Green internet of things and machine learning : towards a smart sustainable world / edited by Roshani Raut [and more]

Includes bibliographical references and index.

Table of Contents

Preface xvii

1 G-IoT and ML for Smart Computing 1
Karunendra Verma, Vineet Raj Singh Kushwah and Nilesh

1.1 Introduction 2

1.2 Machine Learning 2

1.3 Deep Learning 6

1.4 Correlation Between AI, ML, and dl 7

1.5 Machine Learning–Based Smart Applications 7

1.6 IoT 11

1.7 Green IoT 12

1.8 Green IoT–Based Technologies 13

1.9 Life Cycle of Green IoT 16

1.10 Applications 16

1.11 Challenges and Opportunities for Green IoT 21

1.12 Future of G-IoT 22

1.13 Conclusion 22

References 23

2 Machine Learning–Enabled Techniques for Reducing Energy Consumption of IoT Devices 27
Yogini Dilip Borole, Jaya Dofe and C. G. Dethe

2.1 Introduction 28

2.2 Internet of Things (IoT) 33

2.3 Empowering Tools 35

2.4 IoT in the Energy Sector 48

2.5 Difficulties of Relating IoT 61

2.6 Future Trends 66

2.7 Conclusion 72

References 73

3 Energy-Efficient Routing Infrastructure for Green IoT Network 87
Pradeep Bedi, S. B. Goyal, Jugnesh Kumar and Shailesh Kumar

3.1 Introduction 88

3.2 Overview of IoT 89

3.3 Perspectives of Green Computing: Green IoT 91

3.4 Routing Protocols for Heterogeneous IoT 99

3.5 Machine Learning Application in Green IoT 104

3.6 Conclusion 107

References 107

4 Green IoT Towards Environmentally Friendly, Sustainable and Revolutionized Farming 113
Ravi Manne and Sneha Chowdary Kantheti

4.1 Introduction 114

4.2 How is Machine Learning Used in Agricultural Field? 119

4.3 What is IoT? How Can IoT Be Applied in Agriculture? 127

4.4 What is Green IoT and Use of Green IoT in Agriculture? 130

4.5 Conclusion: Risks of Using G-IoT in Agriculture 135

References 138

5 CIoT: Internet of Green Things for Enhancement of Crop Data Using Analytics and Machine Learning 141
Sahana Shetty and Narayana Swamy Ramaiah

5.1 Introduction 142

5.2 Motivation 146

5.3 Review of Literature 147

5.4 Problem with Traditional Approach 154

5.5 Tool Requirement 155

5.6 Methodology 159

5.7 Conclusion 160

References 161

6 Smart Farming Through Deep Learning 163
Sandeep Mathur, Disha Vaid and Ajay Rana

6.1 Introduction 163

6.2 Literature Review 165

6.3 Deep Learning in Agriculture 169

6.4 Smart Farming 174

6.5 Image Analysis of Agricultural Products 176

6.6 Land-Quality Check 178

6.7 Arduino-Based Soil Moisture Reading Kit 180

6.8 Conclusion 183

6.9 Future Work 184

References 185

7 Green IoT and Machine Learning for Agricultural Applications 189
Keshavi Nalla and Seshu Vardhan Pothabathula

7.1 Introduction 190

7.2 Green IoT 192

7.3 Machine Learning 201

7.4 Conclusion 210

References 210

8 IoT-Enabled AI-Based Model to Assess Land Suitability for Crop Production 215
Aneesha Gudavalli, G. JayaLakshmi and Suneetha Manne

8.1 Introduction 216

8.2 Literature Survey 217

8.3 Conclusion 235

References 235

9 Green Internet of Things (GIoT): Agriculture and Healthcare Application System (GIoT-AHAS) 239
Anil L. Wanare and Sahebrao N. Patil

9.1 Introduction 240

9.2 Relevant Work and Research Motivation for GIoT-AHAS 243

9.3 Conclusion 263

References 264

10 Green IoT for Smart Transportation: Challenges, Issues, and Case Study 269
Pradnya Borkar, Vijaya Balpande, Ujjwala Aher, Roshani Raut and M. Sulas Borkar

10.1 Introduction 270

10.2 Challenges of IoT 270

10.3 Green IoT Communication Components 274

10.4 Applications of IoT and Green IoT 275

10.5 Issues of Concern 279

10.6 Challenges for Green IoT 280

10.7 Green IoT in Smart Transportation: Case Studies

10.8 Conclusion 292

References 292

11 Green Internet of Things (IoT) and Machine Learning (ML): The Combinatory Approach and Synthesis in the Banking Industry 297
Prakashkumar Hasmukhbhai Patel, Chetan K Rathod and Karan Zaveri

11.1 Introduction 298

11.2 Research Objective 299

11.3 Methodology 299

11.4 Result and Discussion 299

11.5 Conclusion 313

References 314

12 Green Internet of Things (G-IoT) Technologies, Application, and Future Challenges 317
Komal Saxena, Abdul Basit and Vinod Kumar Shukla

12.1 Introduction 318

12.2 The Internet of Thing (IoT) 319

12.3 Elements of IoT 322

12.4 The Green IoT: Overview 325

12.5 Green IoT Technologies 326

12.6 Green IoT Applications 329

12.7 IoT in 5G Wireless Technologies 333

12.8 Internet of Things in Smart City 335

12.9 Green IoT Architecture for Smart Cities 337

12.10 Advantages and Disadvantages of Green IoT 342

12.11 Opportunities and Challenges 343

12.12 Future of Green IoT 344

12.13 Conclusion 345

References 345

Index 349

The Internet of Things (IoT) is an evolving idea which is responsible for connecting billions of devices that acquire, perceive, and communicate data from their surroundings. Because this transmission of data uses significant energy, improving energy efficiency in IOT devices is a significant topic for research. The green internet of things (G-IoT) makes it possible for IoT devices to use less energy since intelligent processing and analysis are fundamental to constructing smart IOT applications with large data sets. Machine learning (ML) algorithms that can predict sustainable energy consumption can be used to prepare guidelines to make IoT device implementation easier. Green Internet of Things and Machine Learning lays the foundation of in-depth analysis of principles of Green-Internet of Things (G-IoT) using machine learning. It outlines various green ICT technologies, explores the potential towards diverse real-time areas, as well as highlighting various challenges and obstacles towards the implementation of G-IoT in the real world. Also, this book provides insights on how the machine learning and green IOT will impact various applications: It covers the Green-IOT and ML-based smart computing, ML techniques for reducing energy consumption in IOT devices, case studies of G-IOT and ML in the agricultural field, smart farming, smart transportation, banking industry and healthcare.

About the Author

Roshani Raut, PhD is an associate professor in the Department of Information Technology at Pimpri Chinchwad College of Engineering, Pune University, India. She has presented and published more than 70 research communications in national/international conferences and journals and has published 13 patents.

Sandeep Kautish, PhD is a professor & Dean of Academics with LBEF Campus, Kathmandu Nepal. He has published more than 40 papers in international journals.

Zdzislaw Polkowski, PhD is a professor in the Faculty of Technical Sciences, Jan Wyzykowski University, Polkowice, Poland. He has published more than 75 research articles in peer-reviewed journals.

Anil Kumar, PhD is a professor of CSE and Head of Department of Information Technology, DIT University, India. He has published more than 200 research papers.

Chuan-Ming Liu, PhD is a professor in the Department of Computer Science and Information Engineering (CSIE), National Taipei University of Technology (Taipei Tech), Taiwan. He has published more than 100 research article is international journals.