Computational Intelligence and Image Processing in Agriculture: Applications and Innovations

Revolutionizing Agricultural Quality Control with AI, Image Processing, and Computational Intelligence Techniques

As the global demand for high-quality, sustainable agricultural products increases, advanced technology becomes critical in meeting these challenges. Computational Intelligence and Image Processing in Agriculture explores how innovative technologies are transforming agricultural quality evaluation. Combining foundational concepts with practical applications, this comprehensive text delves into innovative techniques to improve accuracy, efficiency, and sustainability in quality control.

Addressing key challenges faced by researchers, practitioners, and industry professionals, contributions from leading experts in AI, agriculture, and computational intelligence provide a deep understanding of technologies such as deep learning, computer vision, and AI-driven robotics. Real-world examples, step-by-step tutorials, and code snippets make the concepts accessible and actionable, while coverage of emerging trends and future directions highlights the evolving landscape of agricultural technology. Offering interdisciplinary insights and practical tools to modernize evaluation techniques, reduce waste, enhance food safety, and meet the growing demands of sustainable farming practices, this book:

  • Addresses challenges and solutions for real-time monitoring systems in agriculture
  • Highlights cutting-edge applications such as AI-driven robotics and LiDAR in farming
  • Emphasizes sustainability and environmental impact through technological innovation
  • Offers detailed coverage of image analysis algorithms for quality control
  • Discusses ethical and environmental implications of technology in agriculture

This book is ideal for advanced undergraduate and graduate courses in agricultural engineering, computer science, and AI applications. It is also an essential reference for professionals including agricultural scientists, AI practitioners, and quality control experts.

1147284427
Computational Intelligence and Image Processing in Agriculture: Applications and Innovations

Revolutionizing Agricultural Quality Control with AI, Image Processing, and Computational Intelligence Techniques

As the global demand for high-quality, sustainable agricultural products increases, advanced technology becomes critical in meeting these challenges. Computational Intelligence and Image Processing in Agriculture explores how innovative technologies are transforming agricultural quality evaluation. Combining foundational concepts with practical applications, this comprehensive text delves into innovative techniques to improve accuracy, efficiency, and sustainability in quality control.

Addressing key challenges faced by researchers, practitioners, and industry professionals, contributions from leading experts in AI, agriculture, and computational intelligence provide a deep understanding of technologies such as deep learning, computer vision, and AI-driven robotics. Real-world examples, step-by-step tutorials, and code snippets make the concepts accessible and actionable, while coverage of emerging trends and future directions highlights the evolving landscape of agricultural technology. Offering interdisciplinary insights and practical tools to modernize evaluation techniques, reduce waste, enhance food safety, and meet the growing demands of sustainable farming practices, this book:

  • Addresses challenges and solutions for real-time monitoring systems in agriculture
  • Highlights cutting-edge applications such as AI-driven robotics and LiDAR in farming
  • Emphasizes sustainability and environmental impact through technological innovation
  • Offers detailed coverage of image analysis algorithms for quality control
  • Discusses ethical and environmental implications of technology in agriculture

This book is ideal for advanced undergraduate and graduate courses in agricultural engineering, computer science, and AI applications. It is also an essential reference for professionals including agricultural scientists, AI practitioners, and quality control experts.

132.0 In Stock
Computational Intelligence and Image Processing in Agriculture: Applications and Innovations

Computational Intelligence and Image Processing in Agriculture: Applications and Innovations

Computational Intelligence and Image Processing in Agriculture: Applications and Innovations

Computational Intelligence and Image Processing in Agriculture: Applications and Innovations

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Overview

Revolutionizing Agricultural Quality Control with AI, Image Processing, and Computational Intelligence Techniques

As the global demand for high-quality, sustainable agricultural products increases, advanced technology becomes critical in meeting these challenges. Computational Intelligence and Image Processing in Agriculture explores how innovative technologies are transforming agricultural quality evaluation. Combining foundational concepts with practical applications, this comprehensive text delves into innovative techniques to improve accuracy, efficiency, and sustainability in quality control.

