Milind Shrinivas Dangate, PhD, is currently an associate professor in the Department of Chemistry, Vellore Institute of Technology, Chennai, India. He has authored several publications and has a grant and a fellowship to his credit, in addition to several postdoctoral appointments. W. S. Sampath, PhD, is a professor in the Department of Mechanical Engineering, Colorado State University, Director for Next Generation Photovoltaics (NGPV) Laboratory at Colorado State University, and Site Director at NSF I/UCRC for Next Generation Photovoltaics. With over 30 years of industry experience, he has contributed significantly to the science of renewable energy. O. V. Gnana Swathika, PhD, is an associate professor in the School of Electrical Engineering at VIT Chennai, India. She earned her PhD in electrical engineering at VIT University and completed her postdoc at the University of Moratuwa, Sri Lanka. Sanjeevikumar Padmanaban, PhD, is a faculty member with the Department of Electrical Engineering, IT and Cybernetics, University of South-Eastern Norway, Porsgrunn, Norway. He received his PhD in electrical engineering from the University of Bologna, Italy. 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. He is currently involved in publishing multiple books with Wiley-Scrivener.

• Preface xvii1 Green Economy and the Future in a Post-Pandemic World 1Luke Gerard Christie and Deepa Cherian1.1 Intergovernmental Panel on Climate Change 21.2 The Need to Question How we Do Business and the Evolution of Green Policies 31.3 The Shift from Fossil Fuels to Nuclear Energy for a Cleaner, Sustainable Environment 41.4 Significance of Emergent Technologies in the Reduction of Global Warming and Climate Change 6Conclusion 8Bibliography 92 Home Automation System Using Internet of Things for Real-Time Power Analysis and Control of Devices 11Richik Ray, Rishita Shanker, V. Anantha Krishnan, O.V. Gnana Swathika and C. Vaithilingam2.1 Introduction 122.2 Methodology 142.3 Design Specifications 152.3.1 Components Required 152.3.2 Circuit Diagram and Working 182.3.3 Blynk GUI (Graphical User Interface) for Smartphone 192.3.4 PCB (Printed Circuit Board) Design 202.4 Results and Discussion 202.4.1 Prototype Design Completion 202.4.2 Testing and Observations 222.4.3 Future Prospects 232.5 Conclusion 24References 253 Energy Generation from Secondary Li-Ion Batteries to Economical Na-Ion Batteries 27R. Rajapriya and Milind Shrinivas Dangate3.1 Introduction 283.2 Li-Ion Battery 293.3 Sodium-Ion Batteries 333.4 Conclusion 40References 414 Hydrogen as a Fuel Cell 45R. Rajapriya and Milind Shrinivas Dangate4.1 Introduction 454.2 Operating Principle 484.2.1 Types of Fuel Cells 494.3 Why Hydrogen as a Fuel Cell? 504.3.1 Electrolyte 524.3.2 Catalyst Layer (At the Cathode & Anode) 524.3.3 Bipolar Plate (Cathode & Anode) 524.4 Hydrogen as an Energy-Vector in a Long-Term Fuel Cell 534.5 Application 554.6 Conclusion 56References 575 IoT and Machine Learning–Based Energy-Efficient Smart Buildings 61Aaron Biju, Gautum Subhash V.P., Menon Adarsh Sivadas, Thejus R. Krishnan, Abhijith R. Nair, Anantha Krishnan V. and O.V. Gnana Swathika5.1 Introduction 615.2 Methodology 635.3 Design Specifications 655.3.1 NodeMCU 655.3.2 Relay 655.3.3 Firebase 665.3.4 Raspberry Pi 665.3.5 Camera 665.4 Results 665.5 Conclusion 69References 696 IOT-Based Smart Metering 71Parth Bhargav, Umar Ansari, Fahad Nishat and O.V. Gnana SwathikaAbbreviations and Nomenclature 726.1 Introduction 726.1.1 Motivation 726.1.2 Objectives 736.2 Methodology 736.2.1 Advent of Smart Meter 736.2.2 Modules 776.2.3 Energy Meter 776.2.4 Wi-Fi Module 786.2.5 Arduino UNO 786.2.6 Back End 786.3 Design of IOT-Based Smart Meter 816.3.1 Energy Meter 816.3.2 Arduino UNO 826.3.3 Wi-Fi Module 836.3.4 Calculations 846.3.5 Units 846.4 Results and Discussion 846.4.1 Working 846.4.2 Readings Captured in the Excel Sheet 856.4.3 Predication Using Statistical Analytics 866.4.4 Quantitative Analytics 866.4.5 Predication of Missing Data 876.4.6 Hardware Output 876.5 Conclusion 88References 897 IoT-Based Home Automation and Power Consumption Analysis 93K. Trinath Raja, Challa Ravi Teja, K. Madhu Priya and Berlin Hency V.7.1 Introduction 947.2 Literature Review 947.3 IoT (Internet of Things) 967.4 Architecture 967.5 Software 977.5.1 IFTTT 977.5.2 ThingSpeak 977.5.3 Google Assistant 987.6 Hardware 987.6.1 DHT Sensor 987.6.2 Motor 987.6.3 NodeMCU 997.6.4 Gas Sensor 997.7 Implementation, Testing and Results 997.8 Conclusion 102References 1038 Advanced Technologies in Integrated Energy Systems 105Maheedhar and Deepa T.8.1 Introduction 1068.2 Combined Heat and Power 1078.2.1 Stirling Engines 1078.2.2 Turbines 1088.2.3 Fuel