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Группа авторов. Design and Development of Efficient Energy Systems
Table of Contents
List of Illustrations
List of Tables
Guide
Pages
Design and Development of Efficient Energy Systems
Preface
1. Design of Low Power Junction-Less Double-Gate MOSFET
1.1 Introduction
1.2 MOSFET Performance Parameters
1.3 Comparison of Existing MOSFET Architectures
1.4 Proposed Heavily Doped Junction-Less Double Gate MOSFET (AJ-DGMOSFET)
1.5 Heavily Doped JL-DG MOSFET for Biomedical Application
1.6 Conclusion
References
2. VLSI Implementation of Vedic Multiplier
2.1 Introduction
2.2 8x8 Vedic Multiplier
2.3 The Architecture of 8x8 Vedic Multiplier (VM)
2.3.1 Compressor Architecture
2.3.1.1 3:2 Compressor
2.3.1.2 4:3 Compressor
2.3.1.3 5:3 Compressor
2.3.1.4 8:4 Compressor
2.3.1.5 10:4 Compressor
2.3.1.6 12:5 Compressor
2.3.1.7 15:5 Compressor
2.3.1.8 20:5 Compressor
2.4 Results and Discussion
2.4.1 Instance Power
2.4.2 Net Power
2.4.3 8-Bit Multiplier
2.4.4 16-Bit Multiplier
2.4.5 Applications of Multiplier
2.5 Conclusion
References
3. Gas Leakage Detection from Drainage to Offer Safety for Sanitary Workers
3.1 Introduction. 3.1.1 IOT-Based Sewer Gas Detection
3.1.1.1 IoT Sensors
3.1.2 Objective
3.1.3 Contribution of this Chapter
3.1.4 Outline of the Chapter
3.2 Related Works
3.2.1 Sewer Gas Leakage Detection
3.2.2 Crack Detection
3.3 Methodology
3.3.1 Sewer Gas Detection
3.3.1.1 Proposed Tristate Pattern
3.3.2 Crack Detection
3.3.3 Experimental Setup
3.4 Experimental Results
3.5 Conclusion
References
4. Machine Learning for Smart Healthcare Energy-Efficient System
4.1 Introduction. 4.1.1 IoT in the Digital Age
4.1.2 Using IoT to Enhance Healthcare Services
4.1.3 Edge Computing
4.1.4 Machine Learning
4.1.5 Application in Healthcare
4.2 Related Works
4.3 Edge Computing. 4.3.1 Architecture
4.3.2 Advantages of Edge Computing over Cloud Computing
4.3.3 Applications of Edge Computing in Healthcare
4.3.4 Edge Computing Advantages
4.3.5 Challenges
4.4 Smart Healthcare System. 4.4.1 Methodology
4.4.2 Data Acquisition and IoT End Device
4.4.3 IoT End Device and Backend Server
4.5 Conclusion and Future Directions
References
5. Review of Machine Learning Techniques Used for Intrusion and Malware Detection in WSNs and IoT Devices
5.1 Introduction
5.2 Types of Attacks
5.3 Some Countermeasures for the Attacks
5.4 Machine Learning Solutions
5.5 Machine Learning Algorithms
5.6 Authentication Process Based on Machine Learning
5.7 Internet of Things (IoT)
5.8 IoT-Based Attacks. 5.8.1 Botnets
5.8.2 Man-in-the-Middle
5.9 Information and Identity Theft
5.10 Social Engineering
5.11 Denial of Service
5.12 Concerns
5.13 Conclusion
References
6. Smart Energy-Efficient Techniques for Large-Scale Process Industries
6.1 Pumps Operation
6.1.1 Parts in a Centrifugal Pump
6.1.2 Pump Efficiency
6.1.3 VFD
6.1.4 VFD and Pump Motor
6.1.5 Large HT Motors
6.1.6 Smart Pumps
6.2 Vapour Absorption Refrigeration System
6.2.1 Vapour Compression Refrigeration
6.2.2 Vapour Absorption Refrigeration
6.3 Heat Recovery Equipment
6.3.1 Case Study
