to be a kind of north-south divide in their countries, marking a barrier between different social groups and regional characteristics. Now a new study by MIT researchers reveals that such divides can be seen in the patterns of communication in those countries and others.

"Transit Data for All" Victory

Nov 25, 2013. Posted by Ezra Glenn

SMART/SimMobility on CNBC

Oct 02, 2013. Posted by Ezra Glenn

DUSP Professor Joe Ferreira was featured on CNBC's "The Edge" in a segment featuring MIT's SMART/SimMobility project. 

MIT Presents "Best Paper" at UrbComp 2013

Aug 21, 2013. Posted by Ezra Glenn

A paper entitled "A Review of Urban Computing for Mobile Phone Traces: Current Methods, Challenges and Opportunities," presented by DUSP's Shan Jiang was awarded the "Best Paper" award at the 2nd ACM SIGKDD International Workshop on Urban Computing (UrbComp 2013).  The paper was authored by three students (Jiang, Gaston Fiore, and Yingxiang Yang) with thier faculty advisors (Joseph Ferreira, Emilio Frazzoli, and Marta Gonz├ílez). 

The Future Olympic Village

Aug 19, 2012. Posted by Site Admin

The Olympics are a special time when the world comes together to celebrate the excitement of sport. But the planning, creation and operation of the games also gives us a rare opportunity to imagine what the city of tomorrow might have in store for us. For a new online project, MIT's SENSEable City Lab teamed up with GE to put forth a vision of what systems and technologies could grace the Future Olympic Village.

SENSEable Study Looks at Building Occupancy and Energy Use

Aug 11, 2012. Posted by Ezra Glenn

Many workplaces feature major changes in occupancy over the course of a week. In academic buildings, hundreds of students may pour in for a lecture, then leave an hour or two later, while faculty, researchers and staff can enter and exit in irregular patterns. In commercial structures, workers may come and go en masse during short time periods during the day. As a result, energy use in virtually all workspaces can rapidly become inefficient -- too large or too small -- in relation to the number of people inside.