Innovative Technologies for Market Leadership (eBook)

Foreword 6
Preface 8
About the Book 9
Contents 10
Editors and Contributors 12
About the Editors 12
Contributors 13
Smart Grid, Future Innovation and Investment Opportunities 15
1 Introduction 15
2 Energy Transformation 16
3 Smart Grid and Renewable Energy 17
4 Harnessing Variability 18
4.1 Harnessing Variability at Distribution Grid Level (Small Energy Level) 19
4.2 Hydrogen Production 21
4.3 Desalination Plants 22
4.4 CO2 Extraction from Nature 23
5 Conclusion 24
References 24
Quantum Technologies 25
1 Introduction 25
2 Concepts 26
2.1 Superposition: Life Is Uncertain 26
2.2 Measuring: To Measure or Not to Measure Is the Question 27
2.3 Entanglement: Spooky Action at a Distance 28
3 Applications 28
3.1 Quantum Computers 28
3.2 Shor's Algorithm: The End of Encryption? 30
3.3 Quantum Networks 30
3.4 Quantum “Blind” Clouds 31
3.5 Other Applications with Quantum Mechanics 31
4 Conclusions 32
References 33
Security in Intelligent Transportation Telematics 34
1 The ITS Ecosystem 34
2 Application Scenario Versus Vulnerability 36
3 Signature as the Primary Security Measure 37
4 Security, Safety, Integrity—and Privacy—Issues 38
5 Why May Someone Want to Attack Any ITS Network? 40
6 Conclusions 41
References 42
Innovation and Future Technology Scenarios in Health Care: Ideas and Studies 43
1 Self-Driving Hospital Beds 44
2 Reorganization of Medical Studies with Contests and Crowdsourcing 45
3 All-In-Data-Approach in Health Care for New Business Models 47
3.1 Introduction 47
3.2 Theoretical Background 48
3.3 Research Design 48
3.4 First Study 48
3.5 Follow-Up Study 49
3.6 Future Health Care IT Service Prototype Model 51
3.7 Findings 51
3.8 Conclusions of the Study 52
4 Drone-Supported Emergency Concepts in Combination with Automotive Health Systems 52
5 Conclusions 53
References 54
Unlocking the Power of Artificial Intelligence for Your Business 56
1 Introduction 56
2 Motivation: China Is Spearheading AI Innovation 57
3 Artificial Intelligence 58
3.1 History 58
3.2 Machine Learning 59
3.3 The Three Pillars of Machine Learning 60
3.4 Neural Networks 61
3.5 Recent Advances and Deep Learning 61
3.6 Frontiers 62
4 AI Transformation of a Company 63
5 The Fear of an Out-of-Control AI Is Exaggerated 68
6 Conclusions 69
References 69
Innovation Means: Asking the Right Questions 71
1 Introduction 71
2 So Let Us Innovate 72
3 What Is Innovation Anyway? 73
4 Do You Really Need to Constantly Innovate? 73
5 Where Is Your Game Plan? 73
6 Innovation Is Hard 74
7 Innovation Is Not Rocket Science Though 74
8 It All Starts with a Question 75
9 Innovate by Gut Feeling 75
9.1 Learn to Ask Questions Again 76
10 The Innovation Canvas 76
10.1 What Do We Want to Innovate? 77
10.2 Why Are We Doing This? 78
10.2.1 Trigger 78
10.2.2 Demand 78
10.2.3 Value Proposition 78
10.2.4 Competitive Advantages 78
10.3 Who Do We Do It For? 79
10.3.1 Target Groups 79
10.3.2 Marketing 79
10.3.3 Pilot Application 79
10.3.4 Expansion Stages 80
10.3.5 Activities 80
10.3.6 Resources 80
10.3.7 External Partners 81
10.3.8 Other Projects 81
10.4 How Does It Pay Off? 81
10.4.1 Cost Structure 81
10.4.2 Project Budget 82
10.4.3 Revenue Streams 82
10.4.4 Risks 83
11 Nothing Worth Without Culture 83
12 Drive Your Innovation Culture! 83
13 Conclusions 84
Reference 84
Innovative Technologies in the Ageing Population: Breaking the Boundaries 85
1 Introduction 85
2 Demographic Shift 86
3 Digital Sovereignty 87
4 Digital Education and Social Interaction 89
5 Data Security and Trust 90
6 Usability 91
7 Artificial Intelligence as an Innovation Driver of Digital Technologies Amongst the Elderly 91
8 The Future of Humans and Technology 93
9 The Digital Divide 94
10 Conclusions 95
References 96
Using Augmented Reality and Machine Learning in Radiology 98
1 Introduction 98
2 Related Work 100
3 Methodology 102
3.1 The Machine Learning Algorithm 104
3.1.1 Preprocessing 104
3.1.2 Loss Objective 105