6.3.2 Advantages of Heat Recovery
6.4 Lighting System. 6.4.1 Technical Terms
6.4.2 Introduction
6.4.3 LED Lighting
6.4.4 Energy-Efficiency Techniques
6.4.5 Light Control with IoT
6.4.5.1 Wipro Scheme
6.4.5.2 Tata Scheme
6.4.6 EU Practices
6.5 Air Conditioners
6.5.1 Technical Terms
6.5.2 Types of Air Conditioners
6.5.3 Star Rating of BEE
6.5.4 EU Practices
6.5.5 Energy-Efficiency Tips
6.5.6 Inverter Air Conditioners
6.5.7 IoT-Based Air Conditioners
6.6 Fans and Other Smart Appliances
6.6.1 BLDC Fan Motors
6.6.2 Star Ratings
6.6.3 Group Drive of Fans
6.6.4 Other Smart Appliances
6.7 Motors
6.7.1 Motor Efficiency
6.7.2 Underrated Operation
6.7.3 Energy-Efficient Motors
6.7.3.1 Energy-Efficiency Ratings of BEE
6.7.3.2 Energy-Efficiency Ratings of IEC
6.7.4 Retrofit of Standard Motors with Energy-Efficient Motors
6.7.5 Other Salient Points
6.7.6 Use of Star-Delta Starter Motor
6.8 Energy-Efficient Transformers
6.8.1 IEC Recommendation
6.8.2 Super Conducting Transformers
References
7. Link Restoration and Relay Node Placement in Partitioned Wireless Sensor Network
7.1 Introduction
7.2 Related Work
7.2.1 Existing Techniques
7.3 Proposed K-Means Clustering Algorithm
7.3.1 Homogenous and Heterogeneous Network Clustering Algorithms
7.3.2 Dynamic and Static Clustering
7.3.2.1 Routing
7.3.3 Flow Diagram
7.3.4 Objective Function
7.4 System Model and Assumption
7.4.1 Simulation Parameters
7.4.1.1 Residual Energy
7.4.1.2 End-to-End Delay
7.4.1.3 Number of Hops or Hop Count in the Network
7.5 Results and Discussion
7.6 Conclusions
References
8. Frequency Modulated PV Powered MLI Fed Induction Motor Drive for Water Pumping Applications
8.1 Introduction
8.2 PV Panel as Energy Source. 8.2.1 Solar Cell
8.3 Multi-Level Inverter Topologies. 8.3.1 Types of Inverters Used for Drives
8.3.2 Multi-Level Inverters
8.4 Experimental Results and Discussion
8.4.1 PV Powered H Bridge Inverter-Fed Drive
8.4.2 PV Powered DCMLI Fed Drive
8.5 Conclusion and Future Scope
References
9. Analysis and Design of Bidirectional Circuits for Energy Storage Application
9.1 Introduction
9.2 Modes of Operation Based on Main Converters
9.2.1 Single-Stage Rectification
9.2.2 Single-Stage Inversion
9.2.3 Double-Stage Rectification
9.2.3.1 Duty Mode - Interval -I
9.2.3.2 Freewheeling Mode - Interval -II
9.2.4 Double-Stage Inversion
9.2.4.1 Charging Mode - Interval -I
9.2.4.2 Duty Mode - Interval -II
9.3 Proposed Methodology for Three-Phase System
9.3.1 Control Block of Overall System
9.3.2 Proposed Carrier-Based PWM Strategy
9.3.3 Experiment Results
9.4 Conclusion
References
10. Low-Power IOT-Enabled Energy Systems
10.1 Overview. 10.1.1 Conceptions
10.1.2 Motivation
10.1.3 Methodology
10.2 Empowering Tools
10.2.1 Sensing Components
10.2.2 Movers
10.2.3 Telecommunication Technology
10.2.4 Internet of Things Information and Evaluation
10.2.4.1 Distributed Evaluation
10.2.4.2 Fog Computing (Edge Computing)
10.3 Internet of Things within Power Region
10.3.1 Internet of Things along with Vitality Production
10.3.2 Smart Metropolises
10.3.3 Intelligent Lattice Network
