Cover Image


View/Hide Left Panel

•   Gerard M. Mooney, vice president of IBM Global Smarter Cities

•   Thomas D. O’Rourke, Thomas R. Briggs Professor of Engineering at Cornell University

•   Theodore S. Rappaport, David Lee/Ernst Weber Professor of Electrical Engineering at NYU-Poly

It became clear in the session that an important component of the answer to these questions lies in the systematic gathering and use of data about cities. The data can come in a variety of modalities: visual, infrared, cellular/GPS signals, water monitor outputs, and so on. Analysis of the data can be used for optimization and to generate efficiencies of all kinds, such as shorter commuting time, less wasteful water and energy management, improved disaster response, and more efficient product distribution.

A second component of any solution is modeling and simulation. Cities are highly complex both structurally and organizationally. Changing any one variable even slightly can have unanticipated catastrophic effects in unexpected places. The better we use data to model and understand cities, the better we can optimize outcomes and minimize negative repercussions.

Finally, key to success will be partnerships between city agencies and the academic and private sectors. The city needs to open its data to careful analysis, which can stimulate novel “smart” solutions from the general public and the private sector. The academic and private sectors are motivated to help; what they need is direction and encouragement from city and state agencies, augmented by small amounts of seed funding.

As with many things, George Bugliarello understood these issues well before most of the scientific community. Perhaps more slowly than optimum, we are finally following his lead.

The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement