Future connected vehicles: Challenges and opportunities for spatio-temporal computing

Reem Y. Ali; Venkata M.V. Gunturi; Shashi Shekhar; Ahmed Eldawy; Mohamed F. Mokbel; Andrew J. Kotz; William F. Northrop

doi:10.1145/2820783.2820885

Future connected vehicles: Challenges and opportunities for spatio-temporal computing

Reem Y. Ali
, Venkata M.V. Gunturi
, Shashi Shekhar
, Ahmed Eldawy
, Mohamed F. Mokbel
, Andrew J. Kotz
, William F. Northrop

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Scopus citations

Abstract

Modern vehicles are increasingly being equipped with rich instrumentation that enables them to collect location aware data on a wide variety of travel related phenomena such as the real-world performance of engines and powertrain, driver preferences, context of the vehicle with respect to others nearby, and-indirectly-traffic on the transportation network itself. Combined with their increased access to the Internet, these connected vehicles are opening up vast opportunities to improve the safety, environmental friendliness, and the overall experience of urban travel. However, significant spatial computing challenges need to be addressed before we can realize the full potential of connected vehicles. This paper presents some of the open research questions under this theme from the perspectives of query processing, data science and data engineering.

Original language	English (US)
Title of host publication	23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2015
Editors	Yan Huang, Mohamed Ali, Jagan Sankaranarayanan, Matthias Renz, Michael Gertz
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450339674
DOIs	https://doi.org/10.1145/2820783.2820885
State	Published - Nov 3 2015
Event	23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2015 - Seattle, United States Duration: Nov 3 2015 → Nov 6 2015

Publication series

Name	GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
Volume	03-06-November-2015

Other

Other	23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2015
Country/Territory	United States
City	Seattle
Period	11/3/15 → 11/6/15

Bibliographical note

Publisher Copyright:
© 2015 ACM.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Connected vehicles
Spatial and spatio-temporal data mining
Spatial and spatio-temporal graphs
Spatial big data
Spatial statistics
Transportation

Publisher link

10.1145/2820783.2820885

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Cite this

Ali, R. Y., Gunturi, V. M. V., Shekhar, S., Eldawy, A., Mokbel, M. F., Kotz, A. J., & Northrop, W. F. (2015). Future connected vehicles: Challenges and opportunities for spatio-temporal computing. In Y. Huang, M. Ali, J. Sankaranarayanan, M. Renz, & M. Gertz (Eds.), 23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2015 Article a14 (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems; Vol. 03-06-November-2015). Association for Computing Machinery. https://doi.org/10.1145/2820783.2820885

Future connected vehicles: Challenges and opportunities for spatio-temporal computing. / Ali, Reem Y.; Gunturi, Venkata M.V.; Shekhar, Shashi et al.
23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2015. ed. / Yan Huang; Mohamed Ali; Jagan Sankaranarayanan; Matthias Renz; Michael Gertz. Association for Computing Machinery, 2015. a14 (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems; Vol. 03-06-November-2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ali, RY, Gunturi, VMV, Shekhar, S, Eldawy, A, Mokbel, MF, Kotz, AJ & Northrop, WF 2015, Future connected vehicles: Challenges and opportunities for spatio-temporal computing. in Y Huang, M Ali, J Sankaranarayanan, M Renz & M Gertz (eds), 23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2015., a14, GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, vol. 03-06-November-2015, Association for Computing Machinery, 23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2015, Seattle, United States, 11/3/15. https://doi.org/10.1145/2820783.2820885

Ali RY, Gunturi VMV, Shekhar S, Eldawy A, Mokbel MF, Kotz AJ et al. Future connected vehicles: Challenges and opportunities for spatio-temporal computing. In Huang Y, Ali M, Sankaranarayanan J, Renz M, Gertz M, editors, 23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2015. Association for Computing Machinery. 2015. a14. (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems). doi: 10.1145/2820783.2820885

Ali, Reem Y. ; Gunturi, Venkata M.V. ; Shekhar, Shashi et al. / Future connected vehicles : Challenges and opportunities for spatio-temporal computing. 23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2015. editor / Yan Huang ; Mohamed Ali ; Jagan Sankaranarayanan ; Matthias Renz ; Michael Gertz. Association for Computing Machinery, 2015. (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems).

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title = "Future connected vehicles: Challenges and opportunities for spatio-temporal computing",

abstract = "Modern vehicles are increasingly being equipped with rich instrumentation that enables them to collect location aware data on a wide variety of travel related phenomena such as the real-world performance of engines and powertrain, driver preferences, context of the vehicle with respect to others nearby, and-indirectly-traffic on the transportation network itself. Combined with their increased access to the Internet, these connected vehicles are opening up vast opportunities to improve the safety, environmental friendliness, and the overall experience of urban travel. However, significant spatial computing challenges need to be addressed before we can realize the full potential of connected vehicles. This paper presents some of the open research questions under this theme from the perspectives of query processing, data science and data engineering.",

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note = "Publisher Copyright: {\textcopyright} 2015 ACM.; 23rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2015 ; Conference date: 03-11-2015 Through 06-11-2015",

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AB - Modern vehicles are increasingly being equipped with rich instrumentation that enables them to collect location aware data on a wide variety of travel related phenomena such as the real-world performance of engines and powertrain, driver preferences, context of the vehicle with respect to others nearby, and-indirectly-traffic on the transportation network itself. Combined with their increased access to the Internet, these connected vehicles are opening up vast opportunities to improve the safety, environmental friendliness, and the overall experience of urban travel. However, significant spatial computing challenges need to be addressed before we can realize the full potential of connected vehicles. This paper presents some of the open research questions under this theme from the perspectives of query processing, data science and data engineering.

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KW - Spatial big data

KW - Spatial statistics

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Future connected vehicles: Challenges and opportunities for spatio-temporal computing

Abstract

Publication series

Other

Bibliographical note

UN SDGs

Keywords

Publisher link

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