Optimizing Real-Time Video Transmission for Surgical Tele-Education Through ERV Algorithm

In the field of surgical tele-education, the need for high-quality real-time video transmission in real-time networks is crucial and often compromised by delays and inefficiency. This paper provides a comprehensive study of enhancing the real-time transmission of video in the field of surgical tele-education. The primary focus is on resolving the significant issues of delays in transmission and deterioration in video quality. We propose an improved approach called the Enhanced Real-time Video (ERV) algorithm that greatly improves the efficiency of bandwidth usage, reduces the latency from start to finish, and guarantees the dependability of video transmission. The ERV algorithm is intricately crafted to assess and choose the most dependable communication route, therefore optimizing the transmission duration for video packets that are vital for real-time applications. Comparative analyses with existing approaches demonstrate that the ERV algorithm significantly improves the Peak Signal-to-Noise Ratio (PSNR) of videos, obtaining an average of 58.53 db. This represents a noteworthy enhancement compared to the prior benchmark of 51.878 db. In addition, the method exhibits a faster processing time, with an average of 40.4 milliseconds, which is much better than the existing standard of 64.3 milliseconds. This enhancement is crucial in situations when even the smallest unit of time is significant, such as live broadcasts of surgical procedures. The ERV method significantly improves transmission efficiency by reducing the average end-to-end delay in real-time video streaming from 132.77 ms to 82.3 ms. The primary achievement of this research is its thorough methodology to reduce latency and enhance transmission dependability, therefore improving the quality of real-time video in surgical tele-education.