Design and Development of Efficient Energy Systems

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 xv1 Design of Low Power Junction-Less Double-Gate MOSFET 1Namrata Mendiratta and Suman Lata Tripathi1.1 Introduction 11.2 MOSFET Performance Parameters 21.3 Comparison of Existing MOSFET Architectures 31.4 Proposed Heavily Doped Junction-Less Double Gate MOSFET (AJ-DGMOSFET) 31.5 Heavily Doped JL-DG MOSFET for Biomedical Application 81.6 Conclusion 9References 102 VLSI Implementation of Vedic Multiplier 13Abhishek Kumar2.1 Introduction 132.2 8x8 Vedic Multiplier 142.3 The Architecture of 8x8 Vedic Multiplier (VM) 162.3.1 Compressor Architecture 172.3.1.1 3:2 Compressor 182.3.1.2 4:3 Compressor 182.3.1.3 5:3 Compressor 182.3.1.4 8:4 Compressor 192.3.1.5 10:4 Compressor 192.3.1.6 12:5 Compressor 202.3.1.7 15:5 Compressor 212.3.1.8 20:5 Compressor 212.4 Results and Discussion 232.4.1 Instance Power 232.4.2 Net Power 242.4.3 8-Bit Multiplier 252.4.4 16-Bit Multiplier 262.4.5 Applications of Multiplier 272.5 Conclusion 28References 283 Gas Leakage Detection from Drainage to Offer Safety for Sanitary Workers 31Dr. D. Jeyabharathi, Dr. D. Kesavaraja and D. Sasireka3.1 Introduction 313.1.1 IOT-Based Sewer Gas Detection 313.1.1.1 IoT Sensors 323.1.2 Objective 323.1.3 Contribution of this Chapter 333.1.4 Outline of the Chapter 333.2 Related Works 333.2.1 Sewer Gas Leakage Detection 333.2.2 Crack Detection 343.3 Methodology 343.3.1 Sewer Gas Detection 343.3.1.1 Proposed Tristate Pattern 353.3.2 Crack Detection 363.3.3 Experimental Setup 373.4 Experimental Results 393.5 Conclusion 40References 404 Machine Learning for Smart Healthcare Energy-Efficient System 43S. Porkodi, Dr. D. Kesavaraja and Dr. Sivanthi Aditanar4.1 Introduction 434.1.1 IoT in the Digital Age 434.1.2 Using IoT to Enhance Healthcare Services 444.1.3 Edge Computing 444.1.4 Machine Learning 444.1.5 Application in Healthcare 454.2 Related Works 454.3 Edge Computing 474.3.1 Architecture 474.3.2 Advantages of Edge Computing over Cloud Computing 474.3.3 Applications of Edge Computing in Healthcare 484.3.4 Edge Computing Advantages 494.3.5 Challenges 504.4 Smart Healthcare System 504.4.1 Methodology 504.4.2 Data Acquisition and IoT End Device 514.4.3 IoT End Device and Backend Server 514.5 Conclusion and Future Directions 52References 525 Review of Machine Learning Techniques Used for Intrusion and Malware Detection in WSNs and IoT Devices 57Dr. Jeyabharathi, Dr. A. Sherly Alphonse, Ms. E.L. Dhivya Priya and Dr. M. Kowsigan5.1 Introduction 575.2 Types of Attacks 585.3 Some Countermeasures for the Attacks 595.4 Machine Learning Solutions 595.5 Machine Learning Algorithms 595.6 Authentication Process Based on Machine Learning 605.7 Internet of Things (IoT) 625.8 IoT-Based Attacks 625.8.1 Botnets 625.8.2 Man-in-the-Middle 625.9 Information and Identity Theft 625.10 Social Engineering 635.11 Denial of Service 635.12 Concerns 635.13 Conclusion 64References 646 Smart Energy-Efficient Techniques for Large-Scale Process Industries 67B Koti Reddy and N V Raghavaiah6.1 Pumps Operation 676.1.1 Parts in a Centrifugal Pump 686.1.2 Pump Efficiency 686.1.3 VFD 706.1.4 VFD and Pump Motor 726.1.5 Large HT Motors 736.1.6 Smart Pumps 736.2 Vapour Absorption Refrigeration System 746.2.1 Vapour Compression Refrigeration 746.2.2 Vapour Absorption Refrigeration 756.3 Heat Recovery Equipment 776.3.1 Case Study 776.3.2 Advantages of Heat Recovery 786.4 