Addressing key challenges faced by researchers, practitioners, and industry professionals, contributions from leading experts in AI, agriculture, and computational intelligence provide a deep understanding of technologies such as deep learning, computer vision, and AI-driven robotics. Real-world examples, step-by-step tutorials, and code snippets make the concepts accessible and actionable, while coverage of emerging trends and future directions highlights the evolving landscape of agricultural technology. Offering interdisciplinary insights and practical tools to modernize evaluation techniques, reduce waste, enhance food safety, and meet the growing demands of sustainable farming practices, this book:

  • Addresses challenges and solutions for real-time monitoring systems in agriculture
  • Highlights cutting-edge applications such as AI-driven robotics and LiDAR in farming
  • Emphasizes sustainability and environmental impact through technological innovation
  • Offers detailed coverage of image analysis algorithms for quality control
  • Discusses ethical and environmental implications of technology in agriculture

This book is ideal for advanced undergraduate and graduate courses in agricultural engineering, computer science, and AI applications. It is also an essential reference for professionals including agricultural scientists, AI practitioners, and quality control experts.


Product Details

ISBN-13: 9781394320882
Publisher: Wiley
Publication date: 11/27/2025
Sold by: JOHN WILEY & SONS
Format: eBook
Pages: 272
File size: 20 MB
Note: This product may take a few minutes to download.

About the Author

Jay Kumar Pandey is an Assistant Professor at Shri Ramswaroop Memorial University, India, and specializes in AI, machine learning, image processing, biomedical engineering, and renewable energy. Holding a Ph.D. and M.Tech. in Power Control, and an MBA in Finance&Marketing, he focuses on real-time imaging, surveillance, emotion recognition, driving AI solutions for healthcare, agriculture, disaster prediction, renewable energy, and advanced surveillance systems.

Mritunjay Rai is an Assistant Professor at Shri Ramswaroop Memorial University, India. He specializes in digital image processing, machine learning, and thermal imaging. His research, including a Ph.D. from IIT (ISM) Dhanbad, focuses on real-time thermal imaging, surveillance, and emotion recognition. With numerous publications and editorial contributions, he advances AI-driven solutions for healthcare, disaster prediction, and next-generation surveillance systems.

Tanmay Sarkar is currently working as a Lecturer in the Department of Food Processing Technology, Government of West Bengal. He is the top 2% global most cited researcher, by Stanford University, USA and Elsevier (2024). His research areas include AI, and food bioactive.