3.1.3 Input Multiple 2D Slices to Take Advantage of 3D Data 105
3.1.4 ROI Cropping 105
3.1.5 Using the Liver Segmentation for the Lesion Segmentation 106
3.1.6 Lesion Detector Module 106
3.1.7 3D Conditional Random Fields 106
3.1.8 Loss Balancing 106
3.2 Using Unity and WebRTC to Deliver PC Rendering Power to HoloLens 107
3.2.1 Server 109
3.2.2 Client 110
4 Evaluation and Discussion 111
5 Conclusions and Outreach 113
References 114
Digitalization in Mechanical Engineering 116
1 Introduction 116
2 Comparison to Traditional Industrial Automation 118
3 Opportunities and Challenges 118
4 The Way of Thinking: People, Processes, and Technology 120
5 Selected Use Cases and Applications 121
5.1 Reducing the Number of Simulation Runs 121
5.2 Intelligent Mechatronic Modules: Cyber-Physical Systems 122
5.3 Self-X and Organic Computing 123
5.4 Automatically Layouting New Machine Variants 124
6 Conclusions 125
References 125
Lean Launch Data Engineering Projects with Super Type Power 127
1 Introduction 127
2 Towards Type Safe and Reusable Spark Applications 128
2.1 Loosely Typed Data 128
2.2 Type-Setting the Data 130
2.3 Sending Them for Classes 131
2.4 A Quick Summary 132
3 Sailing Safe Through the Storm 132
3.1 An Untyped Storm Topology 133
3.2 Storm Is Dangerous 135
3.3 Phantom Types to the Rescue 136
4 Conclusion 138
References 139
Ubiquitous Computing: From 5G to the Edge and Beyond 140
1 Ubiquitous Computing 140
2 The Journey: Or How We Got Here 141
2.1 The Becoming of the Inter-Networking Network 141
2.2 Hard- and Software Evolution 142
2.3 Mobile Telecommunications Everywhere 143
3 Mixing The Dough 144
4 Status Quo 2019 148
5 The Evolutionary Revolution to 5G 148
6 Edge Computing 150
7 Benefits of 5G and Edge Computing 151
8 Top Five Use Case Categories 152
8.1 Human Beings 152
8.2 Smart Mobility 153
8.3 Smart Logistics 154
8.4 Smart Environment 154
8.5 Smart Industry 155
9 Conclusions/What Is Left to Do 156
References 157
Autonomous Driving on the Thin Trail of Great Opportunities and Dangerous Trust 159
1 Introduction 159
2 Understanding the Environment 161
3 The Critical Role of Artificial Intelligence 161
4 Ambitious Goals and Their Consequences 162
4.1 Advances in Autonomous Driving and Artificial Intelligence 163
4.2 Contemporary Forecasts and Challenges 164
5 The Challenge of Easy Access to Complex Technologies 165
6 Interpreting Deep Learning Models in Self-Driving Cars 166
6.1 Convolutional Neural Networks for End-to-End Driving 166
6.2 Visualizing What Deep Learning Models Learn 167
7 Conclusions 169
References 170
Analytic Philosophy for Biomedical Research: The Imperative of Applying Yesterday's Timeless Messages to Today's Impasses 172
1 Successes and Lingering Challenges in Biomedicine Today 173
2 The Current State of Theory in Biomedical Research 176
3 Lessons from the History of Philosophy and Rational Thought 177
3.1 Ancient Philosophy 178
3.2 After the Galilean Revolution in Science 182
4 Precedents of “Philosophical Biology” 184
5 The Imperative for a Coherent and Unified Theoretical and Philosophical Biology 186
5.1 Contours of a Revived Philosophical Biology 187
5.2 Theoretical Methods and Tools (TMT) 188
5.3 Theoretical Problems and Solutions (TPS) 191
5.4 Inherent and Experimental Verifiability 196
6 Conclusions 197
References 197
Proposal-Based Innovation: A New Approach to Opening Up the Innovation Process 206
1 Introduction 207
2 A New Approach to Innovation: Task and Goal 207
3 Manufacturing Industries: A Definition for This Chapter 208
4 Challenges and Opportunities in Manufacturing Industries 209
4.1 An Example 209
4.2 The Options 210
4.3 Insight Is Essential 210
4.4 Early Warning Indicators 211
4.5 Need for Worldwide Intelligence? 211
4.6 Changes and Influences 211
4.6.1 Changes in the Nature of Globalization 212
4.6.2 Changing World Order 212
4.6.3 Innovation Centers Are Shifting 213
4.6.4 How Innovation Has Changed 214
4.6.5 Increasing R& D Expenditures
4.6.6 Time to Market 215
