Sustainable Farming Through Machine Learning
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Sustainable Farming Through Machine Learning
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Author : Suneeta Satpathy
language : en
Publisher: CRC Press
Release Date : 2024-11-25
Sustainable Farming Through Machine Learning written by Suneeta Satpathy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-25 with Technology & Engineering categories.
This book explores the transformative potential of machine learning (ML) technologies in agriculture. It delves into specific applications, such as crop monitoring, disease detection, and livestock management, demonstrating how artificial intelligence/machine learning (AI/ML) can optimize resource management and improve overall productivity in farming practices. Sustainable Farming through Machine Learning: Enhancing Productivity and Efficiency provides an in-depth overview of AI and ML concepts relevant to the agricultural industry. It discusses the challenges faced by the agricultural sector and how AI/ML can address them. The authors highlight the use of AI/ML algorithms for plant disease and pest detection and examine the role of AI/ML in supply chain management and demand forecasting in agriculture. It includes an examination of the integration of AI/ML with agricultural robotics for automation and efficiency. The authors also cover applications in livestock management, including feed formulation and disease detection; they also explore the use of AI/ML for behavior analysis and welfare assessment in livestock. Finally, the authors also explore the ethical and social implications of using such technologies. This book can be used as a textbook for students in agricultural engineering, precision farming, and smart agriculture. It can also be a reference book for practicing professionals in machine learning, and deep learning working on sustainable agriculture applications.
Artificial Intelligence And Iot Based Technologies For Sustainable Farming And Smart Agriculture
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Author : Tomar, Pradeep
language : en
Publisher: IGI Global
Release Date : 2021-01-08
Artificial Intelligence And Iot Based Technologies For Sustainable Farming And Smart Agriculture written by Tomar, Pradeep and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-08 with Technology & Engineering categories.
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.
Sustainable Farming Through Machine Learning
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Author : Suneeta Satpathy
language : en
Publisher:
Release Date : 2025
Sustainable Farming Through Machine Learning written by Suneeta Satpathy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Agricultural innovations categories.
"This book explores the transformative potential of ML technologies in agriculture. It delves into specific applications, such as crop monitoring, disease detection, and livestock management, demonstrating how AI/ML can optimize resource management and improve overall productivity in farming practices"--
Green Internet Of Things And Machine Learning
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Author : Roshani Raut
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-10
Green Internet Of Things And Machine Learning written by Roshani Raut and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-10 with Computers categories.
Health Economics and Financing Encapsulates different case studies where green-IOT and machine learning can be used for making significant progress towards improvising the quality of life and sustainable environment. The Internet of Things (IoT) is an evolving idea which is responsible for connecting billions of devices that acquire, perceive, and communicate data from their surroundings. Because this transmission of data uses significant energy, improving energy efficiency in IOT devices is a significant topic for research. The green internet of things (G-IoT) makes it possible for IoT devices to use less energy since intelligent processing and analysis are fundamental to constructing smart IOT applications with large data sets. Machine learning (ML) algorithms that can predict sustainable energy consumption can be used to prepare guidelines to make IoT device implementation easier. Green Internet of Things and Machine Learning lays the foundation of in-depth analysis of principles of Green-Internet of Things (G-IoT) using machine learning. It outlines various green ICT technologies, explores the potential towards diverse real-time areas, as well as highlighting various challenges and obstacles towards the implementation of G-IoT in the real world. Also, this book provides insights on how the machine learning and green IOT will impact various applications: It covers the Green-IOT and ML-based smart computing, ML techniques for reducing energy consumption in IOT devices, case studies of G-IOT and ML in the agricultural field, smart farming, smart transportation, banking industry and healthcare. Audience The book will be helpful for research scholars and researchers in the fields of computer science and engineering, information technology, electronics and electrical engineering. Industry experts, particularly in R&D divisions, can use this book as their problem-solving guide.
Smart Agricultural Services Using Deep Learning Big Data And Iot
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Author : Amit Kumar Gupta
language : en
Publisher: Engineering Science Reference
Release Date : 2020-08
Smart Agricultural Services Using Deep Learning Big Data And Iot written by Amit Kumar Gupta and has been published by Engineering Science Reference this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08 with categories.
Machine Learning And Artificial Intelligence For Agricultural Economics
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Author : Chandrasekar Vuppalapati
language : en
Publisher: Springer Nature
Release Date : 2021-10-04
Machine Learning And Artificial Intelligence For Agricultural Economics written by Chandrasekar Vuppalapati and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-04 with Business & Economics categories.
This book discusses machine learning and artificial intelligence (AI) for agricultural economics. It is written with a view towards bringing the benefits of advanced analytics and prognostics capabilities to small scale farmers worldwide. This volume provides data science and software engineering teams with the skills and tools to fully utilize economic models to develop the software capabilities necessary for creating lifesaving applications. The book introduces essential agricultural economic concepts from the perspective of full-scale software development with the emphasis on creating niche blue ocean products. Chapters detail several agricultural economic and AI reference architectures with a focus on data integration, algorithm development, regression, prognostics model development and mathematical optimization. Upgrading traditional AI software development paradigms to function in dynamic agricultural and economic markets, this volume will be of great use to researchers and students in agricultural economics, data science, engineering, and machine learning as well as engineers and industry professionals in the public and private sectors.
