Guest Editors
Dr. Manoj Kumar, University of Wollongong in Dubai, UAE
Dr. Xiaochun Cheng, Middlesex University, UK
Dr. Mai Elbarachi, University of Wollongong in Dubai, UAE
Dr. Ashutosh Mishra, Yonsei University, Incheon, South Korea
Summary
Internet traffic is projected to increase by 62 percent with a business incentive of more than $85 billion by 2025. Various sources, such as multimedia streaming apps (Netflix/Amazon and so on), communication channels (IPTV/HDTV), Internet-of-Things (IoT) gadgets (sensors and actuators), social network apps (Facebook/Twitter and so on), cloud stages (Dropbox/Google cloud and so on and so on, generate crude data. In unified workers such as cloud or disseminated workers in different far-off areas over a network, the produced crude data is then placed away. In nature, the data put away is mostly unstructured, unformatted, and heterogeneous. Multimedia Data Analytics (MDA) is an emerging field that extracts useful and significant examples from unstructured big data. In view of the fact that the data should be cleaned and pre-prepared before sufficient analytics can be implemented to achieve this. MDA produces potential inferences that drive an association's business rationales and amplify its profits. In this way, MDA meets Industry 5.0 requirements-computerization, control, security, and faster data handling among industry partners through optimized solutions. The administration of multimedia data is a developing field of examination that raises concerns through various sources, data pre-processing, analytics, correspondence network, optimization and security starting from the data assortment. The current examination focuses primarily on the previously mentioned board problems and issues in the MDA which can also be solved by suggesting optimization-based methods.
In order to guarantee Industry prerequisites and to guarantee valid network and multimedia data protection, this issue aims is to solve any problems between security solutions and key developments associated with multimedia data analytics. The difficulties associated with multimedia data were studied by researchers and combined with Machine Learning (ML), Deep Learning (DL) Solutions, Optimization, Social Network Analysis (SNA) and IoT applications in various fields. To fix security issues, good cryptographic solutions are implemented in the cloud as new techniques, security conventions; decentralized trust by blockchain, and many more.
Keywords
• Secure Multimedia data analytics for distributed computing
• Multimedia data practices and applications
• Multimedia and Security
• Optimization Methods
• Multimedia data retrieval, processing, analysis, and analytics
• Managing multimodal data with interactive Machine learning techniques
• Managing multimodal data with interactive Deep learning techniques with optimization methods
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