Machine Learning for Blockchain and IoT Systems in Smart City
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 20 December 2024 | Viewed by 20429
Special Issue Editors
Interests: cryptography; mathematical cryptography; data security; network security; mobile communications; mobile computing; wireless communications
Special Issues, Collections and Topics in MDPI journals
Interests: ML/federated learning in wireless systems; heterogeneous networks; massive MIMO; reconfigurable intelligent surface-assisted networks; mmWave communication networks; energy harvesting; full-duplex communications; cognitive radio; small cell; non-orthogonal multiple access (NOMA); physical layer security; UAV networks; visible light communication; IoT system
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The role of machine learning in implementing and facilitating the design and development of smart cities cannot be overstated. The design of secured smart cities requires a comprehensive analysis of complex Internet of Things (IoT) data. Traditional analytical tools lack the desired accuracy, consume huge energy resources, and are cost prohibitive. Further, smart city data are transmitted over open wireless channels, posing huge security risks. In order to address these problems, machine learning tools and Blockchain technology have been gainfully exploited. Machine learning supports the application of IoT systems to enhance smart cities socially, economically and environmentally. Blockchain complements IoT for enhanced interoperability, reliability, and scalability, with guaranteed security and trust. However, the integration of Blockchain and IoT in smart cities has not been widely considered in the literature. This Special Issue presents machine learning for Blockchain and IoT systems in smart cities. The Special Issue calls for original contributions on designing and developing sustainable machine learning techniques for Blockchain and IoT systems in emerging smart cities.
Topics of interest include, but are not limited to, the following:
- Machine learning tools for Blockchain and IoT systems in smart cities
- Sustainable ML models for Blockchain and IoT systems in smart cities
- Digital twins enabling Blockchain and IoT systems in smart cities
- Blockchain and IoT systems enabling energy-efficient smart cities
- Harnessing machine learning for human mobility prediction in smart cities
- Novel architectures for ML-assisted Blockchain and IoT systems in smart cities
- Hardware implementation of ML-empowered Blockchain and IoT systems in smart cities
- Leveraging machine learning in reducing carbon footprint in smart cities
- Machine learning aiding visualization of IoT-assisted smart cities
- Security and privacy challenges for Blockchain and IoT systems in smart cities
- Experimentation and deployment of Blockchain-based technology for smart cities
- Blockchain facilitates cloud, rain, and fog computing in IoT-enabled smart cities
- Location-aware and location-based services for Blockchain and IoT-assisted smart cities
- Performance analysis and real measurement for Blockchain-based IoT applications
- Machine learning and Blockchain-enabled smart cities and sustainable environments
- Social and economic policies on Blockchain and IoT systems in smart cities
- Case studies and recommendations for designing and developing emerging smart cities
This Special Issue will provide novel contributions that will drive cutting-edge research, leading to the development of smart cities of the future, leveraging Blockchain technology and the Internet of Things. Quality submissions from academia and industry are welcome.
Finally, I would like to thank Agbotiname Lucky Imoize and his valuable work for assisting me with this Special Issue.
Prof. Dr. Cheng-Chi Lee
Dr. Dinh-Thuan Do
Guest Editors
Manuscript Submission Information
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Keywords
- machine learning
- internet of things
- blockchain technology
- smart cities
- security and privacy
- wireless communication
- artificial intelligence
- energy efficiency
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