Artificial Intelligence In Daily Life

Organization of This Book......Page 6
Readers of This Book......Page 10
How to Use This Book?......Page 11
 Acknowledgements......Page 12
 About This Book......Page 14
 Contents......Page 16
 About the Author......Page 25
Part I AI Concepts......Page 27
1 A Brief Journey of Human Intelligence......Page 28
1.2 Greek Mythology—Prometheus......Page 29
1.4 Philosophical View of Human Intelligence—Mind‒Body Dualism......Page 30
1.5 Philosophical View of Human Intelligence—Kant and Priori Knowledge......Page 32
1.6 Psychological View of Human Intelligence......Page 33
1.7 Cognitive Scientific View of Human Intelligence......Page 35
1.8 Neuroscience View of Human Intelligence......Page 38
1.9 Conclusion......Page 40
References......Page 42
2 AI Fundamentals......Page 44
2.1 What is AI?......Page 45
2.2.2 First Golden Age of AI (1956–1974)......Page 47
2.2.3 First Winter of AI (1974–1980s)......Page 49
2.2.4 Second Golden Age of AI (1980–1987)......Page 50
2.2.5 Second Winter of AI (1987–1993)......Page 51
2.2.6 Third Golden Age of AI (1994–Now)......Page 52
2.3 Turing Test and AI......Page 53
2.4 Strong AI Versus Weak AI......Page 54
2.4.2 Weak (Soft) AI......Page 56
2.6 Case Study—John Searle’s Chinese Room Thought Experiment......Page 58
2.7 Conclusion......Page 59
References......Page 61
Part II AI Technology......Page 63
3 Machine Learning......Page 64
3.1 The von Neumann Machine......Page 65
3.2 Case 1–7—Day Weather Forecast System......Page 67
3.4 How Humans Learn?......Page 68
3.5 Three Pillars of Machine Learning Methods......Page 70
3.6 Supervised Learning......Page 71
3.7 Unsupervised Learning......Page 72
3.7.1 Pattern Clustering......Page 73
3.7.2 Figure-Ground Segmentation......Page 74
3.7.3 High-Level Mental Process......Page 75
3.8 Reinforcement Learning......Page 76
3.9.1 Our Brain......Page 77
3.9.2 Integrate-and-Fire Operations in Biological Neural Network......Page 79
3.10.1 A Neuron Model......Page 80
3.10.2 Artificial Neural Network......Page 82
3.10.3 Classification of Neural Networks by Machine Learning Technique......Page 83
3.11.1 Associative Neural Network for Associative Learning......Page 84
3.11.2 Hopfield Network for Memory Storage and Retrieval......Page 85
3.11.3 Feedforward Backpropagation Network for Supervised Learning......Page 86
3.11.4 Actor-Critic Multi-agent Model for Reinforcement Learning......Page 88
3.12 Case Study—Learning at School......Page 89
3.13 Conclusion......Page 90
References......Page 91
4 Data Mining......Page 94
4.1 What is Data Mining?......Page 95
4.3 Knowledge Discovery Process (KDP)......Page 96
4.4 Data Preprocessing......Page 98
4.5 Data Cleaning......Page 100
4.6 Data Integration......Page 101
4.7 Data Transformation......Page 103
4.8 Data Discretization......Page 104
4.9 Data Normalization......Page 106
4.10 Feature Extraction......Page 107
4.11 Data Reduction......Page 110
4.12 Dimension Reduction......Page 114
4.13 Classical Methods of Data Mining......Page 115
4.14 Classification Using Decision Tree......Page 116
4.15 Clustering Using KNN Method......Page 119
4.16 Regression Method......Page 123
4.17 Association Rule Method......Page 128
4.18 Deep Neural Networks for Data Mining......Page 132
4.19 Case Study: Where to Open a New Pizza Shop?......Page 136
4.20 Conclusion......Page 138
References......Page 139
5 Computer Vision......Page 142
5.1 What is Computer Vision?......Page 143
5.2 How Human See the World?......Page 144
5.3 Real-World Versus Perceived World......Page 145
5.4 How Computer See?......Page 147
5.5 Main Components of Computer Vision......Page 148
5.6.1 Gestalt Theory of Visual Perception......Page 149
5.6.2 Traditional Figure-Ground Segmentation Methods......Page 151
