Repository logo
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
Repository logo
  • Communities & Collections
  • All of DSpace
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Smaine ,MAZOUZI"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    Item
    Big Data Paradigm: Methods, Tools and Applications, Case of the Internet of Things
    (UNIVERSITY 20 AUGUST 1955 - SKIKDA, 2024) Mohamed Lamine, BOUGHOUAS; Smaine ,MAZOUZI
    Big data’s distinguishing features include its substantial volume, swift velocity, and wide-ranging variety of data types, which present obstacles for traditional data processing software. The proliferation of big data is propelled by the Internet of Things (IoT), which produces massive data volumes via interconnected devices. The collaboration between IoT and big data is revolutionary, facilitating the development of intelligent applications across various fields, such as healthcare and higher education. This thesis discusses the challenges and opportunities in managing and extracting insights from Big Data, mainly focusing on IoT-generated Big Data in sectors like higher education and environmental perception and management. It highlights the potential benefits of utilizing Big Data in these sectors and emphasizes the importance of advanced technologies for improving monitoring, analysis, and response mechanisms. In higher education, the study introduces the concept of Big Data Analytics (BDA) for improving student performance and decision-making, presenting a model for educational supply chain management and predictive analytics for student outcomes. In environmental management, a multi-layered architecture leveraging IoT and fog computing is proposed for forest fire management, emphasizing the importance of fog computing in handling data volume and improving system response time to fire incidents. Implementing advanced technologies like BDA and fog computing can significantly enhance efficiency and decision-making processes in various fields, revolutionizing how data is managed and utilized.

DSpace software copyright © 2002-2025 LYRASIS

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback

We collect and process your personal information for the following purposes: Authentication, Preferences, Acknowledgement and Statistics.
To learn more, please read our
privacy policy.

Customize