Convergence of Cloud Computing, AI, and Agricultural Science
Title | Convergence of Cloud Computing, AI, and Agricultural Science PDF eBook |
Author | Sharma, Avinash Kumar |
Publisher | IGI Global |
Total Pages | 401 |
Release | 2023-08-18 |
Genre | Technology & Engineering |
ISBN |
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.
Industry 4.0 Convergence with AI, IoT, Big Data and Cloud Computing: Fundamentals, Challenges and Applications
Title | Industry 4.0 Convergence with AI, IoT, Big Data and Cloud Computing: Fundamentals, Challenges and Applications PDF eBook |
Author | Parikshit N. Mahalle, Gitanjali R. Shinde, Prachi M. Joshi |
Publisher | Bentham Science Publishers |
Total Pages | 196 |
Release | 2023-12-25 |
Genre | Computers |
ISBN | 9815179195 |
This volume showcases upcoming trends and applications that are set to redefine our technological landscape. Chapters comprise referenced reviews focused on the recent research that introduces new methods and techniques for using AI in Industry 4.0, and the integration of Internet of Things (IoT) to drive new industrial processes. The contributors have discussed challenges in industry 4.0 along with the applications and the way it is shaping different industries. Key themes: AI in Communication Media: Uncover the latest research, with insights into the challenges and adoption of AI in remote processes. New AI Techniques for Industry 4.0: Learn about technologies such as blockchains and applications of machine learning, deep learning, and image processing. IoT and AI for Smart Systems: Understand IoT with a special focus on enhancing smart systems, in different industries, including agriculture and transaction processing Explorable AI: Gain a quick understanding of Explainable AI (XAI) and its role in improving the predictability and transparency of IoT applications. Whether you're a tech enthusiast, researcher, or industry professional, this book offers a glimpse into the innovative world of Industry 4.0 and its intersection with AI, IoT, big data, and cloud computing.
Methodologies, Frameworks, and Applications of Machine Learning
Title | Methodologies, Frameworks, and Applications of Machine Learning PDF eBook |
Author | Srivastava, Pramod Kumar |
Publisher | IGI Global |
Total Pages | 315 |
Release | 2024-03-22 |
Genre | Computers |
ISBN |
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).
Using Traditional Design Methods to Enhance AI-Driven Decision Making
Title | Using Traditional Design Methods to Enhance AI-Driven Decision Making PDF eBook |
Author | Nguyen, Tien V. T. |
Publisher | IGI Global |
Total Pages | 528 |
Release | 2024-01-10 |
Genre | Computers |
ISBN |
In the rapidly evolving landscape of industrial activities, artificial intelligence (AI) has emerged as a powerful force driving transformative change. Among its many applications, AI has proven to be instrumental in reducing processing costs associated with optimization challenges. The intersection of AI with optimization and multi-criteria decision making (MCDM) techniques has led to practical solutions in diverse fields such as manufacturing, transportation, finance, economics, and artificial intelligence. Using Traditional Design Methods to Enhance AI-Driven Decision Making delves into a wide array of topics related to optimization, decision-making, and their applications. Drawing on foundational contributions, system developments, and innovative techniques, the book explores the synergy between traditional design methods and AI-driven decision-making approaches. The book is ideal for higher education faculty and administrators, students of higher education, librarians, researchers, graduate students, and academicians. Contributors are invited to explore a wide range of topics, including the role of AI-driven decision-making in leadership, trends in AI-driven decision-making in Industry 5.0, applications in various industries such as manufacturing, transportation, healthcare, and banking services, as well as AI-driven optimization in mechanical engineering and materials.
Serverless Computing Concepts, Technology and Architecture
Title | Serverless Computing Concepts, Technology and Architecture PDF eBook |
Author | Aluvalu, Rajanikanth |
Publisher | IGI Global |
Total Pages | 330 |
Release | 2024-04-04 |
Genre | Computers |
ISBN |
Serverless computing has emerged as a transformative technology, gaining prominence over traditional cloud computing. It is characterized by reduced costs, lower latency, and the elimination of server-side management overhead, and is driven by the increasing adoption of containerization and microservices architectures. However, there is a significant lack of comprehensive resources for academic research purposes in this field. Serverless Computing Concepts, Technology, and Architecture addresses this gap and provides a comprehensive exploration of the fundamental concepts, characteristics, challenges, applications, and futuristic approaches of serverless computing. This book serves as a valuable reference for doctorate and post-doctorate research scholars, undergraduates, and postgraduates in fields such as computer science, information technology, electronics engineering, and other related disciplines. Serverless Computing Concepts, Technology, and Architecture is poised to be a one-stop reference point for those seeking to understand and harness the potential of serverless computing. It will serve as a prominent guide for researchers in this field for years to come, enriching their knowledge and advancing the study of serverless computing.
Future of AI in Medical Imaging
Title | Future of AI in Medical Imaging PDF eBook |
Author | Sharma, Avinash Kumar |
Publisher | IGI Global |
Total Pages | 327 |
Release | 2024-03-11 |
Genre | Computers |
ISBN |
Academic scholars and professionals are currently grappling with hurdles in optimizing diagnostic processes, as traditional methodologies prove insufficient in managing the intricate and voluminous nature of medical data. The diverse range of imaging techniques, spanning from endoscopy to magnetic resonance imaging, necessitates a more unified and efficient approach. This complexity has created a pressing need for streamlined methodologies and innovative solutions. Academic scholars find themselves at the forefront of addressing these challenges, seeking ways to leverage AI's full potential in improving the accuracy of medical imaging diagnostics and, consequently, enhancing overall patient outcomes. Future of AI in Medical Imaging, stands as a solution to the challenges faced by academic scholars in the realm of medical imaging. The book lays a solid groundwork for understanding the complexities of medical imaging systems. Through an exploration of various imaging modalities, it not only addresses the current issues but also serves as a guide for scholars to navigate the landscape of AI-integrated medical diagnostics. This collaborative effort not only illuminates the existing hurdles of medical imaging but also looks towards a future where AI-driven diagnostics and personalized medicine become indispensable tools, significantly elevating patient outcomes.
Advanced Geospatial Practices in Natural Environment Resource Management
Title | Advanced Geospatial Practices in Natural Environment Resource Management PDF eBook |
Author | Vohra, Rubeena |
Publisher | IGI Global |
Total Pages | 311 |
Release | 2024-03-18 |
Genre | Technology & Engineering |
ISBN |
Today, the relentless depletion of natural resources has reached a critical juncture, demanding innovative solutions. Advanced Geospatial Practices in Natural Environment Resource Management dives into the intricate tapestry of issues jeopardizing ecosystems. This book systematically dissects the fundamental drivers, traces the historical evolution, and elucidates the underlying causes that have led to this precarious point. From deforestation to pollution, from climate change to habitat destruction, these challenges are multifaceted. By harnessing the power of data-driven decision-making and predictive modeling, this book advocates for a profound shift in the approach to environmental issues. This book also explores the complexities of water, soil, and air-related challenges, offering technically sound solutions that strike a balance between legislative, economic, social, and political considerations. The holistic approach championed in these pages holds the potential to benefit governments, businesses, and communities alike. This book is ideal for a diverse audience, including students, scholars, and researchers, as well as environmental science enthusiasts, geospatial technology professionals, and AI/ML practitioners. Policymakers, environmental engineers, and professionals engaged in governmental and corporate sustainability initiatives will also discover practical solutions to address the pressing challenges.