This book provides extensive information about smart farming, precision agriculture and the technologies that make them succeed. The authors provide detailed machine learning and deep learning models and algorithms that can be implemented effectively to improve smart farming methods. The authors also give elaborate information about the various IoT devices and types of drones that are used vastly in smart farming culture. The authors show specifically how methods and techniques used to improve the crop yield can be executed to help the farmers to improve the agricultural process and cultivation methods using a rule-based methodology. The purpose of this book is to articulate the need for processes, platforms, practices, patterns, and rules to be followed for the better yield of crop production and how IoT, robotics and drones can be used to improve the economy of the countries in the field of agriculture. In a nutshell, the book shows how the combination of multiple cutting-edge technologies leads to the realization of state-of-the-art infrastructures for next-generation agriculture.

This book provides a review of the state-of-the-art of agricultural robotics in different aspects of PA, the goals, and the gaps. The book introduces the area of Agricultural Robotics for Precision Agriculture (PA) specifically the conditions and limitations for implementing robots in this field and presents the concepts, principles, required abilities, components, characteristics and performance measures, conditions, and rules for robots in PA.

With the convergence of the Internet of Things (IoT) and Artificial Intelligence (AI), the traditional methods of farming are undergoing transformation. By harnessing the power of data-driven insights and automation, farmers can now make informed decisions in real time, optimize resource utilization, and mitigate risks associated with crop management and livestock welfare. This book serves as a guide to the integration of IoT and AI in agriculture and discusses the methodologies, applications, and challenges in this rapidly evolving field. It details various aspects of smart farming—from crop monitoring and precision agriculture to livestock management and food supply chain transparency—and provides insight into the potential of IoT and AI to revolutionize agricultural practices and address the global challenges of food security, environmental sustainability, and economic development. Print edition not for sale in South Asia (India, Sri Lanka, Nepal, Bangladesh, Pakistan or Bhutan)

This book covers three main types of agricultural systems: the use of robotics, drones (unmanned aerial vehicles), and satellite-guided precision farming methods. Some of these are well refined and are currently in use, while others are in need of refinement and are yet to become popular. The book provides a valuable source of information on this developing field for those involved with agriculture and farming and agricultural engineering. The book is also applicable as a textbook for students and a reference for faculty.

In an era overshadowed by pressing global challenges such as climate change, burgeoning populations, and the depletion of natural resources, the agricultural landscape is at a critical juncture. The need for sustainable practices has never been more urgent, with conventional methods struggling to meet the demands of a growing population while grappling with environmental degradation. Harnessing NanoOmics and Nanozymes for Sustainable Agriculture delves into the heart of the problem, navigating the intricate web of challenges facing agriculture today. From dwindling crop yields to the environmental repercussions of conventional farming practices, the urgency to find innovative, sustainable solutions is paramount. Harnessing NanoOmics and Nanozymes for Sustainable Agriculture offers a comprehensive exploration of nanotechnology's potential to revolutionize agriculture, presenting a promising pathway toward enhanced productivity, minimizing environmental impact, and optimal resource utilization.

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.

This book examines the fundamentals and technologies of Artificial Intelligence (AI) and describes their tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product development, agriculture, human resource management, environmental management, and marketing. The book is a boon to students, software developers, teachers, members of boards of studies, and researchers who need a reference resource on artificial intelligence and its applications and is primarily intended for use in courses offered by higher education institutions that strive to equip their graduates with Industry 4.0 skills. FEATURES: Gender disparity in the enterprises involved in the development of AI-based software development as well as solutions to eradicate such gender bias in the AI world A general framework for AI in environmental management, smart farming, e-waste management, and smart energy optimization The potential and application of AI in medical imaging as well as the challenges of AI in precision medicine AI’s role in the diagnosis of various diseases, such as cancer and diabetes The role of machine learning models in product development and statistically monitoring product quality Machine learning to make robust and effective economic policy decisions Machine learning and data mining approaches to provide better video indexing mechanisms resulting in better searchable results ABOUT THE EDITORS: Prof. Dr. P. Kaliraj is Vice Chancellor at Bharathiar University, Coimbatore, India. Prof. Dr. T. Devi is Professor and Head of the Department of Computer Applications, Bharathiar University, Coimbatore, India.