This book was created with the intention of informing an international audience about the latest technological aspects for developing smart agricultural applications. As artificial intelligence (AI) takes the main role in this, the majority of the chapters are associated with the role of AI and data analytics components for better agricultural applications. The first two chapters provide alternative, wide reviews of the use of AI, robotics, and the Internet of Things as effective solutions to agricultural problems. The third chapter looks at the use of blockchain technology in smart agricultural scenarios. In the fourth chapter, a future view is provided of an Internet of Things-oriented sustainable agriculture. Next, the fifth chapter provides a governmental evaluation of advanced farming technologies, and the sixth chapter discusses the role of big data in smart agricultural applications. The role of the blockchain is evaluated in terms of an industrial view under the seventh chapter, and the eighth chapter provides a discussion of data mining and data extraction, which is essential for better further analysis by smart tools. The ninth chapter evaluates the use of machine learning in food processing and preservation, which is a critical issue for dealing with issues concerns regarding insufficient foud sources. The tenth chapter also discusses sustainability, and the eleventh chapter focuses on the problem of plant disease prediction, which is among the critical agricultural issues. Similarly, the twelfth chapter considers the use of deep learning for classifying plant diseases. Finally, the book ends with a look at cyber threats to farming automation in the thirteenth chapter and a case study of India for a better, smart, and sustainable agriculture in the fourteenth chapter. This book presents the most critical research topics of today’s smart agricultural applications and provides a valuable view for both technological knowledge and ability that will be helpful to academicians, scientists, students who are the future of science, and industrial practitioners who collaborate with academia.

There are various factors that influence the quality and quantity of agricultural products; among them, weather conditions play the most significant role in agriculture. More reliable weather forecasting enables farmers to make important planting and harvesting decisions that can enhance agricultural yield. Thus, there is a dire need to combine all available modern technologies and agricultural science for economic and environmentally sustainable crop production. In this direction, artificial intelligence (AI) serves as a budding solution in the domain of agriculture practices. Artificial Intelligence Tools and Technologies for Smart Farming and Agriculture Practices discusses various tools and technologies that can be used in smart farming and agriculture practice and explores the role of different emerging technologies like the internet of things, big data, machine learning, deep learning, and AI from agricultural prospects. Covering key topics such as farming, pests, soil, and weeds, this premier reference source is ideal for environmentalists, farmers, agriculturalists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

As technology continues to saturate modern society, agriculture has started to adopt digital computing and data-driven innovations. This emergence of “smart” farming has led to various advancements in the field, including autonomous equipment and the collection of climate, livestock, and plant data. As connectivity and data management continue to revolutionize the farming industry, empirical research is a necessity for understanding these technological developments. Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture provides emerging research exploring the theoretical and practical aspects of critical technological solutions within the farming industry. Featuring coverage on a broad range of topics such as crop monitoring, precision livestock farming, and agronomic data processing, this book is ideally designed for farmers, agriculturalists, product managers, farm holders, manufacturers, equipment suppliers, industrialists, governmental professionals, researchers, academicians, and students seeking current research on technological applications within agriculture and farming.

Agriculture 5.0: Artificial Intelligence, IoT & Machine Learning provides an interdisciplinary, integrative overview of latest development in the domain of smart farming. It shows how the traditional farming practices are being enhanced and modified by automation and introduction of modern scalable technological solutions that cut down on risks, enhance sustainability, and deliver predictive decisions to the grower, in order to make agriculture more productive. An elaborative approach has been used to highlight the applicability and adoption of key technologies and techniques such WSN, IoT, AI and ML in agronomic activities ranging from collection of information, analysing and drawing meaningful insights from the information which is more accurate, timely and reliable.It synthesizes interdisciplinary theory, concepts, definitions, models and findings involved in complex global sustainability problem-solving, making it an essential guide and reference. It includes real-world examples and applications making the book accessible to a broader interdisciplinary readership. This book clarifies hoe the birth of smart and intelligent agriculture is being nurtured and driven by the deployment of tiny sensors or AI/ML enabled UAV’s or low powered Internet of Things setups for the sensing, monitoring, collection, processing and storing of the information over the cloud platforms. This book is ideal for researchers, academics, post-graduate students and practitioners of agricultural universities, who want to embrace new agricultural technologies for Determination of site-specific crop requirements, future farming strategies related to controlling of chemical sprays, yield, price assessments with the help of AI/ML driven intelligent decision support systems and use of agri-robots for sowing and harvesting. The book will be covering and exploring the applications and some case studies of each technology, that have heavily made impact as grand successes. The main aim of the book is to give the readers immense insights into the impact and scope of WSN, IoT, AI and ML in the growth of intelligent digital farming and Agriculture revolution 5.0.The book also focuses on feasibility of precision farming and the problems faced during adoption of precision farming techniques, its potential in India and various policy measures taken all over the world. The reader can find a description of different decision support tools like crop simulation models, their types, and application in PA. Features: Detailed description of the latest tools and technologies available for the Agriculture 5.0. Elaborative information for different type of hardware, platforms and machine learning techniques for use in smart farming. Elucidates various types of predictive modeling techniques available for intelligent and accurate agricultural decision making from real time collected information for site specific precision farming. Information about different type of regulations and policies made by all over the world for the motivation farmers and innovators to invest and adopt the AI and ML enabled tools and farming systems for sustainable production.

In today's world, the pressing challenges of sustainable development and societal progress demand innovative solutions that harness the power of science and technology. From climate change to resource depletion and social inequalities, the urgency to find sustainable, intelligent, and ethical approaches has never been greater. Academic scholars and researchers play a crucial role in driving these advancements but often struggle to find comprehensive resources that bridge the gap between theory and real-world applications. The need of the hour is a definitive guide that unites expertise from diverse disciplines and offers practical insights into leveraging sustainable science and intelligent technologies to create meaningful societal development. Sustainable Science and Intelligent Technologies for Societal Development, edited by Brojo Kishore Mishra of GIET University, India, is the much-awaited solution to the challenges faced by academic scholars and researchers. This persuasive book brings together an esteemed collection of leading experts, academics, and industry professionals, all dedicated to addressing global challenges through the lens of applied sciences and intelligent technology applications. By presenting a wide range of innovative topics, such as renewable energy, smart healthcare, sustainable finance, and more, the book serves as a comprehensive resource that empowers scholars with actionable knowledge and innovative ideas. The book not only covers the theoretical aspects but also delves into the ethical considerations essential in shaping the future. In a world increasingly dependent on technology, it is vital to ensure that societal development aligns with principles of inclusivity, fairness, and environmental responsibility. With a focus on the United Nations Sustainable Development Goals (SDGs), the book provides a clear roadmap for scholars to contribute meaningfully to global progress. By offering concrete examples and real-world case studies, the book enables researchers to grasp the potential impact of their work, fostering collaborations that transcend traditional disciplinary boundaries. Sustainable Science and Intelligent Technologies for Societal Development is the go-to resource for academic scholars, scientists, researchers, innovators, industry professionals, and students who seek to be effective in the world. As a comprehensive guide that blends sustainable science and intelligent technologies with ethical considerations, this book equips its readers to create tangible solutions that address pressing global challenges. Through collective knowledge and interdisciplinary collaboration, this book stands as a beacon of hope and inspiration for driving meaningful societal development, paving the way for a more sustainable and prosperous future.

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).