Lighting System 786.4.1 Technical Terms 786.4.2 Introduction 786.4.3 LED Lighting 796.4.4 Energy-Efficiency Techniques 796.4.5 Light Control with IoT 806.4.5.1 Wipro Scheme 806.4.5.2 Tata Scheme 806.4.6 EU Practices 816.5 Air Conditioners 826.5.1 Technical Terms 826.5.2 Types of Air Conditioners 826.5.3 Star Rating of BEE 836.5.4 EU Practices 836.5.5 Energy-Efficiency Tips 836.5.6 Inverter Air Conditioners 856.5.7 IoT-Based Air Conditioners 856.6 Fans and Other Smart Appliances 866.6.1 BLDC Fan Motors 876.6.2 Star Ratings 876.6.3 Group Drive of Fans 886.6.4 Other Smart Appliances 886.7 Motors 926.7.1 Motor Efficiency 926.7.2 Underrated Operation 936.7.3 Energy-Efficient Motors 946.7.3.1 Energy-Efficiency Ratings of BEE 946.7.3.2 Energy-Efficiency Ratings of IEC 946.7.4 Retrofit of Standard Motors with Energy-Efficient Motors 966.7.5 Other Salient Points 976.7.6 Use of Star-Delta Starter Motor 976.8 Energy-Efficient Transformers 986.8.1 IEC Recommendation 986.8.2 Super Conducting Transformers 99References 997 Link Restoration and Relay Node Placement in Partitioned Wireless Sensor Network 101Manwinder Singh and Anudeep Gandam7.1 Introduction 1017.2 Related Work 1037.2.1 Existing Techniques 1057.3 Proposed K-Means Clustering Algorithm 1057.3.1 Homogenous and Heterogeneous Network Clustering Algorithms 1057.3.2 Dynamic and Static Clustering 1057.3.2.1 Routing 1067.3.3 Flow Diagram 1067.3.4 Objective Function 1067.4 System Model and Assumption 1087.4.1 Simulation Parameters 1087.4.1.1 Residual Energy 1087.4.1.2 End-to-End Delay 1097.4.1.3 Number of Hops or Hop Count in the Network 1097.5 Results and Discussion 1097.6 Conclusions 114References 1158 Frequency Modulated PV Powered MLI Fed Induction Motor Drive for Water Pumping Applications 119Arunkumar S, Mohana Sundaram N and K. Malarvizhi8.1 Introduction 1198.2 PV Panel as Energy Source 1208.2.1 Solar Cell 1208.3 Multi-Level Inverter Topologies 1218.3.1 Types of Inverters Used for Drives 1218.3.2 Multi-Level Inverters 1218.4 Experimental Results and Discussion 1228.4.1 PV Powered H Bridge Inverter-Fed Drive 1238.4.2 PV Powered DCMLI Fed Drive 1268.5 Conclusion and Future Scope 128References 1299 Analysis and Design of Bidirectional Circuits for Energy Storage Application 131Suresh K, Sanjeevikumar Padmanaban and S Vivek9.1 Introduction 1319.2 Modes of Operation Based on Main Converters 1339.2.1 Single-Stage Rectification 1349.2.2 Single-Stage Inversion 1359.2.3 Double-Stage Rectification 1379.2.3.1 Duty Mode - Interval -I 1379.2.3.2 Freewheeling Mode - Interval -II 1389.2.4 Double-Stage Inversion 1399.2.4.1 Charging Mode - Interval -I 1409.2.4.2 Duty Mode - Interval -II 1419.3 Proposed Methodology for Three-Phase System 1419.3.1 Control Block of Overall System 1439.3.2 Proposed Carrier-Based PWM Strategy 1449.3.3 Experiment Results 1459.4 Conclusion 148References 14810 Low-Power IOT-Enabled Energy Systems 151Yogini Dilip Borole and Dr. C. G. Dethe10.1 Overview 15110.1.1 Conceptions 15110.1.2 Motivation 15210.1.3 Methodology 15410.2 Empowering Tools 15610.2.1 Sensing Components 15610.2.2 Movers 15910.2.3 Telecommunication Technology 16010.2.4 Internet of Things Information and Evaluation 16610.2.4.1 Distributed Evaluation 16610.2.4.2 Fog Computing (Edge Computing) 16710.3 Internet of Things within Power Region 16710.3.1 Internet of Things along with Vitality Production 16810.3.2 Smart Metropolises 16810.3.3 Intelligent Lattice Network 17110.3.4 