Special Issue "Data Analytics Challenges in Smart Cities Applications"
Deadline for manuscript submissions: 30 April 2021.
Interests: artificial intelligence; machine learning; IoT; smart cities; blockchain
Special Issues and Collections in MDPI journals
Special Issue in Processes: Bioinformatics Applications Based On Machine Learning
Special Issue in Smart Cities: Challenges for the Development of Sustainable Smart Cities
Special Issue in Sensors: Evolution of Distributed Computing in Sensor Systems
Interests: urban mobility; accessibility; smart cities; advanced driving assistants
This special issue is based on extended versions of selected papers to be presented at GMC-Technology 2020.
A ‘smart city’ is defined as a complex and interconnected system that applies new technologies to manage all the elements that make it up, from transport to the efficient use of energy resources, including the social and economic aspects of its inhabitants.
In order to manage this correct operation, the research community is developing numerous applications that deal with the enormous amounts of data produced in cities. In this aspect, data analysis plays a fundamental role, in which the application of Big Data, Machine Learning or Deep Learning techniques stands out. Currently, there are several challenges in the field of application of these techniques through applications focused on the management and optimization of the activities that take place in a smart city.
This Special Issue is devoted to promoting the investigation of the latest research in Data Analytics in smart cities and their effective applications, to explore the latest innovations in models, technologies, and tools to assess the impact of the approach, and to facilitate technology transfer of these techniques to our cities.
The topics of interest for this Issue include but are not limited to the following:
- Applications of AI (TTIA);
- Case-based reasoning;
- Data analysis;
- Machine learning;
- Deep learning;
- Big Data;
- Edge computing;
- Fog computing;
- High-performance systems;
- AI in mobile device development;
- Intelligent environments;
- Learning through reinforcement;
- Mobile and wireless systems;
- Model-based reasoning;
- Multiagent systems;
- Multimedia and distributed animation systems;
- Neural networks;
- Smart cities challenges;
- Smart home and smart buildings;
- Open data and big data analytics;
- Smart health and emergency management;
- Smart environments;
- Smart manufacturing and logistics.
Dr. Alfonso González-Briones
Dr. Mohammad M. Banat
Dr. Sara Paiva
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- data analytics
- machine learning
- deep learning
- smart cities
- open data