Internet of Things (IoT): Concepts and Applications (S.M.A.R.T. Environments)

Preface
Acknowledgments
Contents
Contributors
Part I: Internet of Things (IoT) Architecture
	Chapter 1: Foundation of IoT: An Overview
		1.1 Introduction
		1.2 Historical Development
		1.3 Internet of Things (IoT)
		1.4 Smart Object
			1.4.1 Characteristics of Smart Object
			1.4.2 Trends in Smart Object
		1.5 Features and Challenges of IoT
		1.6 IoT as an Industrial Commodity
		1.7 Applications
		1.8 Conclusion
		References
	Chapter 2: Cloud Computing for IoT
		2.1 Introduction
		2.2 Basic Concepts
			2.2.1 Cloud Computing
			2.2.2 Importance of Cloud Computing for IoT
		2.3 Cloud Based IoT Architecture
			2.3.1 Models
		2.4 CloudIoT Applications
		2.5 Cloud Platforms Available for IoT
			2.5.1 Commercial IoT Platform
			2.5.2 Open Source IoT Platform
		2.6 Challenges
		2.7 Conclusion
		References
	Chapter 3: Open Service Platforms for IoT
		3.1 Introduction
		3.2 IoT Reference Architecture
			3.2.1 Sensor Layer
			3.2.2 Gateway and Network Layer
			3.2.3 Service Management Layer
			3.2.4 Application Layer
		3.3 IoT Platform Requirements
			3.3.1 Service Requirements
			3.3.2 Architectural Requirements
		3.4 Case Study of IoT Service Platforms
			3.4.1 Amazon Web Service (AWS IoT)
			3.4.2 Microsoft Azure IoT
			3.4.3 Google Cloud Platform
			3.4.4 IBM Watson IoT
		3.5 Challenges and Open Research Problems
		3.6 Conclusion
		References
Part II: Solutions and Enablers for IoT
	Chapter 4: Resource Management Techniques for Cloud-Based IoT Environment
		4.1 Introduction
		4.2 Basic Concepts of IoT, Cloud and Resource Management
			4.2.1 What Are the Basic Elements of the IoT Environment?
				4.2.1.1 Identifiers
				4.2.1.2 Sensing Devices
				4.2.1.3 Communications Devices
				4.2.1.4 Compute Devices
				4.2.1.5 Services IoT
				4.2.1.6 Semantics
			4.2.2 What Are the Various IoT Architecture Frameworks?
				4.2.2.1 Layer 1: Physical Devices and Controllers
				4.2.2.2 Layer 2: Connectivity
				4.2.2.3 Layer 3: Edge Connecting
				4.2.2.4 Layer 4: Data Accumulation
				4.2.2.5 Layer 5: Data Abstraction
				4.2.2.6 Layer 6: The Application Layer
				4.2.2.7 Layer 7: Collaboration and Processes
			4.2.3 How Cloud Computing Supports IoT Infrastructure?
			4.2.4 Why Resource Allocation Is Important for IoT?
		4.3 Related Works
		4.4 Classification of Cloud-Based IoT Resource Management Techniques
			4.4.1 SLA-Aware IoT Resource Allocation
			4.4.2 Context-Aware IoT Resource Allocation
			4.4.3 QoS-Aware IoT Resource Allocation
			4.4.4 Energy-Aware IoT Resource Allocation
			4.4.5 Cost-Aware IoT Resource Allocation
		4.5 Parameters of IoT Resource Management Techniques
			4.5.1 What Are the Various Parameters of Resource Allocation?
			4.5.2 How Much Degree of Improvement Have Been Done in These Parameters?
			4.5.3 How Much Improvement Is Required in the Remaining Parameters?
		4.6 Challenges and Issues
		4.7 Future Directions
		4.8 Conclusion
		References
	Chapter 5: Data Management for the Internet of Things
		5.1 Introduction
		5.2 Management of Data in IoT
			5.2.1 Life-Cycle of Information
			5.2.2 Management of Information for IoT and Data Management Systems for the Traditional Methods