10.3.4 Smart Buildings Structures
10.3.5 Powerful Usage of Vitality in Production
10.3.6 Insightful Transport
10.4 Difficulties - Relating Internet of Things
10.4.1 Vitality Ingestion
10.4.2 Synchronization via Internet of Things through Sub-Units
10.4.3 Client Confidentiality
10.4.4 Safety Challenges
10.4.5 IoT Standardization and Architectural Concept
10.5 Upcoming Developments
10.5.1 IoT and Block Chain
10.5.2 Artificial Intelligence and IoT
10.5.3 Green IoT
10.6 Conclusion
References
11. Efficient Renewable Energy Systems
Introduction
11.1 Renewable-Based Available Technologies
11.1.1 Wind Power
11.1.1.1 Modeling of the Wind Turbine Generator (WTG)
11.1.1.2 Categorization of Wind Turbine
11.1.2 Solar Power
11.1.2.1 PV System
11.1.2.2 Network-Linked Photovoltaic Grid-Connected PV Set-Up
11.1.3 Tidal Energy
11.1.4 Battery Storage System
11.1.5 Solid Oxide Energy Units for Enhancing Power Life
11.1.5.1 Common Utility of SOFC
11.1.5.2 Integrated Solid Oxide Energy Components and Sustainable Power Life
11.2 Adaptability Frameworks
11.2.1 Distributed Energy Resources (DER)
11.2.2 New Age Grid Connection
11.3 Conclusion
References
12. Efficient Renewable Energy Systems
12.1 Introduction
12.1.1 World Energy Scenario
12.2 Sources of Energy: Classification
12.3 Renewable Energy Systems
12.3.1 Solar Energy
12.3.2 Wind
12.3.3 Geothermal
12.3.4 Biomass
12.3.5 Ocean
12.3.6 Hydrogen
12.4 Solar Energy
12.5 Wind Energy
12.6 Geothermal Energy
12.7 Biomass
12.7.1 Forms of Biomass
12.8 Ocean Power
12.9 Hydrogen
12.10 Hydro Power
12.11 Conclusion
References
13. Agriculture-IoT-Based Sprinkler System for Water and Fertilizer Conservation and Management
13.1 Introduction
13.1.1 Novelty of the Work
13.1.2 Benefit to Society
13.2 Development of the Proposed System
13.3 System Description
13.3.1 Study of the Crop Under Experiment
13.3.2 Hardware of the System
13.3.3 Software of the System
13.4 Layers of the System Architecture
13.4.1 Application Layer
13.4.2 Cloud Layer
13.4.3 Network Layer
13.4.4 Physical Layer
13.5 Calibration
13.6 Layout of the Sprinkler System
13.7 Testing
13.8 Results and Discussion
13.9 Conclusion
References
14. A Behaviour-Based Authentication to Internet of Things Using Machine Learning
14.1 Introduction
14.2 Basics of Internet of Things (IoT)
14.2.1 The IoT Reference Model
14.2.2 Working of IoT
14.2.2.1 Device
14.2.2.2 Connectivity to Cloud
14.2.2.3 Data Analysis
14.2.2.4 User Interface
14.2.3 Utilization of Internet of Things (IoT)
14.3 Authentication in IoT
14.3.1 Methods of Authentication
14.3.1.1 Authentication Based on Knowledge
14.3.1.2 Authentication Based on Possession
14.3.1.3 Authentication Based on Biometric
14.3.1.3.1 Authentication Based on Physical Biometric
14.3.1.3.2 Authentication Based on Behavioral Biometric
14.4 User Authentication Based on Behavioral-Biometric
14.4.1 Machine Learning
14.4.1.1 Supervised Machine Learning
14.4.1.2 Unsupervised Machine Learning
14.4.2 Machine Learning Algorithms
14.4.2.1 RIPPER
14.4.2.2 Multilayer Perceptron
14.4.2.3 Decision Tree
14.4.2.4 Random Forest
14.4.2.5 Instance-Based Learning