Cell 1108.2.4 Chillers 1128.2.5 PV/T System 1138.3 Economic Aspects 1148.4 Conclusion 115References 1169 A Study to Enhance the Alkaline Surfactant Polymer (ASP) Process Using Organic Base 119M.J.A. Prince and Adhithiya Venkatachalapati Thulasiraman9.1 Introduction 1199.2 Materials and Methods 1219.3 Similarity Study of NA in the Saline Water Containing Cations Having a Valency of 2 1229.4 Results and Discussion 1239.4.1 Alkalinity Contributed by NA for Intensifying the IFT Characteristics 1239.4.2 Interfacial Tension Properties 1249.4.3 The Similarity of NA + Polymer 1249.4.4 Traits of Adsorption 1259.4.5 Economics 1259.4.6 Regular NA Injection Recommendation 1259.5 Conclusions 126References 12610 Flexible Metamaterials for Energy Harvesting Applications 129K.A. Karthigeyan, E. Manikandan, E. Papanasam and S. Radha10.1 Introduction 13010.2 Metamaterials 13110.2.1 Energy Harvesting Using Metamaterials 13210.2.2 Solar Energy Harvesting 13210.2.2.1 Numerical Setup 13310.2.3 Acoustic Energy Harvesting 13510.2.4 RF Energy Harvesting 13710.3 Summary and Challenges 138References 13811 Smart Robotic Arm 141Rangit Ray, Koustav Das, Akash Adhikary, Akash Pandey, Ananthakrishnan V. and O.V. Gnana SwathikaAbbreviations and Nomenclature 14111.1 Introduction 14211.1.1 Motivation 14211.1.2 Objectives 14311.1.3 Scope of the Work 14311.1.4 Organization 14311.2 Design of Robotic Arm with a Bot 14411.2.1 Design Approach 14411.2.1.1 Codes and Standards 14411.2.1.2 Realistic Constraints 14411.2.2 Design Specifications 14911.3 Project Demonstration 15211.3.1 Introduction 15211.3.2 Analytical Results 15311.3.3 Simulation Results 15311.3.4 Hardware Results 15411.4 Conclusion 15511.4.1 Cost Analysis 15511.4.2 Scope of Work 15511.4.3 Summary 155References 15612 Energy Technologies and Pricing Policies: Case Study 157Shanmugha S. and Milind Shrinivas Dangate12.1 Introduction 15712.2 Literature Review 15912.3 Non-Linear Pricing 16112.4 Agricultural Water Demand 16212.5 Priced Inputs and Unpriced Resources 16312.6 Proposed Set Up on Paper 16412.7 Empirical Model 16712.8 Identification Strategy 16812.9 Data 17012.10 Empirical Results 17112.11 Counterfactual Simulation A 17312.12 Counterfactual Simulation B 17412.13 Counterfactual Simulation: Costs of Reduced Groundwater Demand 17612.14 Conclusion 180References 18113 Energy Availability and Resource Management: Case Study 185Shanmugha S. and Milind Shrinivas Dangate13.1 Introduction 18513.2 Literature Review 18713.3 Study Area 18913.3.1 Producer Survey 19213.4 Empirical Model of Adoption 19313.5 Material and Methods 19613.6 Results 19813.7 Conclusion 203References 20414 Energy-Efficient Dough Rolling Machine 207Nerella Venkata Sai Charan, Abhishek Antony Mathew, Adnan Ahamad Syed, Nallavelli Preetham Reddy, Anantha Krishnan V. and O.V. Gnana Swathika14.1 Introduction 20814.2 Methodology 20814.3 Specifications 21014.3.1 Motor 21014.3.2 Switch Mode Power Supply (SMPS) 21014.3.3 Speed Reduction 21114.3.4 Coupler 21214.3.5 Main Base Structure 21214.3.6 Rotating Platform and Rollers 21214.3.7 Rotating Platform 21314.3.8 Rollers 21314.4 Result and Discussion 21514.5 Conclusion 215References 21515 Peak Load Management System Using Node-Red Software Considering Peak Load Analysis 217Mohit Sharan, Prantika Das, Harsh Gupta, S. Angalaeswari, T. Deepa, P. Balamurugan and D. Subbulekshmi15.1 Introduction 21815.2 Methodology 21915.2.1 Peak Demand and Load Profile 21915.2.2 Need of Peak Load Management (PLM) 22015.2.3 Data Analysis 22015.2.4 Need to Flatten the Load Curve 22115.2.5 Current Observations 22115.2.6 Equations 22115.3 Model Specifications 22115.4 Features of UI Interface 22515.4.1 App Prototype 22515.5 Conclusions 227Bibliography 22716 An Overview on the Energy Economics Associated with the Energy Industry 229Adhithiya Venkatachalapati Thulasiraman and M.J.A. Prince16.1 Time Value of Money 23016.1.1 Present Value of an Asset 23016.1.2 Future Value of an Investment 23016.1.3 Rule of 72 23116.2 Classification of Cost 23216.2.1 Fixed Cost of an Asset (FCA) 23216.2.2 Variable Cost of a Plant (VCP) 23216.2.3 Total Cost of a Plant (TCP) 23216.2.4 Break-Even Location (BEL) 23216.3 Economic Specification 23316.3.1 Return on Cost (ROC) 23316.3.2 Payback Span 23316.3.3 Net Present Worth 23316.3.4 Discounted Money Flow (DMF) 23416.3.5 Internal Charge of Returns (ICR) 23416.4 Analysis 23416.4.1 Incremental Analysis (IA) 23416.4.1.1 Pertinent Cost (PC) 23416.4.1.2 Non-Pertinent Cost (NPC) 23516.4.2 Sensitivity Analysis (SA) 23516.4.3 Replacement Analysis (RA) 23716.5 Conclusion 239Bibliography 24017 IoT-Based Unified Child Monitoring and Security System 241A.R. Mirunalini, Shwetha. S., R. Priyanka