- Cover
- Title page
- Copyright
- Preface
- Acknowledgment
- 1 Machine Learning–Based Data Analysis
- 1.1 Introduction
- 1.2 Machine Learning for the Internet of Things Using Data Analysis
- 1.3 Machine Learning Applied to Data Analysis
- 1.4 Practical Issues in Machine Learning
- 1.5 Data Acquisition
- 1.6 Understanding the Data Formats Used in Data Analysis Applications
- 1.7 Data Cleaning
- 1.8 Data Visualization
- 1.9 Understanding the Data Analysis Problem-Solving Approach
- 1.10 Visualizing Data to Enhance Understanding and Using Neural Networks in Data Analysis
- 1.11 Statistical Data Analysis Techniques
- 1.12 Text Analysis and Visual and Audio Analysis
- 1.13 Mathematical and Parallel Techniques for Data Analysis
- 1.14 Conclusion
- References
- 2 Machine Learning for Cyber-Immune IoT Applications
- 3 Employing Machine Learning Approaches for Predictive Data Analytics in Retail Industry
- 4 Emerging Cloud Computing Trends for Business Transformation
- 4.1 Introduction
- 4.2 History of Cloud Computing
- 4.3 Core Attributes of Cloud Computing
- 4.4 Cloud Computing Models
- 4.5 Core Components of Cloud Computing Architecture: Hardware and Software
- 4.6 Factors Need to Consider for Cloud Adoption
- 4.7 Transforming Business Through Cloud
- 4.8 Key Emerging Trends in Cloud Computing
- 4.9 Case Study: Moving Data Warehouse to Cloud Boosts Performance for Johnson & Johnson
- 4.10 Conclusion
- References
- 5 Security of Sensitive Data in Cloud Computing
- 6 Cloud Cryptography for Cloud Data Analytics in IoT
- 7 Issues and Challenges of Classical Cryptography in Cloud Computing
- 8 Cloud-Based Data Analytics for Monitoring Smart Environments
- 8.1 Introduction
- 8.2 Environmental Monitoring for Smart Buildings
- 8.3 Smart Health
- 8.4 Digital Network 5G and Broadband Networks
- 8.5 Emergent Smart Cities Communication Networks
- 8.6 Smart City IoT Platforms Analysis System
- 8.7 Smart Management of Car Parking in Smart Cities
- 8.8 Smart City Systems and Services Securing: A Risk-Based Analytical Approach
- 8.9 Virtual Integrated Storage System
- 8.10 Convolutional Neural Network (CNN)
- 8.11 Challenges and Issues
- 8.12 Future Trends and Research Directions in Big Data Platforms for the Internet of Things
- 8.13 Case Study
- 8.14 Conclusion
- References
- 9 Performance Metrics for Comparison of Heuristics Task Scheduling Algorithms in Cloud Computing Platform
- 10 Smart Environment Monitoring Models Using Cloud-Based Data Analytics: A Comprehensive Study
- 11 Advancement of Machine Learning and Cloud Computing in the Field of Smart Health Care
- 11.1 Introduction
- 11.2 Survey on Architectural WBAN
- 11.3 Suggested Strategies
- 11.4 CNN-Based Image Segmentation (UNet Model)
- 11.5 Emerging Trends in IoT Healthcare
- 11.6 Tier Health IoT Model
- 11.7 Role of IoT in Big Data Analytics
- 11.8 Tier Wireless Body Area Network Architecture
- 11.9 Conclusion
- References
- 12 Study on Green Cloud Computing—A Review
- 12.1 Introduction
- 12.2 Cloud Computing
- 12.3 Features of Cloud Computing
- 12.4 Green Computing
- 12.5 Green Cloud Computing
- 12.6 Models of Cloud Computing
- 12.7 Models of Cloud Services
- 12.8 Cloud Deployment Models
- 12.9 Green Cloud Architecture
- 12.10 Cloud Service Providers
- 12.11 Features of Green Cloud Computing
- 12.12 Advantages of Green Cloud Computing
- 12.13 Limitations of Green Cloud Computing
- 12.14 Cloud and Sustainability Environmental
- 12.15 Statistics Related to Cloud Data Centers
- 12.16 The Impact of Data Centers on Environment
- 12.17 Virtualization Technologies
- 12.18 Literature Review
- 12.19 The Main Objective
- 12.20 Research Gap
- 12.21 Research Methodology
- 12.22 Conclusion and Suggestions
- 12.23 Scope for Further Research
- References
- 13 Intelligent Reclamation of Plantae Affliction Disease
- 14 Prediction of the Stock Market Using Machine Learning–Based Data Analytics
- 15 Pehchaan: Analysis of the ‘Aadhar Dataset’ to Facilitate a Smooth and Efficient Conduct of the Upcoming NPR
- 16 Deep Learning Approach for Resource Optimization in Blockchain, Cellular Networks, and IoT: Open Challenges and Current Solutions
- 17 Unsupervised Learning in Accordance With New Aspects of Artificial Intelligence
- 17.1 Introduction
- 17.2 Applications of Machine Learning in Data Management Possibilities
- 17.3 Solutions to Improve Unsupervised Learning Using Machine Learning
- 17.4 Open Source Platform for Cutting Edge Unsupervised Machine Learning
- 17.5 Applications of Unsupervised Learning
- 17.6 Applications Using Machine Learning Algos
- References
- 18 Predictive Modeling of Anthropomorphic Gamifying Blockchain-Enabled Transitional Healthcare System
- Index
- End User License Agreement
Machine Learning Approach for Cloud Data Analytics in IoT
Edited by
Sachi Nandan Mohanty
Jyotir Moy Chatterjee
Monika Mangla
Suneeta Satpathy
Sirisha Potluri
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