Guest Editorial: Smart Multimedia Communication Technologies for New-Generation Artificial Intelligence Applications

Abstract

With the development of the Internet of thing (IoT) mechanism nowadays, the required techniques for artificial intelligence (AI)-related applications will be equipped with a crucial property, which is Bsmart.^Smart multimedia communication technologies are composed of two main technique categories: the smart multimedia processing technique class and the smart communication transmission technique class. These will be the necessity for constructing a new-generation AI application. The technical category of multimedia processing involves lots of types of techniques where pattern recognition, video (or image) processing, and human machine interaction (HCI) are three kernel technique types to establish an AI application under the regulation of the IoT mechanism. Video coding and decoding (codecs) techniques, media streaming techniques, and hardware-based techniques for enhancing media communication play important roles for establishing an efficient communication transmission channel between the user end device and the remote media handling server.BSmart multimedia communication technologies^associated with the new-generation AI application will absolutely be an evolution tendency for the development of multimedia and communication technologies. Following this thought line, we deeply believe that the appropriate term Bsmart^will be given to pattern recognition, video processing, human machine interaction, media streaming, and hardware-based media communication enhancement techniques for building up a smart multimedia communication system.The special issue, BSmart Multimedia Communication Technologies for New-Generation Artificial Intelligence Applications,^acts as a path breaker for exploring new-generation AI applications using multimedia communication technologies with intelligence. We totally received around 30 submissions, and the vast majority of all submissions are significant in Multimed Tools Appl (2016) 75:9665-9668