Integration of IoT with Cloud Computing for Smart Applications

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Notes on the Editors
Contributors
Chapter 1: Novel Techniques Using IoT and Cloud Computing in Agriculture
1.1 Introduction
1.2 Role of Sensors in Agriculture
1.3 Types of Sensors in Agriculture
1.3.1 Location Sensors
1.3.2 Electromagnetic Sensors
1.3.3 Optical Sensors
1.3.4 Mechanical Sensors
1.3.5 Dielectric Soil Moisture Sensors
1.3.6 Airflow Sensor
1.3.7 Acoustic Sensors
1.4 Needs of the Cloud in IoT-Based Agriculture
1.4.1 Use of Infrastructure as a Service in Agriculture
1.4.2 Use of Software as a Service in Agriculture
1.4.3 Use of Platform as a Service in Agriculture
1.5 Types of Cloud Architecture and Their Uses in Agriculture
1.5.1 Features of Public Cloud
1.5.2 Features of Private Cloud
1.5.3 Features of Community Cloud
1.5.4 Features of Hybrid Cloud
1.6 Applications
1.6.1 Crop Recommendation
1.6.2 Cattle Tracking
1.6.3 Precision Farming
1.6.4 Soil Monitoring
1.6.5 Ripening of Fruits
1.6.6 Smart Greenhouses
1.6.6.1 Applications of Smart Greenhouses
1.6.6.2 Advantages of Smart Greenhouses
1.6.7 Choosing Crops Based on Soil Texture and Weather
1.6.8 Crop Protection
1.7 Future Scope
1.7.1 Optimized Usage of Scarecrows
1.7.2 SONAR for Creature Detection at Night
1.7.3 Proper Weather Forecasting
1.7.4 Drones for Farm Management
1.7.5 Combining Solar Panels with IoT Devices to Enhance Power Usage
1.7.6 Weed-Killing Using New Techniques
1.7.7 Soil Heat Maintenance
1.8 Conclusion
References
Chapter 2: A Comparative Analysis on Performance Factors for Communicating Devices in MIPv6 Environment under Smart City Model
2.1 Introduction
2.2 Related Work
2.3 Simulation
2.3.1 Components Used for the Proposed Scenario
2.3.1.1 Home Agent
2.3.1.2 Foreign Agent
2.3.1.3 Mobile Node
2.3.1.4 Correspondent Node
2.3.1.5 Tunneling
2.3.2 Types of Handover Management Techniques
2.3.2.1 Hard Handover
2.3.2.2 Soft Handover
2.3.3 Proposed Scenario
2.3.3.1 Devices Communicating in Existing IoT-based Environment
2.3.3.2 Devices Communicating in IoT-based Environment with Applied Proxy
2.4 Simulation Analysis
2.4.1 Delay
2.4.2 Load
2.4.3 Throughput
2.5 Conclusion and Future Scope
References
Chapter 3: Futuristic Trends in Vehicle Communication Based on IoT and Cloud Computing
3.1 Introduction
3.2 Background
3.2.1 Traditional VANETs
3.2.2 Cluster
3.2.3 V2I
3.2.4 V2V
3.2.5 Fog Computing
3.2.6 Improvement in V2V Communication Using Fog Computing
3.2.7 Dedicated Short-Range Communication (DSRC)
3.2.8 Edge Devices
3.2.9 AdHoc Routing Protocols for Vehicle Communication
3.2.10 Proactive Routing Protocols
3.2.11 Reactive Routing Protocol
3.2.12 Hybrid Routing Protocol
3.2.13 Dynamic Source Routing (DSR) Protocol
3.2.13.1 Route Discovery
3.2.13.2 Route Maintenance
3.2.13.3 Route Cache
3.2.14 AdHoc On-Demand Vector(AODV) Routing Protocol
3.2.15 In AODV Routing Protocol-based Scenario There Are Two Phrases
3.2.16 Hierarchical Routing Protocols
3.2.17 Hierarchical State Routing (HSR) Protocol
3.3 Conclusion
3.3.1 Future Scope
References
Chapter 4: Towards Resolving Privacy and Security Issues in IoT-Based Cloud Computing Platforms for Smart City Applications
4.1 Introduction