Smart Agriculture
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Author : Govind Singh Patel
language : en
Publisher: CRC Press
Release Date : 2021-02-10
Smart Agriculture written by Govind Singh Patel and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-10 with Technology & Engineering categories.
This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and Smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures.
Smart Farming Technologies For Sustainable Agricultural Development
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Author : Poonia, Ramesh C.
language : en
Publisher: IGI Global
Release Date : 2018-08-10
Smart Farming Technologies For Sustainable Agricultural Development written by Poonia, Ramesh C. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-10 with Technology & Engineering categories.
In order to meet food needs, farmers need to integrate the latest technologies enabling them to make more informed decisions. Smart Farming Technologies for Sustainable Agricultural Development provides innovative insights into the latest farming advancements in terms of informatics and communication. The content within this publication represents the work of topics such as sensor systems, wireless communication, and the integration of the Internet of Things in agriculture-related processes. It is a vital reference source for farmers, academicians, researchers, government agencies, technology developers, and graduate-level students seeking current research on smart farming technologies.
Agriculture 5 0
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Author : Latief Ahmad
language : en
Publisher: CRC Press
Release Date : 2021-03-24
Agriculture 5 0 written by Latief Ahmad and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-24 with Science categories.
Agriculture 5.0: Artificial Intelligence, IoT & Machine Learning provides an interdisciplinary, integrative overview of latest development in the domain of smart farming. It shows how the traditional farming practices are being enhanced and modified by automation and introduction of modern scalable technological solutions that cut down on risks, enhance sustainability, and deliver predictive decisions to the grower, in order to make agriculture more productive. An elaborative approach has been used to highlight the applicability and adoption of key technologies and techniques such WSN, IoT, AI and ML in agronomic activities ranging from collection of information, analysing and drawing meaningful insights from the information which is more accurate, timely and reliable.It synthesizes interdisciplinary theory, concepts, definitions, models and findings involved in complex global sustainability problem-solving, making it an essential guide and reference. It includes real-world examples and applications making the book accessible to a broader interdisciplinary readership. This book clarifies hoe the birth of smart and intelligent agriculture is being nurtured and driven by the deployment of tiny sensors or AI/ML enabled UAV’s or low powered Internet of Things setups for the sensing, monitoring, collection, processing and storing of the information over the cloud platforms. This book is ideal for researchers, academics, post-graduate students and practitioners of agricultural universities, who want to embrace new agricultural technologies for Determination of site-specific crop requirements, future farming strategies related to controlling of chemical sprays, yield, price assessments with the help of AI/ML driven intelligent decision support systems and use of agri-robots for sowing and harvesting. The book will be covering and exploring the applications and some case studies of each technology, that have heavily made impact as grand successes. The main aim of the book is to give the readers immense insights into the impact and scope of WSN, IoT, AI and ML in the growth of intelligent digital farming and Agriculture revolution 5.0.The book also focuses on feasibility of precision farming and the problems faced during adoption of precision farming techniques, its potential in India and various policy measures taken all over the world. The reader can find a description of different decision support tools like crop simulation models, their types, and application in PA. Features: Detailed description of the latest tools and technologies available for the Agriculture 5.0. Elaborative information for different type of hardware, platforms and machine learning techniques for use in smart farming. Elucidates various types of predictive modeling techniques available for intelligent and accurate agricultural decision making from real time collected information for site specific precision farming. Information about different type of regulations and policies made by all over the world for the motivation farmers and innovators to invest and adopt the AI and ML enabled tools and farming systems for sustainable production.
Agricultural Informatics
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Author : Amitava Choudhury
language : en
Publisher: John Wiley & Sons
Release Date : 2021-03-02
Agricultural Informatics written by Amitava Choudhury and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-02 with Computers categories.
Despite the increasing population (the Food and Agriculture Organization of the United Nations estimates 70% more food will be needed in 2050 than was produced in 2006), issues related to food production have yet to be completely addressed. In recent years, Internet of Things technology has begun to be used to address different industrial and technical challenges to meet this growing need. These Agro-IoT tools boost productivity and minimize the pitfalls of traditional farming, which is the backbone of the world's economy. Aided by the IoT, continuous monitoring of fields provides useful and critical information to farmers, ushering in a new era in farming. The IoT can be used as a tool to combat climate change through greenhouse automation; monitor and manage water, soil and crops; increase productivity; control insecticides/pesticides; detect plant diseases; increase the rate of crop sales; cattle monitoring etc. Agricultural Informatics: Automation Using the IoT and Machine Learning focuses on all these topics, including a few case studies, and they give a clear indication as to why these techniques should now be widely adopted by the agriculture and farming industries.