		5.3 Systematic Survey of the Management for the Devices of IoT and Design Primitives
			5.3.1 Data Collection and Information Management Systems
				5.3.1.1 Collection Strategy for Data
			5.3.2 Design Elements for Database Framework
			5.3.3 Preparing Elements
				5.3.3.1 Access Model
				5.3.3.2 Proficient Handling Procedure
				5.3.3.3 Versatile Query Handling, Streamlining and Optimization
		References
	Chapter 6: Machine Learning for IoT Systems
		6.1 Introduction
		6.2 IoT Overview
		6.3 Machine Learning Taxonomy
			6.3.1 Supervised Learning
			6.3.2 Unsupervised Learning
			6.3.3 Reinforcement Learning
			6.3.4 Evolutionary Computation
			6.3.5 Fuzzy Logic
		6.4 Machine Learning for IoT Basic Operation
			6.4.1 Node Localization
			6.4.2 Clustering
			6.4.3 Routing
			6.4.4 Data Aggregation
		6.5 Machine Learning for IoT Performance Aspects
			6.5.1 Congestion Control
			6.5.2 Fault Detection
			6.5.3 Resource Management
			6.5.4 Security
		6.6 Concluding Remarks
		References
	Chapter 7: Supervising Data Transmission Services Using Secure Cloud Based Validation and Admittance Control Mechanism
		7.1 Introduction
		7.2 Objectives and Challenges of Cloud Based Data Transmission Research
			7.2.1 Objectives
			7.2.2 Challenges
		7.3 Access Control Mechanisms of Data Transmission Using Cloud Services
			7.3.1 Securing Virtual Machines
		7.4 Governance and Operations in Cloud Computing Environment
		7.5 Security Issues for Cloud Servers and Transmission Systems
			7.5.1 Security Concerns in Data/Video Transmission Through Cloud Server
			7.5.2 Transportation System Requirements
			7.5.3 Secure Cloud Test Setup Model
			7.5.4 Performance Evaluation
		7.6 Conclusions
		References
Part III: IoT Challenges and Issues
	Chapter 8: Tackling Jamming Attacks in IoT
		8.1 Introduction
		8.2 Literature Survey
		8.3 Proposed Study
			8.3.1 Notations Used in the Study
			8.3.2 Assumptions Made in the Study
			8.3.3 Creating Awareness
			8.3.4 Identifying the Jammer Location
			8.3.5 Choosing Appropriate Path for Delivery
		8.4 Analysis of the Work
			8.4.1 Energy Consumption
			8.4.2 Taking Jammer into Confidence
			8.4.3 Communication Overhead
			8.4.4 Simulation of the Work
		8.5 Conclusion
		References
	Chapter 9: Bioinspired Techniques for Data Security in IoT
		9.1 Introduction
		9.2 Data Security in IoT
		9.3 Bioinspired Computing
			9.3.1 Relationship Between Traditional and Bio-Inspired Data Security
			9.3.2 Achieving Security in IoT Using Bioinspired Techniques
			9.3.3 Types of Bioinspired Computing Algorithms
		9.4 Different Approaches for Data Security in IoT Using Bioinspired Computing
			9.4.1 Ant Colony Optimization (Birattari et al. 2007; Dorigo and Birattari 2011)
				9.4.1.1 Routing Protocols Derived from Ant Colony Optimization for Data Security in IoT (Liu 2017)
					Types of ACO Inspired Routing in WSNs
					Behavior of Operation
					Main Aim
					Topology of Network
					Probability Transition
				9.4.1.2 Ant Colony Approach to Solve Travelling Salesman Problem (Beckers et al. 1992; Bolondi and Bondanza 1993)
					Ant Specific Algorithm
			9.4.2 Genetic Bee Colony (GBC) Algorithm (Alshamlan et al. 2015)
				9.4.2.1 Bee Colony Algorithm Used for Data Security Using Routing System Protocols (Okdem et al. 2011)
