Big Data Paradigm: Methods, Tools and Applications, Case of the Internet of Things

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Date
2024
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UNIVERSITY 20 AUGUST 1955 - SKIKDA
Abstract
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.
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Big Data Paradigm, Methods, Tools and Applications, Higher education
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