Real-time Multimedia Analytics for IoT Applications: Leveraging Machine Learning for Insights

Real time multi-media analytics is currently high in trend in businesses as it is helping the companies to track the real time data and develop useful insights. The process of Real-time Multimedia Analytics includes collection analysis and also usage of the data in real time in order to make better informed decisions. The major aim of the study is to explore Real-time Multimedia Analytics for IoT Applications: Leveraging Machine Learning for Insights. Along with this, the study also focuses on Real-Time Multimedia Analytics. The coming together of the IoT and ML has been analysed in the research. Also, the classification process of the IoT data analytics has been analysed according to technological facilities. A complete exploration of the IoT Data Analytics and its uses has been discussed. The research has studied the aspects using the data collected from books and journals. The previous journals on similar topics have been analysed and studied to develop the findings of this research. The research followed the strategy of empirical research and thus a secondary data collection process has been used. In the findings, it has been found that real-time data analytics are of greater help for the business. It can be divided into two aspects which are prescriptive and predictive data analysis. These two processes place a higher value on current time reactions than described and diagnostic analysis. Also, the coming together of IoT and ML can result in better management, enhanced computing and communication success, and improved choice-making. IoT data modelling is widely used in various aspects of businesses like farming, intelligent automobiles and smart medical. Lastly, the challenges and future directions of IoT applications have been studied to improve the process.