14.4.2.6 Bootstrap Aggregating
14.4.2.7 Naïve Bayes
14.5 Threats and Challenges in the Current Security Solution for IoT
14.6 Proposed Methodology
14.6.1 Collection of Gait Dataset
14.6.2 Gait Data Preprocessing
14.6.3 Reduction in Data Size
14.6.4 Gaits Feature
14.6.5 Classification
14.7 Conclusion and Future Work
References
15. A Fuzzy Goal Programming Model for Quality Monitoring of Fruits during Shipment Overseas
15.1 Introduction
15.2 Proposed System. 15.2.1 Problem Statement
15.2.2 Overview
15.2.3 System Components
15.3 Work Process. 15.3.1 System Hardware
15.3.2 Connections and Circuitry
15.4 Optimization Framework
15.4.1 Fuzzy Goal Description
15.4.2 Characterizing Fuzzy Membership Function
15.4.3 Construction of FGP Model
15.4.4 Definition of Variables and Parameters
15.4.5 Fuzzy Goal Description
15.5 Creation of Database and Website. 15.5.1 Hosting PHP Application and Creation of MySQL Database
15.5.2 Creation of API (Application Programming Interfaces) Key
15.5.2.1 $api_key_value = “3mM44UaC2DjFcV_63GZ14aWJcRDNmYBMsxceu”;
15.5.2.2 Preparing Mysql Database
15.5.2.3 Structured Query Language (SQL)
15.5.2.4 Use of HTTP (Hypertext Transfer Protocol) in Posting Request
15.5.2.5 Adding a Dynamic Map to the Website
15.5.2.6 Adding Dynamic Graph to the Website
15.5.2.7 Adding the Download Option of the Data Set
15.6 Libraries Used and Code Snipped
15.7 Mode of Communication
15.8 Conclusion
Abbreviations
References
16. Internet of Things – Definition, Architecture, Applications, Requirements and Key Research Challenges
16.1 Introduction
16.2 Defining the Term Internet of Things (IoT)
16.3 IoT Architecture
16.4 Applications of Internet of Things (IoT)
16.5 Requirement for Internet of Things (IoT) Implementation
16.6 Key Research Challenges in Internet of Things (IoT)
16.6.1 Computing, Communication and Identification
16.6.2 Network Technology
16.6.3 Greening of Internet of Things (IoT)
16.6.4 Security
16.6.5 Diversity
16.6.6 Object Safety and Security
16.6.7 Data Confidentiality and Unauthorized Access
16.6.8 Architecture
16.6.9 Network and Routing Information Security
References
17. FinFET Technology for Low-Power Applications
17.1 Introduction
17.2 Exiting Multiple-Gate MOSFET Architectures
17.3 FinFET Design and Analysis
17.4 Low-Power Applications
17.4.1 FinFET-Based Digital Circuit Design
17.4.2 FinFET-Based Memory Design
17.4.3 FinFET-Based Biosensors
17.5 Conclusion
References
18. An Enhanced Power Quality Single-Source Large Step-Up Switched-Capacitor Based Multi-Level Inverter Configuration with Natural Voltage Balancing of Capacitors
18.1 Introduction
18.2 Suggested Topology. 18.2.1 Circuit Configuration
18.2.2 Generation of Output Voltage Steps
18.2.3 Voltage Stress of Switches
18.3 Cascaded Configuration of Suggested Topology
18.4 Modulation Technique
18.5 Power Loss Analysis
18.5.1 Conduction Losses
18.5.2 Switching Losses
18.5.3 Capacitor Losses
18.6 Design of Capacitors
18.7 Comparative Analysis
18.8 Simulation Results
18.9 Conclusions
References
Index
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