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Signal Processing Architectures, Algorithms, and Human–Machine Interactions in Urban Applications

  • Anandakumar Haldorai
  • Arulmurugan Ramu
  • Suriya Murugan
Chapter
Part of the Urban Computing book series (UC)

Abstract

The current state of art techniques used for signal processing and modeling comprises of vast number of instances of the framework inclusive of dissimilar modalities fused together such as vision, speech, textual data, language that essentially improves comprehension, modeling, performance processes of human and computer interface gadget and frameworks which augments human–human communication. Thus the all-embracing idea of this chapter will be solicitation of signal processing and computational methods based on challenges arising within vast number of disciplinary aspects used in city computing. Moreover, this chapter will state the capacities of and precincts of the present tech and analyzes the technical difficulties which should be overwhelmed in order to advance user-friendly and effective multi-modal interactive platform used of urban solicitation.

Keywords

Urbanization Signal Multimodality ANN Multi-agent Traffic data SAR 

References

  1. 1.
    Zheng, Y.: Location-based social networks: users. In: Computing with Spatial Trajectories, pp. 243–276. Springer, New York (2011)CrossRefGoogle Scholar
  2. 2.
    Pan, B., Zheng, Y., Wilkie, D., Shahabi, C.: Crowd sensing of traffic anomalies based on human mobility and social media. In: Proceedings of the 21th ACM SIGSPATIAL Conference on Advances in Geographical Information Systems. ACM, New York (2013)Google Scholar
  3. 3.
    Lee, R., Sumiya, K.: Measuring geographical regularities of crowd behaviors for Twitter-based geosocial event detection. In: Proceedings of ACM SIGSPATIAL GIS Workshop on Location Based Social Networks, pp. 1–10. ACM, New York (2010)Google Scholar
  4. 4.
    Bradshaw, M.: Software Agents. AAAI Press/MIT Press, Menlo Park (1997)Google Scholar
  5. 5.
    Ferber, J.: Multi-Agent Systems: Introduction to Distributed Artificial Intelligence. Addison-Wesley, Reading (1995)zbMATHGoogle Scholar
  6. 6.
    Gasser, L., Huhns, M.: Distributed Artificial Intelligence, vol. 2. Pitman, London (1989)Google Scholar
  7. 7.
    Franklin, S., Graesser, A.: It is an agent, or just a program? A taxonomy for autonomous agents. In: Proceedings of the 3rd International Workshop on Agent Theories, Architectures, and Languages. Springer, Berlin (1986)Google Scholar
  8. 8.
    Logan, B.: Classifying agent systems. In: Baxter, J., Logan, B. (eds.) Software Tools for Developing Agents: Papers from the 1998 Workshop. Technical Report WS-98-10, pp. 11–21. AAAI Press, Menlo Park (1998)Google Scholar
  9. 9.
    Wooldridge, M., Jennings, N.: Intelligent agents: theory and practice. Knowl. Eng. Rev. 10(2), 115–152 (1995)CrossRefGoogle Scholar
  10. 10.
    Bond, A., Gasser, L.: Readings in Distributed Artificial Intelligence. Morgan Kaufman, San Mateo (1988)Google Scholar
  11. 11.
    Mandiau, R., Le Strugeon, E., Agimont, G.: Study of the influence of organizational structure of the efficiency of a multiagent system. Netw. Inf. Syst. J. 2(2), 153–179 (1999)Google Scholar
  12. 12.
    Coutaz, J.: Software architecture modeling for user interfaces. In: Marciniak, J. (ed.) Architectural Design for User Interfaces: The Encyclopedia of Software Engineering, pp. 38–49. Wiley, New York (1993)Google Scholar
  13. 13.
    Coutaz, J., Nigay, L.: Architecture logicielleconceptuelle des syste’mesinteractifs. In: Kolski, C. (ed.) Analyse et conception de l’IHM, pp. 207–246. Hermes, Paris (2001)Google Scholar
  14. 14.
    Coutaz, J.: PAC, an implementation model for dialog design. In: Bullinger, H.J., Shackel, B. (eds.) Proceedings of the Interact’87 Conference, pp. 431–436. North-Holland, Amsterdam (1987)Google Scholar
  15. 15.
    Nigay, L.: Conception et modelisation logicielles des systemesinteractifs: Application aux interfaces multimodales. Universite Joseph Fourier, Grenoble (1994)Google Scholar
  16. 16.
    Nigay, L., Coutaz, J.: Building user interfaces: organizing software agents. In: Commission of the European Communities, Directorate-General, Telecommunications, Information Industries and Innovation (ed.) Proceedings of the Annual ESPRIT Conference, ESPRIT’91, pp. 707–719. Commission of the European Communities, Luxembourg (1991)Google Scholar
  17. 17.
    Manley, E., Cheng, T.: Exploring the role of spatial cognition in predicting urban traffic flow through agent-based modelling. Transp. Res. A. 109, 14–23 (2018)Google Scholar
  18. 18.
    Ed, M., Tao, C.: Exploring the role of spatial cognition in predicting urban traffic flow through agent-based modelling. Transp. Res. A. 109, 14–23 (2018)Google Scholar
  19. 19.
    Shinozuka, M., et al.: Damage detection in urban areas by SAR imagery. J. Eng. Mech. 126, 769 (2000)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSri Eshwar College of EngineeringCoimbatoreIndia
  2. 2.Department of Computer Science and EngineeringPresidency UniversityYelahanka, BengaluruIndia
  3. 3.Department of Computer Science and EngineeringKPR Institute of Engineering and TechnologyCoimbatoreIndia

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