Smart Buildings Structures 17210.3.5 Powerful Usage of Vitality in Production 17310.3.6 Insightful Transport 17410.4 Difficulties - Relating Internet of Things 17410.4.1 Vitality Ingestion 17810.4.2 Synchronization via Internet of Things through Sub-Units 17810.4.3 Client Confidentiality 18010.4.4 Safety Challenges 18010.4.5 IoT Standardization and Architectural Concept 18110.5 Upcoming Developments 18210.5.1 IoT and Block Chain 18210.5.2 Artificial Intelligence and IoT 18410.5.3 Green IoT 18510.6 Conclusion 187References 18811 Efficient Renewable Energy Systems 199Prabhansu and Nayan KumarIntroduction 19911.1 Renewable-Based Available Technologies 20011.1.1 Wind Power 20111.1.1.1 Modeling of the Wind Turbine Generator (WTG) 20111.1.1.2 Categorization of Wind Turbine 20211.1.2 Solar Power 20211.1.2.1 PV System 20211.1.2.2 Network-Linked Photovoltaic Grid-Connected PV Set-Up 20311.1.3 Tidal Energy 20311.1.4 Battery Storage System 20411.1.5 Solid Oxide Energy Units for Enhancing Power Life 20411.1.5.1 Common Utility of SOFC 20411.1.5.2 Integrated Solid Oxide Energy Components and Sustainable Power Life 20511.2 Adaptability Frameworks 20611.2.1 Distributed Energy Resources (DER) 20611.2.2 New Age Grid Connection 20911.3 Conclusion 210References 21112 Efficient Renewable Energy Systems 215Dr. Arvind Dhingra12.1 Introduction 21512.1.1 World Energy Scenario 21512.2 Sources of Energy: Classification 21712.3 Renewable Energy Systems 21712.3.1 Solar Energy 21812.3.2 Wind 21812.3.3 Geothermal 21812.3.4 Biomass 21812.3.5 Ocean 21812.3.6 Hydrogen 21812.4 Solar Energy 21812.5 Wind Energy 22312.6 Geothermal Energy 22512.7 Biomass 22612.7.1 Forms of Biomass 22612.8 Ocean Power 22712.9 Hydrogen 22712.10 Hydro Power 22712.11 Conclusion 227References 22713 Agriculture-IoT-Based Sprinkler System for Water and Fertilizer Conservation and Management 229Dilip Kumar and Ujala Choudhury13.1 Introduction 22913.1.1 Novelty of the Work 23213.1.2 Benefit to Society 23213.2 Development of the Proposed System 23313.3 System Description 23313.3.1 Study of the Crop Under Experiment 23313.3.2 Hardware of the System 23513.3.3 Software of the System 23513.4 Layers of the System Architecture 23613.4.1 Application Layer 23613.4.2 Cloud Layer 23713.4.3 Network Layer 23713.4.4 Physical Layer 23713.5 Calibration 23713.6 Layout of the Sprinkler System 23913.7 Testing 23913.8 Results and Discussion 24113.9 Conclusion 242References 24214 A Behaviour-Based Authentication to Internet of Things Using Machine Learning 245Mohit Goyal and Durgesh Srivastava14.1 Introduction 24614.2 Basics of Internet of Things (IoT) 24614.2.1 The IoT Reference Model 24814.2.2 Working of IoT 24914.2.2.1 Device 24914.2.2.2 Connectivity to Cloud 25014.2.2.3 Data Analysis 25014.2.2.4 User Interface 25014.2.3 Utilization of Internet of Things (IoT) 25014.3 Authentication in IoT 25114.3.1 Methods of Authentication 25114.3.1.1 Authentication Based on Knowledge 25214.3.1.2 Authentication Based on Possession 25214.3.1.3 Authentication Based on Biometric 25314.4 User Authentication Based on Behavioral-Biometric 25514.4.1 Machine Learning 25614.4.1.1 Supervised Machine Learning 25614.4.1.2 Unsupervised Machine Learning 25614.4.2 Machine Learning Algorithms 25714.4.2.1 RIPPER 25714.4.2.2 Multilayer Perceptron 25714.4.2.3 Decision Tree 25714.4.2.4 Random Forest 25814.4.2.5 Instance-Based Learning 25814.4.2.6 Bootstrap Aggregating 25814.4.2.7 Naïve Bayes 25814.5 