and Berlin Hency V.17.1 Introduction 24217.2 Literature Review 24317.3 Proposed System 24717.3.1 Block Diagram 24717.3.2 Design Approach 24917.3.3 Software Analysis 24917.3.4 Hardware Analysis 25217.3.4.1 Experimental Setup 25317.4 Result and Analysis 25617.5 Conclusion and Future Enhancement 25917.5.1 Conclusion and Inference 25917.5.2 Future Enhancement 260References 26018 IoT-Based Plant Health Monitoring System Using CNN and Image Processing 263Anindita Banerjee, Ekta Lal and Berlin Hency V.18.1 Introduction 26418.2 Literature Survey 26518.3 Data Analysis 26818.3.1 Convolutional Neural Network 26818.3.2 Phases of the Model 26918.3.3 Proposed Architecture 26918.4 Proposed Methodology 27118.4.1 System Module and Structure 27118.4.2 System Design and Methods 27218.4.3 Plant Disease Detection and Classification 27218.4.3.1 Dataset Used 27218.4.3.2 Preprocessing and Labelling Methods 27318.4.3.3 Procedure of Augmentation 27318.4.3.4 Training Using CNN 27318.4.3.5 Analysis 27518.4.3.6 Final Polishing of Results 27518.4.4 Hardware and Software Instruments 27518.5 Results and Discussion 27518.6 Conclusion 286References 28619 IoT-Based Self-Checkout Stores Using Face Mask Detection 291Shreya M., R. Nandita, Seshan Rajaraman and Berlin Hency V.19.1 Introduction 29219.2 Literature Review 29219.2.1 Self-Checkout Stores 29219.2.2 Face Mask Detection 29319.3 Convolution Neural Network 29519.4 Architecture 29819.5 Hardware Requirements 29919.5.1 PIR Sensor 29919.5.2 LCD 29919.5.3 Arduino UNO 29919.5.4 Piezo Sensor 29919.5.5 Potentiometer 30019.5.6 Led 30019.5.7 Raspberry Pi 30019.6 Software 30019.6.1 Jupyter Notebook 30019.6.2 TinkerCAD 30019.7 Implementation 30019.7.1 Building and Training the Model 30119.7.2 Testing The Model 30219.8 Results and Discussions 30319.9 Conclusion 306References 30620 IoT-Based Color Fault Detection Using TCS 3200in Textile Industry 309T. Kalavathidevi, S. Umadevi, S. Ramesh, D. Renukadevi and S. Revathi20.1 Introduction 31020.2 Literature Survey 31120.3 Methodology 31320.3.1 Sensor 31420.3.2 Microcontroller 31520.3.3 NodeMCU and Wi-Fi Module 31720.3.4 Servomotor 31720.3.5 IoT-Based Data Monitoring 31820.3.6 IR Sensor 31820.3.7 Proximity Sensor 31920.3.8 Blynk 31920.4 Experimental Setup 32120.5 Results and Discussion 32220.6 Conclusion 324References 32421 Energy Management System for Smart Buildings 327Shivangi Shukla, V. Jayashree Nivedhitha, Akshitha Shankar, P. Tejaswi and O.V. Gnana Swathika21.1 Introduction 32821.2 Literature Survey 32821.3 Modules of the Project 33121.3.1 Data Collection for Accurate Energy Prediction 33121.3.2 ML Prediction 33221.3.3 Web Server 33221.3.4 Hardware Description and Implementation 33221.4 Design of Smart Energy Management System 33421.4.1 Design Approach 33421.4.1.1 ML Algorithm 33421.4.1.2 EMS Algorithm 33421.4.2 Design Specifications 33621.5 Result & Analysis 33721.5.1 Introduction 33721.5.2 ML Model Results 33721.5.3 Web Page Results 33721.5.4 Hardware Results 33921.6 Conclusion 346References 34622 Mobile EV Charging Stations for Scalability of EV in the Indian Automobile Sector 349Mohit Sharan, Ameesh K. Singh, Harsh Gupta, Apurv Malhotra, Muskan Karira, O.V. Gnana Swathika and Anantha Krishnan V.22.1 Introduction 35022.2 Methodology 35022.2.1 Design Specifications 35122.2.2 Block Diagrams 35622.3 Result 35722.4 Conclusions 358Bibliography 358About the Editors 361Index 363

Milind Shrinivas Dangate, PhD, is currently an associate professor in the Department of Chemistry, Vellore Institute of Technology, Chennai, India. He has authored several publications and has a grant and a fellowship to his credit, in addition to several postdoctoral appointments. W. S. Sampath, PhD, is a professor in the Department of Mechanical Engineering, Colorado State University, Director for Next Generation Photovoltaics (NGPV) Laboratory at Colorado State University, and Site Director at NSF I/UCRC for Next Generation Photovoltaics. With over 30 years of industry experience, he has contributed significantly to the science of renewable energy. O. V. Gnana Swathika, PhD, is an associate professor in the School of Electrical Engineering at VIT Chennai, India. She earned her PhD in electrical engineering at VIT University and completed her postdoc at the University of Moratuwa, Sri Lanka. Sanjeevikumar Padmanaban, PhD, is a faculty member with the Department of Electrical Engineering, IT and Cybernetics, University of South-Eastern Norway, Porsgrunn, Norway. He received his PhD in electrical engineering from the University of Bologna, Italy. 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. He is currently involved in publishing multiple books with Wiley-Scrivener.

