TY - GEN
T1 - Transforming Smart Cities with Spatial Computing
AU - Xie, Yiqun
AU - Gupta, Jayant
AU - Li, Yan
AU - Shekhar, Shashi
PY - 2019/2/28
Y1 - 2019/2/28
N2 - Spatial methods have a rich history of reforming city infrastructure. For example, John Snow's 1854 London Cholera map spurred cities to protect drinking water via sewer systems and to increase green spaces for public health. Today, geospatial data and mapping are among the technologies that cities use the most due to strategic (e.g., long-Term planning, land-use), tactical (e.g., property tax, site selection, asset tracking) and operational (e.g., E-911, situation awareness, gunshot location) use cases. Moreover, they (e.g., Google Maps) help citizens navigate, drones stay clear of restricted spaces (e.g., airports, NFL games), and sharing-economy (e.g., Uber) match consumers with nearby providers. Future spatial computing opportunities for smart cities are even more compelling. GIS promises to help re-imagine, redesign, see, and compare alternative infrastructure futures to address risks (e.g., climate change, rising inequality, population growth) and opportunities (e.g., autonomous vehicles, distributed energy production). This paper surveys recent spatial computing accomplishments and identifies research needs for smart-city use-cases.
AB - Spatial methods have a rich history of reforming city infrastructure. For example, John Snow's 1854 London Cholera map spurred cities to protect drinking water via sewer systems and to increase green spaces for public health. Today, geospatial data and mapping are among the technologies that cities use the most due to strategic (e.g., long-Term planning, land-use), tactical (e.g., property tax, site selection, asset tracking) and operational (e.g., E-911, situation awareness, gunshot location) use cases. Moreover, they (e.g., Google Maps) help citizens navigate, drones stay clear of restricted spaces (e.g., airports, NFL games), and sharing-economy (e.g., Uber) match consumers with nearby providers. Future spatial computing opportunities for smart cities are even more compelling. GIS promises to help re-imagine, redesign, see, and compare alternative infrastructure futures to address risks (e.g., climate change, rising inequality, population growth) and opportunities (e.g., autonomous vehicles, distributed energy production). This paper surveys recent spatial computing accomplishments and identifies research needs for smart-city use-cases.
KW - infrastructure
KW - smart city
KW - spatial computing
UR - http://www.scopus.com/inward/record.url?scp=85063471203&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063471203&partnerID=8YFLogxK
U2 - 10.1109/ISC2.2018.8656800
DO - 10.1109/ISC2.2018.8656800
M3 - Conference contribution
AN - SCOPUS:85063471203
T3 - 2018 IEEE International Smart Cities Conference, ISC2 2018
BT - 2018 IEEE International Smart Cities Conference, ISC2 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Smart Cities Conference, ISC2 2018
Y2 - 16 September 2018 through 19 September 2018
ER -