计算机科学
编码器
发射机
远程医疗
实时计算
计算机网络
加密
数据传输
网络数据包
数据压缩
互联网
人工智能
医疗保健
万维网
频道(广播)
经济
经济增长
操作系统
作者
Shahidul Islam,Anil Kumar Budati,Mohammad Kamrul Hasan,S. B. Goyal,Ashish K. Khanna
标识
DOI:10.1016/j.compeleceng.2023.108712
摘要
Fifth Generation (5G) communication access technology has been implemented to provide highly reliable and efficient video data streaming in telemedicine applications. The Internet of Things (IoT) advancement enhances the 5G network for smart healthcare services and applications. The existing research work focused only on Lagrangian Encoder (LE) based video compression technique with H.265 Protocol for video data transmission in 5G networks for telemedicine applications. This paper proposes a novel KNN classifier-based H.265 protocol with a single buffer model incorporated with multiple sensors for telemedicine applications. The proposed multiple sensors are placed at the transmitter and receiver base stations to exchange data efficiently and accurately between transmitter and receiver devices. The data transmission performance is measured using collision error, propagation error, sensing error, and visual security with encryption for the proposed and existing methods. The performance of the proposed model is compared with the existing LE-based single buffer and identifies the proposed KNN classifier-based single buffer with a multi-sensor technique that performs better.
科研通智能强力驱动
Strongly Powered by AbleSci AI