Convergence Of Cloud Computing Ai And Agricultural Science
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Convergence of Cloud Computing, AI, and Agricultural Science
Convergence of Cloud Computing, AI, and Agricultural Science explores the transformative potential of integrating cutting-edge technologies into the field of agriculture. With the rapid advancements in cloud computing, Artificial Intelligence (AI), and the Internet of Things (IoT), this research presents a comprehensive framework for monitoring agriculture farms remotely using a smart cloud-based system. The book delves into the application of AI-based machine learning models, such as the Support Vector Machine (SVM), to accurately classify and process the collected data. This advanced research reference book also explores how digital information can provide farmers with information about international markets, enabling them to make informed decisions regarding their crops. With its academic tone and in-depth exploration of cloud computing in smart agriculture, this book serves as an essential resource for researchers, academics, and professionals in the fields of agriculture, computer science, and environmental science. By examining the convergence of cloud computing, AI, and agricultural science, it provides a roadmap for harnessing technology to revolutionize farming practices and ensure sustainable agri-food systems in the digital era.
Methodologies, Frameworks, and Applications of Machine Learning
Author: Srivastava, Pramod Kumar
language: en
Publisher: IGI Global
Release Date: 2024-03-22
Technology is constantly evolving, and machine learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest machine learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making. Academic scholars seeking to unlock the potential of machine learning in the context of Industry 5.0 and advanced IoT applications will find that the groundbreaking book, Methodologies, Frameworks, and Applications of Machine Learning, introduces an unmissable opportunity to delve into the forefront of modern research and application. This book offers a wealth of knowledge and practical insights across a wide array of topics, ranging from conceptual frameworks and methodological approaches to the application of probability theory, statistical techniques, and machine learning in domains as diverse as e-government, healthcare, cyber-physical systems, and sustainable development, this comprehensive guide equips you with the tools to navigate the complexities of Industry 5.0 and the Internet of Things (IoT).
Advancements in Cloud-Based Intelligent Informative Engineering
In this ever-changing world, the rapid evolution of cloud computing and AI has paved the way for advancements in cloud-based intelligent engineering. This emerging field integrates cloud computing, big data, and AI to enhance the efficiency and automation of engineering processes. By leveraging cloud-based intelligent systems, industries can optimize data management, improve real-time collaboration, and drive innovation across various engineering domains. Advancements in Cloud-Based Intelligent Informative Engineering explores technological advancements and devices in cloud technology. It examines cloud-based intelligent system approaches and developments in informative engineering. This book covers topics such as IoT, machine learning, and blockchain, and is a useful resource for researchers, engineers, business owners, academicians, and scientists.