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E-raamat: Design and Development of Efficient Energy Systems

Edited by (Lovely Professional University, India), Edited by (Lovely Professional University, India), Edited by (Lovely Professional University, India), Edited by (University of South-Eastern Norway, Norway)
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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 anddevelopment. 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"--

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. 

Preface xv
1 Design of Low Power Junction-Less Double-Gate MOSFET
1(12)
Namrata Mendiratta
Suman Lata Tripathi
1.1 Introduction
1(1)
1.2 MOSFET Performance Parameters
2(1)
1.3 Comparison of Existing MOSFET Architectures
3(1)
1.4 Proposed Heavily Doped Junction-Less Double Gate MOSFET (AJ-DGMOSFET)
3(5)
1.5 Heavily Doped JL-DG MOSFET for Biomedical Application
8(1)
1.6 Conclusion
9(4)
References
10(3)
2 VLSI Implementation of Vedic Multiplier
13(18)
Abhishek Kumar
2.1 Introduction
13(1)
2.2 8×8 Vedic Multiplier
14(2)
2.3 The Architecture of 8×8 Vedic Multiplier (VM)
16(7)
2.3.1 Compressor Architecture
17(1)
2.3.1.1 3:2 Compressor
18(1)
2.3.1.2 4:3 Compressor
18(1)
2.3.1.3 5:3 Compressor
18(1)
2.3.1.4 8:4 Compressor
19(1)
2.3.1.5 10:4 Compressor
19(1)
2.3.1.6 12:5 Compressor
20(1)
2.3.1.7 15:5 Compressor
21(1)
2.3.1.8 20:5 Compressor
21(2)
2.4 Results and Discussion
23(5)
2.4.1 Instance Power
23(1)
2.4.2 Net Power
24(1)
2.4.3 8-Bit Multiplier
25(1)
2.4.4 16-Bit Multiplier
26(1)
2.4.5 Applications of Multiplier
27(1)
2.5 Conclusion
28(3)
References
28(3)
3 Gas Leakage Detection from Drainage to Offer Safety for Sanitary Workers
31(12)
Dr. D. Jeyabharathi
Dr. D. Kesavaraja
D. Sasireka
3.1 Introduction
31(2)
3.1.1 IOT-Based Sewer Gas Detection
31(1)
3.1.1.1 IoT Sensors
32(1)
3.1.2 Objective
32(1)
3.1.3 Contribution of this
Chapter
33(1)
3.1.4 Outline of the
Chapter
33(1)
3.2 Related Works
33(1)
3.2.1 Sewer Gas Leakage Detection
33(1)
3.2.2 Crack Detection
34(1)
3.3 Methodology
34(5)
3.3.1 Sewer Gas Detection
34(1)
3.3.1.1 Proposed Tristate Pattern
35(1)
3.3.2 Crack Detection
36(1)
3.3.3 Experimental Setup
37(2)
3.4 Experimental Results
39(1)
3.5 Conclusion
40(3)
References
40(3)
4 Machine Learning for Smart Healthcare Energy-Efficient System
43(14)
S. Porkodi
Dr. D. Kesavaraja
Dr. Sivanthi Aditanar
4.1 Introduction
43(2)
4.1.1 IoT in the Digital Age
43(1)
4.1.2 Using IoT to Enhance Healthcare Services
44(1)
4.1.3 Edge Computing
44(1)
4.1.4 Machine Learning
44(1)
4.1.5 Application in Healthcare
45(1)
4.2 Related Works
45(2)
4.3 Edge Computing
47(3)
4.3.1 Architecture
47(1)
4.3.2 Advantages of Edge Computing over Cloud Computing
47(1)
4.3.3 Applications of Edge Computing in Healthcare
48(1)
4.3.4 Edge Computing Advantages
49(1)
4.3.5 Challenges
50(1)
4.4 Smart Healthcare System
50(2)
4.4.1 Methodology
50(1)
4.4.2 Data Acquisition and IoT End Device
51(1)
4.4.3 IoT End Device and Backend Server
51(1)
4.5 Conclusion and Future Directions
52(5)
References
52(5)
5 Review of Machine Learning Techniques Used for Intrusion and Malware Detection in WSNs and IoT Devices
57(10)
