Amitava Choudhury - Agricultural Informatics: Automation Using the IoT and Machine Learning

Scrivener Publishing
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Advances in Learning Analytics for Intelligent Cloud-IoT Systems

Series Editor: Dr. Souvik Pal and Dr. Dac-Nhuong Le

The role of adaptation, learning analytics, computational Intelligence, and data analytics in the field of cloud-IoT systems is becoming increasingly essential and intertwined. The capability of an intelligent system depends on various self-decision-making algorithms in IoT devices. IoT-based smart systems generate a large amount of data (big data) that cannot be processed by traditional data processing algorithms and applications. Hence, this book series involves different computational methods incorporated within the system with the help of analytics reasoning and sense-making in big data, which is centered in the cloud and IoT-enabled environments. The series publishes volumes that are empirical studies, theoretical and numerical analysis, and novel research findings.

Submission to the series:
Please send proposals to Dr. Souvik Pal, Department of Computer Science and Engineering, Global Institute of Management and Technology, Krishna Nagar, West Bengal, India.
E-mail:

Publishers at Scrivener
Martin Scrivener ()
Phillip Carmical ()

Edited by

Amitava Choudhury,

Arindam Biswas, Manish Prateek

and

Amlan Chakrabarti

This edition first published 2021 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA
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Library of Congress Cataloging-in-Publication Data

ISBN 978-1-119-76884-5

Cover image: Pixabay.Com
Cover design by Russell Richardson

Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines

Printed in the USA

10 9 8 7 6 5 4 3 2 1

The emergence of automation in agriculture has become an important issue for every country. The world population is increasing at a very fast rate, and along with this increase in population the need for food is also increasing at a brisk pace. Traditional methods used by farmers are no longer sufficient to serve this increasing demand, resulting in the intensified use of harmful pesticides. This in turn has had a profound effect on agricultural practices, which in the end can render the land barren. This book discusses the different automation practices, including the internet of things (IoT), wireless communications, machine learning, artificial intelligence, and deep learning, currently being employed to address this problem. There are some areas of concern in the field of agriculture, such as crop disease, lack of storage, weed and water management, pesticide control, and lack of irrigation, all of which can be solved using the different techniques mentioned above.

From the earliest civilizations up till now, clothing, shelter and food have been the three primary needs of human beings that have remained constant. And even though we have become quite advanced in addressing issues related to housing and clothing, despite the increasing population (as per the Food and Agriculture Organization of the United Nations, 70% more food will need to be produced in 2050 than was produced in 2006), issues related to food production have yet to be completely addressed. In recent years, the IoT began to be used to address different industrial and technical challenges to meet this growing need. Therefore, now is the time to meet the future demands of farming which can only be accomplished by smart Agro-IoT tools. This will in turn boost productivity and minimize the pitfalls of traditional farming, which is the backbone of the worlds economy. Aided by the IoT, continuous monitoring of fields will provide useful information to farmers, ushering in a new era in farming. The IoT can be used as a tool to combat climate change; monitor and manage water, land, soil and crops; increase productivity; control insecticides/pesticides; detect plant diseases; increase the rate of crop sales; etc. This book will focus on some case studies that involve monitoring of climate conditions, greenhouse automation, crop management, cattle monitoring and management for smart farming with IoT devices, which will give a clear indication as to why these techniques should be used in agriculture rather than some of the previously developed agricultural tools currently in use.

Organization of the Book

We are delighted to present this book, which was made possible with the support and contributions from academicians from various highly reputable institutions. It is a manifestation of various interesting and important aspects of theoretical and applied research covering complementary facets of innovative algorithms and applications in the fields of agriculture and cultivation processes, including:

• Machine learning algorithm and its role in agriculture
• Smart farming using machine learning and the IoT
• Agricultural informatics vis--vis the IoT
• Application of agricultural drones
• Real-time monitoring of environmental parameters in agriculture
• Deep neural network-based multiclass image classification of plant diseases