4.2 Smart City Overview: Cloud-Based System Architecture, Security and Privacy Issues, and Applications
4.2.1 General Architecture of a Smart System
4.2.2 General Cloud-based Architecture of a Smart System
4.2.2.1 Cloud Computing Deployment Models
4.2.2.2 Cloud Computing Service Delivery Models
4.2.3 Privacy and Security Issues in Cloud Computing Infrastructure
4.3 Privacy and Security Issues in Smart City Infrastructure
4.4 Data Confidentiality and Security of Smartphone Devices and Services
4.5 Power Grid Systems within Smart Cities
4.6 Smart Healthcare Systems within Smart Cities
4.7 Privacy and Security in Smart Transportation
4.8 Smart Environment
4.9 Security in Smart IoT Devices
4.10 Security and Privacy Frameworks
4.11 Cryptography
4.11.1 Homomorphic Encryption
4.11.2 Zero-Knowledge Proofs
4.11.3 Secret Sharing
4.11.4 Secure Multi-party Computation
4.11.5 Multi-Factor Authentication
4.11.6 Blockchain
4.11.7 Side-Channel Attacks
4.12 Biometric
4.13 AI-ML Models for Detecting Security and Privacy Issues
4.14 Anonymity
4.15 Security Issues, Properties, and Countermeasures Against Threats
4.16 Sustainable Security and Privacy Approaches
4.17 Conclusion
4.18 Future Scope
References
Chapter 5: Challenges and Opportunities Toward Integration of IoT with Cloud Computing
5.1 Introduction
5.1.1 Internet of Things
5.1.2 Cloud Computing
5.1.2.1 Platform as a Service
5.1.2.2 Infrastructure as a Service
5.1.2.3 Software as a Service
5.1.3 Middleware for Internet of Things
5.2 Architecture of Cloud-Integrated IoT
5.3 Benefits of Integrating IoT and Cloud
5.3.1 Storage
5.3.2 Processing
5.3.3 Data Transmission
5.3.4 Modern Capacities
5.4 Existing Solutions for Integrating IoT and Cloud
5.4.1 OpenIoT
5.4.2 Nimbits
5.4.3 AWS IoT
5.4.3.1 Device Software
5.4.3.2 Connectivity and Control Services
5.4.3.3 Analytics Services
5.4.4 CloudPlugs IoT
5.4.5 ThingSpeak
5.5 Application of Cloud-Integrated IoT
5.5.1 Smart City
5.5.2 Smart Environment Monitoring
5.5.3 Smart Home
5.5.4 Smart Healthcare
5.5.5 Smart Mobility
5.5.6 Smart Surveillance
5.5.7 Towards Serverless Computing
5.6 Issues and Research Challenges
5.6.1 Security and Privacy
5.6.2 Unnecessary Data Communication
5.6.3 Deployment of IPv6
5.6.4 Resource Allocation and Management
5.6.5 Interoperability
5.6.6 Service Discovery
5.6.7 Scaling
5.6.8 Energy Efficiency
5.7 Conclusion
References
Chapter 6: Multi-variant Processing Model in IIoT
6.1 Introduction
6.2 Applications of IIoT
6.2.1 Supply Chain Management
6.2.2 Automotive Manufacturing
6.2.3 Remote Power Grid
6.2.4 Recycling and Sorting System
6.3 Literature Survey
6.4 Previous Work
6.4.1 Drawbacks of the Previous System
6.5 Proposed System
6.6 Analysis of Work
6.7 Future Scope
6.8 Conclusion
References
Chapter 7: Mobile Health: Roles of Sensors and IoT in Healthcare Technology
7.1 Introduction
7.2 Roles of Sensors in mHealth
7.2.1 Roles of External Sensors Used in mHealth
7.2.2 Roles of Sensors of the Smart Mobile in mHealth
7.3 Software Feature of the Smart Mobile
7.4 IoT Role, Benefits, and Customers in mHealth
7.5 Role of the Cloud in mHealth
7.6 IoT in Healthcare: Challenges and Future Trends
7.7 Future Role of IoT and Cloud in mHealth
7.8 Conclusions
References
Chapter 8: IoT and Cloud Computing: Two Promising Pillars for Smart Agriculture and Smart Healthcare
