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AI and IoT-Based Intelligent Automation in Robotics. Edition No. 1

  • ID: 5235676
  • Book
  • April 2021
  • 432 Pages
  • John Wiley and Sons Ltd
The 24 chapters in this book provides a deep overview of robotics and the application of AI and IoT in robotics. It contains the exploration of AI and IoT based intelligent automation in robotics. The various algorithms and frameworks for robotics based on AI and IoT are presented, analyzed, and discussed. This book also provides insights on application of robotics in education, healthcare, defense and many other fields which utilize IoT and AI. It also introduces the idea of smart cities using robotics.
Note: Product cover images may vary from those shown

Preface xvii

1 Introduction to Robotics 1
Srinivas Kumar Palvadi, Pooja Dixit and Vishal Dutt

1.1 Introduction 1

1.2 History and Evolution of Robots 3

1.3 Applications 6

1.4 Components Needed for a Robot 7

1.5 Robot Interaction and Navigation 10

1.5.1 Humanoid Robot 11

1.5.2 Control 11

1.5.3 Autonomy Levels 12

1.6 Conclusion 12

References 13

2 Techniques in Robotics for Automation Using AI and IoT 15
Sandeep Kr. Sharma, N. Gayathri, S. Rakesh Kumar and Rajiv Kumar Modanval

2.1 Introduction 16

2.2 Brief History of Robotics 16

2.3 Some General Terms 17

2.4 Requirements of AI and IoT for Robotic Automation 20

2.5 Role of AI and IoT in Robotics 21

2.6 Diagrammatic Representations of Some Robotic Systems 23

2.7 Algorithms Used in Robotics 25

2.8 Application of Robotics 27

2.9 Case Studies 30

2.9.1 Sophia 30

2.9.2 ASIMO 30

2.9.3 Cheetah Robot 30

2.9.4 IBM Watson 31

2.10 Conclusion 31

References 31

3 Robotics, AI and IoT in the Defense Sector 35
Rajiv Kumar Modanval, S. Rakesh Kumar, N. Gayathri and Sandeep Kr. Sharma

3.1 Introduction 36

3.2 How Robotics Plays an Important Role in the Defense Sector 36

3.3 Review of the World’s Current Robotics Capabilities in the Defense Sector 38

3.3.1 China 38

3.3.2 United State of America 39

3.3.3 Russia 40

3.3.4 India 41

3.4 Application Areas of Robotics in Warfare 43

3.4.1 Autonomous Drones 43

3.4.2 Autonomous Tanks and Vehicles 44

3.4.3 Autonomous Ships and Submarines 45

3.4.4 Humanoid Robot Soldiers 47

3.4.5 Armed Soldier Exoskeletons 48

3.5 Conclusion 50

3.6 Future Work 50

References 50

4 Robotics, AI and IoT in Medical and Healthcare Applications 53
Pooja Dixit, Manju Payal, Nidhi Goyal and Vishal Dutt

4.1 Introduction 53

4.1.1 Basics of AI 53

4.1.1.1 AI in Healthcare 54

4.1.1.2 Current Trends of AI in Healthcare 55

4.1.1.3 Limits of AI in Healthcare 56

4.1.2 Basics of Robotics 57

4.1.2.1 Robotics for Healthcare 57

4.1.3 Basics of IoT 59

4.1.3.1 IoT Scenarios in Healthcare 60

4.1.3.2 Requirements of Security 61

4.2 AI, Robotics and IoT: A Logical Combination 62

4.2.1 Artificial Intelligence and IoT in Healthcare 62

4.2.2 AI and Robotics 63

4.2.2.1 Limitation of Robotics in Medical Healthcare 66

4.2.3 IoT with Robotics 66

4.2.3.1 Overview of IoMRT 67

4.2.3.2 Challenges of IoT Deployment 69

4.3 Essence of AI, IoT, and Robotics in Healthcare 70

4.4 Future Applications of Robotics, AI, and IoT 71

4.5 Conclusion 72

References 72

5 Towards Analyzing Skill Transfer to Robots Based on Semantically Represented Activities of Humans 75
Devi.T, N. Deepa, S. Rakesh Kumar, R. Ganesan and N. Gayathri