					Fire Evacuation Routing and Artificial Bee Colony Optimization (BCO)
					Bee Colony Algorithm and Applications
					Finding Fire Evacuation Route Using BCO Algorithm
					Optimal Routing Solution for Fire Evacuation
				9.4.2.2 Dependable Data Gathering in IoT Using Bee Colony (Najjar-Ghabel et al. 2018)
					The Proposed Model
					Reliable Spanning Tree-Based Data Gathering in IoT
			9.4.3 Firefly Algorithm (Yang 2008)
				9.4.3.1 Analysis of Performance Using Firefly Algorithm Used for the Purpose of Data Clustering (Banati and Bajaj 2013)
					Analysis of Performance
					Using Artificial Data Sets
					Using Real World Data Sets
					Percentage of Success
				9.4.3.2 Security System for Image in IoT with High Performance (Alam et al. 2013; Suwetha et al. 2017)
					Methodology
					Image Hiding Using Firefly Algorithm
					Process of Hiding Images
		9.5 Conclusion
		References
	Chapter 10: A Chaos-Based Multi-level Dynamic Framework for Image Encryption
		10.1 Introduction
		10.2 Background
			10.2.1 Chaos in Cryptography
			10.2.2 Survey on Dynamism in Encryption
		10.3 Proposed Approach
			10.3.1 Description of the Proposed Framework
			10.3.2 Description of Per-round Operations
			10.3.3 Definition of Diffusion Stage
			10.3.4 Key Description
		10.4 Results
			10.4.1 NPCR, UACI and Co-relation Coefficient
			10.4.2 Histogram and Entropy
			10.4.3 Avalanche Properties
			10.4.4 NIST Statistical Test Suite for Randomness
			10.4.5 Resistance Against Known/Chosen Plaintext Attacks & Differential Cryptanalysis
		10.5 Conclusion & Future Scope
		References
	Chapter 11: Privacy Challenges and Their Solutions in IoT
		11.1 Introduction
		11.2 Privacy Requirements for IoT
		11.3 IoT Privacy Research Analysis
		11.4 Security and Privacy Concerns/Challenges
		11.5 Theoretical Solutions Provided for IoT Technology
		11.6 Privacy or Security Solutions from Technical and Industry Areas
			11.6.1 Impact of Security in Heterogeneous Environment
			11.6.2 Industrial Solutions
				11.6.2.1 Security Embedded with Respect to IOT Design
				11.6.2.2 Data Minimization
				11.6.2.3 Transparency Among Consumers
		11.7 Conclusion
		References
Part IV: The IoT World of Applications
	Chapter 12: Mobile Computing and IoT: Radio Spectrum Requirement for Timely and Reliable Message Delivery Over Internet of Vehicles (IoVs)
		12.1 Introduction
		12.2 System Model
			12.2.1 MAC Layer Models
				12.2.1.1 CSMA/CA Based MAC Algorithm
				12.2.1.2 STDMA Based MAC Algorithm
			12.2.2 PHY Layer Model
		12.3 Performance Analysis
			12.3.1 Safety Message Transmission (MAC-to-MAC) Delay
			12.3.2 Simulation Setup
			12.3.3 Simulation Settings and Assumptions
			12.3.4 Results and Discussion
				12.3.4.1 Probability of Message Reception Failure
				12.3.4.2 Safety Message Transmission Delay
		12.4 Conclusion
		References
	Chapter 13: Single Activity Recognition System: A Review
		13.1 Introduction
		13.2 Smart Home Assisted Living System
		13.3 Assisted Living System for Energy Saving
		13.4 Assisted Living System for Health Care
		13.5 Assisted Living System for Safety and Security
		13.6 Assisted Living System for Anomalous Situation Detection
		13.7 Assisted Living System for Monitoring Daily Activities