8.1 Introduction
8.2 Benefits of the Internet of Things (IoT)
8.3 Smart Agriculture
8.3.1 Benefits of Smart Agriculture
8.3.2 Background Literature
8.3.3 Methodologies
8.3.4 Combined Analysis of IoT End Device Data with Drone Data
8.4 Smart Healthcare
8.4.1 Why is IoT Important in Healthcare?
8.4.2 How IoT Helps in Healthcare – Process
8.4.3 Applications of IoT in Healthcare
8.4.4 Current Status
8.4.5 Challenges of IoT in Healthcare
8.4.6 Future of IoT in Healthcare
8.5 Conclusion
References
Chapter 9: Splitter with Cryptographic Model for Cloud Data Transmission Security
9.1 Introduction
9.1.1 Cloud Computing
9.1.2 Need for Proposed System
9.1.3 Various Attacks
9.2 Literature Review
9.3 Objective of Proposed Work
9.4 Proposed Model
9.5 Results
9.5.1 File Splitter
9.5.2 GUI for Client Interface
9.5.3 GUI for Server Interface
9.5.4 Secure Files
9.6 Fog Implementation
9.7 Conclusion
9.8 Future Scope
References
Chapter 10: IoT in Connected Electric Vehicles for Smart Cities
10.1 Introduction
10.2 Research Gap and Motivation
10.3 Components of a Smart City
10.3.1 Smart Concept in Agriculture
10.3.2 Services Available in a Smart City
10.3.3 Power System of a Smart City
10.3.4 Innovation in Health
10.3.5 Automated Home
10.3.6 New Generation Industries
10.3.7 Smart Structure
10.3.8 Automated Transport
10.4 Usage OF IoT in Smart Cities
10.4.1 Architecture of a Smart City with IoT
10.4.2 Smart City Challenges with IoT
10.4.2.1 Privacy and Security
10.4.2.2 Sensors for Smart Cities
10.4.2.3 Concept of Networking
10.4.2.4 Data Analytics
10.4.3 Technologies Used for Sensing Data
10.4.4 Technologies Used for Networking
10.4.4.1 Network Topologies
10.4.4.2 Architectures
10.4.5 Privacy and Security with IoT in a Smart City
10.5 SWOT Method for Data Analysis
10.5.1 Strengths
10.5.2 Flaws
10.5.3 Prospects
10.5.4 Coercions
10.6 Conclusion
10.7 Future Recommendations
References
Chapter 11: Artificial Intelligence and Machine Learning for Smart Farming Using Cloud Computing
11.1 Introduction
11.2 Machine Learning Approaches
11.2.1 Literature Review
11.3 ML and IoT-based Framework for Smart Farming
11.3.1 IoT- and AI-based Sensor System for Effective Farming
11.4 Usability of Smart Farming: How AI and IoT are Benefitting Agriculture
11.5 Benefits of AI in Environment Supported Agriculture
11.6 Demerits of AI in Agriculture and Environment
11.7 Challenges of AI and IoT Approach in Agriculture
11.8 Conclusion
References
Chapter 12: Parivem–Parivahan Emulator
12.1 Introduction
12.2 Material and Methods
12.3 State of Art Methods
12.4 Proposed System Architecture
12.5 Conclusion
References
Chapter 13: Building Integrated Systems for Healthcare Considering Mobile Computing and IoT
13.1 Introduction
13.1.1 Healthcare
13.1.1.1 Applications of Technology in Healthcare
13.1.1.1.1 Research Purposes
13.1.1.1.2 Seamless Switching of Patients between Providers
13.1.1.1.3 Faster, Cheaper, Better Patient Care
13.1.1.1.4 Interoperable Electronic Health Records
13.1.2 IoT
13.1.2.1 Characteristics of IoT
13.1.2.2 IoT: Things, Internet, and Human
13.1.2.3 Benefits of IoT
13.1.3 Mobile Computing
13.1.3.1 Elements of Mobile Computing
13.1.3.2 Advantages of Mobile Computing
13.1.3.3 Limitations of Mobile Computing are Discussed Ahead
13.1.4 Impact of Mobile Computing and IoT on Healthcare
13.1.4.1 End to End Connectivity and Affordability
13.1.4.2 Improving the Health of Patients
13.1.4.3 Simultaneous Monitoring and Support
13.1.4.4 Tracking and Alerts
13.1.4.5 Research
13.1.4.6 Data Analysis
13.2 Literature Review
13.3 Role of Deep Learning in Healthcare
13.3.1 Deep Learning and Medical Imaging
13.3.2 Diabetic Retinopathy (DR)
13.3.3 Gastrointestinal (GI) Disease
13.3.4 Tumor Detection
13.4 Problem Statement
13.5 Proposed Methodology
13.5.1 Flowchart of Proposed Work
13.6 Results and Discussion
13.6.1 Time Consumption
13.6.2 Error Rate
13.6.3 Accuracy Rate
13.7 Conclusion
13.8 Future Scope
References
Chapter 14: Clustering of Big Data in Cloud Environments for Smart Applications
14.1 Introduction
14.1.1 Big Data
14.1.1.1 Characteristics of Big Data
14.1.1.2 Advantages of Big Data Processing
14.1.2 Cluster
14.1.3 Cloud Computing
14.1.3.1 Types of Cloud Computing
14.1.3.2 Opportunities for Cluster Computing in the Cloud
14.1.3.3 Cloud for Big Data
14.1.4 Smart Applications of Big Data
14.1.5 Issues in Using Cloud Services
14.2 Literature Review
14.3 Problem Statement
14.4 Research Methodology
14.5 Proposed Work
14.6 Result and Discussion
14.6.1 K-means Algorithm
14.6.2 EM Algorithm
14.6.3 MATLAB Simulation for Comparative Analysis of Security
14.6.4 Man-in-the-Middle Attack
14.6.5 Brute Force Attack
14.6.6 Denial-of-Service Attack
14.7 Conclusion
14.8 Future Scope
References
Index