Dr. Jeyabharathi
Dr. A. Sherly Alphonse
Ms. E.L. Dhivya Priya
Dr. M. Kowsigan
5.1 Introduction
57(1)
5.2 Types of Attacks
58(1)
5.3 Some Countermeasures for the Attacks
59(1)
5.4 Machine Learning Solutions
59(1)
5.5 Machine Learning Algorithms
59(1)
5.6 Authentication Process Based on Machine Learning
60(2)
5.7 Internet of Things (IoT)
62(1)
5.8 IoT-Based Attacks
62(1)
5.8.1 Botnets
62(1)
5.8.2 Man-in-the-Middle
62(1)
5.9 Information and Identity Theft
62(1)
5.10 Social Engineering
63(1)
5.11 Denial of Service
63(1)
5.12 Concerns
63(1)
5.13 Conclusion
64(3)
References
64(3)
6 Smart Energy-Efficient Techniques for Large-Scale Process Industries
67(34)
B. Koti Reddy
N. V. Raghavaiah
6.1 Pumps Operation
67(7)
6.1.1 Parts in a Centrifugal Pump
68(1)
6.1.2 Pump Efficiency
68(2)
6.1.3 VFD
70(2)
6.1.4 VFD and Pump Motor
72(1)
6.1.5 Large HT Motors
73(1)
6.1.6 Smart Pumps
73(1)
6.2 Vapour Absorption Refrigeration System
74(3)
6.2.1 Vapour Compression Refrigeration
74(1)
6.2.2 Vapour Absorption Refrigeration
75(2)
6.3 Heat Recovery Equipment
77(1)
6.3.1 Case Study
77(1)
6.3.2 Advantages of Heat Recovery
78(1)
6.4 Lighting System
78(4)
6.4.1 Technical Terms
78(1)
6.4.2 Introduction
78(1)
6.4.3 LED Lighting
79(1)
6.4.4 Energy-Efficiency Techniques
79(1)
6.4.5 Light Control with IoT
80(1)
6.4.5.1 Wipro Scheme
80(1)
6.4.5.2 Tata Scheme
80(1)
6.4.6 EU Practices
81(1)
6.5 Air Conditioners
82(4)
6.5.1 Technical Terms
82(1)
6.5.2 Types of Air Conditioners
82(1)
6.5.3 Star Rating of BEE
83(1)
6.5.4 EU Practices
83(1)
6.5.5 Energy-Efficiency Tips
83(2)
6.5.6 Inverter Air Conditioners
85(1)
6.5.7 IoT-Based Air Conditioners
85(1)
6.6 Fans and Other Smart Appliances
86(6)
6.6.1 BLDC Fan Motors
87(1)
6.6.2 Star Ratings
87(1)
6.6.3 Group Drive of Fans
88(1)
6.6.4 Other Smart Appliances
88(4)
6.7 Motors
92(6)
6.7.1 Motor Efficiency
92(1)
6.7.2 Underrated Operation
93(1)
6.7.3 Energy-Efficient Motors
94(1)
6.7.3.1 Energy-Efficiency Ratings of BEE
94(1)
6.7.3.2 Energy-Efficiency Ratings of IEC
94(2)
6.7.4 Retrofit of Standard Motors with Energy-Efficient Motors
96(1)
6.7.5 Other Salient Points
97(1)
6.7.6 Use of Star-Delta Starter Motor
97(1)
6.8 Energy-Efficient Transformers
98(3)
6.8.1 IEC Recommendation
98(1)
6.8.2 Super Conducting Transformers
99(1)
References
99(2)
7 Link Restoration and Relay Node Placement in Partitioned Wireless Sensor Network
101(18)
Manwinder Singh
Anudeep Gandam
7.1 Introduction
101(2)
7.2 Related Work
103(2)
7.2.1 Existing Techniques
105(1)
7.3 Proposed K-Means Clustering Algorithm
105(3)
7.3.1 Homogenous and Heterogeneous Network Clustering Algorithms
105(1)
7.3.2 Dynamic and Static Clustering
105(1)
7.3.2.1 Routing
106(1)
7.3.3 Flow Diagram
106(1)
7.3.4 Objective Function
106(2)
7.4 System Model and Assumption
108(1)
7.4.1 Simulation Parameters
108(1)
7.4.1.1 Residual Energy
108(1)
7.4.1.2 End-to-End Delay
109(1)
7.4.1.3 Number of Hops or Hop Count in the Network
109(1)
7.5 Results and Discussion
109(5)
7.6 Conclusions
114(5)
References
115(4)
8 Frequency Modulated PV Powered MLI Fed Induction Motor Drive for Water Pumping Applications
119(12)
Arunkumar S. Mohana Sundaram N
K. Malarvizhi
8.1 Introduction
119(1)