Threats and Challenges in the Current Security Solution for IoT 25814.6 Proposed Methodology 25914.6.1 Collection of Gait Dataset 25914.6.2 Gait Data Preprocessing 25914.6.3 Reduction in Data Size 26014.6.4 Gaits Feature 26014.6.5 Classification 26014.7 Conclusion and Future Work 261References 26115 A Fuzzy Goal Programming Model for Quality Monitoring of Fruits during Shipment Overseas 265Pushan Kr. Dutta, Somsubhra Gupta, Simran Kumari and Akshay Vinayak15.1 Introduction 26515.2 Proposed System 26615.2.1 Problem Statement 26615.2.2 Overview 26615.2.3 System Components 26815.3 Work Process 27115.3.1 System Hardware 27115.3.2 Connections and Circuitry 27115.4 Optimization Framework 27115.4.1 Fuzzy Goal Description 27115.4.2 Characterizing Fuzzy Membership Function 27215.4.3 Construction of FGP Model 27215.4.4 Definition of Variables and Parameters 27315.4.5 Fuzzy Goal Description 27415.5 Creation of Database and Website 27515.5.1 Hosting PHP Application and Creation of MySQL Database 27515.5.2 Creation of API (Application Programming Interfaces) Key 27515.5.2.1 $api_key_value = “3mM44UaC2DjFcV_63GZ14aWJcRDNmYBMsxceu”; 27515.5.2.2 Preparing Mysql Database 27515.5.2.3 Structured Query Language (SQL) 27515.5.2.4 Use of HTTP (Hypertext Transfer Protocol) in Posting Request 27615.5.2.5 Adding a Dynamic Map to the Website 27715.5.2.6 Adding Dynamic Graph to the Website 27715.5.2.7 Adding the Download Option of the Data Set 27815.6 Libraries Used and Code Snipped 27815.7 Mode of Communication 28015.8 Conclusion 280Abbreviations 282References 28216 Internet of Things – Definition, Architecture, Applications, Requirements and Key Research Challenges 285Dushyant Kumar Singh, Himani Jerath and P. Raja16.1 Introduction 28516.2 Defining the Term Internet of Things (IoT) 28616.3 IoT Architecture 28716.4 Applications of Internet of Things (IoT) 28916.5 Requirement for Internet of Things (IoT) Implementation 29016.6 Key Research Challenges in Internet of Things (IoT) 29116.6.1 Computing, Communication and Identification 29116.6.2 Network Technology 29216.6.3 Greening of Internet of Things (IoT) 29216.6.4 Security 29316.6.5 Diversity 29316.6.6 Object Safety and Security 29316.6.7 Data Confidentiality and Unauthorized Access 29316.6.8 Architecture 29316.6.9 Network and Routing Information Security 293References 29417 FinFET Technology for Low-Power Applications 297Bindu Madhavi, Suman Lata Tripathi and Bhagwan Shree Ram17.1 Introduction 29717.2 Exiting Multiple-Gate MOSFET Architectures 29917.3 FinFET Design and Analysis 30117.4 Low-Power Applications 30417.4.1 FinFET-Based Digital Circuit Design 30417.4.2 FinFET-Based Memory Design 30417.4.3 FinFET-Based Biosensors 30417.5 Conclusion 305References 30518 An Enhanced Power Quality Single-Source Large Step-Up Switched-Capacitor Based Multi-Level Inverter Configuration with Natural Voltage Balancing of Capacitors 307Mahdi Karimi, Paria Kargar, Kazem Varesi and Sanjeevikumar Padmanaban18.1 Introduction 30718.2 Suggested Topology 30918.2.1 Circuit Configuration 30918.2.2 Generation of Output Voltage Steps 31018.2.3 Voltage Stress of Switches 32018.3 Cascaded Configuration of Suggested Topology 32018.4 Modulation Technique 32118.5 Power Loss Analysis 32418.5.1 Conduction Losses 32418.5.2 Switching Losses 32618.5.3 Capacitor Losses 32718.6 Design of Capacitors 32818.7 Comparative Analysis 33018.8 Simulation Results 33318.9 Conclusions 336References 336Index 339