LIVE Singapore! 2.0

MIT Investigator(s): Carlo RATTI


Team Members:
MIT
  • Paolo SANTIResearch ScientistMIT-DUSP
  •   SMART
  • Iva BOJICResearch ScientistSMART-FM
  • Daniel KONDORPostdocSMART-FM
  • Rui ZHUPostdocSMART-FM
  • Mohit SHAH*Project LeadSMART-FM
  • Aliaksandr BELY*Software EngineerSMART-FM
  • Gerald PNG*Full Stack DeveloperSMART-FM
  •   Collaborators
  • Arijit KHANAsst. Prof.NTU
  • LIVE Singapore encompasses four research topics: a) A travel-focused data visualization interface; b) Data on the Street to achieve transition to liveable cities today and in the future; c) Urban Data Analytics to investigate the limits of shared AV fleet size and parking needs; d) Data-driven optimization approach to systemically or holistically improve the resilience of the MRT. Through these innovative approaches we are seeking to change the way the people interact and communicate with the city.

    Social Implications of Universal Mobility
    • This research activity aims at analyzing large scale, fine grained global mobility data sets as the ones derived from cellular phone data and social networks to advance our knowledge and understanding of the fundamental laws governing human mobility at the urban and regional scale. More concretely, we investigate global mobility patterns from the perspective of a multi-layer complex network, built using a combination of three data sets: Twitter, Flickr and official migration data. Those data sets provide different, but equally important insights on the global mobility: while the first two highlight short-term visits of people from one country to another, the last one (i.e. migration) shows the long-term mobility perspective, when people relocate for good. The main purpose of the research pillar is to emphasize importance of this multi-layer approach capturing both aspects of human mobility at the same time. From one hand, we show that although the general properties of different layers of the global mobility network are similar, there are important quantitative differences between them. From the other hand, we demonstrate that applications of a multi-layered network can sometimes infer patterns that cannot be seen from studying each network layer separately.
      Indoor Tracing
    • Objective of this project is to analyze human occupancy and flows through public spaces as it is essential to improve already existing environments, and to better plan and design future spaces. Of utmost importance is not only gaining knowledge about human flows in outdoor spaces, but also inside buildings. A breakthrough in this respect could potentially come from pervasive use of digital devices with tracking capability, such as GPS-equipped smartphones, watches, wearables, etc., which could provide large data sets with high spatial and temporal granularity for accurate characterization of human flows. However, to date GPS technology can be effectively used only in outdoor environments, while its use in indoor scenarios remains a major technological and research challenge to be addressed. This research activity aims at exploring novel indoor tracking technologies that bypass GPS and are instead based on standard cellular phone communications.
      DataCollider
    • Objective of this project is to continue to refine a tool that allows the user to turn real-time data streams into sophisticated, next- generation visualizations. This tool allows the user to map data into perceivable and beautiful objects that interact and animate to tell a story with data. Through this innovative approach we are seeking to change the way the people interact and communicate with.