Preface

Agriculture provides an opportunity to enhance the lives of millions suffering from food insecurity and to aid countries in developing economies that generate employment and increase incomes. In order to feed the world's population, agriculture in the modern day must produce more food. In the agricultural industry, brand-new technologies and solutions are being introduced to provide an excellent alternative for the collection and processing of data while simultaneously enhancing net productivity. An innovation in network-based high-tech farm management, smart farming focuses on incorporating information and communication technology into equipment, machinery, and sensors. It is anticipated that new technologies like cloud computing and the Internet of Things (IoT) will spur expansion and make it easier for farmers to employ robots using artificial intelligence. It includes a number of technologies, including wireless sensor networks, cloud computing, and artificial intelligence. Real-time processing, live remote analysis, and administrative capabilities are a few advantages of these technologies. To increase yields and save costs, IoT devices monitor soil conditions, weather patterns, crops, animals, and insect infestations. The Internet of Things is the focus of extensive study worldwide, with an emphasis on improved wireless communication in smart agriculture, which encompasses crop production, livestock farming, snail farming, and aquaculture.

This book, “IoT-Based Technologies for Precision Farming and Smart Agriculture,” aims to present a comprehensive overview of the latest developments, applications, and research trends in this rapidly evolving domain. It brings together contributions from researchers, academicians, and practitioners to highlight how IoT, combined with data analytics, machine learning, and sensor technologies, is reshaping modern agriculture. The scope of this volume covers a wide range of topics, including smart farming concepts, IoT-based crop management systems, precision agriculture techniques, and intelligent irrigation strategies. It also explores emerging areas such as predictive analytics, image processing for yield improvement, integration of RFID and sensor networks, and the use of machine learning and deep learning in agricultural decision-making. Additionally, the book addresses applications across diverse farming sectors such as aquaculture, livestock management, and urban farming, as well as sustainable rural development.

A key objective of this book is to bridge the gap between theoretical research and practical implementation. By presenting functional frameworks, case studies, and technological insights, it seeks to provide readers with a clear understanding of how IoT-enabled solutions can enhance productivity, reduce resource wastage, and improve overall farm management efficiency.

This book is intended for researchers, students, industry professionals, and policymakers who are interested in smart agriculture and precision farming technologies. It also serves as a valuable reference for those exploring interdisciplinary approaches involving electronics, communication systems, data science, and agricultural engineering. We sincerely hope that this book will contribute to advancing knowledge in the field and inspire further innovation toward building a sustainable, technology-driven agricultural ecosystem.