Table of Contents

Preface xvii

Acknowledgements xxi

1 Introduction 1

1.1 Introduction 2

1.2 Emerging Technologies that Use Advanced Electromagnetics 4

1.3 Wireless Mobile Communication Systems 9

1.4 Modern Pedagogy in Advanced Electromagnetics 26

1.5 Design Project: Wireless Energy Harvester 27

1.6 Conclusion 30

1.7 Questions 30

References 32

2 Vector Analyses 33

2.1 Introduction 34

2.2 Vector Analysis 35

2.3 Vector Operators: Gradient, Divergence and Curl 56

2.4 Divergence Theorem 62

2.5 Stokes’ Theorem 64

2.6 Two Vector Null Identities 66

2.7 Chapter Summary 67

Problems 69

Part I Historical Perspective 73

3 Electromagnetism 75

3.1 Introduction to Electromagnetism 75

3.2 Historical Perspective of Electromagnetic Theory 79

3.3 Time-varying/Dynamic Electromagnetics Field 81

3.4 Discussion of Advanced Electromagnetic Theory 88

3.5 Problems 93

4 Electrostatics 109

4.1 Detailed Revision of Electromagnetic Fundamentals 109

4.2 Electric Field Intensity 114

4.3 Gauss’ Law 129

4.4 Electrostatic Current and Ohm’s Law 132

4.5 Electric Energy and Joule’s Law 137

4.6 Boundary Value Problem and Electrostatic Boundary Conditions 140

4.7 Electrostatic Potential Energy 144

4.8 Summary of Electrostatic Theory 147

4.9 Problems 148

5 Magnetostatics 159

5.1 Magnetostatic 159

5.2 Magnetic Flux Density 164

5.3 Ampere’s Circuital Law 166

5.4 Magnetic Vector Potential 173

5.5 Boundary Conditions of Magnetic Fields 184

5.6 Boundary Conditions for Tangential Components of H 187

5.7 Magnetic Energy and Inductance 190

5.8 Mutual Inductance 196

5.9 Duality Between Electric and Magnetic Circuit Quantities 200

5.10 Summary of Chapter 200

5.11 Problems 202

References 206

6 Time-varying Electromagnetics 207

6.1 Introduction 208

6.2 The Dawn of Time-varying Electromagnetic Field 214

6.3 Maxwell’s Current Continuity Equation 219

6.4 Relaxation Time and Conductivity of Conductor 221

6.5 Displacement Current 222

6.6 Example of Displacement Current 225

6.7 Maxwell’s Equations 227

6.8 Boundary Conditions in Static Electromagnetic Fields 230

6.9 Boundary Conditions of Time-varying Electromagnetic Fields 232

6.10 Non-homogenous Wave Equation for Potential Functions 236

6.11 Retarded Potentials 238

6.12 Homogenous Electromagnetic Wave Equations 239

6.13 Usefulness of Phasor Notation of Field Quantities 242

6.14 Electromagnetic Spectrum 245

6.15 Summary of Time-varying Electromagnetism 247

6.16 Chapter Summary 249

6.17 Problems 250

References 253

7 Uniform Plane Wave 255

7.1 Introduction to Uniform Plane Wave 256

7.2 Fundamental Concept of Wave Propagation 259

7.3 Plane Wave Concept 262

7.4 One-dimensional Wave Equation Concept 269

7.5 Wave Motion and Wave Front 272

7.6 Phase Velocity of UPW 273

7.7 Wave Impedance 277

7.8 Time Harmonic Field Wave Equations 279

7.9 Refractive Index of Medium and Dispersion 284

7.10 Time Harmonic Wave Solution 287

7.11 Polarisation of UPW 289

7.12 Poynting Theorem 292

7.13 Static Poynting Theorem 297

7.14 Energy Balance Equation in the Presence of a Generator: In-flux and Out-flow of Power 299

7.15 Time Harmonic Poynting Vector 300

7.16 Application: Doppler Radar 306

7.17 Summary of Chapter 308

7.18 Questions: UPW Propagation 310

Part II Boundary Value problems 319

8 Reflection and Transmission of Uniform Plane Wave 321

8.1 Introduction 321

8.2 Electromagnetic Waves Analysis in the Context of Boundary Value Problems 326

8.3 Reflection and Refraction at Plane Surface 329

8.4 Normal Incidence at Dielectric Boundary 331

8.5 Concept of Standing Waves 345

8.6 Problems 361

Reference 370

9 Propagation in Emerging and Advanced Materials 371

9.1 Introduction 372

9.2 Applications 374

9.3 Normal Incidence on Imperfect Media 377

9.4 Applications of Normal Incidences on Lossy Dielectric Boundary 387

9.5 Oblique Incidence in Lossy Medium 396

9.6 Emerging Applications AEM in Precision Agriculture 416

9.7 Summary of Chapter 427

9.9 Problems 428

References 431

10 Electromagnetic Passive Guiding Devices 433

10.1 Introduction 435

10.2 Various Transmission Lines 437

10.3 Transmission Line Theory 440

10.4 Calculations of Distributive Parameters of Transmission Lines 459

10.5 Loaded Transmission Line 470

10.6 Smith Chart 495

10.7 Conclusion 515

References 516

11 Electromagnetic Testing Method 517

11.1 Basic Principles 517

11.2 History of ET 518

11.3 Who Conducted ET Method? 520

11.4 Standard for ET Method 522

11.5 Type of Standard 526

11.6 Types of ET 530

References 543

12 Simulation Tools and Artificial Intelligence 545

12.2 Functional of AI 545

12.4 Electromagnetic Simulation and Modelling 552

12.5 Electromagnetic Interference and Electromagnetic Compatibility 554

12.6 Wireless communication 558

12.7 Non-destructive Testing 565

12.8 Radar and Imaging Systems 566

References 569

13 Radio Frequency Sources and Interference 571

13.1 Introduction 571

13.2 Fundamentals of RF Sources 572

13.3 Types of RF Sources 575

13.4 Design and Operation of RF Sources 578

13.5 Introduction to EMI/EMC 580

13.6 Sources of EMI 582

13.7 Effects of EMI 584

13.8 EMC Design Principles 585

13.9 Testing and Measurement for EMI/EMC 587

13.10 Case Studies and Applications 589

13.11 Future Trends and Technologies 589

13.12 Conclusion 590

References 591

14 Deep Space Communications and Positioning 595

14.1 Introduction 595

14.2 The History of NASA’s DSN 596

14.3 The DSN Functional Description 597

14.4 Advanced Techniques in Deep Space Navigation 600

14.5 Telemetry Operations in the DSN 603

14.6 DSN Capabilities and Innovations 606

14.7 Data Types and Handling in the DSN 611

14.8 The Role of the DSN in the Apollo Program 615

References 616

Index 621

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