5.6.3 Neural Oscillators in Our Brain......Page 154
5.6.4 Figure-Ground Segmentation Using Neuro-oscillators......Page 156
5.6.5 Lee-Associator and Gestalt Visual Perception......Page 158
5.7.1 How Human Recognize Objects?......Page 159
5.7.2 Classical Object Recognition Model......Page 161
5.7.3 Model Extraction and Object Matching Technique......Page 162
5.7.4 Feature Extraction and Object Matching Technique......Page 163
5.7.5 Combine Extraction and Object Matching Technique......Page 164
5.7.6 Objection Recognition Using Neural Oscillators......Page 165
5.8.1 VR and Shared Consciousness......Page 167
5.8.2 3D Modelling Technology in Computer Vision......Page 168
5.8.3 3D from VR to AR......Page 169
5.9 Applications of Computer Vision in Daily Activities......Page 171
5.10 Case Study: Gait Recognition......Page 173
5.11 Conclusion......Page 175
References......Page 176
6 Natural Language Processing......Page 179
6.1 Human Language and Intelligence......Page 180
6.2 Levels of Linguistic in Human Language......Page 181
6.3 Ambiguity in Human Language......Page 184
6.4 A Brief History of NLP......Page 185
6.5 Natural Language Processing and AI......Page 189
6.6 Main Components of NLP......Page 190
6.7 Natural Language Understanding (NLU)......Page 192
6.8.1 Speech Recognition: The Basics......Page 194
6.8.2 Hidden Markov Model (HMM)......Page 195
6.9.1 Parsing......Page 197
6.10 Semantic Analysis......Page 198
6.11 Pragmatic Analysis......Page 200
6.12 Speech Synthesis......Page 201
6.13 Applications of NLP......Page 205
6.14 Case Study: Language Learning Robots Using NLP......Page 210
6.15 Conclusion......Page 211
References......Page 213
7 Ontological-Based Search Engine......Page 215
7.1 World Wide Web and Search Engine......Page 216
7.2 A Brief History of Search Engine......Page 218
7.3 Main Components of Search Engine......Page 220
7.4 Google Crawler......Page 222
7.5.1 Google Search Engine......Page 224
7.5.2 Google Image Search......Page 226
7.5.3 Harvest Search Engine......Page 227
7.5.4 AltaVista Search Engine......Page 228
7.6.1 Search Performance Perspective......Page 230
7.6.2 User Perspective......Page 231
7.7.1 From Knowledge to Computational Knowledge......Page 233
7.7.2 Knowledge Engineering and Representation......Page 234
7.7.3 What is Ontology?......Page 235
7.7.4 Computational Ontology......Page 237
7.7.5 Ontology Engineering Tools......Page 241
7.8.1 What is Semantic Web?......Page 242
7.8.2 Semantic Web Framework......Page 244
7.8.3 Semantic Modeling......Page 245
7.8.4 Ontology Languages––RDF......Page 248
7.8.5 Ontology Languages––OWL......Page 249
7.9.1 KnowledgeSeeker......Page 251
7.9.2 Ontology Graph......Page 253
7.9.3 Ontology Learning Model......Page 254
7.10.1 Intelligent Content Management System......Page 255
7.10.2 Intelligent News Retrieval and Ontological Search Engine......Page 256
7.10.3 Intelligent Web Ontology Learning System......Page 258
7.11 Case Study: Language Learning Robots Using NLP......Page 259
7.12 Conclusion......Page 260
References......Page 261
Part III AI Applications......Page 264
8 Intelligent Agents and Software Robots......Page 265
8.1 Intelligent Agents––The Soul of Robotics......Page 266
8.2 What Are Intelligent Agents?......Page 268
8.3 Basic Requirements of Intelligent Agents......Page 269
8.4 Variety of Intelligent Agents......Page 270
8.5 General-Purpose Intelligent Agent (GIA)......Page 272
8.7 Intelligent Agent Framework......Page 273
8.8.1 Agent Shoppers......Page 275
8.8.2 Agent Negotiators......Page 276
8.8.3 Agent Weatherman......Page 278
8.8.4 COSMOS Traders......Page 279
8.9 Agent Technology––Threats and Challenges......Page 281
