Intelligent Data Analytics, IoT, and Blockchain
Auerbach (Verlag)
978-1-032-44278-5 (ISBN)
This book focuses on data analytics with machine learning using IoT and blockchain technology. Integrating these three fields by examining their interconnections, Intelligent Data Analytics, IoT, and Blockchain examines the opportunities and challenges of developing systems and applications exploiting these technologies. Written primarily for researchers who are working in this multi-disciplinary field, the book also benefits industry experts and technology executives who want to develop their organizations’ decision-making capabilities. Highlights of the book include:
Using image processing with machine learning techniques
A deep learning approach for facial recognition
A scalable system architecture for smart cities based on cognitive IoT
Source authentication of videos shared on social media
Survey of blockchain in healthcare
Accident prediction by vehicle tracking
Big data analytics in disaster management
Applicability, limitations, and opportunities of blockchain technology
The book presents novel ideas and insights on different aspects of data analytics, blockchain technology, and IoT. It views these technologies as interdisciplinary fields concerning processes and systems that extract knowledge and insights from data. Focusing on recent advances, the book offers a variety of solutions to real-life challenges with an emphasis on security.
Bashir Alam is a professor at Jamia Millia Islamia, New Delhi, India, where he heads the Department of Computer Engineering and obtained a PhD degree. He has 22 years of teaching and research experience. His areas of research include Big Data analytics, Artificial Intelligence, parallel and distributed systems, Cloud Computing, machine learning, GPU computing, blockchain, and information security. Mansaf Alam is a professor in the Department of Computer Science, Faculty of Natural Sciences, Jamia Millia Islamia. A Young Faculty Research Fellow and the Editor-in-Chief of the Journal of Applied Information Science, he pursues research in Artificial Intelligence, Big Data analytics, machine learning, deep learning, Cloud Computing, and data mining.
1. Skin Cancer Classification Using Image Processing with Machine Learning Techniques 2. Trusted Location Information Verification Using Blockchain in Internet of Vehicles 3. Comparative Analysis of Word-Embeddings Techniques Using LSTM Model 4. A Deep Learning Approach for Mask-Based Face Detection 5. A Scalable System Architecture for Smart Cities Based on Cognitive IoT 6. Bagging-Based Ensemble Learning for Imbalanced Data Classification Problem 7. Design and Implementation of a Network Security Model within a Local Area Network 8. Review Study of Modern Symmetric and Asymmetric Cryptographic Techniques 9. Quantum Computing-Based Image Representation with IBM QISKIT Liberaries 10. Source Authentication of Videos Shared on Social Media 11. Task Scheduling using MOIPSO Algorithm in Cloud Computing 12. Feature Selection-Based Comparative Analysis for Cardiovascular Disease Prediction using Machine Learning Model 13. Use of the Cryptography in Networking to Preserve Secure Systems 14. Issues and Challenges of Blockchain in Healthcare15. Accident Prediction by Vehicle Tracking 16. Blockchain-Based Cryptographic Model in Cloud Environment 17. Big- Data Analytics in Disaster Management 18. Fuzzy Minimum Spanning Tree Calculation-Based Approach on Acceptability Index Method 19. Encoder/Decoder Transformer-Based Framework to Detect Hate Speech from Tweets 20. Understanding Dark Web Protection against Cyber Attacks 21. Various Elements of Analysis of Authentication Schemes for IoT Devices: A Brief Overview 22. A Study of Carbon Emissions in Transport Sector 23. An Exploration of Blockchain Technology: Applicability, Limitations, and Opportunities 24. A Survey of Security Challenges and Existing Prevention Methods in FANET 25. MENA Sukuk Price Prediction Modelling using Prophet Algorithm 26. Cancer Biomarkers Identification from Transcriptomic Data Using Supervised Machine Learning Approaches 27. Development of a Secured and Interoperable Multi-Tenant Software-as-a-Service Electronic Health Record System 28. Investigating Classification with Quantum Computing 29. A Comprehensive Analysis of Techniques Offering Dynamic Group Management In Cloud Computing Environment 30. Improved YOLOv5 with Attention Mechanism for Real-Time Weed Detection in the Paddy Field: A Deep Learning Approach
| Erscheinungsdatum | 01.11.2023 |
|---|---|
| Zusatzinfo | 42 Tables, black and white; 131 Line drawings, black and white; 131 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 860 g |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Netzwerke ► Sicherheit / Firewall | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Mathematik / Informatik ► Informatik ► Web / Internet | |
| Recht / Steuern ► Privatrecht / Bürgerliches Recht ► IT-Recht | |
| ISBN-10 | 1-032-44278-6 / 1032442786 |
| ISBN-13 | 978-1-032-44278-5 / 9781032442785 |
| Zustand | Neuware |
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