To build smart cities and societies is to mine valuable information from tremendous amounts of data, and it is being driven by technologies such as cloud computing and big data. As mobile video and picture capture technologies have evolved, a large amount of multimedia data has emerged, namely, big multimedia data. Big multimedia data technologies run through nearly all fields of smart city building, such as smart transportation, smart education, smart community, smart security, smart medical treatment, smart ecology, and so on. The widespread use of big multimedia data technologies is promoting the rapid development of smart cities. Therefore, it is of great practical value to research the application of multimedia big data technology in smart city building.

Big multimedia data is characterized by large data volumes, multiple data types, large differences between data types, and complex input and output. These characteristics make it difficult to effectively integrate and manage big multimedia data, as well as to automate its processing and analysis. Performing data mining of big multimedia data containing spatial information also presents multiple challenges.

The aim of this Special Issue is to gather research articles focusing on the use of big multimedia data mining techniques for smart cities and societies. Articles of particular interest are practical experiences and research that overcomes the high cost of big data storage, the inefficiency of automated retrieval of big data, and other barriers to building smart cities. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• Application of big multimedia data in smart cities and societies
• Data mining, processing and analysis for big multimedia data
• Big multimedia data technologies in smart transportation and smart security
• Data mining for smart healthcare, smart community and smart ecology
• Big data technologies and applications in e-government and information security system
• Big data-based smart campus construction and smart teaching
• Big data storage techniques and automated retrieval techniques
• Video processing, image processing and audio processing in smart cities and societies
• Advanced machine learning, deep learning and reinforcement learning
• Data visualization techniques and applications
• Privacy and security issues of big data