5.1 Introduction 76

5.2 Related Work 77

5.3 Overview of Proposed System 78

5.3.1 Visual Data Retrieval 79

5.3.2 Data Processing to Attain User Objective 80

5.3.3 Knowledge Base 82

5.3.4 Robot Attaining User Goal 83

5.4 Results and Discussion 83

5.5 Conclusion 85

References 85

6 Healthcare Robots Enabled with IoT and Artificial Intelligence for Elderly Patients 87
S. Porkodi and D. Kesavaraja

6.1 Introduction 88

6.1.1 Past, Present, and Future 88

6.1.2 Internet of Things 88

6.1.3 Artificial Intelligence 89

6.1.4 Using Robotics to Enhance Healthcare Services 89

6.2 Existing Robots in Healthcare 90

6.3 Challenges in Implementation and Providing Potential Solutions 90

6.4 Robotic Solutions for Problems Facing the Elderly in Society 98

6.4.1 Solutions for Physical and Functional Challenges 98

6.4.2 Solutions for Cognitive Challenges 98

6.5 Healthcare Management 99

6.5.1 Internet of Things for Data Acquisition 99

6.5.2 Robotics for Healthcare Assistance and Medication Management 102

6.5.3 Robotics for Psychological Issues 103

6.6 Conclusion and Future Directions 103

References 104

7 Robotics, AI, and the IoT in Defense Systems 109
Manju Payal, Pooja Dixit, T.V.M. Sairam and Nidhi Goyal

7.1 AI in Defense 110

7.1.1 AI Terminology and Background 110

7.1.2 Systematic Sensing Applications 111

7.1.3 Overview of AI in Defense Systems 112

7.2 Overview of IoT in Defense Systems 114

7.2.1 Role of IoT in Defense 116

7.2.2 Ministry of Defense Initiatives 117

7.2.3 IoT Defense Policy Challenges 117

7.3 Robotics in Defense 118

7.3.1 Technical Challenges of Defense Robots 120

7.4 AI, Robotics, and IoT in Defense: A Logical Mix in Context 123

7.4.1 Combination of Robotics and IoT in Defense 123

7.4.2 Combination of Robotics and AI in Defense 124

7.5 Conclusion 126

References 127

8 Techniques of Robotics for Automation Using AI and the IoT 129
Kapil Chauhan and Vishal Dutt

8.1 Introduction 130

8.2 Internet of Robotic Things Concept 131

8.3 Definitions of Commonly Used Terms 132

8.4 Procedures Used in Making a Robot 133

8.4.1 Analyzing Tasks 133

8.4.2 Designing Robots 134

8.4.3 Computerized Reasoning 134

8.4.4 Combining Ideas to Make a Robot 134

8.4.5 Making a Robot 134

8.4.6 Designing Interfaces with Different Frameworks or Robots 134

8.5 IoRT Technologies 135

8.6 Sensors and Actuators 137

8.7 Component Selection and Designing Parts 138

8.7.1 Robot and Controller Structure 140

8.8 Process Automation 141

8.8.1 Benefits of Process Automation 141

8.8.2 Incorporating AI in Process Automation 141

8.9 Robots and Robotic Automation 142

8.10 Architecture of the Internet of Robotic Things 142

8.10.1 Concepts of Open Architecture Platforms 143

8.11 Basic Abilities 143

8.11.1 Discernment Capacity 143

8.11.2 Motion Capacity 144

8.11.3 Manipulation Capacity 144

8.12 More Elevated Level Capacities 145

8.12.1 Decisional Self-Sufficiency 145

8.12.2 Interaction Capacity 145

8.12.3 Cognitive Capacity 146

8.13 Conclusion 146

References 146

9 An Artificial Intelligence-Based Smart Task Responder: Android Robot for Human Instruction Using LSTM Technique 149
T. Devi, N. Deepa, SP. Chokkalingam, N. Gayathri and S. Rakesh Kumar

9.1 Introduction 150

9.2 Literature Review 152

9.3 Proposed System 152

9.4 Results and Discussion 157

9.5 Conclusion 161

References 162

10 AI, IoT and Robotics in the Medical and Healthcare Field 165
V. Kavidha, N. Gayathri and S. Rakesh Kumar

10.1 Introduction 165

10.2 A Survey of Robots and AI Used in the Health Sector 167

10.2.1 Surgical Robots 167

10.2.2 Exoskeletons 168

10.2.3 Prosthetics 170

10.2.4 Artificial Organs 171

10.2.5 Pharmacy and Hospital Automation Robots 172

10.2.6 Social Robots 173

10.2.7 Big Data Analytics 175

10.3 Sociotechnical Considerations 176

10.3.1 Sociotechnical Influence 176

10.3.2 Social Valence 177

10.3.3 The Paradox of Evidence-Based Reasoning 178

10.4 Legal Considerations 180

10.4.1 Liability for Robotics, AI and IoT 180

10.4.2 Liability for Physicians Using Robotics, AI and IoT 181

10.4.3 Liability for Institutions Using Robotics, AI and IoT 182

10.5 Regulating Robotics, AI and IoT as Medical Devices 183

10.6 Conclusion 185

References 185

11 Real-Time Mild and Moderate COVID-19 Human Body Temperature Detection Using Artificial Intelligence 189
K. Logu, T. Devi, N. Deepa, S. Rakesh Kumar and N. Gayathri

