Intelligent Data Analytics, IoT, and Blockchain

Bashir Alam · Mansaf Alam

2023년 10월 · CRC Press

eBook

366

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eBook 정보

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.

저자 정보

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.