Self-Powered Cyber Physical Systems

Cover
Title Page
Copyright Page
Contents
Preface
Acknowledgements
Chapter 1 Self-Powered Sensory Transducers: A Way Toward Green Internet of Things
	1.1 Introduction
	1.2 Need of the Work
	1.3 Energy Scavenging Schemes in WSAN
		1.3.1 Photovoltaic or Solar Cell
		1.3.2 Temperature Gradient
		1.3.3 Pressure Variations
		1.3.4 Plant Microbial Fuel
		1.3.5 Wind/Liquid Flow
		1.3.6 Vibrations
		1.3.7 Friction
	1.4 Self Powered Systems and Green IoT (G-IoT)
	1.5 Application Area and Scope of Self-Powered System in G-IoT
		1.5.1 Terrestrial Applications
			1.5.1.1 Agriculture
			1.5.1.2 Smart Home and Cities
			1.5.1.3 Industry
			1.5.1.4 Medicines
			1.5.1.5 Environment Monitoring
			1.5.1.6 Structural Monitoring
			1.5.1.7 Indoor Applications
			1.5.1.8 Arial Vehicles
			1.5.1.9 Military Applications
			1.5.1.10 Underwater Applications
			1.5.1.11 Submarine and Event Localization
			1.5.1.12 Water Contamination
			1.5.1.13 Intelligent Water Distribution and Smart Meter
			1.5.1.14 Underground Applications
			1.5.1.15 Coal and Petroleum Mining Application
			1.5.1.16 Underground Structural Monitoring
	1.6 Challenges and Future Scope of the Self-Powered G-IoT
		1.6.1 Challenges Pertain to Energy Efficient Design and Protocols
		1.6.2 Size and Cost of the Harvester
		1.6.3 Energy-Efficient Routing and Scheduling Protocols
		1.6.4 Design of Application-Specific Passive Wake-Up Receivers
		1.6.5 Redefined Protocol with Application-Specific Goals
		1.6.6 Embedded Operating Systems
		1.6.7 AI and Cloud-Assisted Lifetime Prediction Techniques
		1.6.8 Design of Energy-Efficient/Harvested Service-Oriented Architecture
		1.6.9 Smart Web Interfaces for Monitoring
		1.6.10 Cross Layer Exploitations with Energy Harvesting
		1.6.11 Security Aspects and Need of Standardization
		1.6.12 Challenges Related to Energy Harvesting Techniques
		1.6.13 Generic Energy Generator
		1.6.14 Hybrid Energy Sources
		1.6.15 Cooperation Among Different Energy Sources
		1.6.16 Energy Storage
		1.6.17 Intelligent Prediction Model for Amount of Harvested Energy
		1.6.18 Focus on Energy Generator for Underwater and Underground Applications
	1.7 Conclusion
	References
Chapter 2 Self-Powered Wireless Sensor Networks in Cyber Physical System
	2.1 Introduction
	2.2 Wireless Sensor Networks in CPS
	2.3 Architecture of WSNs with Energy Harvesting
	2.4 Energy Harvesting for WSN
	2.5 Energy Harvesting Due to Mechanical Vibrations
	2.6 Piezoelectric Generators
	2.7 Piezoelectric Materials
	2.8 Types of Piezoelectric Structures
		2.8.1 Nanogenerators
		2.8.2 Piezoelectric Nanogenerators
		2.8.3 Triboelectric Nanogenerators
		2.8.4 Pyroelectric Nanogenerators
		2.8.5 Thermoelectric Nanogenerator
	2.9 Hybridized Nanogenerators for Energy Harvesting
	2.10 Conclusion
	References
Chapter 3 The Emergence of Cyber-Physical System in the Context of Self-Powered Soft Robotics
	3.1 Introduction
	3.2 Actuators and Its Types
		3.2.1 Nature of Actuation
			3.2.1.1 Actuators Based on Thermal Materials
			3.2.1.2 Actuators Based on Pressure
			3.2.1.3 Actuators Based on Photo Responsivity
			3.2.1.4 Actuators Based on Explosive Function
			3.2.1.5 Electric Actuation Methods
	3.3 Soft Actuator Electrodes
	3.4 Sensors
	3.5 Soft Robotic Structures and Control Methods
	3.6 Soft Robot Applications
	3.7 Future Scope
	3.8 Conclusion
	References
Chapter 4 Dynamic Butterfly Optimization Algorithm-Based Task Scheduling for Minimizing Energy Consumption in Distributed Green Data Centers
	4.1 Introduction
	4.2 Related Work
		4.2.1 Green Data Centers
