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Mobile and Pervasive Computing for Urban Development

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

Abstract

Mobile and pervasive computing was introduced through the technological vision by Mark Weiser. With the ideology of urban development, the researcher considered the world to be composed of interconnected devices and system models of networks that allow the accessibility of information around the world. A U-city characterized by the information and computing technologies is gradually becoming indistinguishable and inviable from daily life. In that regard, this article provides an in-depth evaluation of mobile and pervasive computing considered as an evolutionary framework applicable in electric motors, which are invisible hence forming a pervasive environment. The need for mobile technology is apt for urban development, which signifies that mobility initiatives are applicable in many telecommunication aspects used in our daily lives. The article starts by illustrating the significant of mobile technology in urban areas, thereby elaborating on the planning format of pervasive computing meant for urban development. To effective plan for the establishment or expansion of urban centers, the article calls for planners to concentrate on the formation of pervasive computing areas that define the correlations between people, places, objects, buildings, and infrastructure. Mobile crowdsourcing technologies for smart environments call for planners to concentrate on revolutionizing the worlds hence aligning technological functions and enhance the integration and coordination of various services of technological intelligence.

Keywords

Mobile computing Pervasive computing Urban development Virtual reality Mobile crowdsourcing technologies 

References

  1. 1.
    Chen, P.: Study on coordinated development of urban environment and economy based on cluster computing. Clust. Comput. (2018). doi: 10.1007/s10586-018-2043-0
  2. 2.
    Cremades, R., Sommer, P.: Computing climate-smart urban land use with the integrated urban complexity model (IUCm 1.0). Geosci. Model Dev. 12(1), 525–539 (2019)CrossRefGoogle Scholar
  3. 3.
    Meier, E.: Situating technology professional development in urban schools. J. Educ. Comput. Res. 32(4), 395–407 (2005)CrossRefGoogle Scholar
  4. 4.
    Gao, K., Zhang, Y., Sadollah, A., Su, R.: Optimizing urban traffic light scheduling problem using harmony search with ensemble of local search. Appl. Soft Comput. 48, 359–372 (2016)CrossRefGoogle Scholar
  5. 5.
    Nourian, P., Martinez-Ortiz, C., Ohori, K.: Essential means for urban computing: specification of web-based computing platforms for urban planning, a Hitchhiker’s guide. Urban Plan. 3(1), 47 (2018)CrossRefGoogle Scholar
  6. 6.
    Khatun, R.: Smart city development and other urban development programmes in India for urban reconstruction and urban rejuvenation. Int. J. Emerg. Trends Sci. Technol. 4, 10 (2017)Google Scholar
  7. 7.
    Parnell, S., Robinson, J.: Development and urban policy: Johannesburg’s city development strategy. Urban Stud. 43(2), 337–355 (2006)CrossRefGoogle Scholar
  8. 8.
    Khakee, A.: An unbalanced model for sustainable urban development. Int. J. Urban Sustain. Dev. 6(1), 52–64 (2014)CrossRefGoogle Scholar
  9. 9.
    Brouwers, N., Woehrle, M.: Dwelling in the canyons: dwelling detection in urban environments using GPS, Wi-Fi, and geolocation. Pervasive Mob. Comput. 9(5), 665–680 (2013)CrossRefGoogle Scholar
  10. 10.
    Cesario, E., Comito, C., Talia, D.: An approach for the discovery and validation of urban mobility patterns. Pervasive Mob. Comput. 42, 77–92 (2017)CrossRefGoogle Scholar
  11. 11.
    Ciman, M., Gaggi, O.: An empirical analysis of energy consumption of cross-platform frameworks for mobile development. Pervasive Mob. Comput. 39, 214–230 (2017)CrossRefGoogle Scholar
  12. 12.
    Ferrari, L., Mamei, M.: Identifying and understanding urban sport areas using Nokia Sports Tracker. Pervasive Mob. Comput. 9(5), 616–628 (2013)CrossRefGoogle Scholar
  13. 13.
    Gerla, M.: From battlefields to urban grids: new research challenges in ad hoc wireless networks. Pervasive Mob. Comput. 1(1), 77–93 (2005)CrossRefGoogle Scholar
  14. 14.
    Helal, S., Bose, R., Li, W.: Mobile platforms and development environments. Synth. Lectures Mob. Pervasive Comput. 7(1), 1–120 (2012)CrossRefGoogle Scholar
  15. 15.
    Kant, K., Midkiff, S.: Pervasive computing and communications for sustainability. Pervasive Mob. Comput. 9(1), 118–119 (2013)CrossRefGoogle Scholar
  16. 16.
    Khan, A., Imon, S., Das, S.: A novel localization and coverage framework for real-time participatory urban monitoring. Pervasive Mob. Comput. 23, 122–138 (2015)CrossRefGoogle Scholar
  17. 17.
    Kjeldskov, J., Skov, M., Nielsen, G., Thorup, S., Vestergaard, M.: Digital urban ambience: mediating context on mobile devices in a city. Pervasive Mob. Comput. 9(5), 738–749 (2013)CrossRefGoogle Scholar
  18. 18.
    Kumar, M., Zambonelli, F.: Middleware for pervasive computing. Pervasive Mob. Comput. 3(4), 329–331 (2007)CrossRefGoogle Scholar
  19. 19.
    Palazzi, C., Pezzoni, F., Ruiz, P.: Delay-bounded data gathering in urban vehicular sensor networks. Pervasive Mob. Comput. 8(2), 180–193 (2012)CrossRefGoogle Scholar
  20. 20.
    Sadri, A., Ren, Y., Salim, F.: Information gain-based metric for recognizing transitions in human activities. Pervasive Mob. Comput. 38, 92–109 (2017)CrossRefGoogle Scholar
  21. 21.
    Chmidt, A., Terrenghi, L., Holleis, P.: Methods and guidelines for the design and development of domestic ubiquitous computing applications. Pervasive Mob. Comput. 3(6), 721–738 (2007)CrossRefGoogle Scholar
  22. 22.
    Serral, E., Valderas, P., Pelechano, V.: Towards the model driven development of context-aware pervasive systems. Pervasive Mob. Comput. 6(2), 254–280 (2010)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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