Design and Development of Efficient Energy Systems

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Design and Development of Efficient Energy Systems, Wiley
Von Suman Lata Tripathi, Dushyant Kumar Singh, Sanjeevikumar Padmanaban, P. Raja, im heise Shop in digitaler Fassung erhältlich
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There is not a single industry which will not be transformed by machine learning and Internet of Things (IoT). IoT and machine learning have altogether changed the technological scenario by letting the user monitor and control things based on the prediction made by machine learning algorithms. There has been substantial progress in the usage of platforms, technologies and applications that are based on these technologies. These breakthrough technologies affect not just the software perspective of the industry, but they cut across areas like smart cities, smart healthcare, smart retail, smart monitoring, control, and others. Because of these “game changers,” governments, along with top companies around the world, are investing heavily in its research and development. Keeping pace with the latest trends, endless research, and new developments is paramount to innovate systems that are not only user-friendly but also speak to the growing needs and demands of society.

This volume is focused on saving energy at different levels of design and automation including the concept of machine learning automation and prediction modeling. It also deals with the design and analysis for IoT-enabled systems including energy saving aspects at different level of operation.

The editors and contributors also cover the fundamental concepts of IoT and machine learning, including the latest research, technological developments, and practical applications. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in the area of IoT and machine technology, this is a must-have for any library.

SUMAN LATA TRIPATHI, PHD, is a professor at Lovely Professional with more than seventeen years of experience in academics. She has published more than 45 research papers in refereed journals and conferences. She has organized several workshops, summer internships, and expert lectures for students, and she has worked as a session chair, conference steering committee member, editorial board member, and reviewer for IEEE journals and conferences. She has published one edited book and currently has multiple volumes scheduled for publication, including volumes available from Wiley-Scrivener.

DUSHYANT KUMAR SINGH, is an assistant professor and Head of Embedded Systems Domain at Lovely Professional University. With a masters degree from Punjab Engineering College, University of Technology, Chandigarh, he has several years of industrial experience and more than ten years of teaching experience.

SANJEEVIKUMAR PADMANABAN, PHD, is a faculty member with the Department of Energy Technology, Aalborg University, Esbjerg, Denmark. He has almost ten years of teaching, research and industrial experience and is an associate editor on a number of international scientific refereed journals. He has published more than 300 research papers and has won numerous awards for his research and teaching.

P. RAJA is currently working as an assistant professor at Lovely Professional University. His expertise is in VLSI and embedded systems. He has more than 14 years of experience with 5 years in embedded industry. He has 14 publications in UGC-approved and other reputable journals. He also has 10 patents to his credit.