		4.2.2 Energy-Aware Task Scheduling
	4.3 Improved Dynamic Butterfly Optimization Algorithm (IDBOA)-Based Task Scheduling (IDBOATS)
		4.3.1 Problem Definition
		4.3.2 Delay Constraint
		4.3.3 Green Energy Model
		4.3.4 Energy Consumption Model
		4.3.5 Constraint-Imposed Optimization Problem
		4.3.6 Primitives of Dynamic Butterfly Optimization Algorithm (DBOA)
		4.3.7 Classical Butterfly Optimization Algorithm
		4.3.8 Transformation of BOA into DBOA using Mutation-Based Local Searching Strategy (MLSS)
	4.4 Results and Discussion
	4.5 Conclusion
	References
Chapter 5 Wireless Power Transfer for IoT Applications—A Review
	5.1 Introduction
	5.2 Sensors
	5.3 Actuators
	5.4 Energy Requirement in Wireless Sensor Networks (WSNs)
	5.5 Wireless Sensor Network and Green IoT (G-IoT)
	5.6 Purpose of G-IoT
	5.7 Motivation
	5.8 Contribution
	5.9 Need of the Work
	5.10 Energy Transferring Schemes in WSAN
	5.11 Electromagnetic Induction
		5.11.1 Electrodynamic and Electrostatic
		5.11.2 Electrostatic Field
		5.11.3 Electrostatic Force
		5.11.4 Electromagnetic
		5.11.5 Electromagnetic Field
	5.12 Inductive Coupling
	5.13 Resonance Inductive Coupling
	5.14 Wireless Power Transmission Using Microwaves
	5.15 Electromagnetic Radiations
	5.16 Conclusion
	References
Chapter 6 Adaptive Energy Intelligence Using AI/ML Techniques
	6.1 Introduction
	6.2 Evolution of Cyber Physical System
	6.3 Relationship With Internet of Things
	6.4 Challenges in Design and Integration of Cyber Physical Systems
	6.5 Future Challenges and Promises
	6.6 Machine Learning Models
	6.7 Estimation of Building Energy Consumption
	6.8 Development of Artificial Intelligence
	6.9 Usage of AI/ML in Adaptive Energy Management
	6.10 Use of Hybrid/Ensemble Machine Learning Algorithm for Better Prediction
	6.11 Conclusion
	References
Chapter 7 Renewable Energy Smart Grids for Electric Vehicles
	7.1 Introduction
	7.2 Integration of Electric Vehicles (EVs) into the Power Grid
	7.3 EV Charging and Electric Grid Interaction
	7.4 EVs with V2G System Architecture
	7.5 EVs and Smart Grid Infrastructure
	7.6 Renewable Energy Sources Integration With EVs
		7.6.1 PV Solar Energy With EVs
		7.6.2 Wind Energy With EVs
	7.7 Application in Transport Sector
	7.8 Application in Micro-Grid
	7.9 State-of-the-Art Review
	7.10 Future Trends
	References
Chapter 8 Recent Advances in Integrating Renewable Energy Micro-Grid Systems With Electric Vehicles
	8.1 Introduction
	8.2 Electric Vehicles and Renewable Energy Sources: A General Overview
		8.2.1 Electric Vehicles
		8.2.2 Battery Electric Vehicles
		8.2.3 Parallel Hybrid Electric Vehicles
		8.2.4 Battery Chargers for EVs
		8.2.5 Renewable Energy Sources
			8.2.5.1 Wind Energy
			8.2.5.2 Solar Energy
	8.3 Microgrid
		8.3.1 Domestic Use
		8.3.2 Industrial Use
		8.3.3 Benefits of Microgrids
		8.3.4 Locations of Microgrid
	8.4 Interactions Between Cost-Conscious EVs and RESs
		8.4.1 Operational Cost Reduction
		8.4.2 Lowering the Electricity Generation Cost
		8.4.3 Growth in Profit or Benefit
		8.4.4 Reduction in Charging Cost for EVs Owners
		8.4.5 Other Cost-Conscious Efforts
	8.5 Interaction Between Efficiency-Conscious EVs and RESs
		8.5.1 Microgrid Implementation
		8.5.2 Increasing the Use of RESs
		8.5.3 Other Works With a Focus on Efficiency
	8.6 Open Problems
		8.6.1 Grid Integration of RESs on a Large Scale
		8.6.2 The Use of EV Batteries in Conjunction With RESs
		8.6.3 V2G’s Ability to Allow the Interaction of RESs
	8.7 Conclusion
	References
Chapter 9 Overview of Fast Charging Technologies of Electric Vehicles
	9.1 Introduction
	9.2 Different Levels of Charging Electric Vehicles