4.6.7 Digital Divide 216
4.6.8 Increasing Competition 216
4.6.9 Corporate Social Responsibility (CSR) 216
4.6.10 Growing Middle Class 217
4.6.11 Aging Society 217
4.6.12 Megacities 217
5 About Startups and Manufacturing 218
5.1 Services Startup Environment 218
5.2 Manufacturing Services Startups 218
5.3 Mass Manufacturing Startups 219
5.4 Conclusion 220
6 Open Innovation (OI) 221
6.1 General Limitations 222
6.2 Cultural Barriers 223
6.3 Process Barriers 223
6.4 Intermediaries 223
7 Barriers in Web Search 225
7.1 The Language Barrier Web 226
7.2 The Relevance Barrier Web 227
8 Proposal-Based Innovation (PBI) 228
8.1 PBI in the Global Environment 228
8.2 The Concept of PBI 229
8.3 Artificial Intelligence (AI) 232
8.4 The Vision 233
9 Conclusion and a Special Concern 233
References 235
Technologies and Innovations for the Plastics Industry: Polymer 2030 237
1 Technologies and Innovations for the Plastics Industry: Polymer 2030: Fit for the Future Thanks to Innovations and Technology 237
2 Structure of the Plastics Sector 239
3 Megatrends and New Business Models for the Plastics Industry 240
4 Trends and Technologies: Best Practice Examples for the Plastics Industry 244
4.1 Technologies for Individualisation in the Plastics Industry 244
4.2 Resource Efficiency 244
4.3 Digital Transformation 246
5 Recommended Approaches for the Plastic Industry 246
References 247
How Do Innovative Business Concepts Enable Investment Opportunities in the Complete Construction Value Chain? 248
1 Introduction to the Global Construction Market 249
2 What Is the Construction Value Chain? 249
3 How Is the World Population Developing? 250
4 Globally, What Are the Major Impacting Trends on Construction? 250
5 Is the Technology Breakthrough There? 252
5.1 Smart Building Material and Green Technology 252
5.1.1 Interpanel GmbH 252
5.1.2 Nuki Home Solutions GmbH 254
5.1.3 Airthings 254
5.1.4 Breeze Technologies 254
5.1.5 Field Factors 255
5.2 Artificial Intelligence, Data Analytics, and Internet of Things 255
5.2.1 Fieldwire 256
5.2.2 INDUS.AI 257
5.2.3 Building Radar 257
5.2.4 bGrid 258
5.2.5 reINVENT Innovation GmbH 258
5.3 Building Information Modeling (BIM), Virtual (VR) and Augmented Reality (AR) 259
5.3.1 Finalcad 259
5.3.2 Matterport 260
5.3.3 IrisVR 261
5.3.4 XYZ Reality 261
5.4 Robotics, Drones, and 3D Printing 262
5.4.1 MX3D 262
5.4.2 KEWAZO 263
5.4.3 XtreeE 264
5.4.4 Apis Cor 264
5.4.5 Yingchuang Building Technique 264
5.4.6 ICON3D 265
5.4.7 RedWorks Construction Technologies Inc. 265
5.5 Smart and Mobile/Modular Homes 265
5.5.1 haus.me 265
5.5.2 Mighty Buildings Inc. 266
5.5.3 Containerwerk eins GmbH 266
6 Conclusion 266
References 267
Motivation, Employees, and Communication in the Start-Up Phase 268
1 Motivation: The Engine of Our Founder Scene 268
2 Creating a Basis for the Team 269
2.1 Create Room for Feedback 269
2.2 Agile Planning 270
2.3 Fast Communication 270
2.4 Limitation of Freedom 271
3 Limits of Capabilities 271
4 Motivation Comes from Success 271
References 273
AI to Solve the Data Deluge: AI-Based Data Compression 274
1 Introduction 274
2 Data Compression Preliminaries 276
3 AI for Data Compression 279
3.1 DeepZip: Compressing Numerical Data with Neural Networks 281
3.1.1 Probability Prediction Block 281
3.1.2 Arithmetic Encoder Block 281
3.1.3 DeepZip Compression 282
3.1.4 Thoughts on DeepZip 283
3.2 Classification and Anomaly Detection on Lossy Compressed Data 283
3.2.1 Tensor Decomposition for Natural Compression 284
4 Conclusion 287
References 287
Digital Transformation in Plastics Industry: From Digitization Toward Virtual Material 289
1 Introduction: What Is an Innovative Technology? 289
2 The Perspective of Material Science 291
3 The Perspective of Covestro 293
4 Virtual Customer Experience of Materials 295
5 Suggestions 297
6 Conclusion 299
References 299
Correction to: Analytic Philosophy for Biomedical Research: The Imperative of Applying Yesterday's Timeless Messages to Today's Impasses 301