Title Details

HOUBING SONG, PhD is an Assistant Professor at Embry-Riddle Aeronautical University and the Director of Security and Optimization for Networked Globe Laboratory (SONG Lab, www.SONGLab.us).

RAVI SRINIVASAN, PhD is an Assistant Professor at University of Florida.

TAMIM SOOKOOR, PhD is a Senior Professional Staff at The Johns Hopkins University Applied Physics Laboratory, Laurel.

SABINA JESCHKE, Dr. rer. nat. is a Professor at RWTH Aachen University, Germany and Visiting Professor at Volvo, Sweden.

Editors Biographies xxiii

List of Contributors xxvii

Foreword xxxiii

Preface xxxv

Acknowledgments xxxvii

1 Cyber–Physical Systems in Smart Cities – Mastering Technological, Economic, and Social Challenges 1
Martina Fromhold-Eisebith

1.1 Introduction 1

1.2 Setting the Scene: Demarcating the Smart City and Cyber–Physical Systems 3

1.3 Process Fields of CPS-Driven Smart City Development 4

1.4 Economic and Social Challenges of Implementing the CPS-Enhanced Smart City 10

1.5 Conclusions: Suggestions for Planning the CPS-Driven Smart City 15

FinalThoughts 17

Questions 18

References 18

2 Big Data Analytics Processes and Platforms Facilitating Smart Cities 23
Pethuru Raj and Sathish A. P. Kumar

2.1 Introduction 24

2.2 Why Big Data Analytics (BDA) Is Significant for Smarter Cities 24

2.3 Describing the Big Data Paradigm 26

2.4 The Prominent Sources of Big Data 27

2.5 Describing Big Data Analytics (BDA) 29

2.6 The Big Trends and Use Cases of Big Data Analytics 31

2.7 The Open Data for Next-Generation Cities 38

2.8 The Big Data Analytics (BDA) Platforms 39

2.9 Big Data Analytics Frameworks and Infrastructure 45

2.10 Summary 51

FinalThoughts 51

References 52

3 Multi-Scale Computing for a Sustainable Built Environment 53
Massimiliano Manfren

3.1 Introduction 53

3.2 Modeling and Computing for Sustainability Transitions 55

3.3 Multi-ScaleModeling and Computing for the Built Environment 66

3.4 Research inModeling and Computing for the Built Environment 70

FinalThoughts 82

Questions 84

References 84

4 Autonomous Radios and Open Spectrum in Smart Cities 99
Corey D. Cooke and Adam L. Anderson

4.1 Introduction 99

4.2 CandidateWireless Technologies 101

4.3 PHY and MAC Layer Issues in Cognitive Radio Networks 105

4.4 Frequency Envelope Modulation (FEM) 110

4.5 Conclusion 116

FinalThoughts 117

Questions 118

References 118

5 Mobile Crowd-Sensing for Smart Cities 125
Chandreyee Chowdhury and Sarbani Roy

5.1 Introduction 125

5.2 Overview of Mobile Crowd-Sensing 127

5.3 Issues and Challenges of Crowd-sensing in Smart Cities 135

5.4 Crowd-sensing Frameworks for Smart City 144

5.5 Conclusion 149

FinalThoughts 149

Questions 150

References 150

6 Wide-AreaMonitoring and Control of Smart Energy Cyber-Physical Systems (CPS) 155
Nilanjan R. Chaudhuri

6.1 Introduction 155

6.2 Challenges and Opportunities 156

6.3 Solutions 159

6.4 Conclusions and Future Direction 173

FinalThoughts 175

Questions 175

References 175

7 Smart Technologies and Vehicle-to-X (V2X) Infrastructures for Smart Mobility Cities 181
Bernard Fong, Lixin Situ, and Alvis C. M. Fong

7.1 Introduction 181

7.2 Data Communications in Smart City Infrastructure 182

7.3 Deployment: An Economic Point of View 186

7.4 Connected Cars 195

7.5 Concluding Remarks 202

FinalThoughts 203

Questions 203

References 204

8 Smart Ecology of Cities: Integrating Development Impacts on EcosystemServices for Land Parcels 209
Marc Morrison, Ravi S. Srinivasan, and Cynnamon Dobbs