		9.2.1 Level I
		9.2.2 Level II
		9.2.3 Level III
		9.2.4 DC vs AC
		9.2.5 Fast Charging
	9.3 State-of-the-Art Fast-Charging Implementation
	9.4 DC Fast-Charging Structure
	9.5 Fast Chargers
		9.5.1 Fast Chargers Working
		9.5.2 DC Plug Connectors
		9.5.3 EV Fast-Charging Infrastructure
	9.6 Today’s Situation and Future Needs
	9.7 Fast-Charging Point Power Requirements
	9.8 Recent Technologies in Fast Charging, Machine Learning, and Artificial Intelligence
		9.8.1 Machine Learning
		9.8.2 Artificial Intelligence
		9.8.3 Energy Storage Materials
	9.9 Effect of Fast Charging on EV Powertrain Systems
		9.9.1 Battery Technology Gap and Lithium Plating
		9.9.2 Thermal Management Systems
		9.9.3 Battery Cycle Life
	9.10 Grid Impacts Caused by EV Charging
		9.10.1 Impact on Load Profile
		9.10.2 Impact on Grid Components
		9.10.3 Impact on Power Losses
		9.10.4 Impact on Voltage Profile
		9.10.5 Harmonic Impact
	9.11 Fast-Charging Technologies on the Self-Powered Automotive Cyber-Physical Systems
	9.12 Conclusions
	References
Chapter 10 A Survey of VANET Routing Attacks and Defense Mechanisms in Intelligent Transportation System
	10.1 Introduction
	10.2 Attacks in VANET
		10.2.1 Attack on V2V Communication
		10.2.2 Various Attacks on Safety Applications
		10.2.3 Attack on Infotainment Applications
	10.3 Impacts of Attacks on VANET Routing
	10.4 Nonintentional Misbehavior
	10.5 Intentional Misbehavior
	10.6 Defence Mechanism of Routing Attacks in VANET Routing
	10.7 Intrusion Detection Techniques in VANETs
	10.8 Anonymous Routing in VANETs
	10.9 Challenges and Future Directions
	10.10 Conclusion
	References
Chapter 11 ANN-Based Cracking Model for Flexible Pavement in the Urban Roads
	11.1 Introduction
	11.2 Literature Review
	11.3 Methodology
	11.4 Structural Number
	11.5 Modeling Methodology
	11.6 Model Validation
	11.7 Sensitivity Analysis
	11.8 Conclusions
	11.9 Limitations
	11.10 Future Scope of Study
	References
Chapter 12 A Review of Autonomous Vehicles
	12.1 Introduction
	12.2 History
	12.3 Degrees in Automation
	12.4 Benefits and Drawbacks
	12.5 Working Principle of Autonomous Vehicles
	12.6 Mechanics Involved
	12.7 Conclusion
	References
Chapter 13 Meeting Privacy Concerns in Intelligent Transportation Systems
	13.1 Introduction
	13.2 Synopsis of ITS
	13.3 Future Research Direction
	13.4 Contributions to this Research
	13.5 Conclusions
	References
Chapter 14 Feasibility Study of Digital Twin in Automotive Industry—Trends and Challenges
	14.1 Introduction
	14.2 Industrial Evolution
		14.2.1 Industry 1.0
		14.2.2 Industry 2.0
		14.2.3 Industry 3.0
		14.2.4 Industry 4.0
	14.3 Influence of IoT on Digital Twin
	14.4 Digital Twin in CPS Applications
		14.4.1 Health Care CPS
		14.4.2 Manufacturing CPS
		14.4.3 Retail CPS
		14.4.4 Smart Cities and Infrastructure CPS
		14.4.5 Intelligent Transportation CPS
	14.5 Digital Twin Types
		14.5.1 Product Digital Twin—Using Digital Twins to Create More Efficient New Product Designs
		14.5.2 Production Digital Twins—Manufacturing and Production Planning Using Digital Twins
		14.5.3 Performance Digital Twins—Operational Data are Captured, Analyzed, and Acted on Using Digital Twins
	14.6 Levels of Digital Twin
		14.6.1 Level 1: Descriptive Twin
		14.6.2 Level 2: Informative Twin
		14.6.3 Level 3: Predictive Twin
		14.6.4 Level 4: Comprehensive Twin
		14.6.5 Level 5: Autonomous Twin
	14.7 Digital Thread
	14.8 State-of-the-Art Digital Twin Deployment
	14.9 Benefits of Digital Twin
	14.10 Digital Twin Life Cycle
	14.11 Digital Twin in Automotive Industry
