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內容簡介

　　《數據驅動的信息物理系統(tǒng)（英文版）》聚焦于數據驅動CPS系統(tǒng)的原則、設計和實現，涵蓋了數據采集、分析和建模、機器學習和人工智能、網絡與分布式計算以及網絡安全等主題?！稊祿寗拥男畔⑽锢硐到y(tǒng)（英文版）》全面介紹了開發(fā)數據驅動信息物理系統(tǒng)所使用的最先進的技術和方法，以及它們在制造業(yè)、醫(yī)療保健、交通運輸和能源等各個行業(yè)中的應用。

作者簡介

　　李方昱，北京工業(yè)大學教授，博士生導師，國家海外優(yōu)青、國家重點研發(fā)計劃青年科學家，長期致力于數據驅動的復雜系統(tǒng)模型構建與分析研究，主持國家重點研發(fā)計劃項目、國家自然科學基金面上項目多項，在權威國際期刊上發(fā)表SCI論文90余篇，ESI高被引論文3篇，入選斯坦福全球前2%頂尖科學家榜單。伍小龍，北京工業(yè)大學副教授，碩士生導師。從事大數據分析、人工神經網絡設計、智能特征建模、智能控制等方向的研究。曾獲中國自動化學會優(yōu)秀博士學位論文獎，中國自動化科技進步一等獎，中國發(fā)明協(xié)會創(chuàng)業(yè)獎×創(chuàng)新獎一等獎，曾在國內外期刊及會議上發(fā)表學術論文30余篇，參與撰寫專著2本，現任中國自動化學會青年工作委員會委員，中國環(huán)境感知與保護自動化委員會委員。韓紅桂，北京工業(yè)大學教授，博士生導師，國家重點研發(fā)計劃項目首席科學家、國家自然科學基金杰出青年科學基金項目獲得者、國家自然科學基金優(yōu)秀青年科學基金項目獲得者、中國自動化學會青年科學家，長期從事復雜系統(tǒng)智能優(yōu)化運行控制理論方法和關鍵技術的研究?，F任“數字社區(qū)”工程研究中心主任、“計算智能與智能系統(tǒng)”北京市重點實驗室主任等，兼任中國自動化學會環(huán)保自動化專業(yè)委員會秘書長、中國自動化學會過程控制專業(yè)委員會委員。