Preface xv

1 DESIGN OF LOW POWER JUNCTION-LESS DOUBLE-GATE MOSFET 1

Namrata Mendiratta and Suman Lata Tripathi

1.1 Introduction 1

1.2 MOSFET Performance Parameters 2

1.3 Comparison of Existing MOSFET Architectures 3

1.4 Proposed Heavily Doped Junction-Less Double Gate MOSFET (AJ-DGMOSFET) 3

1.5 Heavily Doped JL-DG MOSFET for Biomedical Application 8

1.6 Conclusion 9

References 10

2 VLSI IMPLEMENTATION OF VEDIC MULTIPLIER 13

Abhishek Kumar

2.1 Introduction 13

2.2 8x8 Vedic Multiplier 14

2.3 The Architecture of 8x8 Vedic Multiplier (VM) 16

2.3.1 Compressor Architecture 17

2.3.1.1 3:2 Compressor 18

2.3.1.2 4:3 Compressor 18

2.3.1.3 5:3 Compressor 18

2.3.1.4 8:4 Compressor 19

2.3.1.5 10:4 Compressor 19

2.3.1.6 12:5 Compressor 20

2.3.1.7 15:5 Compressor 21

2.3.1.8 20:5 Compressor 21

2.4 Results and Discussion 23

2.4.1 Instance Power 23

2.4.2 Net Power 24

2.4.3 8-Bit Multiplier 25

2.4.4 16-Bit Multiplier 26

2.4.5 Applications of Multiplier 27

2.5 Conclusion 28

References 28

3 GAS LEAKAGE DETECTION FROM DRAINAGE TO OFFER SAFETY FOR SANITARY WORKERS 31

Dr. D. Jeyabharathi, Dr. D. Kesavaraja and D. Sasireka

3.1 Introduction 31

3.1.1 IOT-Based Sewer Gas Detection 31

3.1.1.1 IoT Sensors 32

3.1.2 Objective 32

3.1.3 Contribution of this Chapter 33

3.1.4 Outline of the Chapter 33

3.2 Related Works 33

3.2.1 Sewer Gas Leakage Detection 33

3.2.2 Crack Detection 34

3.3 Methodology 34

3.3.1 Sewer Gas Detection 34

3.3.1.1 Proposed Tristate Pattern 35

3.3.2 Crack Detection 36

3.3.3 Experimental Setup 37

3.4 Experimental Results 39

3.5 Conclusion 40

References 40

4 MACHINE LEARNING FOR SMART HEALTHCARE ENERGY-EFFICIENT SYSTEM 43

S. Porkodi, Dr. D. Kesavaraja and Dr. Sivanthi Aditanar

4.1 Introduction 43

4.1.1 IoT in the Digital Age 43

4.1.2 Using IoT to Enhance Healthcare Services 44

4.1.3 Edge Computing 44

4.1.4 Machine Learning 44

4.1.5 Application in Healthcare 45

4.2 Related Works 45

4.3 Edge Computing 47

4.3.1 Architecture 47

4.3.2 Advantages of Edge Computing over Cloud Computing 47

4.3.3 Applications of Edge Computing in Healthcare 48

4.3.4 Edge Computing Advantages 49

4.3.5 Challenges 50

4.4 Smart Healthcare System 50

4.4.1 Methodology 50

4.4.2 Data Acquisition and IoT End Device 51

4.4.3 IoT End Device and Backend Server 51

4.5 Conclusion and Future Directions 52

References 52

5 REVIEW OF MACHINE LEARNING TECHNIQUES USED FOR INTRUSION AND MALWARE DETECTION IN WSNS AND IOT DEVICES 57

Dr. Jeyabharathi, Dr. A. Sherly Alphonse, Ms. E.L. Dhivya Priya and Dr. M. Kowsigan