	14.12 Applications of Digital Twinning Technology in the Automotive Industry
		14.12.1 Vehicle Development
		14.12.2 Vehicle Manufacturing
		14.12.3 Vehicle Sales
		14.12.4 Vehicle Maintenance and Servicing
		14.12.5 Product Life Cycle of the Automotive Sector
	14.13 Role of Digital Twins in Addressing Current Automotive Challenges
		14.13.1 Unifying Data
		14.13.2 Easy Verification
		14.13.3 Minimization of Failures
		14.13.4 Predict Customer Demands
	14.14 Challenges for Implementing Digital Twin in Automotive Industry
	14.15 Bridging the Gap
	References
Chapter 15 State-of-the-Art and Future Applications of Farming Robotics
	15.1 Introduction
	15.2 Components of Agricultural Robots
		15.2.1 Control System
		15.2.2 Sensor and Actuators
		15.2.3 Power Supply
		15.2.4 End-Effectors
		15.2.5 Artificial Intelligence
		15.2.6 Robotic Arm
		15.2.7 Driving System
	15.3 Types of Agricultural Robots
		15.3.1 Weed Removing Robots
		15.3.2 Pest and Infection-Spotting Robots
		15.3.3 Seed Sowing Robots
		15.3.4 Robots for Scouting Crops
		15.3.5 Robots for Spraying Fertilizers and Pesticides
		15.3.6 Robots for Harvesting
	15.4 Implementation of Robotics in the Agricultural Process
		15.4.1 Ploughing/Tilling
		15.4.2 Sowing Seeds
		15.4.3 Manures and Fertilizers
		15.4.4 Weeding
		15.4.5 Protection of Crops
		15.4.6 Harvesting, Threshing, and Winnowing
	15.5 Challenges
	15.6 Conclusions
	References
Chapter 16 Review on Robot Operating System
	16.1 Introduction
		16.1.1 What is ROS?
		16.1.2 Characteristics of ROS
	16.2 Nomenclature
	16.3 ROS Implementation
		16.3.1 Smart SEAL: A Building Automation Framework for Smart Buildings Based on ROS
		16.3.2 The Development of an Intelligent Drilling Robot System Based on ROS
		16.3.3 AgROS: A ROS-Based Computing Tool for Agricultural Robotics
	16.4 Conclusion
	References
Chapter 17 An Overview of Collaborative Robots and Their Applications
	17.1 Introduction
	17.2 Art of Study
	17.3 Implementation of Collaborative Robots
		17.3.1 Collaborative Robot Revenue Split by Industries
		17.3.2 Drawbacks of the Collaborative Robots
	17.4 Conclusion
	References
Chapter 18 State-of-the-Art and Future Applications of Powered Exoskeleton
	18.1 Introduction
	18.2 Powered Exoskeleton
	18.3 State of the Art
	18.4 Design Parameters to be Considered
	18.5 Challenges to Tackle
	18.6 Applications of Powered Exoskeleton
	18.7 Conclusion
	References
Chapter 19 An Overview of Recent Trends in Consumer Robotics
	19.1 Introduction
	19.2 Entertainment Robot
		19.2.1 Actroid
		19.2.2 Driving Partner Robot
		19.2.3 Manus
	19.3 Educational Robot
		19.3.1 Robokind
		19.3.2 TERRI
	19.4 Social Robot
		19.4.1 BHR Series: BHR 3
		19.4.2 Mertz
	19.5 Toy Robot
		19.5.1 AIBO
		19.5.2 DragonFly
		19.5.3 Robopet
	19.6 Conclusion
	References
Chapter 20 Soft Robotics in Waste Management
	20.1 Introduction
	20.2 Soft Robotics Insights
		20.2.1 Materials and Actuators
	20.3 Soft Robots in Waste Management
		20.3.1 Operation of Soft Robots in Recycling Separation
		20.3.2 Recycling of Soft Robotics After Its Shelf Life
	20.4 Are Soft Robots the First Step for a Sustainable Future?
	20.5 Conclusions
	References
Chapter 21 State-of-the-Art Review of Robotics in Crop Agriculture
	21.1 Introduction
	21.2 Scope
	21.3 Advantages
	21.4 Disadvantages
	21.5 Applications
		21.5.1 Robot Drone Tractors
		21.5.2 Flying Robots to Spread Fertilizer
		21.5.3 Fruit Picking Robots
		21.5.4 Robot Cattle Grazing and Automatic Milking
	21.6 Automation in Agriculture
		21.6.1 Forestry
		21.6.2 Animal Husbandry
	21.7 Precision Agriculture
	21.8 Conclusion
	References
Index
EULA