8.2 PV Panel as Energy Source
120(1)
8.2.1 Solar Cell
120(1)
8.3 Multi-Level Inverter Topologies
121(1)
8.3.1 Types of Inverters Used for Drives
121(1)
8.3.2 Multi-Level Inverters
121(1)
8.4 Experimental Results and Discussion
122(6)
8.4.1 PV Powered H Bridge Inverter-Fed Drive
123(3)
8.4.2 PV Powered DCMLI Fed Drive
126(2)
8.5 Conclusion and Future Scope
128(3)
References
129(2)
9 Analysis and Design of Bidirectional Circuits for Energy Storage Application
131(20)
Suresh K
Sanjeevikumar Padmanaban
S. Vivek
9.1 Introduction
131(2)
9.2 Modes of Operation Based on Main Converters
133(8)
9.2.1 Single-Stage Rectification
134(1)
9.2.2 Single-Stage Inversion
135(2)
9.2.3 Double-Stage Rectification
137(1)
9.2.3.1 Duty Mode - Interval - I
137(1)
9.2.3.2 Freewheeling Mode - Interval - II
138(1)
9.2.4 Double-Stage Inversion
139(1)
9.2.4.1 Charging Mode - Interval - I
140(1)
9.2.4.2 Duty Mode - Interval - II
141(1)
9.3 Proposed Methodology for Three-Phase System
141(7)
9.3.1 Control Block of Overall System
143(1)
9.3.2 Proposed Carrier-Based PWM Strategy
144(1)
9.3.3 Experiment Results
145(3)
9.4 Conclusion
148(3)
References
148(3)
10 Low-Power IOT-Enabled Energy Systems
151(48)
Yogini Dilip Borole
Dr. C. G. Dethe
10.1 Overview
151(5)
10.1.1 Conceptions
151(1)
10.1.2 Motivation
152(2)
10.1.3 Methodology
154(2)
10.2 Empowering Tools
156(11)
10.2.1 Sensing Components
156(3)
10.2.2 Movers
159(1)
10.2.3 Telecommunication Technology
160(6)
10.2.4 Internet of Things Information and Evaluation
166(1)
10.2.4.1 Distributed Evaluation
166(1)
10.2.4.2 Fog Computing (Edge Computing)
167(1)
10.3 Internet of Things within Power Region
167(7)
10.3.1 Internet of Things along with Vitality Production
168(1)
10.3.2 Smart Metropolises
168(3)
10.3.3 Intelligent Lattice Network
171(1)
10.3.4 Smart Buildings Structures
172(1)
10.3.5 Powerful Usage of Vitality in Production
173(1)
10.3.6 Insightful Transport
174(1)
10.4 Difficulties -- Relating Internet of Things
174(8)
10.4.1 Vitality Ingestion
178(1)
10.4.2 Synchronization via Internet of Things through Sub-Units
178(2)
10.4.3 Client Confidentiality
180(1)
10.4.4 Safety Challenges
180(1)
10.4.5 IoT Standardization and Architectural Concept
181(1)
10.5 Upcoming Developments
182(5)
10.5.1 IoT and Block Chain
182(2)
10.5.2 Artificial Intelligence and IoT
184(1)
10.5.3 Green IoT
185(2)
10.6 Conclusion
187(12)
References
188(11)
11 Efficient Renewable Energy Systems
199(16)
Prabhansu
Nayan Kumar
Introduction
199(1)
11.1 Renewable-Based Available Technologies
200(6)
11.1.1 Wind Power
201(1)
11.1.1.1 Modeling of the Wind Turbine Generator (WTG)
201(1)
11.1.1.2 Categorization of Wind Turbine
202(1)
11.1.2 Solar Power
202(1)
11.1.2.1 PV System
202(1)
11.1.2.2 Network-Linked Photovoltaic Grid-Connected PV Set-Up
203(1)
11.1.3 Tidal Energy
203(1)
11.1.4 Battery Storage System
204(1)
11.1.5 Solid Oxide Energy Units for Enhancing Power Life
204(1)
11.1.5.1 Common Utility of SOFC
204(1)
11.1.5.2 Integrated Solid Oxide Energy Components and Sustainable Power Life
205(1)
11.2 Adaptability Frameworks
206(4)
11.2.1 Distributed Energy Resources (DER)
206(3)
11.2.2 New Age Grid Connection
209(1)
11.3 Conclusion
210(5)