• Preface xvii1 Green Economy and the Future in a Post-Pandemic World 1Luke Gerard Christie and Deepa Cherian1.1 Intergovernmental Panel on Climate Change 21.2 The Need to Question How we Do Business and the Evolution of Green Policies 31.3 The Shift from Fossil Fuels to Nuclear Energy for a Cleaner, Sustainable Environment 41.4 Significance of Emergent Technologies in the Reduction of Global Warming and Climate Change 6Conclusion 8Bibliography 92 Home Automation System Using Internet of Things for Real-Time Power Analysis and Control of Devices 11Richik Ray, Rishita Shanker, V. Anantha Krishnan, O.V. Gnana Swathika and C. Vaithilingam2.1 Introduction 122.2 Methodology 142.3 Design Specifications 152.3.1 Components Required 152.3.2 Circuit Diagram and Working 182.3.3 Blynk GUI (Graphical User Interface) for Smartphone 192.3.4 PCB (Printed Circuit Board) Design 202.4 Results and Discussion 202.4.1 Prototype Design Completion 202.4.2 Testing and Observations 222.4.3 Future Prospects 232.5 Conclusion 24References 253 Energy Generation from Secondary Li-Ion Batteries to Economical Na-Ion Batteries 27R. Rajapriya and Milind Shrinivas Dangate3.1 Introduction 283.2 Li-Ion Battery 293.3 Sodium-Ion Batteries 333.4 Conclusion 40References 414 Hydrogen as a Fuel Cell 45R. Rajapriya and Milind Shrinivas Dangate4.1 Introduction 454.2 Operating Principle 484.2.1 Types of Fuel Cells 494.3 Why Hydrogen as a Fuel Cell? 504.3.1 Electrolyte 524.3.2 Catalyst Layer (At the Cathode & Anode) 524.3.3 Bipolar Plate (Cathode & Anode) 524.4 Hydrogen as an Energy-Vector in a Long-Term Fuel Cell 534.5 Application 554.6 Conclusion 56References 575 IoT and Machine Learning–Based Energy-Efficient Smart Buildings 61Aaron Biju, Gautum Subhash V.P., Menon Adarsh Sivadas, Thejus R. Krishnan, Abhijith R. Nair, Anantha Krishnan V. and O.V. Gnana Swathika5.1 Introduction 615.2 Methodology 635.3 Design Specifications 655.3.1 NodeMCU 655.3.2 Relay 655.3.3 Firebase 665.3.4 Raspberry Pi 665.3.5 Camera 665.4 Results 665.5 Conclusion 69References 696 IOT-Based Smart Metering 71Parth Bhargav, Umar Ansari, Fahad Nishat and O.V. Gnana SwathikaAbbreviations and Nomenclature 726.1 Introduction 726.1.1 Motivation 726.1.2 Objectives 736.2 Methodology 736.2.1 Advent of Smart Meter 736.2.2 Modules 776.2.3 Energy Meter 776.2.4 Wi-Fi Module 786.2.5 Arduino UNO 786.2.6 Back End 786.3 Design of IOT-Based Smart Meter 816.3.1 Energy Meter 816.3.2 Arduino UNO 826.3.3 Wi-Fi Module 836.3.4 Calculations 846.3.5 Units 846.4 Results and Discussion 846.4.1 Working 846.4.2 Readings Captured in the Excel Sheet 856.4.3 Predication Using Statistical Analytics 866.4.4 Quantitative Analytics 866.4.5 Predication of Missing Data 876.4.6 Hardware Output 876.5 Conclusion 88References 897 IoT-Based Home Automation and Power Consumption Analysis 93K. Trinath Raja, Challa Ravi Teja, K. Madhu Priya and Berlin Hency V.7.1 Introduction 947.2 Literature Review 947.3 IoT (Internet of Things) 967.4 Architecture 967.5 Software 977.5.1 IFTTT 977.5.2 ThingSpeak 977.5.3 Google Assistant 987.6 Hardware 987.6.1 DHT Sensor 987.6.2 Motor 987.6.3 NodeMCU 997.6.4 Gas Sensor 997.7 Implementation, Testing and Results 997.8 Conclusion 102References 1038 Advanced Technologies in Integrated Energy Systems 105Maheedhar and Deepa T.8.1 Introduction 1068.2 Combined Heat and Power 1078.2.1 Stirling Engines 1078.2.2 Turbines 1088.2.3 Fuel Cell 1108.2.4 Chillers 1128.2.5 PV/T System 1138.3 Economic Aspects 1148.4 Conclusion 115References 1169 A Study to Enhance the Alkaline Surfactant Polymer (ASP) Process Using Organic Base 119M.J.A. Prince and Adhithiya Venkatachalapati Thulasiraman9.1 Introduction 1199.2 Materials and Methods 1219.3 Similarity Study of NA in the Saline Water Containing Cations Having a Valency of 2 1229.4 Results and Discussion 1239.4.1 Alkalinity Contributed by NA for Intensifying the IFT Characteristics 1239.4.2 Interfacial Tension Properties 1249.4.3 The Similarity of NA + Polymer 1249.4.4 Traits of Adsorption 1259.4.5 Economics 1259.4.6 Regular NA Injection Recommendation 1259.5 Conclusions 126References 12610 Flexible Metamaterials for Energy Harvesting Applications 129K.A. Karthigeyan, E. Manikandan, E. Papanasam and S. Radha10.1 Introduction 13010.2 Metamaterials 13110.2.1 Energy Harvesting Using Metamaterials 13210.2.2 Solar Energy Harvesting 13210.2.2.1 Numerical Setup 13310.2.3 Acoustic Energy Harvesting 13510.2.4 RF Energy Harvesting 13710.3 Summary and Challenges 138References 13811 Smart Robotic Arm 141Rangit Ray, Koustav Das, Akash Adhikary, Akash Pandey, Ananthakrishnan V. and O.V. Gnana SwathikaAbbreviations and Nomenclature 14111.1 Introduction 14211.1.1 Motivation 14211.1.2 Objectives 14311.1.3 Scope of the Work 14311.1.4 Organization 14311.2 Design of Robotic Arm with a Bot 14411.2.1 Design Approach 14411.2.1.1 Codes and Standards 