8.1 Introduction 209

8.2 Need for Smart Ecology of Cities 212

8.3 Ecosystem Service Modeling (CO2 Sequestration, PM10 Filtration, Drainage) 214

8.4 Methodology 219

8.5 Implementation of Development Impacts in Dynamic-SIM Platform 231

8.6 Discussion (Assumptions, Limitations, and FutureWork) 234

8.7 Conclusion 235

FinalThoughts 236

Questions 236

References 236

9 Data-Driven Modeling, Control, and Tools for Smart Cities 243
Madhur Behl and Rahul Mangharam

9.1 Introduction 243

9.2 RelatedWork 248

9.3 Problem Definition 250

9.4 Data-Driven Demand Response 252

9.5 DR Synthesis with Regression Trees 254

9.6 The Case for Using Regression Trees for Demand Response 259

9.7 DR-Advisor: Toolbox Design 261

9.8 Case Study 263

9.9 Conclusions and OngoingWork 271

References 272

10 Bringing Named Data Networks into Smart Cities 275
Syed Hassan Ahmed, Safdar Hussain Bouk, Dongkyun Kim, and Mahasweta Sarkar

10.1 Introduction 275

10.2 Future Internet Architectures 278

10.3 Named Data Networking (NDN) 282

10.4 NDN-based Application Scenarios for Smart Cities 285

10.5 Future Aspects of NDN in Smart Cities 297

10.6 Conclusion 303

FinalThoughts 304

Questions 304

References 304

11 Human Context Sensing in Smart Cities 311
Juhi Ranjan and KaminWhitehouse

11.1 Introduction 311

11.2 Human Context Types 312

11.3 Sensing Technologies 317

11.4 Conclusion 331

FinalThoughts 332

Questions 332

References 333

12 Smart Cities and the Symbiotic Relationship between Smart Governance and Citizen Engagement 343
Tori Onker

12.1 Smart Governance 344

12.2 Case Study – Somerville, Massachusetts 348

12.3 Looking Ahead 365

FinalThoughts 368

Questions 370

References 370

13 Smart Economic Development 373
Madhavi Venkatesan

13.1 Introduction 373

13.2 Perception of Resource Value, Market Outcomes, and Price 378

13.3 Conscious Consumption and the Sustainability Foundation of Smart

Cities 384

FinalThoughts 388

Questions 388

References 388

14 Managing the Cyber Security Life-Cycle of Smart Cities 391
Mridul S. Barik, Anirban Sengupta, and Chandan Mazumdar

14.1 Introduction 391

14.2 Smart City Services 393

14.3 Smart Services Technologies 394

14.4 Smart Services Security Issues 396

14.5 Management of Cyber Security of Smart Cities 397

14.6 Discussion 403

14.7 Conclusion 404

Questions 404

References 405

15 Mobility as a Service 409
Christopher Expósito-Izquierdo, Airam Expósito-Márquez, and Julio Brito-Santana

15.1 Introduction 409

15.2 Mobility as a Service 413

15.3 Case Studies on Mobility as a Service 427

15.4 Conclusions and Further Research 432

Acknowledgments 433

FinalThoughts 433

Questions 433

References 434

16 Clustering and Fuzzy Reasoning as Data Mining Methods for the Development of Retrofit Strategies for Building Stocks 437
Philipp Geyer and Arno Schlüter

16.1 Introduction 438

16.2 Method 440

16.3 Application Case 442

16.4 Data Sources and Preprocessing 443

16.5 Clustering 448

16.6 Fuzzy Reasoning 456

16.7 Mixed Fuzzy Reasoning and Clustering 459

16.8 Postprocessing: Interpretation and Strategy Identification 459

16.9 Comparison and Discussion ofMethods 464

16.10 Conclusion 467

FinalThoughts 468

Questions 468

Acknowledgments 469

References 469

17 A Framework to Achieve Large Scale Energy Savings for Building Stocks through Targeted Occupancy Interventions 473
Aslihan Karatas, Allisandra Stoiko, and Carol C. Menassa

17.1 Introduction 474

17.2 Objectives 475

17.3 Review of Occupancy-Focused Energy Efficiency Interventions 476

17.4 Role of Occupants’ Characteristics in Building Energy Use 481

17.5 A Conceptual Framework for Delivering Targeted Occupancy-Focused Interventions 483

17.6 Case Study Example 490

17.7 Discussion 493

17.8 Conclusions and Policy Implications 494

Questions 496

Acknowledgment 496

References 496

18 Sustainability in Smart Cities: Balancing Social, Economic, Environmental, and Institutional Aspects of Urban Life 503
Ali Komeily and Ravi Srinivasan

