Internet of Things (IoT) big data analysis is a process of constantly acquiring, integrating, and analyzing a variety of heterogeneous data collected by sensors to solve the challenges faced by the city. With the increasing role of information and communication technology in implementing and supporting smart cities, the demand for IoT big data analysis solutions is also increasing. In recent years, artificial neural network models have achieved considerable success in various machine learning tasks. Due to its strong hierarchical feature learning ability in the spatio-temporal domain, it has been widely used in IoT big data prediction learning, representation learning, anomaly detection, and classification. In a world, artificial intelligence promotes the use of IoT big data to improve the social, economic, transportation and environmental well-being of cities. IoT big data analysis and artificial intelligence have become important disruptive technologies to help smart cities achieve 'intelligence'.

However, in the process of embracing artificial intelligence empowered IoT big data analytics, there are many problems, such as multi-source heterogeneous data fusion, processing of data incompleteness, security and privacy of large-scale data storage. Specifically, the challenges of artificial intelligence empowered IoT big data analytics include communication costs and energy consumption, algorithm accuracy and convergence speed, the design of smart city services that deliver information from IoT big data and assessing data quality in terms of its usefulness to actual applications.

This Special Issue aims to present the state-of-the-art research in the area of artificial intelligence empowered IoT big data analytics towards smart cities and to provide a forum for experts to disseminate their recent advanced works, views, and ideas on future directions in this field.

Potential topics include but are not limited to the following:

• Architecture and algorithms for IoT big data analytics
• IoT big data analytics for intelligent transportation
• Security and privacy issues in IoT big data analytics
• The interpretability for IoT big data analytics
• Incomplete IoT data repair
• Human mobility prediction leveraging IoT big data and AI
• Traffic control and management using IoT big data and AI
• AI Empowered IoT big data analytics in energy supply and cost
• AI and IoT big data analytics for environmental governance
• AI and IoT big data analytics-based communication techniques
• AI and IoT big data analytics-based sensing techniques