This book discusses major issues in the field of agriculture like crop diseases, lack of storage management, pesticide control etc. and their effective resolution via automation including IoT, wireless communications, machine learning, artificial intelligence, and deep learning.
This book discusses major issues in the field of agriculture: crop diseases, lack of storage management, pesticide control, weed management, lack of irrigation and water management and their effective resolution via automation, including IoT, wireless communications, machine learning, artificial intelligence, and deep learning. It further discusses the sterile insect technique, which is a replacement of conventional pesticide and fertilizer techniques. Hydroponics and vertical farming, two of the top-ranked agricultural engineering accomplishments of the past century, are also discussed. Features: Offers in-depth insights regarding the fundamentals of technologies associated with the agriculture sector Synthesizes earlier works of researchers and inventors in this field Sheds light on the challenges and problems of supply and demand worldwide Encourages the reader to innovate and ideate upon those issues Analyses the wide array of services provided by companies worldwide and discusses recent breakthroughs in agriculture automation This book is aimed at the work of many researchers to obtain a concise overview of the current implementation of automation in agriculture and derive important insight into its upcoming challenges.
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.
Food is a necessary aspect of human life, and agriculture is crucial to any country’s global economy. Because the food business is essential to both a country’s economy and global economy, artificial intelligence (AI)-based smart solutions are needed to assure product quality and food safety. The agricultural sector is constantly under pressure to boost crop output as a result of population growth. This necessitates the use of AI applications. Artificial Intelligence Applications in Agriculture and Food Quality Improvement discusses the application of AI, machine learning, and data analytics for the acceleration of the agricultural and food sectors. It presents a comprehensive view of how these technologies and tools are used for agricultural process improvement, food safety, and food quality improvement. Covering topics such as diet assessment research, crop yield prediction, and precision farming, this premier reference source is an essential resource for food safety professionals, quality assurance professionals, agriculture specialists, crop managers, agricultural engineers, food scientists, computer scientists, AI specialists, students, libraries, government officials, researchers, and academicians.
Machine Learning and Deep Learning for Smart Agriculture and Applications delves into the captivating realm of artificial intelligence and its pivotal role in transforming the landscape of modern agriculture. With a focus on precision agriculture, digital farming, and emerging concepts, this book illuminates the significance of sustainable food production and resource management in the face of evolving digital hardware and software technologies. Geospatial technology, robotics, the Internet of Things (IoT), and data analytics converge with machine learning and big data to unlock new possibilities in agricultural management. This book explores the synergy between these disciplines, offering cutting-edge insights into data-intensive processes within operational agricultural environments. From automated irrigation systems and agricultural drones for field analysis to crop monitoring and precision agriculture, the applications of machine learning are far-reaching. Animal identification and health monitoring also benefit from these advanced techniques. With practical case studies on vegetable and fruit leaf disease detection, drone-based agriculture, and the impact of pesticides on plants, this book provides a comprehensive understanding of the applications of machine learning and deep learning in smart agriculture. It also examines various modeling techniques employed in this field and showcases how artificial intelligence can revolutionize plant disease detection. This book serves as a comprehensive guide for researchers, practitioners, and students seeking to harness the power of AI in transforming the agricultural landscape.
Agriculture has always been a vital sector of the global economy, providing food and raw materials for industries and households. However, with the growing population, changing climate conditions, and limited resources, the agriculture sector is facing numerous challenges. To address these challenges, farmers and agricultural companies are turning to advanced technologies such as Robotics, Artificial Intelligence (AI), and the Internet of Things (IoT). This exciting new volume provides a comprehensive overview of the latest technological advances in agriculture, focusing on the use of these three cutting-edge technologies. The book will explore the potential benefits of these technologies in improving agricultural efficiency, productivity, and sustainability. Whether for the veteran engineer, scientist in the lab, student, or faculty, this groundbreaking new volume is a valuable resource for researchers and other industry professionals interested in the intersection of technology and agriculture.