11.1 Introduction 190

11.2 Contactless Temperature 191

11.2.1 Bolometers (IR-Based) 192

11.2.2 Thermopile Radiation Sensors (IR-Based) 193

11.2.3 Fiber-Optic Pyrometers 193

11.2.4 RGB Photocell 194

11.2.5 3D Sensor 195

11.3 Fever Detection Camera 196

11.3.1 Facial Recognition 197

11.3.2 Geometric Approach 198

11.3.3 Holistic Approach 198

11.3.4 Model-Based 198

11.3.5 Vascular Network 199

11.4 Simulation and Analysis 200

11.5 Conclusion 203

References 203

12 Drones in Smart Cities 205
Manju Payal, Pooja Dixit and Vishal Dutt

12.1 Introduction 206

12.1.1 Overview of the Literature 206

12.2 Utilization of UAVs for Wireless Network 209

12.2.1 Use Cases for WN Using UAVs 209

12.2.2 Classifications and Types of UAVs 210

12.2.3 Deployment of UAVS Using IoT Networks 213

12.2.4 IoT and 5G Sensor Technologies for UAVs 214

12.3 Introduced Framework 217

12.3.1 Architecture of UAV IoT 217

12.3.2 Ground Control Station 218

12.3.3 Data Links 218

12.4 UAV IoT Applications 223

12.4.1 UAV Traffic Management 223

12.4.2 Situation Awareness 223

12.4.3 Public Safety/Saving Lives 225

12.5 Conclusion 227

References 227

13 UAVs in Agriculture 229
DeepanshuSrivastava, S. RakeshKumar and N. Gayathri

13.1 Introduction 230

13.2 UAVs in Smart Farming and Take-Off Panel 230

13.2.1 Overview of Systems 230

13.3 Introduction to UGV Systems and Planning 234

13.4 UAV-Hyperspectral for Agriculture 236

13.5 UAV-Based Multisensors for Precision Agriculture 239

13.6 Automation in Agriculture 242

13.7 Conclusion 245

References 245

14 Semi-Automated Parking System Using DSDV and RFID 247
Mayank Agrawal, Abhishek Kumar Rawat, Archana, SandhyaKatiyar and Sanjay Kumar

14.1 Introduction 247

14.2 Ad Hoc Network 248

14.2.1 Destination-Sequenced Distance Vector (DSDV) Routing Protocol 248

14.3 Radio Frequency Identification (RFID) 249

14.4 Problem Identification 250

14.5 Survey of the Literature 250

14.6 PANet Architecture 251

14.6.1 Approach for Semi-Automated System Using DSDV 252

14.6.2 Tables for Parking Available/Occupied 253

14.6.3 Algorithm for Detecting the Empty Slots 255

14.6.4 Pseudo Code 255

14.7 Conclusion 256

References 256

15 Survey of Various Technologies Involved in Vehicle-to-Vehicle Communication 259
Lisha Kamala K., Sini Anna Alex and Anita Kanavalli