References
211(4)
12 Efficient Renewable Energy Systems
215(14)
Dr. Arvind Dhingra
12.1 Introduction
215(2)
12.1.1 World Energy Scenario
215(2)
12.2 Sources of Energy: Classification
217(1)
12.3 Renewable Energy Systems
217(1)
12.3.1 Solar Energy
218(1)
12.3.2 Wind
218(1)
12.3.3 Geothermal
218(1)
12.3.4 Biomass
218(1)
12.3.5 Ocean
218(1)
12.3.6 Hydrogen
218(1)
12.4 Solar Energy
218(5)
12.5 Wind Energy
223(2)
12.6 Geothermal Energy
225(1)
12.7 Biomass
226(1)
12.7.1 Forms of Biomass
226(1)
12.8 Ocean Power
227(1)
12.9 Hydrogen
227(1)
12.10 Hydro Power
227(1)
12.11 Conclusion
227(2)
References
227(2)
13 Agriculture-IoT-Based Sprinkler System for Water and Fertilizer Conservation and Management
229(16)
Dilip Kumar
Ujala Choudhury
13.1 Introduction
229(4)
13.1.1 Novelty of the Work
232(1)
13.1.2 Benefit to Society
232(1)
13.2 Development of the Proposed System
233(1)
13.3 System Description
233(3)
13.3.1 Study of the Crop Under Experiment
233(2)
13.3.2 Hardware of the System
235(1)
13.3.3 Software of the System
235(1)
13.4 Layers of the System Architecture
236(1)
13.4.1 Application Layer
236(1)
13.4.2 Cloud Layer
237(1)
13.4.3 Network Layer
237(1)
13.4.4 Physical Layer
237(1)
13.5 Calibration
237(2)
13.6 Layout of the Sprinkler System
239(1)
13.7 Testing
239(2)
13.8 Results and Discussion
241(1)
13.9 Conclusion
242(3)
References
242(3)
14 A Behaviour-Based Authentication to Internet of Things Using Machine Learning
245(20)
Mohit Goyal
Durgesh Srivastava
14.1 Introduction
246(1)
14.2 Basics of Internet of Things (IoT)
246(5)
14.2.1 The IoT Reference Model
248(1)
14.2.2 Working of IoT
249(1)
14.2.2.1 Device
249(1)
14.2.2.2 Connectivity to Cloud
250(1)
14.2.2.3 Data Analysis
250(1)
14.2.2.4 User Interface
250(1)
14.2.3 Utilization of Internet of Things (IoT)
250(1)
14.3 Authentication in IoT
251(4)
14.3.1 Methods of Authentication
251(1)
14.3.1.1 Authentication Based on Knowledge
252(1)
14.3.1.2 Authentication Based on Possession
252(1)
14.3.1.3 Authentication Based on Biometric
253(2)
14.4 User Authentication Based on Behavioral-Biometric
255(3)
14.4.1 Machine Learning
256(1)
14.4.1.1 Supervised Machine Learning
256(1)
14.4.1.2 Unsupervised Machine Learning
256(1)
14.4.2 Machine Learning Algorithms
257(1)
14.4.2.1 RIPPER
257(1)
14.4.2.2 Multilayer Perceptron
257(1)
14.4.2.3 Decision Tree
257(1)
14.4.2.4 Random Forest
258(1)
14.4.2.5 Instance-Based Learning
258(1)
14.4.2.6 Bootstrap Aggregating
258(1)
14.4.2.7 Naive Bayes
258(1)
14.5 Threats and Challenges in the Current Security Solution for IoT
258(1)
14.6 Proposed Methodology
259(2)
14.6.1 Collection of Gait Dataset
259(1)
14.6.2 Gait Data Preprocessing
259(1)
14.6.3 Reduction in Data Size
260(1)
14.6.4 Gaits Feature
260(1)
14.6.5 Classification
260(1)
14.7 Conclusion and Future Work
261(4)
References
261(4)
15 A Fuzzy Goal Programming Model for Quality Monitoring of Fruits during Shipment Overseas
265(20)
Pushan Kr. Dutta
Somsubhra Gupta
Simran Kumari
Akshay Vinayak
15.1 Introduction
265(1)
15.2 Proposed System
266(5)
15.2.1 Problem Statement
266(1)
15.2.2 Overview
266(2)
15.2.3 System Components
268(3)
15.3 Work Process
271(1)
15.3.1 System Hardware
271(1)