This volume is the last (IV) of four under the main themes of Digitizing Agriculture and Information and Communication Technologies (ICT). The four volumes cover rapidly developing processes including Sensors (I), Data (II), Decision (III), and Actions (IV). Volumes are related to ‘digital transformation” within agricultural production and provision systems, and in the context of Smart Farming Technology and Knowledge-based Agriculture. Content spans broadly from data mining and visualization to big data analytics and decision making, alongside with the sustainability aspects stemming from the digital transformation of farming. The four volumes comprise the outcome of the 12th EFITA Congress, also incorporating chapters that originated from select presentations of the Congress. The focus in this volume is on the directions of Agriculture 4.0 which incorporates the transition to a new era of action in the Agricultural sector, represented by the evolution of digital technologies in 4 aspects: Big Data, Open Data, Internet of Things (IoT), and Cloud Computing. Under the heading of “Action,” 14 Chapters investigate the implementation of cutting-edge technologies on real world applications. It will become apparent to the reader that the penetration of ICT in agriculture can result in several benefits related to the sustainability of the sector and to yield the maximum benefits, successful management is required. The entire discussion highlights the importance of proper education in the adoption of innovative technologies starting with the adaption of educational systems to the new era and moving to the familiarization of farmers to the new technologies. This book covers topics that relate to the digital transformation of farming. It provides examples and case studies of this transformation from around the world, examines the process of diffusion of digital technologies, and assesses the current and future sustainability aspects of digital agriculture. More specifically, it deals with issues such as: Challenges and opportunities from the transition to Agriculture 4.0 Safety and health in agricultural work automation The role of digital farming on regional-spatial planning The enrollment of Social Media in IoT-based agriculture The role of education in digital agriculture Real-life implementation cases of smart agriculture around the world
THE DIGITAL AGRICULTURAL REVOLUTION The book integrates computational intelligence, applied artificial intelligence, and modern agricultural practices and will appeal to scientists, agriculturists, and those in plant and crop science management. There is a need for synergy between the application of modern scientific innovation in the area of artificial intelligence and agriculture, considering the major challenges from climate change consequences viz. rising temperatures, erratic rainfall patterns, the emergence of new crop pests, drought, flood, etc. This volume reports on high-quality research (theory and practice including prototype & conceptualization of ideas, frameworks, real-world applications, policy, standards, psychological concerns, case studies, and critical surveys) on recent advances toward the realization of the digital agriculture revolution as a result of the convergence of different disruptive technologies. The book touches upon the following topics which have contributed to revolutionizing agricultural practices. Applications of Artificial Intelligence in Agriculture (AI models and architectures, system design, real-world applications of AI, machine learning and deep learning in the agriculture domain, integration & coordination of systems and issues & challenges). IoT and Big Data Analytics Applications in Agriculture (theory & architecture and the use of various types of sensors in optimizing agriculture resources and final product, benefits in real-time for crop acreage estimation, monitoring & control of agricultural produce). Robotics & Automation in Agriculture Systems (Automation challenges, need and recent developments and real case studies). Intelligent and Innovative Smart Agriculture Applications (use of hybrid intelligence in better crop health and management). Privacy, Security, and Trust in Digital Agriculture (government framework & policy papers). Open Problems, Challenges, and Future Trends. Audience Researchers in computer science, artificial intelligence, electronics engineering, agriculture automation, crop management, and science.
This book addresses the challenges for developing and emerging trends in Internet-of-Things (IoT) for smart agriculture platforms. It also describes data analytics & machine learning, cloud architecture, automation & robotics and aims to overcome existing barriers for smart agriculture with commercial viability. It discusses IoT-based monitoring systems for analyzing the crop environment, and methods for improving the efficiency of decision-making based on the analysis of harvest statistics. The book explores a range of applications including intelligent field monitoring, intelligent data processing and sensor technologies, predictive analysis systems, crop monitoring, and weather data-enabled analysis in IoT agro-systems. This volume will be helpful for engineering and technology experts and researchers, as well as for policy-makers.
The agriculture industry is facing significant challenges in meeting the increasing demand for food while also ensuring sustainable development. Traditional agricultural methods are not equipped to meet the demands of the modern world. To overcome these challenges, Advanced Technologies and AI-Equipped IoT Applications in High-Tech Agriculture provides an in-depth analysis of the opportunities and challenges for AI-powered management tools and IoT-equipped techniques for the high-tech agricultural ecosystem. The Handbook of Research on AI-Equipped IoT Applications in High-Tech Agriculture explores advanced methodologies, models, techniques, technologies, and applications along with the concepts of real-time supporting systems to help agricultural producers adjust plans or schedules for taking care of their farms. Additionally, it discusses the role of IoT technologies and AI applications in agricultural ecosystems and their potential to improve product quality and market competitiveness. The book includes discussions on the application of blockchain, biotechnology, drones, robotics, data analytics, and visualization in high-tech agriculture. It is an essential reference for anyone interested in the future of high-tech agriculture, including agricultural analysts, investment analysts, scholars, researchers, academics, professionals, engineers, and students.