		13.8 Activity Recognition in Smart Home Assisted Living
		13.9 Communication System in Smart Home Assisted Living
		13.10 Conclusion
		References
	Chapter 14: Deep Learning and IoT for Agricultural Applications
		14.1 Introduction
		14.2 IoT in Agriculture
		14.3 Deep Learning Overview
		14.4 Deep Learning for Smart Agriculture: Concepts, Algorithms, Frameworks and Applications
			14.4.1 Common Deep Learning Algorithms
				14.4.1.1 Convolutional Neural-Network (CNN)
				14.4.1.2 Recurrent Neural Networks (RNN)
				14.4.1.3 Generative Adversarial Networks (GAN)
				14.4.1.4 Long- Short Term Memory (LSTM)
			14.4.2 Deep Learning Frameworks
				14.4.2.1 TensorFlow
				14.4.2.2 Caffe (Convolution Architecture for Feature Extraction)
				14.4.2.3 PyTorch
				14.4.2.4 Theano
		14.5 Applications of Deep Learning in Agriculture
		14.6 Conclusion
		References
	Chapter 15: IoT for Crowd Sensing and Crowd Sourcing
		15.1 Introduction
		15.2 Internet of Things
		15.3 Crowdsourcing
		15.4 Classification of Crowdsourcing
			15.4.1 Collective Intelligence for Problem Solving
			15.4.2 Learning paradigms
			15.4.3 Open Innovation
			15.4.4 New Product Development or Crowd Creation
			15.4.5 Collaborative Initiative Through Crowd Funding
			15.4.6 Crowd Voting
			15.4.7 Crowd Curation
			15.4.8 User-Generated Content (UGC)
			15.4.9 Crowd Labour
		15.5 Applications of Crowdsourcing in India
		15.6 Crowd Sensing
		15.7 Industry Initiatives
			15.7.1 Challenges Faced by the Industry
		15.8 Conclusion
		References
	Chapter 16: Smart Infrastructures
		16.1 Introduction
		16.2 Smart City
			16.2.1 Components of smart city
				16.2.1.1 Smart Parking
				16.2.1.2 Smart Traffic
					The Need for Smart Traffic Systems
					IOT Based Smart Traffic System
					Smart Lighting
					Smart Hospitals
					Smart Waste Disposal
						IOT Based Smart Waste Disposal System
		16.3 Smart Home
			16.3.1 Purpose of Home Automation
		16.4 Conclusion
		References
Part V: IoT for Smart Cities
	Chapter 17: IoT Application for Smart Cities Data Storage and Processing Based on Triangulation Method
		17.1 Introduction
		17.2 Overview of Related Research
		17.3 Data Processing and Storing in Java NetBeans Environments
		17.4 Triangulation Method for Data Storage in Smart City Space
		17.5 Triangulation Method for Data Processing in Smart City Space
		17.6 Discussion
		17.7 Conclusion
		References
	Chapter 18: Intelligent Environment Protection
		18.1 Introduction
			18.1.1 Environment Protection
			18.1.2 Preventing the Environment Degradation
		18.2 Environmental Issues
			18.2.1 Unauthorized Waste Dumping
			18.2.2 Constitutional Nuisance
			18.2.3 Unregulated Usage of Natural Resources
		18.3 Monitoring of Environmental Hazards
		18.4 Intelligent Environment
			18.4.1 Physical Layer of the IoT Eco-System
			18.4.2 Middleware Layer of the IoT Eco-System
			18.4.3 Security Layer of the IoT Eco-System
			18.4.4 Diagnosis Layer of the IoT Eco-System
		18.5 Protection Policies
			18.5.1 Regulatory Method of Environmental Policy
			18.5.2 Economical Method of Environmental Policy
			18.5.3 Voluntary Method of Environmental Policy
			18.5.4 Education & Information Method of Environmental Policy
		18.6 Conclusions
		References