5.1 Introduction 57

5.2 Types of Attacks 58

5.3 Some Countermeasures for the Attacks 59

5.4 Machine Learning Solutions 59

5.5 Machine Learning Algorithms 59

5.6 Authentication Process Based on Machine Learning 60

5.7 Internet of Things (IoT) 62

5.8 IoT-Based Attacks 62

5.8.1 Botnets 62

5.8.2 Man-in-the-Middle 62

5.9 Information and Identity Theft 62

5.10 Social Engineering 63

5.11 Denial of Service 63

5.12 Concerns 63

5.13 Conclusion 64

References 64

6 SMART ENERGY-EFFICIENT TECHNIQUES FOR LARGE-SCALE PROCESS INDUSTRIES 67

B Koti Reddy and N V Raghavaiah

6.1 Pumps Operation 67

6.1.1 Parts in a Centrifugal Pump 68

6.1.2 Pump Efficiency 68

6.1.3 VFD 70

6.1.4 VFD and Pump Motor 72

6.1.5 Large HT Motors 73

6.1.6 Smart Pumps 73

6.2 Vapour Absorption Refrigeration System 74

6.2.1 Vapour Compression Refrigeration 74

6.2.2 Vapour Absorption Refrigeration 75

6.3 Heat Recovery Equipment 77

6.3.1 Case Study 77

6.3.2 Advantages of Heat Recovery 78

6.4 Lighting System 78

6.4.1 Technical Terms 78

6.4.2 Introduction 78

6.4.3 LED Lighting 79

6.4.4 Energy-Efficiency Techniques 79

6.4.5 Light Control with IoT 80

6.4.5.1 Wipro Scheme 80

6.4.5.2 Tata Scheme 80

6.4.6 EU Practices 81

6.5 Air Conditioners 82

6.5.1 Technical Terms 82

6.5.2 Types of Air Conditioners 82

6.5.3 Star Rating of BEE 83

6.5.4 EU Practices 83

6.5.5 Energy-Efficiency Tips 83

6.5.6 Inverter Air Conditioners 85

6.5.7 IoT-Based Air Conditioners 85

6.6 Fans and Other Smart Appliances 86

6.6.1 BLDC Fan Motors 87

6.6.2 Star Ratings 87

6.6.3 Group Drive of Fans 88

6.6.4 Other Smart Appliances 88

6.7 Motors 92

6.7.1 Motor Efficiency 92

6.7.2 Underrated Operation 93

6.7.3 Energy-Efficient Motors 94

6.7.3.1 Energy-Efficiency Ratings of BEE 94

6.7.3.2 Energy-Efficiency Ratings of IEC 94

6.7.4 Retrofit of Standard Motors with Energy-Efficient Motors 96

6.7.5 Other Salient Points 97

6.7.6 Use of Star-Delta Starter Motor 97

6.8 Energy-Efficient Transformers 98

6.8.1 IEC Recommendation 98

6.8.2 Super Conducting Transformers 99

References 99

7 LINK RESTORATION AND RELAY NODE PLACEMENT IN PARTITIONED WIRELESS SENSOR NETWORK 101

Manwinder Singh and Anudeep Gandam

7.1 Introduction 101

7.2 Related Work 103

7.2.1 Existing Techniques 105

7.3 Proposed K-Means Clustering Algorithm 105

7.3.1 Homogenous and Heterogeneous Network Clustering Algorithms 105

7.3.2 Dynamic and Static Clustering 105

7.3.2.1 Routing 106

7.3.3 Flow Diagram 106

7.3.4 Objective Function 106

7.4 System Model and Assumption 108

7.4.1 Simulation Parameters 108

7.4.1.1 Residual Energy 108

7.4.1.2 End-to-End Delay 109

7.4.1.3 Number of Hops or Hop Count in the Network 109

7.5 Results and Discussion 109

7.6 Conclusions 114

References 115

8 FREQUENCY MODULATED PV POWERED MLI FED INDUCTION MOTOR DRIVE FOR WATER PUMPING APPLICATIONS 119

Arunkumar S, Mohana Sundaram N and K. Malarvizhi

8.1 Introduction 119

8.2 PV Panel as Energy Source 120

8.2.1 Solar Cell 120

8.3 Multi-Level Inverter Topologies 121

8.3.1 Types of Inverters Used for Drives 121

8.3.2 Multi-Level Inverters 121

8.4 Experimental Results and Discussion 122

8.4.1 PV Powered H Bridge Inverter-Fed Drive 123

8.4.2 PV Powered DCMLI Fed Drive 126

8.5 Conclusion and Future Scope 128

References 129

9 ANALYSIS AND DESIGN OF BIDIRECTIONAL CIRCUITS FOR ENERGY STORAGE APPLICATION 131

Suresh K, Sanjeevikumar Padmanaban and S Vivek

9.1 Introduction 131

9.2 Modes of Operation Based on Main Converters 133

9.2.1 Single-Stage Rectification 134

9.2.2 Single-Stage Inversion 135

9.2.3 Double-Stage Rectification 137

9.2.3.1 Duty Mode - Interval -I 137

9.2.3.2 Freewheeling Mode - Interval -II 138

9.2.4 Double-Stage Inversion 139

9.2.4.1 Charging Mode - Interval -I 140

9.2.4.2 Duty Mode - Interval -II 141

9.3 Proposed Methodology for Three-Phase System 141

9.3.1 Control Block of Overall System 143

9.3.2 Proposed Carrier-Based PWM Strategy 144

9.3.3 Experiment Results 145

9.4 Conclusion 148

References 148

