Internet of Things and Machine Learning in Agriculture

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Series: Internet of Things and Machine Learning
BISAC: SOC055000; COM094000
DOI: https://doi.org/10.52305/MTXX5116

Agriculture is one of the most fundamental human activities. It has kept humans happier and healthier and helped birth modern society as we know it. As farming has expanded, however, 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, Machine Learning (ML) and the Internet of Things (IoT) can play a very promising role in the agricultural industry. Some examples include: an AI-powered 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 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 irregular conditions such as high acidity and efficiently tackle these issues to improve their yield. In this book, we will point out the challenges facing the agro-industry that can be addressed by ML and IoT and explore the impacts of these technologies in the agriculture sector.

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Table of Contents

Preface

Chapter 1. Smart Farming Enabling Technologies: A Systematic Review
(Himani Mittal – PG Department of Information Technology, Goswami Ganesh Dutta Sanatan Dharma College, Chandigarh, India)

Chapter 2. Internet of Things Platform for Smart Farming
(Mukta Sharma, Neha Aggarwal – Associate Professor and Hod -CS& IT, Trinity Institute of Professional Studies, Dwarka, et al.)

Chapter 3. Internet of Things for Smart Farming
(Md. Alimul Haque, Deepa Sonal, Shameemul Haque and Kailash Kumar – Department of Computer Science, Veer Kunwar Singh University, Ara, India, et al.)

Chapter 4. A Comprehensive Review on Intelligent Systems for Mitigating Pests and Diseases in Agriculture
(G. Rekha and C. Sarada – Koneru Lakshmaiah Educational Foundation, Hyderabad, India, et al.)

Chapter 5. Plant Disease Detection Using Image Sensors: A Step Towards Precision Agriculture
(Indu Sharma, Aditi Sharma, Inderjit Singh, Rahul Kumar, Yogesh Kumar, Ashutosh Sharma – Department of Botany, Sant Baba Bhag Singh University, Khiala, Jalandhar, Punjab, India, et al.)

Chapter 6. Recent Trends in Agriculture Using IoT, Challenges and Opportunities
(S. Kannadhasan, R. Nagarajan, M. Shanmuganantham – Department of Electronics and Communication Engineering, Cheran College of Engineering, Tamilnadu, India, et al.)

Chapter 7. Early Detection of Infection/Disease in Agriculture
(N. Ambika – Department of Computer Applications, Sivananda Sarma Memorial RV College, Bangalore, India)

Chapter 8. Application of Agriculture Using IoT: Future Prospective for Smart Cities Management 5.0
(Rohit Rastogi, Sunil Kumar Prajapati, Shiv Kumar, Satyam Verma, Pardeep Kumar – Computer Science and Engineering Department, ABES Engineering College, Ghaziabad, U. P., India, et al.)

Chapter 9. The Internet of Things (IoT) for Sustainable Agriculture
(M.S. Sadiq, I.P. Singh, M.M. Ahmad And N. Karunakaran – Department of Agricultural Economics and Extension, FUD, Dutse, Nigeria, et al.)

Chapter 10. IoT Based Data Collection and Data Analytics Decision Making for Precision Farming
(A. Firos – IComputer Science & Engineering, Rajiv Gandhi University, Doimukh, Arunachal Pradesh, India)

Index

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