	Chapter 19: A Decade Survey on Internet of Things in Agriculture
		19.1 Introduction
		19.2 Preliminary Research
			19.2.1 Agriculture
				19.2.1.1 Definition
				19.2.1.2 Branches of Agriculture
				19.2.1.3 Top 10 Agriculture Based Economies
				19.2.1.4 Technologies Associated with Agriculture
			19.2.2 IOT
				19.2.2.1 Definition
				19.2.2.2 Framework
				19.2.2.3 Issues and Challenges
				19.2.2.4 Applications
		19.3 Literature Survey
			19.3.1 Crop Cultivation
			19.3.2 Livestock Production
			19.3.3 Agronomics
			19.3.4 Agriculture Engineering
		19.4 Conclusion
		References
	Chapter 20: Intelligent Healthcare Solutions
		20.1 Introduction
		20.2 IT Platforms in Healthcare
			20.2.1 Device Layer
			20.2.2 Network Layer
			20.2.3 Application Layer
		20.3 Handling Data
			20.3.1 Device Centric
			20.3.2 Gateway Centric
			20.3.3 Fog Centric
			20.3.4 Cloud Centric
			20.3.5 Intelligent Approaches Towards Data Processing
			20.3.6 Data Validation
		20.4 Personalised Healthcare Systems
		20.5 Conclusion
		References
	Chapter 21: Smart Car – Accident Detection and Notification Using Amazon Alexa
		21.1 Introduction
		21.2 Related Work
		21.3 Proposed System
		21.4 Proposed Algorithm
		21.5 Experimental Issues
		21.6 Results and Analysis
			21.6.1 Simulation for Moving Car Accident
		21.7 Conclusion
		References
	Chapter 22: Prioritisation of Challenges Towards Development of Smart Manufacturing Using BWM Method
		22.1 Introduction
		22.2 Literature Review
			22.2.1 Overview of Smart Manufacturing
			22.2.2 Smart Manufacturing Related Studies
		22.3 Research Methodology
		22.4 Result
			22.4.1 Identification of Challenges in Smart Manufacturing
			22.4.2 Prioritisation of the Challenges Towards Development of Smart Manufacturing
		22.5 Discussion on Results
		22.6 Conclusion, Limitations and Future Scope
		References
Part VI: Next Generation Smart Applications
	Chapter 23: Surveillance of Type –I & II Diabetic Subjects on Physical Characteristics: IoT and Big Data Perspective in Healthcare @NCR, India
		23.1 Introduction
			23.1.1 Role of Big Data in Healthcare
				23.1.1.1 Big Data Characteristics and Its Benefits in Healthcare
				23.1.1.2 The Future of Healthcare Big Data
				23.1.1.3 Role of Big Data in IoT
				23.1.1.4 Big Data Tools
				23.1.1.5 Big Data Security
			23.1.2 IoT
				23.1.2.1 Origin of IoT
				23.1.2.2 Applications of IoT
				23.1.2.3 Applying Internet of Things (IoT) for Healthcare
				23.1.2.4 Healthcare Applications of IoT
				23.1.2.5 Critical Issues and Challenges of IoT in Healthcare
				23.1.2.6 Examples of IoT Services in Healthcare
			23.1.3 Artificial Intelligence (AI) & Machine Learning (ML)
			23.1.4 Tension Type and Chronic Headache
				23.1.4.1 TTH Treatment
				23.1.4.2 TTH Preventions
			23.1.5 Diabetes Mellitus and Its Types
				23.1.5.1 Facts for Diabetes Cause Tension Type Headache
				23.1.5.2 Diabetes and Headaches
			23.1.6 Hypoglycemia (Low Blood Sugar)
				23.1.6.1 Hypoglycemia and Diabetes
				23.1.6.2 Hypoglycemia and Headaches
				23.1.6.3 Hyperglycemia and Its Causes
				23.1.6.4 Hyperglycemia and Headaches
				23.1.6.5 The Cases When to See a Doctor
			23.1.7 Depression
				23.1.7.1 Depression: Sign and Symptoms
				23.1.7.2 Depression Causes
				23.1.7.3 Depression Treatment
