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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.
Contents
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 Analysisof 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


 
               
               
              


