Integration of Federated Learning and Blockchain for Smart Cities
Dr. Krishna Kant Singh, Director (Academics), Delhi Technical Campus, Greater Noida, India.
Dr. Akansha Singh, Bennett University ,Greater Noida, India. Email: akanshasing@gmail.com
Dr. Mahesh TR, JAIN (Deemed-to-be University), Bengaluru, India
Federated learning plays a key role in the development of smart cities with the integration of advanced computational methods and data privacy frameworks. As the size of the data evolves while adapting multiple such privacy frameworks using emerging new-age technologies like big data and artificial intelligence, federated learning helps to standardize the frameworks. On the other hand, Blockchain is a decentralized method for storing datasets in the form of digital ledgers that does not require the involvement of a third-party environment. By fragmenting these massive payload datasets among several data centers, overhead is reduced on a Single System Image (SSI). Further, the integration of federated learning and blockchain leads to the remarkable development of smart cities.
For this new book volume, We welcome chapters on following topics:
1. Federated Learning retail, finance and banking for smart cities
2. Federated Learning for water management
3. Federated Learning for e-governance in smart city
4. Federated Learning for smart renewable energy production, supply and management
5. Blockchain for smart industry management
6. Blockchain for smart environment management
7. Blockchain for smart tourism and management
8. Blockchain for smart water and electricity supply, and urban waste management
9. Federated Learning and Blockchain for smart education system and governance
10. Federated Learning and Blockchain as a smart public participation platform
11. Federated Learning and Blockchain for smart real estate investment
12. Federated Learning and Blockchain for smart transportation facilities and mobility
Full Chapter Submission: 30th March 2024
Final Acceptance/Rejection Notification: 20th April 2024
We invite researchers, practitioners, and scholars to submit original chapters that contribute to the understanding of generative and responsive AI in creative applications. Chapters should be well-researched, grounded in academic literature, and present insightful analyses. Practical examples, case studies, and ethical considerations are encouraged to enrich the discussions.
The minimum length of the chapter should not be less than 20-25 pages (7,000 to 10,000 words).
The full chapter includes Title of paper, Authors Name, Authors affiliations, email ID, Corresponding author details, department, Authors Bio, etc. with (Font Size 12, Font Style: Times New Roman, Line Space: 1 Point, Headings: 12+Bold) with APA reference style.
All submitted chapters will be reviewed on a double-blind review basis.
There is no fee for inclusion of a chapter. Any queries or issues can be addressed to akanshasing@gmail.com