The Smart Cities Continuum via Machine Learning and Artificial Intelligence
A special issue of Informatics (ISSN 2227-9709). This special issue belongs to the section "Machine Learning".
Deadline for manuscript submissions: 31 December 2024 | Viewed by 4402
Special Issue Editors
Interests: 5GB networks; O-RAN; smart cities; future internet; cloud-to-things continuum (cloud, edge e fog computing); IoT; SDN; NFV
Special Issue Information
Dear Colleagues,
The world is rapidly transitioning to a future of Smart Cities. We have the unique ability to shape this future by providing solutions to the most pressing issues of today and tomorrow. The development of such cities has become a significant research focus in recent years, driven by the need to create efficient, sustainable, and secure urban environments. Because of that, developments in smart cities are becoming increasingly intricate, combining technology from a variety of engineering fields and, thus, requiring the integration of a complex web of interrelated technologies, ranging from private and public transportation, electric grid, telecommunication, water supply and sewage sanitation, education, law enforcement, governmental operations, health care, banking, welfare, and so many others.
Several key technologies have been instrumental in enabling the development of Smart Cities, aiding in the automation of processes and providing real-time insights into the urban environment. However, there are still several open challenges. When it comes to machine learning, the challenge is to create algorithms that can accurately process and interpret the large amounts of data generated by the population and a smart city's infrastructure. These data can be used to make predictions, detect anomalies, and even control some aspects of the smart city's infrastructure, such as traffic lights. Artificial intelligence is also a major component of smart cities, as it can be used to analyze data patterns and automate specific tasks. AI can control autonomous vehicles and manage energy consumption, among other things. Security and privacy are also issues that need to be addressed in these scenarios. Smart Cities rely upon collecting and analyzing large amounts of data to provide insights into their operation and automate processes. This data collection and analysis process must be undertaken in a secure manner to prevent any unauthorized access to the data. This requires robust encryption of the data, as well as strict protocols for how and when the data can be accessed.
This Special Issue welcomes contributions describing tools and methodologies and review papers with state-of-the-art findings that can significantly contribute to advancements in Smart Cities. Moreover, we expect to focus on all aspects and future research directions in the rapidly progressing subject of smart cities and their applications, aiming to provide the opportunity for researchers and practitioners to share their latest work on emerging topics.
We welcome submissions from researchers from all backgrounds and look forward to reading your work.
Relevant topics include, but are not limited to, the following:
- Smart city applications and services
- Smart city management platforms
- Modeling and simulation of smart cities
- Emerging technologies for critical verticals
- Information and communication technology (ICT) in smart cities
- People-centric systems and crowd-based computing in smart cities
- Business models for smart and circular cities
- Cloud, Fog, Edge, and service-oriented computing for smart cities
- Artificial intelligence and machine learning technologies
- AI-based network design, resource allocation, data processing, integrated sensing and communications, and mobile user behavior analysis and inference
- Edge AI component technologies
- Federated learning and distributed machine learning
- Data-intensive computing (big data), analytics, and data mining
- Open data initiatives, cases, and applications
- Digital twins and their application to smart cities
- Artificial Intelligence of Things (AIoT) in smart cities;
- Sustainable development and societal impacts of AIoT
- Computing for smart cities (IoT, Edge/Cloud, Industry 4.0, Society 5.0, etc.)
- Industrial Internet of Things (IIoT)
- Experimental evaluations of smart cities systems and applications.
- Resiliency and privacy of smart city networks
- Cybersecurity, security, and trust (authentication, authorization, assessments, blockchains, encryption methods, anonymization)
- Machine learning mechanisms for cyber security
- Key generation and key distribution schemes
- Modern tools for improving cyber security
- Emerging trends in cyber security
- Authenticated Key Agreement Protocols
- Cyber security in Internet of Things (IoT)
- Cyber security in Cloud
- UHD video processing for next-generation networks
- New generations of telecommunication technology applied for Smart Cities (e.g., 5G, 6G, and 7G)
- Long-range communication technologies for smart cities
- Self-organizing networks (SON)
- Next-generation broadcasting technologies
- Network slicing, mobility, and high-efficiency handover
- Smart sensing, grids, infrastructures, transportation, mobility, energy, buildings, food and agriculture, governance, people, economy, healthcare, living
- Cyber-physical systems
- Connected and unmanned aerial vehicles (UAVs)
- V2X communication systems
- Computer vision
- Tactile internet
Dr. Augusto Neto
Dr. Roger Immich
Guest Editors
Manuscript Submission Information
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Keywords
- smart city
- machine learning
- artificial intelligence
- Big Data
- Artificial Intelligence of Things (AIoT)
- Industrial Internet of Things (IIoT)
- cybersecurity
- privacy
- next-generation networks
- open data
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