18.1 Introduction 503

18.2 Sustainability Assessment in Our Cities 506

18.3 Sustainability in Smart Cities 508

18.4 Achieving Balanced Sustainability 511

FinalThoughts 526

Questions 527

References 536

19 Toward Resilience of the Electric Grid 541
JiankangWang

19.1 Electric Grids in Smart Cities 541

19.2 Threats to Electric Grids 549

19.3 Electric Grid Response under Threats 558

19.4 Defense against Threats to Electric Grids 564

References 573

20 Smart Energy and Grid: Novel Approaches for the Efficient Generation, Storage, and Usage of Energy in the Smart Home and the Smart Grid Linkup 579
Julian Praß, JohannesWeber, Sebastian Staub, Johannes Bürner, Ralf Böhm, Thomas Braun, Moritz Hein, MarkusMichl,Michael Beck, and Jörg Franke

20.1 Generation of Energy 580

20.2 Storage of Energy 585

20.3 Smart Usage of Energy 591

20.4 Summary 604

FinalThoughts 604

Questions 605

References 605

21 Building Cyber-Physical Systems – A Smart Building Use Case 609
Jupiter Bakakeu, Franziska Schäfer, Jochen Bauer, MarkusMichl, and Jörg Franke

21.1 Foundations—From Automation to Smart Homes 610

21.2 From Today’s Technologically Augmented Houses to Tomorrow’s Smart Homes 612

21.3 Smart Home: A Cyber-Physical Ecosystem 616

21.4 Connecting Smart Homes and Smart Cities 633

21.5 Conclusion and Future Research Focus 635

FinalThoughts 636

Questions 636

References 637

22 Climate Resilience and the Design of Smart Buildings 645
Saranya Gunasingh, NoraWang, Doug Ahl, and Scott Schuetter

22.1 Climate Change and Future Buildings and Cities 646

22.2 Carbon Inventory and Current Goals 648

22.3 Incorporating Predicted Climate Variability in Building Design 650

22.4 Case Studies 652

22.5 Implications for Future Cities and Net-Zero Buildings 666

FinalThoughts 668

Questions 668

References 669

23 Smart Audio Sensing-Based HVAC Monitoring 673
Shahriar Nirjon, Ravi Srinivasan, and Tamim Sookoor

23.1 Introduction 673

23.2 Background 675

23.3 The Design of SASEM 679

23.4 Experimental Results 689

FinalThoughts 693

Questions 693

References 694

24 Smart Lighting 701
Jie Lian and Charles L. Brown

24.1 Introduction 701

24.2 Background 702

24.3 Smart Lighting Applications 703

24.4 Visible Light Communication (Smart Lighting Communication) System 705

24.5 Conclusion and Outlook 722

FinalThoughts 723

Questions 723

References 723

25 Large Scale Air-Quality Monitoring in Smart and Sustainable Cities 729
Xiaofan Jiang

25.1 Introduction 730

25.2 Current Approaches to Air Quality Monitoring and Their Limitations 733

25.3 Overview of a Cloud-based Air QualityMonitoring System 735

25.4 Cloud-Connected Air QualityMonitors 737

25.5 Cloud-Side System Design and Considerations 740

25.6 Data Analytics in the Cloud 743

25.7 Applications and APIs 752

FinalThoughts 752

Questions 755

References 755

26 The Smart City Production System 759
Gary Graham, Jag Srai, Patrick Hennelly, and Roy Meriton

26.1 Introduction 759

26.2 Types of Production System: Historical Evolution 761

26.3 The Integrated Smart City Production System Framework 765

26.4 Production System Design 767

26.5 Chapter Summary 771

FinalThoughts 772

Questions 772

References 772

27 Smart Health Monitoring Using Smart Systems 777
Carl Chalmers

27.1 Introduction 777

27.2 Background 779

27.3 Integration for Monitoring Applications 790

27.4 Conclusion 792

FinalThoughts 793

Questions 793

References 793

28 Significance of Automated Driving in Japan 797
Sadayuki Tsugawa

28.1 Introduction 797

28.2 Definitions of Automated Driving Systems 798

28.3 A History of Research and Development of Automated Driving Systems 799

28.4 Expected Benefits of Automated Driving 808

28.5 Issues of Automated Driving for Market Introduction 809

28.6 Possible Market Introduction of Automated Driving Systems in Japan 812

28.7 Conclusion 819

Questions 820

References 820

29 Environmental-Assisted Vehicular Data in Smart Cities 823
Wei Chang, Huanyang Zheng, JieWu, Chiu C. Tan, and Haibin Ling

29.1 Location-Related Security and Privacy Issues in Smart Cities 824

29.2 Opportunities of Using Environmental Evidences 826

29.3 Challenges of Creating Location Proofs 827

29.4 Environmental Evidence-Assisted Vehicular Data Framework 829

29.5 Conclusion 845

FinalThoughts 845

Questions 846

References 846

Index 849