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Semantic multimedia-enhanced spatio-temporal queries in a crowdsourced environment

Published: 03 November 2015 Publication History

Abstract

Social networks, such as Facebook, Instagram, and Twitter, provide intuitive ways to share a variety of information including geotagged multimedia data within users' communities of interest (COI) or publicly in real-time. Real-time geotagged multimedia data can provide semantics to conventional spatial queries in order to enrich the user navigation experience. In this paper, we introduce a mechanism to process spatio-temporal queries by leveraging geotagged multimedia data such as images, audio, video, and text, in order to add semantics to the conventional queries. Our framework collects, stores, and spatially tags multimedia data shared by users through social networks or through our developed mobile application. The system then uses such data in order to enhance the conventional routing services by resolving existing usability issues and by providing semantics to the routes in terms of enriched points of interest while taking dynamic road conditions into account. A proof of concept of the system will be demonstrated with the following spatio-temporal queries on road networks: 1) multimedia-enhanced shortest path queries; 2) multimedia-enhanced k-nearest neighbor queries; and 3) multimedia-enhanced range queries. Finally, a novel technique for finding lost individuals using geotagged multimedia data is also introduced. The results are tailor-made to the users' smartphone bandwidth and resolution requirements

References

[1]
A. Ahmad, A. Rahman, F. U. Rehman, A. Lbath, I. Afyouni, A. Khelil, S. O. Hussain, B. Sadiq, and M. R. Wahiddin. A Framework for Crowd-Sourced Data Collection and Context-Aware Services in Hajj and Umrah. IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA), pp.405--412, Nov. 2014.
[2]
F. U. Rehman, A. Lbath, M. A. Rahman, S. Basalamah, I. Afyouni, A. Ahmad, and S. O. Hussain. Toward dynamic path recommender system based on social network data. Proc. 7th ACM SIGSPATIAL Int. Work. Comput. Transp. Sci. - IWCTS '14, pp. 64--69, 2014.
[3]
X. Wang, Y. Zhao, L. Nie, Y. Gao, and S. Member, Semantic-Based Location Recommendation With Multimodal Venue Semantics. Multimedia, IEEE Transactions, vol. 17, no. 3, pp. 409, 419, March 2015.
[4]
M. Raubal and S. Winter. Enriching Wayfinding Instructions with Local Landmarks. In Proceedings of the Second International Conference on Geographic Information Science, Springer-Verlag, pp. 243--259, London, UK, 2002.
[5]
OpenStreetMap. http://www.openstreetmap.org, Retrieved, March 2014.
[6]
Osm2pgSQL.http://wiki.openstreetmap.org/wiki/Osm2pgsql.
[7]
PgRouting Algorithms. http://workshop.pgrouting.org/chapters/shortest_path.html

Cited By

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  • (2022)Solving Hajj and Umrah Challenges Using Information and Communication Technology: A SurveyIEEE Access10.1109/ACCESS.2022.319085310(75404-75427)Online publication date: 2022
  • (2016)Spatial-crowd: A big data framework for efficient data visualization2016 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2016.7840842(2130-2138)Online publication date: Dec-2016
  • (2015)A spatio-temporal multimedia big data framework for a large crowd2015 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2015.7364075(2742-2751)Online publication date: Oct-2015

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  1. Semantic multimedia-enhanced spatio-temporal queries in a crowdsourced environment

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      cover image ACM Conferences
      SIGSPATIAL '15: Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems
      November 2015
      646 pages
      ISBN:9781450339674
      DOI:10.1145/2820783
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Publication History

      Published: 03 November 2015

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      Author Tags

      1. crowdsourcing social media
      2. multimedia-enhanced routing
      3. spatio-temoral queries

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      • KACST, Saudi Arabia

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      SIGSPATIAL '15 Paper Acceptance Rate 38 of 212 submissions, 18%;
      Overall Acceptance Rate 257 of 1,238 submissions, 21%

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      Cited By

      View all
      • (2022)Solving Hajj and Umrah Challenges Using Information and Communication Technology: A SurveyIEEE Access10.1109/ACCESS.2022.319085310(75404-75427)Online publication date: 2022
      • (2016)Spatial-crowd: A big data framework for efficient data visualization2016 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2016.7840842(2130-2138)Online publication date: Dec-2016
      • (2015)A spatio-temporal multimedia big data framework for a large crowd2015 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2015.7364075(2742-2751)Online publication date: Oct-2015

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