14411.2.1.2 Realistic Constraints 14411.2.2 Design Specifications 14911.3 Project Demonstration 15211.3.1 Introduction 15211.3.2 Analytical Results 15311.3.3 Simulation Results 15311.3.4 Hardware Results 15411.4 Conclusion 15511.4.1 Cost Analysis 15511.4.2 Scope of Work 15511.4.3 Summary 155References 15612 Energy Technologies and Pricing Policies: Case Study 157Shanmugha S. and Milind Shrinivas Dangate12.1 Introduction 15712.2 Literature Review 15912.3 Non-Linear Pricing 16112.4 Agricultural Water Demand 16212.5 Priced Inputs and Unpriced Resources 16312.6 Proposed Set Up on Paper 16412.7 Empirical Model 16712.8 Identification Strategy 16812.9 Data 17012.10 Empirical Results 17112.11 Counterfactual Simulation A 17312.12 Counterfactual Simulation B 17412.13 Counterfactual Simulation: Costs of Reduced Groundwater Demand 17612.14 Conclusion 180References 18113 Energy Availability and Resource Management: Case Study 185Shanmugha S. and Milind Shrinivas Dangate13.1 Introduction 18513.2 Literature Review 18713.3 Study Area 18913.3.1 Producer Survey 19213.4 Empirical Model of Adoption 19313.5 Material and Methods 19613.6 Results 19813.7 Conclusion 203References 20414 Energy-Efficient Dough Rolling Machine 207Nerella Venkata Sai Charan, Abhishek Antony Mathew, Adnan Ahamad Syed, Nallavelli Preetham Reddy, Anantha Krishnan V. and O.V. Gnana Swathika14.1 Introduction 20814.2 Methodology 20814.3 Specifications 21014.3.1 Motor 21014.3.2 Switch Mode Power Supply (SMPS) 21014.3.3 Speed Reduction 21114.3.4 Coupler 21214.3.5 Main Base Structure 21214.3.6 Rotating Platform and Rollers 21214.3.7 Rotating Platform 21314.3.8 Rollers 21314.4 Result and Discussion 21514.5 Conclusion 215References 21515 Peak Load Management System Using Node-Red Software Considering Peak Load Analysis 217Mohit Sharan, Prantika Das, Harsh Gupta, S. Angalaeswari, T. Deepa, P. Balamurugan and D. Subbulekshmi15.1 Introduction 21815.2 Methodology 21915.2.1 Peak Demand and Load Profile 21915.2.2 Need of Peak Load Management (PLM) 22015.2.3 Data Analysis 22015.2.4 Need to Flatten the Load Curve 22115.2.5 Current Observations 22115.2.6 Equations 22115.3 Model Specifications 22115.4 Features of UI Interface 22515.4.1 App Prototype 22515.5 Conclusions 227Bibliography 22716 An Overview on the Energy Economics Associated with the Energy Industry 229Adhithiya Venkatachalapati Thulasiraman and M.J.A. Prince16.1 Time Value of Money 23016.1.1 Present Value of an Asset 23016.1.2 Future Value of an Investment 23016.1.3 Rule of 72 23116.2 Classification of Cost 23216.2.1 Fixed Cost of an Asset (FCA) 23216.2.2 Variable Cost of a Plant (VCP) 23216.2.3 Total Cost of a Plant (TCP) 23216.2.4 Break-Even Location (BEL) 23216.3 Economic Specification 23316.3.1 Return on Cost (ROC) 23316.3.2 Payback Span 23316.3.3 Net Present Worth 23316.3.4 Discounted Money Flow (DMF) 23416.3.5 Internal Charge of Returns (ICR) 23416.4 Analysis 23416.4.1 Incremental Analysis (IA) 23416.4.1.1 Pertinent Cost (PC) 23416.4.1.2 Non-Pertinent Cost (NPC) 23516.4.2 Sensitivity Analysis (SA) 23516.4.3 Replacement Analysis (RA) 23716.5 Conclusion 239Bibliography 24017 IoT-Based Unified Child Monitoring and Security System 241A.R. Mirunalini, Shwetha. S., R. Priyanka and Berlin Hency V.17.1 Introduction 24217.2 Literature Review 24317.3 Proposed System 24717.3.1 Block Diagram 24717.3.2 Design Approach 24917.3.3 Software Analysis 24917.3.4 Hardware Analysis 25217.3.4.1 Experimental Setup 25317.4 Result and Analysis 25617.5 Conclusion and Future Enhancement 25917.5.1 Conclusion and Inference 25917.5.2 Future Enhancement 260References 26018 IoT-Based Plant Health Monitoring System Using CNN and Image Processing 263Anindita Banerjee, Ekta Lal and Berlin Hency V.18.1 Introduction 26418.2 Literature Survey 26518.3 Data Analysis 26818.3.1 Convolutional Neural Network 26818.3.2 Phases of the Model 26918.3.3 Proposed Architecture 26918.4 Proposed Methodology 27118.4.1 System Module and Structure 27118.4.2 System Design and Methods 27218.4.3 Plant Disease Detection and Classification 27218.4.3.1 Dataset Used 27218.4.3.2 Preprocessing and Labelling Methods 27318.4.3.3 Procedure of Augmentation 27318.4.3.4 Training Using CNN 27318.4.3.5 Analysis 27518.4.3.6 Final Polishing of Results 27518.4.4 Hardware and Software Instruments 27518.5 Results and Discussion 27518.6 Conclusion 286References 28619 IoT-Based Self-Checkout Stores Using Face Mask Detection 291Shreya M., R. Nandita, Seshan Rajaraman and Berlin Hency V.19.1 Introduction 29219.2 Literature Review 29219.2.1 Self-Checkout Stores 29219.2.2 Face Mask Detection 29319.3 Convolution Neural Network 29519.4 Architecture 29819.5 Hardware Requirements 29919.5.1 PIR Sensor 29919.5.2 LCD 29919.5.3 Arduino UNO 29919.5.4 Piezo Sensor 29919.5.5 Potentiometer 30019.5.6 Led 30019.5.7 Raspberry Pi 30019.6 Software 30019.6.1 