Video Data Analytics for Smart City Applications: Methods and Trends

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Title: Video Data Analytics for Smart City Applications: Methods and Trends
Description: Video data analytics is rapidly evolving and transforming the way we live in urban environments. In Video Data Analytics for Smart City Applications: Methods and Trends, data science experts present a comprehensive review of the latest advances and trends in video analytics technologies and their extensive applications in smart city planning and engineering. The book covers a wide range of topics including object recognition, action recognition, violence detection, and tracking, exploring deep learning approaches and other techniques for video data analytics. It also discusses the key enabling technologies for smart cities and homes and the scope and application of smart agriculture in smart cities. Moreover, the book addresses the challenges and security issues in terahertz band for wireless communication and the empirical impact of AI and IoT on performance management. One contribution also provides a review of the progress in achieving the Jal Jeevan Mission Goals for institutional capacity building in the Indian State of Chhattisgarh. For researchers, computer scientists, data analytics professionals, smart city planners and engineers, this book provides detailed references for further reading and demonstrates how technologies are serving their use-cases in the smart city. The book highlights the advances and trends in video analytics technologies and extensively addresses key themes, making it an essential resource for anyone looking to gain a comprehensive understanding of video data analytics for smart city applications.
Authors: Abhishek, Singh Rathore, Surendra, Rahamatkar, Syed, Imran Ali, Ramgopal, Kashyap, Nand, Kishore Sharma
Resource Type: eBook.
Subjects: Big data, Internet of things, Machine learning
Categories: COMPUTERS / Data Science / Data Analytics
Database: eBook Collection (EBSCOhost)
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  – Type: ebook-epub
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  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 3599077
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PubType: eBook
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  Data: Video data analytics is rapidly evolving and transforming the way we live in urban environments. In Video Data Analytics for Smart City Applications: Methods and Trends, data science experts present a comprehensive review of the latest advances and trends in video analytics technologies and their extensive applications in smart city planning and engineering. The book covers a wide range of topics including object recognition, action recognition, violence detection, and tracking, exploring deep learning approaches and other techniques for video data analytics. It also discusses the key enabling technologies for smart cities and homes and the scope and application of smart agriculture in smart cities. Moreover, the book addresses the challenges and security issues in terahertz band for wireless communication and the empirical impact of AI and IoT on performance management. One contribution also provides a review of the progress in achieving the Jal Jeevan Mission Goals for institutional capacity building in the Indian State of Chhattisgarh. For researchers, computer scientists, data analytics professionals, smart city planners and engineers, this book provides detailed references for further reading and demonstrates how technologies are serving their use-cases in the smart city. The book highlights the advances and trends in video analytics technologies and extensively addresses key themes, making it an essential resource for anyone looking to gain a comprehensive understanding of video data analytics for smart city applications.
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      – Code: 005.7
        Scheme: ddc
        Type: prePub
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      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Big data
        Type: general
      – SubjectFull: Internet of things
        Type: general
      – SubjectFull: Machine learning
        Type: general
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      – TitleFull: Video Data Analytics for Smart City Applications: Methods and Trends
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2023
            – D: 03
              M: 02
              Type: profile
              Y: 2024
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              Value: 9789815123715
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              Value: 9789815123708
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              Value: 00001
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