Urban Computing: Recent Developments and Analytics Techniques in Big Data

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2022 by IJETT Journal
Volume-70 Issue-7
Year of Publication : 2022
Authors : G. Muneeswari, R. Surendiran, J. Jeneetha Jebanazer, P. Josephin Shermila, E. Anna Devi, A. Jeyam
DOI : 10.14445/22315381/IJETT-V70I7P217

How to Cite?

G. Muneeswari, R. Surendiran, J. Jeneetha Jebanazer, P. Josephin Shermila, E. Anna Devi and A. Jeyam, "Urban Computing: Recent Developments and Analytics Techniques in Big Data" International Journal of Engineering Trends and Technology, vol. 70, no. 7, pp. 158-168, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I7P217

Abstract
Urban computing takes strong computational procedures to tolerate such urban tasks as pollution, energy consumption, and traffic crowding. Nowadays, varied information in an urban context delivers new chances for constructing a better activity over urban computing. Though attributable to dissimilarity, extreme difficulty, and massive volumes, evaluating them is not a simple mission that frequently wants the integration of human observation into the systematic methodology, activating a wide use of Bigdata. This analysis encompasses a tendency to summarize used information varieties in urban Bigdata analytics, therefore intricate on present methods for time, locations, and various belongings of urban information. Moreover, deliberate; however, big data is combined with automatic analytical strategies. Big data analytics is that oftencomplex methodology of testing huge and varied information sets or massive data to uncover data at the side of secreted designs, unidentified parallels, arcade tendencies, and purchaser preferences that will facilitate organizations produce wise business decisions. Big data analytics would direct beneficial data for several administrations. Big data study, though, is still in its early stages. Its attention is rather undistinguishable, and interrelated studies are not well incorporated. The analysis work has provided solutions supported processing techniques, which could meet various challenges in urban turning out and management. Here, outlooks the end of the day of urban big data analytics and achieves the review with probable analysis objectives.

Keywords
Big data analytics, Urban computing, Urban data, Urban data analytics, Urbanization.

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