Jupyter Notebook 30019.6.2 TinkerCAD 30019.7 Implementation 30019.7.1 Building and Training the Model 30119.7.2 Testing The Model 30219.8 Results and Discussions 30319.9 Conclusion 306References 30620 IoT-Based Color Fault Detection Using TCS 3200in Textile Industry 309T. Kalavathidevi, S. Umadevi, S. Ramesh, D. Renukadevi and S. Revathi20.1 Introduction 31020.2 Literature Survey 31120.3 Methodology 31320.3.1 Sensor 31420.3.2 Microcontroller 31520.3.3 NodeMCU and Wi-Fi Module 31720.3.4 Servomotor 31720.3.5 IoT-Based Data Monitoring 31820.3.6 IR Sensor 31820.3.7 Proximity Sensor 31920.3.8 Blynk 31920.4 Experimental Setup 32120.5 Results and Discussion 32220.6 Conclusion 324References 32421 Energy Management System for Smart Buildings 327Shivangi Shukla, V. Jayashree Nivedhitha, Akshitha Shankar, P. Tejaswi and O.V. Gnana Swathika21.1 Introduction 32821.2 Literature Survey 32821.3 Modules of the Project 33121.3.1 Data Collection for Accurate Energy Prediction 33121.3.2 ML Prediction 33221.3.3 Web Server 33221.3.4 Hardware Description and Implementation 33221.4 Design of Smart Energy Management System 33421.4.1 Design Approach 33421.4.1.1 ML Algorithm 33421.4.1.2 EMS Algorithm 33421.4.2 Design Specifications 33621.5 Result & Analysis 33721.5.1 Introduction 33721.5.2 ML Model Results 33721.5.3 Web Page Results 33721.5.4 Hardware Results 33921.6 Conclusion 346References 34622 Mobile EV Charging Stations for Scalability of EV in the Indian Automobile Sector 349Mohit Sharan, Ameesh K. Singh, Harsh Gupta, Apurv Malhotra, Muskan Karira, O.V. Gnana Swathika and Anantha Krishnan V.22.1 Introduction 35022.2 Methodology 35022.2.1 Design Specifications 35122.2.2 Block Diagrams 35622.3 Result 35722.4 Conclusions 358Bibliography 358About the Editors 361Index 363

Milind Shrinivas Dangate, PhD, is currently an associate professor in the Department of Chemistry, Vellore Institute of Technology, Chennai, India. He has authored several publications and has a grant and a fellowship to his credit, in addition to several postdoctoral appointments. W. S. Sampath, PhD, is a professor in the Department of Mechanical Engineering, Colorado State University, Director for Next Generation Photovoltaics (NGPV) Laboratory at Colorado State University, and Site Director at NSF I/UCRC for Next Generation Photovoltaics. With over 30 years of industry experience, he has contributed significantly to the science of renewable energy. O. V. Gnana Swathika, PhD, is an associate professor in the School of Electrical Engineering at VIT Chennai, India. She earned her PhD in electrical engineering at VIT University and completed her postdoc at the University of Moratuwa, Sri Lanka. Sanjeevikumar Padmanaban, PhD, is a faculty member with the Department of Electrical Engineering, IT and Cybernetics, University of South-Eastern Norway, Porsgrunn, Norway. He received his PhD in electrical engineering from the University of Bologna, Italy. 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. He is currently involved in publishing multiple books with Wiley-Scrivener.

• Preface xvii1 Green Economy and the Future in a Post-Pandemic World 1Luke Gerard Christie and Deepa Cherian1.1 Intergovernmental Panel on Climate Change 21.2 The Need to Question How we Do Business and the Evolution of Green Policies 31.3 The Shift from Fossil Fuels to Nuclear Energy for a Cleaner, Sustainable Environment 41.4 Significance of Emergent Technologies in the Reduction of Global Warming and Climate Change 6Conclusion 8Bibliography 92 Home Automation System Using Internet of Things for Real-Time Power Analysis and Control of Devices 11Richik Ray, Rishita Shanker, V. Anantha Krishnan, O.V. Gnana Swathika and C. Vaithilingam2.1 Introduction 122.2 Methodology 142.3 Design Specifications 152.3.1 Components Required 152.3.2 Circuit Diagram and Working 182.3.3 Blynk GUI (Graphical User Interface) for Smartphone 192.3.4 PCB (Printed Circuit Board) Design 202.4 Results and Discussion 202.4.1 Prototype Design Completion 202.4.2 Testing and Observations 222.4.3 Future Prospects 232.5 Conclusion 24References 253 Energy Generation from Secondary Li-Ion Batteries to Economical Na-Ion Batteries 27R. Rajapriya and Milind Shrinivas Dangate3.1 Introduction 283.2 Li-Ion Battery 293.3 Sodium-Ion Batteries 333.4 Conclusion 40References 414 Hydrogen as a Fuel Cell 45R. Rajapriya and Milind Shrinivas Dangate4.1 Introduction 454.2 Operating Principle 484.2.1 Types of Fuel Cells 494.3 Why Hydrogen as a Fuel Cell? 504.3.1 Electrolyte 524.3.2 Catalyst Layer (At the Cathode & Anode) 524.3.3 Bipolar Plate (Cathode & Anode) 524.4 Hydrogen as an Energy-Vector in a Long-Term Fuel Cell 534.5 Application 554.6 Conclusion 56References 575 IoT and Machine Learning–Based Energy-Efficient Smart Buildings 61Aaron Biju, Gautum Subhash V.P., Menon Adarsh Sivadas, Thejus