8.10 Case Study: Shopping and Bargaining Agents......Page 282
References......Page 283
9 Intelligent Transportation......Page 285
9.1 Transportation and Society......Page 286
9.2 From 1 to 5G Technology......Page 287
9.3 5G Specification......Page 291
9.4 Intelligent Transportation System (ITS)......Page 292
9.5.1 5G-Enabled ITS Technology......Page 293
9.5.2 Vehicle-To-Everything (V2X) Technology......Page 295
9.6 Potential Applications of ITS with 5G and AI Technology......Page 296
9.6.3 Intelligent Traffic Management Systems......Page 297
9.6.4 Emergency Response Services......Page 298
9.8 Conclusions......Page 299
References......Page 301
10 Smart Health......Page 303
10.1 Healthcare in the Twenty-First Century......Page 304
10.2 Internet of Things (IoT)......Page 305
10.4.1 Wearable Technology and Health......Page 307
10.4.2 Healthcare Sensing Technology Applied to Wearable Devices......Page 308
10.4.3 Example of Wearables for Health Care......Page 309
10.5 Health Chatbot......Page 313
10.6 Robot-Assisted Surgery (RAS) Technology......Page 314
10.7 Case Study: Can AI Replace a Real Doctor?......Page 316
10.8 Conclusion......Page 317
References......Page 318
11 Smart Education......Page 320
11.1 Smart Education—An Introduction......Page 321
11.2 What is Smart Education?......Page 322
11.3 The Technology of Smart Education (TEL)......Page 325
11.4 Framework of Smart Education......Page 326
11.4.1 Smart Learners......Page 327
11.4.2 Smart Pedagogy......Page 329
11.4.3 Smart Learning Environments......Page 330
11.5 3D Holographic AI Teacher......Page 332
11.6 Language Chatbot Tutor......Page 333
11.7 Case Study: A New Era of Smart Education......Page 334
11.8 Conclusion......Page 336
References......Page 337
12 Smart City......Page 340
12.1 What is a Smart City?......Page 341
12.2 Major Components of Smart Cities......Page 342
12.3 Smart City Infrastructure......Page 344
12.4 Progress of Smart Cities in Different Countries......Page 345
12.5 Smart Transportation......Page 347
12.6 Smart Energy......Page 348
12.7 Smart Health Care......Page 349
12.8 Smart Technology......Page 351
12.9 IoT and Smart City......Page 352
12.10 Big Data and Smart City......Page 353
12.11 AI and Smart City......Page 354
12.12 Smart Pole......Page 356
12.13 Smart House......Page 357
12.14 Smart Campus......Page 359
12.15 Smart Cities—Challenges and Opportunities......Page 361
12.17 Conclusion......Page 362
References......Page 364
Part IV Beyond AI......Page 365
13 AI and Self-consciousness......Page 366
13.1 Consciousness in Machine......Page 367
13.2 Good Old-Fashioned Artificial Consciousness (GOFAC)......Page 368
13.3 The Hard Problem of Robot Consciousness......Page 370
13.4 Major Components of Robot Consciousness......Page 371
13.4.1 Functionalism......Page 372
13.4.2 Information Integration......Page 373
13.4.3 Embodiment......Page 375
13.4.4 Enaction......Page 377
13.5 The Intermediate Level of Robot Consciousness......Page 378
13.6 Case Study: Are We Self-consciousness Robots?......Page 381
References......Page 382
14 AI Ethics, Security and Privacy......Page 386
14.2 Asimov’s Laws of Robot Ethics......Page 387
14.3 Robot Rights......Page 389
14.4 Moral Agents......Page 390
14.6 Privacy and AI Monitoring......Page 392
14.7 Automation and Employment......Page 394
14.8 Prejudices of AI Systems......Page 395
14.9 Responsibility for Autonomous Machines......Page 396
14.10 International AI Ethic Policy......Page 397
14.12 Conclusion......Page 398
References......Page 399
15 What’s Next?......Page 402
15.1 Singularity and Superintelligence......Page 403
15.2 Quantum Computing......Page 404
15.3 6G Technology......Page 406
15.4 Closing Remarks—The Future is Our Choice......Page 409
References......Page 410