Internet of Things and Machine Learning in Agriculture: Technological Impacts and Challenges

by Jyotir Moy Chatterjee (Editor), Abhishek Kumar (Editor), Pramod Singh Rathore (Editor), Vishal Jain (Editor)

Overview

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.

Product Details

ISBN-13:	9783110691283
Publisher:	De Gruyter
Publication date:	02/08/2021
Series:	De Gruyter Frontiers in Computational Intelligence , #8
Sold by:	Barnes & Noble
Format:	eBook
Pages:	424
File size:	16 MB
Note:	This product may take a few minutes to download.
Age Range:	18 Years

About the Author

Jyotir Moy Chatterjee, LBEF, Nepal; Abhishek Kumar, CUIET, India; P. S. Rathore, ACERC, India; Vishal Jain, Sharda University, India

Table of Contents

Preface vii

Acknowledgments ix

List of contributors xiii

Part I Machine learning and Internet of things in agriculture

1 Smart farming: using loT and machine learning techniques Parul Verma Umesh Kumar 3

2 Food security and farming through loT and machine learning Ashish Tripathi Arun Kumar Singh Khararee Narayan Singh Krishna Kant Singh Pushpa Choudhary Prem Chand Vashist 21

3 An innovative combination for new agritechnological era Jyoti Batra Arora 41

4 Recent advancements and challenges of artificial intelligence and IoT in agriculture Nilesh Uke Trupti Thite Supriya Saste 65

5 Technological impacts and challenges of advanced technologies in agriculture Sivakumar Rajagopal Sonai Rajan Thangaraj J. Paul Mansingh B. Prabadevi 83

Part II Applications of Internet of things in agriculture

6 IoT-based platform for smart farming - Kaa Aarti Amit Kumar 109

7 Internet of things platform for smart farming K. Krishnaveni E. Radhamani K. Preethi 131

8 Internet of things platform for smart farming Jibin Varghese J. Jeba Praba John J. Georrge 159

9 Internet of things platform for smart farming Nikunj Rajyaguru Shubhendu Vyas Kunjan Vyas 169

Part III Applications of machine learning in agriculture

10 Kisan-e-Mitra: a tool for soil quality analyzer and recommender system Suvarna Pawar Pravin Futane 205

11 Artificial intelligence for plant disease detection: past, present, and future J. H. Kamdar M. D. Jasani J. D. Jasani J. Jeba Praba John J. Georrge 223

12 Wheat rust disease identification using deep learning Sapna Nigam Rajni Jain Sudeep Marwaha Alka Arora 239

13 Image-based hibiscus plant disease detection using deep teaming Sandip Kumar Roy Preeta Sharan 251

14 Rainfall prediction by applying machine learning technique Mahua Bose Kalyani Mali 275

15 Plant leaf disease classification based on feature selection and deep neural network Tan Pham Nhat Son Vu Truong Dao 293

16 Using deep learning for image-based plant disease detection Shubhendu Vyas Nikunj Rajyaguru Kunjan Vyas 323

17 Using deep learning for image-based plant disease detection Yash Joshi Sachit Mishra R. S. Ponmagal 355

18 Using deep learning for image-based plant disease detection Punam Bedi Pushkar Gole Sumit Kumar Agarwal 369

Index 403