Iot And Advanced Intelligence Computation For Smart Agriculture

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IoT and Advanced Intelligence Computation for Smart Agriculture

Smart agriculture is an approach to maintaining nature without compromising the basic needs of future generations while at the same time improving the efficiency of farming. The main achievements of smart agriculture in terms of sustainable agriculture are crop rotation, controlling nutrient deficiencies in crops, pest and disease control, recycling, and water harvesting, leading to a safer environment overall. Living organisms depend on the nature of biodiversity and are exposed to pollution due to waste emissions, use of fertilizers and pesticides, degraded dead plants, and so on. The emission of greenhouse gases affects plants, animals, humans, and the environment; hence, this necessitates a better environment for living organisms. The purpose of this book is to provide a comprehensive overview of the latest advancements, challenges, and potential applications of artificial intelligence (AI) technology and the Internet of Things (IoT) in the future of intelligent agriculture. The book is primarily focused on equipping younger researchers, graduates, and professionals in the industry with the necessary knowledge to understand the advantages of AI technology, machine learning, and data analytics methods in improving current agricultural practices. Key features include the following: The book showcases the latest advancements in AI and smart agriculture technologies The text emphasizes sustainable practices supported by AI, highlighting how technology can enhance productivity while minimizing environmental impact Readers will learn how to harness big data and analytics to drive informed decision-making and optimize their agricultural yields
Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture

As technology continues to saturate modern society, agriculture has started to adopt digital computing and data-driven innovations. This emergence of “smart” farming has led to various advancements in the field, including autonomous equipment and the collection of climate, livestock, and plant data. As connectivity and data management continue to revolutionize the farming industry, empirical research is a necessity for understanding these technological developments. Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture provides emerging research exploring the theoretical and practical aspects of critical technological solutions within the farming industry. Featuring coverage on a broad range of topics such as crop monitoring, precision livestock farming, and agronomic data processing, this book is ideally designed for farmers, agriculturalists, product managers, farm holders, manufacturers, equipment suppliers, industrialists, governmental professionals, researchers, academicians, and students seeking current research on technological applications within agriculture and farming.
Agricultural Internet of Things and Decision Support for Precision Smart Farming

Author: Annamaria Castrignano
language: en
Publisher: Academic Press
Release Date: 2020-01-09
Agricultural Internet of Things and Decision Support for Smart Farming reveals how a set of key enabling technologies (KET) related to agronomic management, remote and proximal sensing, data mining, decision-making and automation can be efficiently integrated in one system. Chapters cover how KETs enable real-time monitoring of soil conditions, determine real-time, site-specific requirements of crop systems, help develop a decision support system (DSS) aimed at maximizing the efficient use of resources, and provide planning for agronomic inputs differentiated in time and space. This book is ideal for researchers, academics, post-graduate students and practitioners who want to embrace new agricultural technologies. - Presents the science behind smart technologies for agricultural management - Reveals the power of data science and how to extract meaningful insights from big data on what is most suitable based on individual time and space - Proves how advanced technologies used in agriculture practices can become site-specific, locally adaptive, operationally feasible and economically affordable