TITLE:

Transforming Smart Cities and Communities with Spatial Computing

PRESENTER:

Shashi Shekhar : Biography ( 100 words , 350 words ), Homepage , Picture

AFFILIATION:

Computer Science Department, University of Minnesota.

URL:

http://www.cs.umn.edu/~shekhar

VIDEOS, PICTURES:

SLIDES:

ABSTRACT:

Spatial data and methods have a rich history of reforming cities and communities. For example, John Snow's 1854 London Cholera map spurred creation of urban sewer systems to protect drinking water and provision of green spaces for public health . Today, Geospatial data and mapping is among Technology that cities use the most for numerous strategic (e.g., long-term planning, land-use, identify underserved areas), tactical (e.g., zoning, property tax, site selection, asset tracking) and operational (e.g., E-911, situation awareness, gunshot location) use cases. Moreover, they help citizens navigate (e.g., Google Maps) , drones stay clear of restricted spaces (e.g., airports, stadiums), and sharing-economy (e.g., Uber) match consumers with nearby providers.

Future spatial computing opportunities for smart cities are even more compelling. Next generation GPS and positioning may help better locate E-911 callers in high-rise buildings or underground spaces. Higher resolution and continuous remote sensing may help monitor sensitive areas, map tree species (e.g., Ash) or poorly-insulated buildings and create high-fidelity maps for self-driving vehicles. Spatial Databases may help identify under-served areas and geographic interdependence across infrastructures (e.g., water main above a train tunnel with a crucial optical fiber) to improve access and resilience. Spatial Data Science may identify infrastructure deprivation hotspots and their correlates (e.g., co-locations, tele-connections) to generate hypothesis for theory formation. GIS may help re-imagine, redesign, see and compare alternative infrastructure futures to address risks (e.g., climate change, rising inequality) and opportunities (e.g., autonomous vehicles, distributed energy production).

This talk will discuss the above topics leveraging research agenda and early results from our NSF S&CC project titled Connecting Smart-City Paradigm with a Sustainable Urban Infrastructure Systems Framework to Advance Equity in Communities. More details are available in the following publication: Transforming Smart Cities With Spatial Computing, Proc. IEEE International Smart Cities Conference , (with Y. Xie, J. Gupta, Y. Li), 2018.

KEYWORDS: Smart Communities, Smart Cities, Spatial Computing, GPS, Remote Sensing, GIS, Spatial Data Science.

ACKNOWLEDGMENTS: This work was supported in part by the National Science Foundation (Smart and Connected Communities Program) as well as the University of Minnesota.

REFERENCES

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