R. Krishnan, Abhijith R. Nair, Anantha Krishnan V. and O.V. Gnana Swathika5.1 Introduction 615.2 Methodology 635.3 Design Specifications 655.3.1 NodeMCU 655.3.2 Relay 655.3.3 Firebase 665.3.4 Raspberry Pi 665.3.5 Camera 665.4 Results 665.5 Conclusion 69References 696 IOT-Based Smart Metering 71Parth Bhargav, Umar Ansari, Fahad Nishat and O.V. Gnana SwathikaAbbreviations and Nomenclature 726.1 Introduction 726.1.1 Motivation 726.1.2 Objectives 736.2 Methodology 736.2.1 Advent of Smart Meter 736.2.2 Modules 776.2.3 Energy Meter 776.2.4 Wi-Fi Module 786.2.5 Arduino UNO 786.2.6 Back End 786.3 Design of IOT-Based Smart Meter 816.3.1 Energy Meter 816.3.2 Arduino UNO 826.3.3 Wi-Fi Module 836.3.4 Calculations 846.3.5 Units 846.4 Results and Discussion 846.4.1 Working 846.4.2 Readings Captured in the Excel Sheet 856.4.3 Predication Using Statistical Analytics 866.4.4 Quantitative Analytics 866.4.5 Predication of Missing Data 876.4.6 Hardware Output 876.5 Conclusion 88References 897 IoT-Based Home Automation and Power Consumption Analysis 93K. Trinath Raja, Challa Ravi Teja, K. Madhu Priya and Berlin Hency V.7.1 Introduction 947.2 Literature Review 947.3 IoT (Internet of Things) 967.4 Architecture 967.5 Software 977.5.1 IFTTT 977.5.2 ThingSpeak 977.5.3 Google Assistant 987.6 Hardware 987.6.1 DHT Sensor 987.6.2 Motor 987.6.3 NodeMCU 997.6.4 Gas Sensor 997.7 Implementation, Testing and Results 997.8 Conclusion 102References 1038 Advanced Technologies in Integrated Energy Systems 105Maheedhar and Deepa T.8.1 Introduction 1068.2 Combined Heat and Power 1078.2.1 Stirling Engines 1078.2.2 Turbines 1088.2.3 Fuel Cell 1108.2.4 Chillers 1128.2.5 PV/T System 1138.3 Economic Aspects 1148.4 Conclusion 115References 1169 A Study to Enhance the Alkaline Surfactant Polymer (ASP) Process Using Organic Base 119M.J.A. Prince and Adhithiya Venkatachalapati Thulasiraman9.1 Introduction 1199.2 Materials and Methods 1219.3 Similarity Study of NA in the Saline Water Containing Cations Having a Valency of 2 1229.4 Results and Discussion 1239.4.1 Alkalinity Contributed by NA for Intensifying the IFT Characteristics 1239.4.2 Interfacial Tension Properties 1249.4.3 The Similarity of NA + Polymer 1249.4.4 Traits of Adsorption 1259.4.5 Economics 1259.4.6 Regular NA Injection Recommendation 1259.5 Conclusions 126References 12610 Flexible Metamaterials for Energy Harvesting Applications 129K.A. Karthigeyan, E. Manikandan, E. Papanasam and S. Radha10.1 Introduction 13010.2 Metamaterials 13110.2.1 Energy Harvesting Using Metamaterials 13210.2.2 Solar Energy Harvesting 13210.2.2.1 Numerical Setup 13310.2.3 Acoustic Energy Harvesting 13510.2.4 RF Energy Harvesting 13710.3 Summary and Challenges 138References 13811 Smart Robotic Arm 141Rangit Ray, Koustav Das, Akash Adhikary, Akash Pandey, Ananthakrishnan V. and O.V. Gnana SwathikaAbbreviations and Nomenclature 14111.1 Introduction 14211.1.1 Motivation 14211.1.2 Objectives 14311.1.3 Scope of the Work 14311.1.4 Organization 14311.2 Design of Robotic Arm with a Bot 14411.2.1 Design Approach 14411.2.1.1 Codes and Standards 14411.2.1.2 Realistic Constraints 14411.2.2 Design Specifications 14911.3 Project Demonstration 15211.3.1 Introduction 15211.3.2 Analytical Results 15311.3.3 Simulation Results 15311.3.4 Hardware Results 15411.4 Conclusion 15511.4.1 Cost Analysis 15511.4.2 Scope of Work 15511.4.3 Summary 155References 15612 Energy Technologies and Pricing Policies: Case Study 157Shanmugha S. and Milind Shrinivas Dangate12.1 Introduction 15712.2 Literature Review 15912.3 Non-Linear Pricing 16112.4 Agricultural Water Demand 16212.5 Priced Inputs and Unpriced Resources 16312.6 Proposed Set Up on Paper 16412.7 Empirical Model 16712.8 Identification Strategy 16812.9 Data 17012.10 Empirical Results 17112.11 Counterfactual Simulation A 17312.12 Counterfactual Simulation B 17412.13 Counterfactual Simulation: Costs of Reduced Groundwater Demand 17612.14 Conclusion 180References 18113 Energy Availability and Resource Management: Case Study 185Shanmugha S. and Milind Shrinivas Dangate13.1 Introduction 18513.2 Literature Review 18713.3 Study Area 18913.3.1 Producer Survey 19213.4 Empirical Model of Adoption 19313.5 Material and Methods 19613.6 Results 19813.7 Conclusion 203References 20414 Energy-Efficient Dough Rolling Machine 207Nerella Venkata Sai Charan, Abhishek Antony Mathew, Adnan Ahamad Syed, Nallavelli Preetham Reddy, Anantha Krishnan V. and O.V. Gnana Swathika14.1 Introduction 20814.2 Methodology 20814.3 Specifications 21014.3.1 Motor 21014.3.2 Switch Mode Power Supply (SMPS) 21014.3.3 Speed Reduction 21114.3.4 Coupler 21214.3.5 Main Base Structure 21214.3.6 Rotating Platform and Rollers 21214.3.7 Rotating Platform 21314.3.8 Rollers 21314.4 Result and Discussion 21514.5 Conclusion 215References 21515 Peak Load Management System Using Node-Red Software Considering