15.3.2 Connections and Circuitry
271(1)
15.4 Optimization Framework
271(4)
15.4.1 Fuzzy Goal Description
271(1)
15.4.2 Characterizing Fuzzy Membership Function
272(1)
15.4.3 Construction of FGP Model
272(1)
15.4.4 Definition of Variables and Parameters
273(1)
15.4.5 Fuzzy Goal Description
274(1)
15.5 Creation of Database and Website
275(3)
15.5.1 Hosting PHP Application and Creation of MySQL Database
275(1)
15.5.2 Creation of API (Application Programming Interfaces) Key
275(1)
15.5.2.1 $api_key_value = "3mM44UaC2DjFcV_63GZ14aWJcRDNmYBMsxceu";
275(1)
15.5.2.2 Preparing Mysql Database
275(1)
15.5.2.3 Structured Query Language (SQL)
275(1)
15.5.2.4 Use of HTTP (Hypertext Transfer Protocol) in Posting Request
276(1)
15.5.2.5 Adding a Dynamic Map to the Website
277(1)
15.5.2.6 Adding Dynamic Graph to the Website
277(1)
15.5.2.7 Adding the Download Option of the Data Set
278(1)
15.6 Libraries Used and Code Snipped
278(2)
15.7 Mode of Communication
280(1)
15.8 Conclusion
280(5)
Abbreviations
282(1)
References
282(3)
16 Internet of Things -- Definition, Architecture, Applications, Requirements and Key Research Challenges
285(12)
Dushyant Kumar Singh
Himani Jerath
P. Raja
16.1 Introduction
285(1)
16.2 Defining the Term Internet of Things (IoT)
286(1)
16.3 IoT Architecture
287(2)
16.4 Applications of Internet of Things (IoT)
289(1)
16.5 Requirement for Internet of Things (IoT) Implementation
290(1)
16.6 Key Research Challenges in Internet of Things (IoT)
291(6)
16.6.1 Computing, Communication and Identification
291(1)
16.6.2 Network Technology
292(1)
16.6.3 Greening of Internet of Things (IoT)
292(1)
16.6.4 Security
293(1)
16.6.5 Diversity
293(1)
16.6.6 Object Safety and Security
293(1)
16.6.7 Data Confidentiality and Unauthorized Access
293(1)
16.6.8 Architecture
293(1)
16.6.9 Network and Routing Information Security
293(1)
References
294(3)
17 FinFET Technology for Low-Power Applications
297(10)
Bindu Madhavi
Suman Lata Tripathi
Bhagwan Shree Ram
17.1 Introduction
297(2)
17.2 Exiting Multiple-Gate MOSFET Architectures
299(2)
17.3 FinFET Design and Analysis
301(3)
17.4 Low-Power Applications
304(1)
17.4.1 FinFET-Based Digital Circuit Design
304(1)
17.4.2 FinFET-Based Memory Design
304(1)
17.4.3 FinFET-Based Biosensors
304(1)
17.5 Conclusion
305(2)
References
305(2)
18 An Enhanced Power Quality Single-Source Large Step-Up Switched-Capacitor Based Multi-Level Inverter Configuration with Natural Voltage Balancing of Capacitors
307(32)
Mahdi Karimi
Paria Kargar
Kazem Varesi
Sanjeevikumar Padmanaban
18.1 Introduction
307(2)
18.2 Suggested Topology
309(11)
18.2.1 Circuit Configuration
309(1)
18.2.2 Generation of Output Voltage Steps
310(10)
18.2.3 Voltage Stress of Switches
320(1)
18.3 Cascaded Configuration of Suggested Topology
320(1)
18.4 Modulation Technique
321(3)
18.5 Power Loss Analysis
324(4)
18.5.1 Conduction Losses
324(2)
18.5.2 Switching Losses
326(1)
18.5.3 Capacitor Losses
327(1)
18.6 Design of Capacitors
328(2)
18.7 Comparative Analysis
330(3)
18.8 Simulation Results
333(3)
18.9 Conclusions
336(3)
References
336(3)
Index 339
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.
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