10 LOW-POWER IOT-ENABLED ENERGY SYSTEMS 151

Yogini Dilip Borole and Dr. C. G. Dethe

10.1 Overview 151

10.1.1 Conceptions 151

10.1.2 Motivation 152

10.1.3 Methodology 154

10.2 Empowering Tools 156

10.2.1 Sensing Components 156

10.2.2 Movers 159

10.2.3 Telecommunication Technology 160

10.2.4 Internet of Things Information and Evaluation 166

10.2.4.1 Distributed Evaluation 166

10.2.4.2 Fog Computing (Edge Computing) 167

10.3 Internet of Things within Power Region 167

10.3.1 Internet of Things along with Vitality Production 168

10.3.2 Smart Metropolises 168

10.3.3 Intelligent Lattice Network 171

10.3.4 Smart Buildings Structures 172

10.3.5 Powerful Usage of Vitality in Production 173

10.3.6 Insightful Transport 174

10.4 Difficulties - Relating Internet of Things 174

10.4.1 Vitality Ingestion 178

10.4.2 Synchronization via Internet of Things through Sub-Units 178

10.4.3 Client Confidentiality 180

10.4.4 Safety Challenges 180

10.4.5 IoT Standardization and Architectural Concept 181

10.5 Upcoming Developments 182

10.5.1 IoT and Block Chain 182

10.5.2 Artificial Intelligence and IoT 184

10.5.3 Green IoT 185

10.6 Conclusion 187

References 188

11 EFFICIENT RENEWABLE ENERGY SYSTEMS 199

Prabhansu and Nayan Kumar

Introduction 199

11.1 Renewable-Based Available Technologies 200

11.1.1 Wind Power 201

11.1.1.1 Modeling of the Wind Turbine Generator (WTG) 201

11.1.1.2 Categorization of Wind Turbine 202

11.1.2 Solar Power 202

11.1.2.1 PV System 202

11.1.2.2 Network-Linked Photovoltaic Grid-Connected PV Set-Up 203

11.1.3 Tidal Energy 203

11.1.4 Battery Storage System 204

11.1.5 Solid Oxide Energy Units for Enhancing Power Life 204

11.1.5.1 Common Utility of SOFC 204

11.1.5.2 Integrated Solid Oxide Energy Components and Sustainable Power Life 205

11.2 Adaptability Frameworks 206

11.2.1 Distributed Energy Resources (DER) 206

11.2.2 New Age Grid Connection 209

11.3 Conclusion 210

References 211

12 EFFICIENT RENEWABLE ENERGY SYSTEMS 215

Dr. Arvind Dhingra

12.1 Introduction 215

12.1.1 World Energy Scenario 215

12.2 Sources of Energy: Classification 217

12.3 Renewable Energy Systems 217

12.3.1 Solar Energy 218

12.3.2 Wind 218

12.3.3 Geothermal 218

12.3.4 Biomass 218

12.3.5 Ocean 218

12.3.6 Hydrogen 218

12.4 Solar Energy 218

12.5 Wind Energy 223

12.6 Geothermal Energy 225

12.7 Biomass 226

12.7.1 Forms of Biomass 226

12.8 Ocean Power 227

12.9 Hydrogen 227

12.10 Hydro Power 227

12.11 Conclusion 227

References 227

13 AGRICULTURE-IOT-BASED SPRINKLER SYSTEM FOR WATER AND FERTILIZER CONSERVATION AND MANAGEMENT 229

Dilip Kumar and Ujala Choudhury

13.1 Introduction 229

13.1.1 Novelty of the Work 232

13.1.2 Benefit to Society 232

13.2 Development of the Proposed System 233

13.3 System Description 233

13.3.1 Study of the Crop Under Experiment 233

13.3.2 Hardware of the System 235

13.3.3 Software of the System 235

13.4 Layers of the System Architecture 236

13.4.1 Application Layer 236

13.4.2 Cloud Layer 237

13.4.3 Network Layer 237

13.4.4 Physical Layer 237

13.5 Calibration 237

13.6 Layout of the Sprinkler System 239

13.7 Testing 239

13.8 Results and Discussion 241

13.9 Conclusion 242

References 242

14 A BEHAVIOUR-BASED AUTHENTICATION TO INTERNET OF THINGS USING MACHINE LEARNING 245

Mohit Goyal and Durgesh Srivastava

14.1 Introduction 246

14.2 Basics of Internet of Things (IoT) 246

14.2.1 The IoT Reference Model 248

14.2.2 Working of IoT 249

14.2.2.1 Device 249

14.2.2.2 Connectivity to Cloud 250

14.2.2.3 Data Analysis 250

14.2.2.4 User Interface 250

14.2.3 Utilization of Internet of Things (IoT) 250

14.3 Authentication in IoT 251

14.3.1 Methods of Authentication 251

14.3.1.1 Authentication Based on Knowledge 252

14.3.1.2 Authentication Based on Possession 252

14.3.1.3 Authentication Based on Biometric 253

14.4 User Authentication Based on Behavioral-Biometric 255

14.4.1 Machine Learning 256

14.4.1.1 Supervised Machine Learning 256

14.4.1.2 Unsupervised Machine Learning 256

14.4.2 Machine Learning Algorithms 257

