Internet of Things (IoT): Concepts and Applications

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