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Convergence of Cloud Computing, AI, and Agricultural Science explores the transformative potential of integrating cutting-edge technologies into the field of agriculture. With the rapid advancements in cloud computing, Artificial Intelligence (AI), and the Internet of Things (IoT), this research presents a comprehensive framework for monitoring agriculture farms remotely using a smart cloud-based system. By leveraging IoT devices, this innovative system allows for real-time observation of farms and the collection of vast amounts of data, including audio, video, images, text, and digital maps. This data is then able to be analyzed by specialists and farmers to gain valuable insights. The book delves into the application of AI-based machine learning models, such as the Support Vector Machine (SVM), to accurately classify and process the collected data. This advanced research reference book also explores how digital information can provide farmers with information about international markets, enabling them to make informed decisions regarding their crops. Throughout the book, readers will encounter a range of compelling topics, including the development of a cloud-based architecture for effective surveillance, the use of conversational AI for farmer's advisory and communication, the application of intelligent fuzzy logic controllers to predict the impact of global warming on agriculture, and the utilization of hybrid deep learning architectures for plant disease detection in smart agriculture applications. With its academic tone and in-depth exploration of cloud computing in smart agriculture, this book serves as an essential resource for researchers, academics, and professionals in the fields of agriculture, computer science, and environmental science. By examining the convergence of cloud computing, AI, and agricultural science, it provides a roadmap for harnessing technology to revolutionize farming practices and ensure sustainable agri-food systems in the digital era.
