This book explores new and emerging topics in deep learning, big data, and blockchains, with a focus on distributed ledger technology, blockchains, smart cities, machine learning, and deep learning techniques. It is intended for researchers, developers, and practitioners in these fields.

Format: Paperback / softback
Length: 141 pages
Publication date: 31 August 2023
Publisher: Springer International Publishing AG

This comprehensive book offers a wealth of research on cutting-edge topics such as distributed ledger technology, blockchains, smart cities, machine learning, and deep learning techniques. It provides valuable insights into various application areas, including flight pricing, energy demand, and healthcare. The intended readership includes researchers, developers, and practitioners in the fields of deep learning, big data, and blockchain technologies, making it an essential resource for those seeking to stay ahead of the curve in these rapidly evolving technologies.

Book Overview

This book presents research work on new and emerging topics such as distributed ledger technology, blockchains and architectures, smart cities, machine learning and deep learning techniques, and their application areas. The intended readership includes researchers, developers, and practitioners in the areas of deep learning, big data, and blockchain technologies, making it an essential resource for those seeking to stay ahead of the curve in these rapidly evolving technologies.

Distributed Ledger Technology

Distributed ledger technology (DLT) is a decentralized system that allows for secure and transparent transactions between multiple parties. It is used in various applications, such as finance, supply chain management, and healthcare. DLT enables users to maintain control over their data and transactions, while also providing a high level of security and immutability. In this book, researchers explore the various aspects of DLT, including its architecture, consensus mechanisms, and applications. They also discuss the challenges and opportunities associated with DLT, and propose solutions to address them.

Blockchains and Architectures

Blockchains are decentralized systems that use cryptography to secure transactions and create a tamper-proof ledger. They are used in various applications, such as finance, supply chain management, and healthcare. Blockchains enable users to maintain control over their data and transactions, while also providing a high level of transparency and immutability. In this book, researchers explore the various aspects of blockchains, including their architecture, consensus mechanisms, and applications. They also discuss the challenges and opportunities associated with blockchains, and propose solutions to address them.

Smart Cities

Smart cities are cities that use technology to improve the quality of life for their residents. They use technologies such as sensors, IoT devices, and AI to collect data and analyze it to make informed decisions. Smart cities can improve transportation, energy efficiency, and public safety. In this book, researchers explore the various aspects of smart cities, including their architecture, data management, and applications. They also discuss the challenges and opportunities associated with smart cities, and propose solutions to address them.

Machine Learning and Deep Learning Techniques

Machine learning and deep learning techniques are used to analyze large amounts of data and make predictions. They are used in various applications, such as finance, healthcare, and transportation. Machine learning techniques include supervised learning, unsupervised learning, and reinforcement learning. Deep learning techniques include convolutional neural networks, recurrent neural networks, and generative adversarial networks. In this book, researchers explore the various aspects of machine learning and deep learning techniques, including their architecture, algorithms, and applications. They also discuss the challenges and opportunities associated with these techniques, and propose solutions to address them.

Application Areas

This book presents research work on various application areas of deep learning, big data, and blockchain technologies. These application areas include flight pricing, energy demand, and healthcare. In the flight pricing application area, researchers explore the use of machine learning techniques to predict flight prices and optimize flight routes. In the energy demand application area, researchers explore the use of machine learning techniques to predict energy demand and optimize energy usage. In the healthcare application area, researchers explore the use of machine learning techniques to diagnose diseases and develop personalized treatment plans.

Conclusion

This book provides a comprehensive overview of the latest research work on new and emerging topics such as distributed ledger technology, blockchains and architectures, smart cities, machine learning and deep learning techniques, and their application areas. It is intended for researchers, developers, and practitioners in the areas of deep learning, big data, and blockchain technologies, and provides valuable insights into various application areas. By staying ahead of the curve in these rapidly evolving technologies, we can create a more sustainable and prosperous future for ourselves and for future generations.

Dimension: 235 x 155 (mm)
ISBN-13: 9783031423161
Edition number: 1st ed. 2023