An Enhanced Digital Technology to Analyze the Combined Effect of Artificial Intelligence and Big Data Analytics for Multimedia Information Processing

For the past several years, taking very large collections of images in everyday life has become more common. All audiovisual artifacts are more likely to be shared and collaborated on since images might come from various devices such as smartphones, satellites, web cams, and drones. Not only that but they are often employed to represent things in a wide range of settings (public areas, train stations, hospitals, political and sports events, competitions, etc.). Hence, multimedia information processor approaches are growing in significance for the many kinds of visual identification jobs that must be adapted to handle large numbers while filling available window processing time. New approaches are being developed, audiences' tastes are shifting, and digital media technologies are becoming more powerful and accessible regularly, contributing to the medium's ever-evolving landscape. This article presents the planning stages of a MIPS (Multimedia Information Processing System). This study provides a platform for image processing methods using a virtualized toolbox. Virtual servers, applications, system time, and data mining are all made possible on this platform thanks to the combination of these digital processing approaches. Additionally, the necessary frameworks and equipment adapters are automatically linked and installed, allowing members to access various apps without downloading and installing software programs. Experiments employed digital processing applications, (ii) a deep backpropagation algorithm for picture classification and multiobject placement, and (iii) a program for indexing and retrieving images. These analyses indicated the system's goal of facilitating the open distribution of important developments and annotation databases to guarantee the efficacy of artificial intelligence-based applications for processing multimedia content.