圖書目錄

Chapter 1 Introduction to Data-driven Cyber Physical Systems 1
1.1 What are cyber physical systems? 2
1.2 Data-driven approaches for CPS 3
1.3 Importance of DDCPS 3
1.4 Key challenges in DDCPS 4
1.5 Applications of DDCPS 11
1.6 Evolution of data-driven approaches in cyber physical systems 12
1.7 How can data be used to improve cyber physical systems? 15
1.8 Overview of the book 18
References 18
Chapter 2 Fundamentals of Data-driven Cyber Physical Systems 20
2.1 Definitions 20
2.1.1 Definitions of CPS 20
2.1.2 Definitions of DDCPS 31
2.2 Characteristics of DDCPS 34
2.2.1 Networked communication 35
2.2.2 Scalability 36
2.2.3 Heterogeneity 38
2.2.4 Interdisciplinary 39
2.2.5 Real-time processing 40
2.2.6 Real-time decision-making 41
2.3 Components of DDCPS 41
2.3.1 Sensing components 41
2.3.2 Computational components 42
2.3.3 Communication components 43
2.3.4 Control components 44
2.4 Examples of DDCPS in different industries 45
2.4.1 Smart grids 45
2.4.2 Agriculture 46
2.4.3 Healthcare 47
2.4.4 Intelligent transportation 49
2.4.5 Smart manufacturing 51
2.5 Challenges of DDCPS 53
2.5.1 Data storage 54
2.5.2 Integration 55
2.5.3 Communication 56
2.5.4 Cybersecurity 57
2.5.5 System stability 58
2.6 Summary 60
References 60
Chapter 3 Data Collection in Cyber Physical Systems 66
3.1 Sensors and auxiliary components 66
3.1.1 Type of sensor and auxiliary components 67
3.1.2 Factors for selecting sensors and auxiliary components 71
3.1.3 Typical scenarios for data collection 75
3.2 Types of data 79
3.2.1 One dimensional data 81
3.2.2 Image and video data 83
3.2.3 Other types of data 85
3.3 Real time and latency 87
3.3.1 Techniques for reducing latency 88
3.3.2 Key considerations of real time and latency 92
3.3.3 Evaluating the performance 95
3.4 Data quality and reliability issues 98
3.4.1 Data preprocessing techniques 100
3.4.2 Impact of data redundancy on reliability 103
3.4.3 Data validation techniques 104
3.5 Summary 107
References 108
Chapter 4 Data Storage and Management in Cyber Physical Systems 115
4.1 Types of data storage for DDCPS 116
4.1.1 An introduction to data storage in DDCPS 116
4.1.2 Explore data storage instances in the system 128
4.2 Data management and processing techniques 131
4.2.1 Database management techniques 133
4.2.2 Data processing techniques 137
4.3 Big data processing technology of DDCPS 140
4.3.1 Data process for storage and management 141
4.3.2 Storage for DDCPS 141
4.3.3 Management for DDCPS 143
4.3.4 Big data for DDCPS 144
4.4 Summary 144
References 145
Chapter 5 Data Integration and Fusion in Cyber Physical Systems 153
5.1 Data integration and fusion 153
5.1.1 CPS data characteristics 154
5.1.2 CPS data integration 155
5.1.3 CPS data fusion 156
5.1.4 Data integration and fusion framework 157
5.1.5 Data representation 160
5.2 Techniques for fusing data from multiple sources 161
5.2.1 Stage-based data fusion methods 161
5.2.2 Semantic meaning-based data fusion 163
5.2.3 Artificial intelligence-based data fusion 170
5.3 CPS data integration and fusion case studies 173
5.3.1 Cloud-integrated CPS for smart cities case study 173
5.3.2 Data fusion framework for smart healthcare case study 175
5.4 Challenges and future work opportunities 179
5.4.1 Integrated models challenges 179
5.4.2 CPS data fusion challenges 181
5.4.3 Future work opportunities 185
5.5 Summary 187
References 188
Chapter 6 Data-driven Modeling and Simulation in Cyber Physical Systems 194
6.1 Importance of modeling and simulation in cyber physical systems 195
6.1.1 Importance of complex system modeling for CPS 197
6.1.2 Importance of complex system simulation for CPS 200
6.1.3 Benefits of modeling and simulation in CPS 203
6.2 Data-driven modeling techniques 205
6.2.1 Introduction to data-driven modeling 207
6.2.2 Types of data-driven models used in CPS 210
6.2.3 Methods for model selection and validation 226
6.2.4 Examples of data-driven modeling in CPS applications 229
6.3 Simulation and testing of cyber physical systems using data-driven models 230
6.3.1 Introduction to data-driven simulation 232
6.3.2 Types of data-driven simulation used in CPS 234
6.3.3 Model validation and uncertainty quantification 237
6.3.4 Case studies of simulation and testing using data-driven models in CPS
applications 238
6.4 Summary 240
References 241
Chapter 7 Fault Detection and Predictive Maintenance in Cyber Physical
Systems 247
7.1 An overview of fault detection and maintenance 247
7.1.1 The development of CPS fault detection 248
7.1.2 The development of CPS maintenance 250
7.1.3 Future trends of fault detection and predictive maintenance 251
7.2 Data-driven approaches for fault detection and predictive maintenance 253
7.2.1 Data-driven fault detection approaches 254
7.2.2 Data-driven predictive maintenance approaches 259
7.2.3 Discussion of fault detection and predictive maintenance 264
7.3 Applications of fault detection and predictive maintenance 266
7.3.1 Application background of fault detection and predictive maintenance 267
7.3.2 Case studies of fault detection and predictive maintenance 273
7.3.3 Challenges in cases 283
7.4 Summary 285
References 285
Chapter 8 Cybersecurity in Data-driven Cyber Physical System 291
8.1 Cyber attacks in data-driven CPS 293
8.1.1 Attacks at the perception layer 294
8.1.2 Attacks at the transmission layer 297
8.1.3 Attacks at the platform layer 299
8.1.4 Attacks at the application layer 301
8.2 Requirements of cybersecurity 302
8.2.1 Objective of cybersecurity 302
8.2.2 Hardware security 303
8.2.3 Software security 305
8.2.4 Network security 306
8.2.5 Data security 307
8.3 Importance of cybersecurity in data-driven CPS 308
8.3.1 Data integrity and accuracy 309
8.3.2 Privacy and confidentiality 310
8.3.3 System resilience and availability 311
8.3.4 Regulatory requirements 313
8.4 Challenges of cybersecurity in data-driven CPS 314
8.4.1 Data-driven techniques for attack detection and mitigation 314
8.4.2 Data trustworthiness and policy-based sharing 316
8.4.3 Risk-based security metrics 317
8.5 Data-driven techniques of cybersecurity in CPS 318
8.5.1 Data-driven attack detection and migitation 319
8.5.2 Data-driven data confidence assessment 330
8.5.3 Risk assessment metrics 332
8.6 Summary 334
References 334
Chapter 9 Future of Data-driven Cyber Physical Systems 345
9.1 Potential impacts 345
9.2 Emerging trends and technologies in DDCPS 349
9.3 Societal and ethical implications 351
9.4 Concluding remarks 353
Acknowledgements 355