Big Data Processing in Smart City Application Using 6G Driven IoT Framework

Smart city has emerged as a strong technological usage for variety of data consumption and processing. The enormous applications like smart health care, traffic monitoring, climate assessment, security applications etc. in smart city generates huge data. This data handling requires next generation technologies like 6G driven IoT for real time big data processing. In this research study, medical big data processing using 6G networks using Internet of medical things (IoMT) has delve to prove efficiency of ultra-reliable and low latency networks. Efficient data transfer for medical application become challenging in 6G due to resource unavailability and causes network traffic. A State-of-art-works provides solution for efficient data transmission and processing in 6G, but still massive amount of sensor data become challenging for cellular networks. These challenges are overcome by utilizing unused network resources in existing network by utilizing Edge-Cloud devices. The deep learning based data processing for 6G enabled (IoMT) with less human intervention improves the prediction accuracy in earlier. In this research we provide diseases data prediction model with transfer learning method for 6G based medical application in first phase. secondly, novel deep learning model is used for classification. In order to facilitate online diagnosis, we intend to link the integrated deep learning algorithm with 6G-enabled IoMT to share and deliver medical records and monitoring data.