14.4.2.1 RIPPER 257

14.4.2.2 Multilayer Perceptron 257

14.4.2.3 Decision Tree 257

14.4.2.4 Random Forest 258

14.4.2.5 Instance-Based Learning 258

14.4.2.6 Bootstrap Aggregating 258

14.4.2.7 Naïve Bayes 258

14.5 Threats and Challenges in the Current Security Solution for IoT 258

14.6 Proposed Methodology 259

14.6.1 Collection of Gait Dataset 259

14.6.2 Gait Data Preprocessing 259

14.6.3 Reduction in Data Size 260

14.6.4 Gaits Feature 260

14.6.5 Classification 260

14.7 Conclusion and Future Work 261

References 261

15 A FUZZY GOAL PROGRAMMING MODEL FOR QUALITY MONITORING OF FRUITS DURING SHIPMENT OVERSEAS 265

Pushan Kr. Dutta, Somsubhra Gupta, Simran Kumari and Akshay Vinayak

15.1 Introduction 265

15.2 Proposed System 266

15.2.1 Problem Statement 266

15.2.2 Overview 266

15.2.3 System Components 268

15.3 Work Process 271

15.3.1 System Hardware 271

15.3.2 Connections and Circuitry 271

15.4 Optimization Framework 271

15.4.1 Fuzzy Goal Description 271

15.4.2 Characterizing Fuzzy Membership Function 272

15.4.3 Construction of FGP Model 272

15.4.4 Definition of Variables and Parameters 273

15.4.5 Fuzzy Goal Description 274

15.5 Creation of Database and Website 275

15.5.1 Hosting PHP Application and Creation of MySQL Database 275

15.5.2 Creation of API (Application Programming Interfaces) Key 275

15.5.2.1 $api_key_value = “3mM44UaC2DjFcV_63GZ14aWJcRDNmYBMsxceu”; 275

15.5.2.2 Preparing Mysql Database 275

15.5.2.3 Structured Query Language (SQL) 275

15.5.2.4 Use of HTTP (Hypertext Transfer Protocol) in Posting Request 276

15.5.2.5 Adding a Dynamic Map to the Website 277

15.5.2.6 Adding Dynamic Graph to the Website 277

15.5.2.7 Adding the Download Option of the Data Set 278

15.6 Libraries Used and Code Snipped 278

15.7 Mode of Communication 280

15.8 Conclusion 280

Abbreviations 282

References 282

16 INTERNET OF THINGS – DEFINITION, ARCHITECTURE, APPLICATIONS, REQUIREMENTS AND KEY RESEARCH CHALLENGES 285

Dushyant Kumar Singh, Himani Jerath and P. Raja

16.1 Introduction 285

16.2 Defining the Term Internet of Things (IoT) 286

16.3 IoT Architecture 287

16.4 Applications of Internet of Things (IoT) 289

16.5 Requirement for Internet of Things (IoT) Implementation 290

16.6 Key Research Challenges in Internet of Things (IoT) 291

16.6.1 Computing, Communication and Identification 291

16.6.2 Network Technology 292

16.6.3 Greening of Internet of Things (IoT) 292

16.6.4 Security 293

16.6.5 Diversity 293

16.6.6 Object Safety and Security 293

16.6.7 Data Confidentiality and Unauthorized Access 293

16.6.8 Architecture 293

16.6.9 Network and Routing Information Security 293

References 294

17 FINFET TECHNOLOGY FOR LOW-POWER APPLICATIONS 297

Bindu Madhavi, Suman Lata Tripathi and Bhagwan Shree Ram

17.1 Introduction 297

17.2 Exiting Multiple-Gate MOSFET Architectures 299

17.3 FinFET Design and Analysis 301

17.4 Low-Power Applications 304

17.4.1 FinFET-Based Digital Circuit Design 304

17.4.2 FinFET-Based Memory Design 304

17.4.3 FinFET-Based Biosensors 304

17.5 Conclusion 305

References 305

18 AN ENHANCED POWER QUALITY SINGLE-SOURCE LARGE STEP-UP SWITCHED-CAPACITOR BASED MULTI-LEVEL INVERTER CONFIGURATION WITH NATURAL VOLTAGE BALANCING OF CAPACITORS 307

Mahdi Karimi, Paria Kargar, Kazem Varesi and Sanjeevikumar Padmanaban

18.1 Introduction 307

18.2 Suggested Topology 309

18.2.1 Circuit Configuration 309

18.2.2 Generation of Output Voltage Steps 310

18.2.3 Voltage Stress of Switches 320

18.3 Cascaded Configuration of Suggested Topology 320

18.4 Modulation Technique 321

18.5 Power Loss Analysis 324

18.5.1 Conduction Losses 324

18.5.2 Switching Losses 326

18.5.3 Capacitor Losses 327

18.6 Design of Capacitors 328

18.7 Comparative Analysis 330

18.8 Simulation Results 333

18.9 Conclusions 336

References 336

Index 339
Artikel-Details
Anbieter:
Wiley
Autor:
Dushyant Kumar Singh, P. Raja, Sanjeevikumar Padmanaban, Suman Lata Tripathi
Artikelnummer:
9781119761792
Veröffentlicht:
16.03.21
Seitenanzahl:
384