Description
| Product ID: | 9781032120799 |
| Product Form: | Hardback |
| Country of Manufacture: | GB |
| Title: | Artificial Intelligence and Smart Agriculture Technology |
| Authors: | Author: M. Mondal, V. B. Prasath, Utku Kose, Subrato Bharati, Prajoy Podder |
| Page Count: | 290 |
| Subjects: | Agriculture, agribusiness and food production industries, Agriculture & related industries, Machine learning, Machine learning |
| Description: | This book explores the application use of machine learning and artificial intelligence in smart agriculture by Identifying and describing functional and non-functional technologies. It identifies and discusses smart agriculture capabilities and conceptual prototypes, as well as demonstrates critical technological solutions. 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. |
| Imprint Name: | Auerbach |
| Publisher Name: | Taylor & Francis Ltd |
| Country of Publication: | GB |
| Publishing Date: | 2022-06-27 |
