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The reader will be familiar with the standard workflow for approaching and solving machine-learning problems, and how to address commonly encountered issues. The reader will be able to use Artificial Intelligence to tackle real-world problems ranging from crop health prediction to field surveillance analytics, classification to recognition of species of plants etc.
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This edited volume explores the integration of artificial intelligence to improve crop production. It addresses the critical need for intelligent crop management in light of the world's escalating population. Encompassing a spectrum of technologies, including computer vision, image processing, soft computing, machine learning, and deep learning, the book explores advancements in decision-making systems. It integrates data science methodologies, Internet of Things, wireless communications, and a range of sensors and actuators to provide precise, timely, and cost-effective solutions to agricultural challenges, ultimately enhancing both the quality and quantity of crop yields. The book empowers its audience to direct their efforts towards designing models and prototypes that benefit society and the environment, making it an indispensable resource for those eager to shape the future of intelligent agriculture. It serves as a comprehensive guide for students, scholars, and academicians keen on delving into the transformative field of artificial intelligence in agriculture. Researchers, scientists, and field experts will find invaluable insights to guide their exploration and contribution to this domain.
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This book brings new smart farming methodologies to the forefront, sparked by pervasive applications with automated farming technology. New indigenous expertise on smart agricultural technologies is presented along with conceptual prototypes showing how the Internet of Things, cloud computing, machine learning, deep learning, precision farming, crop management systems, etc., will be used in large-scale production in the future. The necessity of available welfare systems for farmers' well-being is also discussed in the book. It draws the conclusion that there is a greater need and demand today for smart farming methodologies driven by technology than ever before.
Agriculture --- Artificial intelligence --- Data processing. --- Agricultural applications.
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Artificial Intelligence is vital to the evolution of agriculture into a smart industry. The objective of this book is to inform readers about how artificial intelligence is improving agriculture by exploring its applications. The book addresses several aspects of artificial intelligence applications in smart agriculture including, pest control, disease identification, weed detection, and security. Chapters are contributed by experts in agriculture, computer science and biotechnology. Key Themes: Advanced machine learning techniques for pest control and disease identificationAutomated recognition and classification of plant diseases, focusing on tomatoes and pearl milletIntegration of artificial intelligence for solar-powered robots to identify weeds and damages in vegetablesDevelopment of field prevention systems to deter wild animals in farming areasUtilization of machine learning for weather forecasting to facilitate smart agriculture practicesIntelligent crop planning and precision farming through AI applicationsIntegration of artificial intelligence and drones to enhance efficiency and effectiveness in smart farming operations Other features of the book include a list of references and simple summaries in each chapter to distil the information for readers. The book is a primary reference material for courses on automation in agriculture. It can also serve as a handbook for anyone interested in advances in farming.
Agricultural innovations. --- Artificial intelligence --- Agricultural applications.
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The volume presents research works on developing Artificial Intelligence based algorithms and methodologies for making social good that too to a notable one. The book discusses latest findings on efficient technological solutions of e-governance and other areas of life from the leading researchers in the field. The prime focus is on solving socio-economic technical problems using state-of-the-art research findings like fuzzy computing, evolutionary and hybrid frameworks, neuro computing, etc., along with other AI based computation platforms. The topics covered include solution frameworks using Artificial Intelligence based models in application areas like agriculture and rural development, road accident, travel and tourism, solid waste management, rural medical care, crowd sourced election monitoring system, ragging, rape and other abuses, cyber criminals and cyber bullying, disaster management, social good, etc. The book offers a valuable resource for all undergraduate, postgraduate students and researchers interested in exploring solution frameworks for social good problems using artificial intelligence.
Artificial intelligence --- Agricultural applications. --- Industrial applications. --- Medical applications.
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"This book presents a detailed exploration of adaption and implementation of cloud IoT systems in the field of agriculture. Agro IoT bridges the gap between the conventional agricultural methods and modern technologies. Recently, cloud computing, IoT, big data, machine learning & deep learning technologies are initiated to adopt in the smart agricultural engineering. This edited book covers all the aspects of the smart agriculture with state-of-the-art Cloud IoT systems in the complete 360 degree view spectrum. This book is aimed primarily at graduates, researchers and practitioners who are engaged in agriculture engineering"--
Agricultural engineering. --- Internet of things --- Agricultural innovations. --- Agricultural applications.
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Agricultural innovations. --- Artificial intelligence --- Detectors. --- Image processing. --- Agricultural applications.
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