			23.1.8 Obesity
			23.1.9 CAD
				23.1.9.1 CAD Causes
				23.1.9.2 CAD Symptoms
				23.1.9.3 CAD Treatment
			23.1.10 Insulin
		23.2 Literature Survey
		23.3 Our Experimental Results, Interpretation and Discussion
			23.3.1 Experimental Setup
			23.3.2 About the Study and Analysis
		23.4 Novelty in Presented Work
		23.5 Future Scopes, Limitations and Possible Applications
		23.6 Recommendations and Future Considerations
		23.7 Conclusions
		References
	Chapter 24: Monitoring System Based in Wireless Sensor Network for Precision Agriculture
		24.1 Introduction
		24.2 Related Work
			24.2.1 Agricultural Monitoring System
		24.3 Wireless Sensor Network for Precision Agriculture Application
			24.3.1 System Overview
			24.3.2 Routing Protocol
		24.4 Experimental Results and Discussion
			24.4.1 Packet Delivery Ratio: PDR
			24.4.2 Average Energy Consumption per Node
			24.4.3 Network Lifetime
		24.5 Conclusion
		References
	Chapter 25: Securing E-Health IoT Data on Cloud Systems Using Novel Extended Role Based Access Control Model
		25.1 Introduction to Internet of Things
			25.1.1 Internet of Things
			25.1.2 Key Fundamentals of Internet of Things
			25.1.3 Architecture of IoT
			25.1.4 Standards of IoT Applications
		25.2 Role of IoT in Health Care Systems
		25.3 Background
		25.4 Access Control and Authorization Using Role Based Access Control (RBAC)
			25.4.1 Rules for Defining RBAC
			25.4.2 RBAC Reference Models
		25.5 Security Healthcare Model Based on Extended RBAC
			25.5.1 Extended Role Based Model (ERBAC)
			25.5.2 Proposed Security Model for Storage of Medical IoT Data Using ERBAC
		25.6 Conclusion
		References
	Chapter 26: An Efficient Approach towards Enhancing the Performance of m-Health Using Sensor Networks and Cloud Technologies
		26.1 Introduction
		26.2 Literature Review
		26.3 The Pillars and Paradigms of Mobile Health Systems
		26.4 Proposed Architecture of Mobile Health System
			26.4.1 Awareness Layer
			26.4.2 Middleware and Application Programme Interface Layer
			26.4.3 E-Mobile Health Application and Service Layer
		26.5 Results and Discussions
			26.5.1 Services Provided by Proposed Cloud and IoT Based Healthcare System
				26.5.1.1 Cloud Data Management and Storage Services
				26.5.1.2 Hospital Services
				26.5.1.3 Emergency and Urgent Response Services
				26.5.1.4 Online Health Advice and Necessary Action Services
				26.5.1.5 Online Patient Monitoring Services
			26.5.2 Online Monitoring the Performance of Cloud and IoT Based Healthcare Systems
		26.6 Conclusions
		References
	Chapter 27: Future Internet of Things (IOT) from Cloud Perspective: Aspects, Applications and Challenges
		27.1 Introduction
		27.2 Background
			27.2.1 Understanding IoT
			27.2.2 IoT and Its Relation with Cloud
		27.3 Application of IoT
			27.3.1 Smart Home
			27.3.2 Wearables Technologies
			27.3.3 Smart City
			27.3.4 Smart Grids
			27.3.5 Industrial Internet
			27.3.6 Connected Car
			27.3.7 Connected Health (Digital Health/Tele Health/Tele Medicine)
			27.3.8 Smart Retail
			27.3.9 Smart Supply Chain
			27.3.10 Smart Farming
			27.3.11 Smart Factories
			27.3.12 Smart Food Industry
		27.4 Future of IoT
			27.4.1 IoT Network in Future
		27.5 Conclusion
		References