Big Data Mining and Applications in Smart Cities
1Hunan University, Changsha, China
2Coventry University, Coventry, UK
3Charles Darwin University, Darwin, Australia
Big Data Mining and Applications in Smart Cities
Description
With the development of a new generation of information technology including the Internet of Things, cloud computing, mobile Internet, etc., the level of urban informatization applications continues to improve, and smart cities have emerged. Through the construction of smart cities, the timely transmission, integration, communication, and use of urban economy, culture, public resources, management services, citizen life, ecological environment, and other information improves interconnection and intercommunication.
Comprehensive perception and use of information capabilities can greatly improve the government's management and service capabilities, and greatly enhance the people's material and cultural living standards. With the popularization of smart cities, a large number of information resources will be generated, such as data reflecting user behaviors, preferences, etc., and reasonable data analysis and mining. Smart cities will make full use of the new generation of information technology in various industries in the city to achieve urban informatization and industrialization. This will enhance the effectiveness of urban management and improve the quality of life of citizens. Smart cities mainly include smart transportation, smart healthcare, smart public security, smart education, etc.
This Special Issue aims to collect the latest developments in the Internet of Things, big data, artificial intelligence, radio frequency identification, and other technologies in smart cities, including data collection and analysis in smart cities, algorithm research, model and framework construction, and existing problems and challenges, the application of artificial intelligence systems, etc. Original research and review articles are welcome.
Potential topics include but are not limited to the following:
- Data-centric and resource allocation-centric architecture
- Artificial intelligence for enterprise and government
- Application of mobile edge computing in smart cities
- Medical data analysis and disease diagnosis
- Smart education and smart transportation
- Smart grid system management
- City data collection and visualization
- Smart environment sensing and forecasting
- Intelligent logistics systems
- Machine learning, data mining, and statistical modeling for urban computing