15.1 Introduction 259

15.2 Survey of the Literature 260

15.3 Brief Description of the Techniques 262

15.3.1 ARM and Zigbee Technology 262

15.3.2 VANET-Based Prototype 262

15.3.2.1 Calculating Distance by Considering Parameters 263

15.3.2.2 Calculating Speed by Considering Parameters 263

15.3.3 Wi-Fi–Based Technology 263

15.3.4 Li-Fi–Based Technique 264

15.3.5 Real-Time Wireless System 266

15.4 Various Technologies Involved in V2V Communication 267

15.5 Results and Analysis 267

15.6 Conclusion 268

References 268

16 Smart Wheelchair 271
Mekala Ajay, Pusapally Srinivas and Lupthavisha Netam

16.1 Background 271

16.2 System Overview 275

16.3 Health-Monitoring System Using IoT 275

16.4 Driver Circuit of Wheelchair Interfaced with Amazon Alexa 276

16.5 MATLAB Simulations 277

16.5.1 Obstacle Detection 277

16.5.2 Implementing Path Planning Algorithms 278

16.5.3 Differential Drive Robot for Path Following 280

16.6 Conclusion 282

16.7 Future Work 282

Acknowledgment 283

References 283

17 Defaulter List Using Facial Recognition 285
Kavitha Esther, Akilindin S.H., Aswin S. and Anand P.

17.1 Introduction 286

17.2 System Analysis 287

17.2.1 Problem Description 287

17.2.2 Existing System 287

17.2.3 Proposed System 287

17.3 Implementation 289

17.3.1 Image Pre-Processing 289

17.3.2 Polygon Shape Family Pre-Processing 289

17.3.3 Image Segmentation 289

17.3.4 Threshold 289

17.3.5 Edge Detection 291

17.3.6 Region Growing Technique 291

17.3.7 Background Subtraction 291

17.3.8 Morphological Operations 291

17.3.9 Object Detection 292

17.4 Inputs and Outputs 292

17.5 Conclusion 292

References 293

18 Visitor/Intruder Monitoring System Using Machine Learning 295
G. Jenifa, S. Indu, C. Jeevitha and V. Kiruthika

18.1 Introduction 296

18.2 Machine Learning 296

18.2.1 Machine Learning in Home Security 297

18.3 System Design 297

18.4 Haar-Cascade Classifier Algorithm 298

18.4.1 Creating the Dataset 298

18.4.2 Training the Model 299

18.4.3 Recognizing the Face 299

18.5 Components 299

18.5.1 Raspberry Pi 299

18.5.2 Web Camera 300

18.6 Experimental Results 300

18.7 Conclusion 302

Acknowledgment 302

References 303

19 Comparison of Machine Learning Algorithms for Air Pollution Monitoring System 305
Tushr Sethi and R. C. Thakur

19.1 Introduction 305

19.2 System Design 306

19.3 Model Description and Architecture 307

19.4 Dataset 308

19.5 Models 310

19.6 Line of Best Fit for the Dataset 312

19.7 Feature Importance 313

19.8 Comparisons 315

19.9 Results 318

19.10 Conclusion 318

References 321

20 A Novel Approach Towards Audio Watermarking Using FFT and CORDIC-Based QR Decomposition 323
Ankit Kumar, Astha Singh, Shiv Prakash and Vrijendra Singh

20.1 Introduction and Related Work 324

20.2 Proposed Methodology 326

20.2.1 Fast Fourier Transform 328

20.2.2 CORDIC-Based QR Decomposition 329

20.2.3 Concept of Cyclic Codes 331

20.2.4 Concept of Arnold’s Cat Map 331

20.3 Algorithm Design 331

20.4 Experiment Results 334

20.5 Conclusion 337

References 338

21 Performance of DC-Biased Optical Orthogonal Frequency Division Multiplexing in Visible Light Communication 339
S. Ponmalar and Shiny J.J.

21.1 Introduction 340

21.2 System Model 341

21.2.1 Transmitter Block 341

21.2.2 Receiver Block 342

21.3 Proposed Method 342

21.3.1 Simulation Parameters for OptSim 343

21.3.2 Block Diagram of DCO-OFDM in OptSim 343

21.4 Results and Discussion 344

21.5 Conclusion 352

References 353

22 Microcontroller-Based Variable Rate Syringe Pump for Microfluidic Application 355
G. B. Tejashree, S. Swarnalatha, S. Pavithra, M. C. Jobin Christ and N. Ashwin Kumar

22.1 Introduction 356

22.2 Related Work 357

22.3 Methodology 358

22.3.1 Hardware Design 359

22.3.2 Hardware Interface with Software 360

22.3.3 Programming and Debugging 361

22.4 Result 362

22.5 Inference 363

22.5.1 Viscosity (η) 365

22.5.2 Time Taken 365

22.5.3 Syringe Diameter 366

22.5.4 Deviation 366

22.6 Conclusion and Future Works 366

References 368

23 Analysis of Emotion in Speech Signal Processing and Rejection of Noise Using HMM 371
S. Balasubramanian

23.1 Introduction 372

23.2 Existing Method 373

23.3 Proposed Method 374

23.3.1 Proposed Module Description 375

23.3.2 MFCC 376

23.3.3 Hidden Markov Models 379

23.4 Conclusion 382

References 383

24 Securing Cloud Data by Using Blend Cryptography with AWS Services 385
Vanchhana Srivastava, Rohit Kumar Pathak and Arun Kumar

24.1 Introduction 385

24.1.1 AWS 387

24.1.2 Quantum Cryptography 388

24.1.3 ECDSA 389

24.2 Background 389

24.3 Proposed Technique 392

24.3.1 How the System Works 393

24.4 Results 394

24.5 Conclusion 396

References 396

Index 399

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Ashutosh Kumar Dubey Abhishek Kumar S. Rakesh Kumar N. Gayathri Prasenjit Das
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