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Internet of Things and Machine Learning in Agriculture
Technological Impacts and Challenges
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Edited by:
Jyotir Moy Chatterjee
Language:
English
Published/Copyright:
2021
About this book
Agriculture is one of the most fundamental human activities. As the farming capacity has expanded, the usage of resources such as land, fertilizer, and water has grown exponentially, and environmental pressures from modern farming techniques have stressed natural landscapes. Still, by some estimates, worldwide food production needs to increase to keep up with global food demand. Machine Learning and the Internet of Things can play a promising role in the Agricultural industry, and help to increase food production while respecting the environment. This book explains how these technologies can be applied, offering many case studies developed in the research world.
Author / Editor information
Jyotir Moy Chatterjee, LBEF, Nepal; Abhishek Kumar, CUIET, India; P. S. Rathore, ACERC, India; Vishal Jain, Sharda University, India
Topics
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Frontmatter
I -
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Preface
VII -
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Acknowledgments
IX -
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Contents
XI -
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List of contributors
XIII - Part I: Machine learning and Internet of things in agriculture
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1 Smart farming: using IoT and machine learning techniques
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2 Food security and farming through IoT and machine learning
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3 An innovative combination for new agritechnological era
41 -
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4 Recent advancements and challenges of artificial intelligence and IoT in agriculture
65 -
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5 Technological impacts and challenges of advanced technologies in agriculture
83 - Part II: Applications of Internet of things in agriculture
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6 IoT-based platform for smart farming – Kaa
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7 Internet of things platform for smart farming
131 -
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8 Internet of things platform for smart farming
159 -
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9 Internet of things platform for smart farming
169 - Part III: Applications of machine learning in agriculture
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10 Kisan-e-Mitra: a tool for soil quality analyzer and recommender system
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11 Artificial intelligence for plant disease detection: past, present, and future
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12 Wheat rust disease identification using deep learning
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13 Image-based hibiscus plant disease detection using deep learning
251 -
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14 Rainfall prediction by applying machine learning technique
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15 Plant leaf disease classification based on feature selection and deep neural network
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16 Using deep learning for image-based plant disease detection
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17 Using deep learning for image-based plant disease detection
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18 Using deep learning for image-based plant disease detection
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Index
403
Publishing information
Pages and Images/Illustrations in book
eBook published on:
February 8, 2021
eBook ISBN:
9783110691276
Hardcover published on:
February 8, 2021
Hardcover ISBN:
9783110691221
Pages and Images/Illustrations in book
Front matter:
16
Main content:
408
Illustrations:
170
Tables:
43
Keywords for this book
Internet der Dinge; Big Data; Künstliche Intelligenz; Maschinelles Lernen; Agrarwissenschaften; Umweltwissenschaften
Audience(s) for this book
Post Graduate students, Research Scholars, Researchers, Practitioners in the Agricultural Industries.
Safety & product resources
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Manufacturer information:
Walter de Gruyter GmbH
Genthiner Straße 13
10785 Berlin
productsafety@degruyterbrill.com
