Applications Of Big Data In Large And Small Scale Systems
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Applications of Big Data in Large- and Small-Scale Systems
With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.
Application of Big Data, Blockchain, and Internet of Things for Education Informatization
The five-volume set LNICST 580-584 constitutes the proceedings of the Third EAI International Conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2023, held in Liuzhou, China, during August 29–31, 2023. The 272 full papers presented in these proceedings were carefully reviewed and selected from 718 submissions. With a primary focus on research fields such as Digitization of education, Smart classrooms and Massive Online Open Courses (MOOCs), these papers are organized in the following topical sections across the five volumes: Part I: Application of data mining in smart education; Application of intelligent algorithms in English teaching. Part II: Application of decision tree algorithm in intelligent management system of universities; Research on the application of Big data in smart teaching. Part III: Exploration of the application of computer-aided technology in intelligent translation; Application of neural network algorithms in intelligent teaching; Application of artificial intelligence algorithms in the field of smart education. Part IV: Research on smart teaching in deep learning; Research and application of recommendation algorithms in personalized intelligent education; Application of cloud computing in intelligent teaching resource library; Application research of computer-aided online intelligent teaching. Part V: Application and practice of new media in smart teaching; Application of clustering algorithm in intelligent education resource library; Application of association rule algorithm in intelligent education system.
Applications of Big Data and Artificial Intelligence in Smart Energy Systems
In the era of propelling traditional energy systems to evolve towards smart energy systems, including power generation, energy storage systems, and electricity consumption have become more dynamic. The quality and reliability of power supply are impacted by the sporadic and rising use of electric vehicles, and domestic & industrial loads. Similarly, with the integration of solid state devices, renewable sources, and distributed generation, power generation processes are evolving in a variety of ways. Several cutting-edge technologies are necessary for the safe and secure operation of power systems in such a dynamic setting, including load distribution automation, energy regulation and control, and energy trading. This book covers the applications of various big data analytics, artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management. The book delves into the new technologies such as the Internet of Things, blockchain, etc. for smart home solutions, and smart city solutions in depth in the context of the modern power systems. Technical topics discussed in the book include: • Hybrid smart energy system technologies • Energy demand forecasting • Use of different protocols and communication in smart energy systems • Power quality and allied issues and mitigation using AI • Intelligent transportation • Virtual power plants • AI business models.