Internet of Things and Machine Learning in Agriculture

256 Pages·2022·11.169 MB·English

by  Vishal Jain, Jyotir Moy Chatterjee

COMPUTER SCIENCE, TECHNOLOGY AND APPLICATIONS

I T
NTERNET OF HINGS
M L
AND ACHINE EARNING
IN AGRICULTURE

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C S , T
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COMPUTER SCIENCE, TECHNOLOGY AND APPLICATIONS

I T
NTERNET OF HINGS
M L
AND ACHINE EARNING
IN AGRICULTURE

VISHAL JAIN
AND
JYOTIR MOY CHATTERJEE
EDITORS
Copyright © 2021 by Nova Science Publishers, Inc.
DOI: https://doi.org/10.52305/MTXX5116

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CONTENTS

Preface vii
Acknowledgments ix
Chapter 1 Smart Farming Enabling Technologies:
A Systematic Review 1
Himani Mittal
Chapter 2 Internet of Things Platform for Smart Farming 19
Mukta Sharma and Neha Aggarwal
Chapter 3 Internet of Things for Smart Farming 43
Md. Alimul Haque, Deepa Sonal,
Shameemul Haque and Kailash Kumar
Chapter 4 A Comprehensive Review on Intelligent Systems
for Mitigating Pests and Diseases in Agriculture 63
G. Rekha and C. Sarada
Chapter 5 Plant Disease Detection Using Image Sensors:
A Step towards Precision Agriculture 89
Indu Sharma, Aditi Sharma, Inderjit Singh,
Rahul Kumar, Yogesh Kumar
and Ashutosh Sharma
vi Contents
Chapter 6 Recent Trends in Agriculture Using IoT,
Challenges and Opportunities 131
S. Kannadhasan, R. Nagarajan
and M. Shanmuganantham
Chapter 7 Early Detection of Infection/Disease
in Agriculture 147
N. Ambika
Chapter 8 Application of Agriculture Using IoT: Future
Perspective for Smart Cities Management 5.0 171
Rohit Rastogi, Sunil Kumar Prajapati,
Shiv Kumar, Satyam Verma and Pardeep Kumar
Chapter 9 The Internet of Things (IoT)
for Sustainable Agriculture 191
M. S. Sadiq, I. P. Singh, M. M. Ahmad
and N. Karunakaran
Chapter 10 IoT Based Data Collection and Data Analytics
Decision Making for Precision Farming 215
A. Firos
About the Editors 235
Index 237
PREFACE

Agriculture is one of the most fundamental human activities. As long
as we’ve pursued it, we’ve tried to master it. Better techniques meant
greater yields. This, in turn, kept humans happier and healthier – and
helped birth modern society as we know it. There’s only one hitch in this
success story, however. As our farming has expanded, the usage of
resources such as land, fertilizer, and water has grown exponentially.
Environmental pressures from modern farming techniques have stressed
our natural landscapes. Still, by some estimates, worldwide food
production will need to increase 70% by 2050 to keep up with global
demand. With global populations rising, it falls to technology to make
farming processes more efficient and keep up with the growing demand.
Fortunately, the combination of more data from the Internet of
agricultural things and new machine learning capabilities can contribute a
crucial part. Machine Learning (ML) and the Internet of Things (IoT) can
play a very promising role in the Agricultural Industry. Some examples
will be: an artificial intelligence programmed drone to monitor the field,
an IoT designed automated crop watering system, sensors embedded in
the field to monitor temperature and humidity, etc. The agriculture
industry is the largest in the world, but when it comes to innovation here
there is a lot more to explore. IoT devices can be used to analyze the
status of crops. For instance, with soil sensors, farmers can detect any
viii Vishal Jain and Jyotir Moy Chatterjee
irregular conditions such as high acidity and efficiently tackle these
issues to improve their yield. The data gathered from sensors allows
applying analytics and getting the insight that aid decisions around
harvesting. In this book, we will try to explore the impacts of ML and
IoT in the agriculture sector and we will try to point out the challenges
facing the agro-industry which can be solved by both Machine Learning
and the Internet of Things.
Chapter 1 brings together the components required in smart farming
and how they are enabled by artificial intelligence and IoT. Chapter 2
begins with the history of agriculture, followed by advances in
agricultural technology, highlighting IoT, smart farming using IoT, the
various uses of IoT in agriculture, benefits and restrictions. Chapter 3
proposes an IoT-based model to alert farmers for soil moisture
conditions, potential damage in agricultural land from the fire and
automatic water irrigation started at low moisture of soil or fire. Chapters
4 and 5 outline intelligent systems, the studies aimed to develop
intelligent systems for identification of pests and diseases and current
literature with proposed solutions in the form of information technology
through Internet of Things (IoT), image analysis, machine learning, AI
algorithms, and cloud services. Chapter 6 demonstrates the potential of
agricultural wireless sensors and the Internet of Things (IoT), as well as
the challenges that are expected to arise when this technology is
integrated with traditional farming techniques. Chapter 7 proposes a
methodology which helps in early detection of disease or infection in
agricultural crops by suggesting a sampling methodology to detect the
infection at an early stage. Chapter 8 aims at developing an automated
smart irrigation system with the help of the Internet of Things. Its aim is
to maintain an adequate amount of water needed by the crop by
monitoring the amount of soil moisture, temperature and humidity in the
soil. Chapter 9 discusses the core ICT-enabled facilities and instruments
that have a potential productive effect on farmers, rural citizens and the
entire nation's agricultural economy. Chapter 10 discusses adapting the
capability of IoT for data collection of features of crops and for
automated decision making with data analytics algorithms.