Peak Load Analysis 217Mohit Sharan, Prantika Das, Harsh Gupta, S. Angalaeswari, T. Deepa, P. Balamurugan and D. Subbulekshmi15.1 Introduction 21815.2 Methodology 21915.2.1 Peak Demand and Load Profile 21915.2.2 Need of Peak Load Management (PLM) 22015.2.3 Data Analysis 22015.2.4 Need to Flatten the Load Curve 22115.2.5 Current Observations 22115.2.6 Equations 22115.3 Model Specifications 22115.4 Features of UI Interface 22515.4.1 App Prototype 22515.5 Conclusions 227Bibliography 22716 An Overview on the Energy Economics Associated with the Energy Industry 229Adhithiya Venkatachalapati Thulasiraman and M.J.A. Prince16.1 Time Value of Money 23016.1.1 Present Value of an Asset 23016.1.2 Future Value of an Investment 23016.1.3 Rule of 72 23116.2 Classification of Cost 23216.2.1 Fixed Cost of an Asset (FCA) 23216.2.2 Variable Cost of a Plant (VCP) 23216.2.3 Total Cost of a Plant (TCP) 23216.2.4 Break-Even Location (BEL) 23216.3 Economic Specification 23316.3.1 Return on Cost (ROC) 23316.3.2 Payback Span 23316.3.3 Net Present Worth 23316.3.4 Discounted Money Flow (DMF) 23416.3.5 Internal Charge of Returns (ICR) 23416.4 Analysis 23416.4.1 Incremental Analysis (IA) 23416.4.1.1 Pertinent Cost (PC) 23416.4.1.2 Non-Pertinent Cost (NPC) 23516.4.2 Sensitivity Analysis (SA) 23516.4.3 Replacement Analysis (RA) 23716.5 Conclusion 239Bibliography 24017 IoT-Based Unified Child Monitoring and Security System 241A.R. Mirunalini, Shwetha. S., R. Priyanka and Berlin Hency V.17.1 Introduction 24217.2 Literature Review 24317.3 Proposed System 24717.3.1 Block Diagram 24717.3.2 Design Approach 24917.3.3 Software Analysis 24917.3.4 Hardware Analysis 25217.3.4.1 Experimental Setup 25317.4 Result and Analysis 25617.5 Conclusion and Future Enhancement 25917.5.1 Conclusion and Inference 25917.5.2 Future Enhancement 260References 26018 IoT-Based Plant Health Monitoring System Using CNN and Image Processing 263Anindita Banerjee, Ekta Lal and Berlin Hency V.18.1 Introduction 26418.2 Literature Survey 26518.3 Data Analysis 26818.3.1 Convolutional Neural Network 26818.3.2 Phases of the Model 26918.3.3 Proposed Architecture 26918.4 Proposed Methodology 27118.4.1 System Module and Structure 27118.4.2 System Design and Methods 27218.4.3 Plant Disease Detection and Classification 27218.4.3.1 Dataset Used 27218.4.3.2 Preprocessing and Labelling Methods 27318.4.3.3 Procedure of Augmentation 27318.4.3.4 Training Using CNN 27318.4.3.5 Analysis 27518.4.3.6 Final Polishing of Results 27518.4.4 Hardware and Software Instruments 27518.5 Results and Discussion 27518.6 Conclusion 286References 28619 IoT-Based Self-Checkout Stores Using Face Mask Detection 291Shreya M., R. Nandita, Seshan Rajaraman and Berlin Hency V.19.1 Introduction 29219.2 Literature Review 29219.2.1 Self-Checkout Stores 29219.2.2 Face Mask Detection 29319.3 Convolution Neural Network 29519.4 Architecture 29819.5 Hardware Requirements 29919.5.1 PIR Sensor 29919.5.2 LCD 29919.5.3 Arduino UNO 29919.5.4 Piezo Sensor 29919.5.5 Potentiometer 30019.5.6 Led 30019.5.7 Raspberry Pi 30019.6 Software 30019.6.1 Jupyter Notebook 30019.6.2 TinkerCAD 30019.7 Implementation 30019.7.1 Building and Training the Model 30119.7.2 Testing The Model 30219.8 Results and Discussions 30319.9 Conclusion 306References 30620 IoT-Based Color Fault Detection Using TCS 3200in Textile Industry 309T. Kalavathidevi, S. Umadevi, S. Ramesh, D. Renukadevi and S. Revathi20.1 Introduction 31020.2 Literature Survey 31120.3 Methodology 31320.3.1 Sensor 31420.3.2 Microcontroller 31520.3.3 NodeMCU and Wi-Fi Module 31720.3.4 Servomotor 31720.3.5 IoT-Based Data Monitoring 31820.3.6 IR Sensor 31820.3.7 Proximity Sensor 31920.3.8 Blynk 31920.4 Experimental Setup 32120.5 Results and Discussion 32220.6 Conclusion 324References 32421 Energy Management System for Smart Buildings 327Shivangi Shukla, V. Jayashree Nivedhitha, Akshitha Shankar, P. Tejaswi and O.V. Gnana Swathika21.1 Introduction 32821.2 Literature Survey 32821.3 Modules of the Project 33121.3.1 Data Collection for Accurate Energy Prediction 33121.3.2 ML Prediction 33221.3.3 Web Server 33221.3.4 Hardware Description and Implementation 33221.4 Design of Smart Energy Management System 33421.4.1 Design Approach 33421.4.1.1 ML Algorithm 33421.4.1.2 EMS Algorithm 33421.4.2 Design Specifications 33621.5 Result & Analysis 33721.5.1 Introduction 33721.5.2 ML Model Results 33721.5.3 Web Page Results 33721.5.4 Hardware Results 33921.6 Conclusion 346References 34622 Mobile EV Charging Stations for Scalability of EV in the Indian Automobile Sector 349Mohit Sharan, Ameesh K. Singh, Harsh Gupta, Apurv Malhotra, Muskan Karira, O.V. Gnana Swathika and Anantha Krishnan V.22.1 Introduction 35022.2 Methodology 35022.2.1 Design Specifications 35122.2.2 Block Diagrams 35622.3 Result 35722.4 Conclusions 358Bibliography 358About the Editors 361Index 363