Real-time Streaming Media Processing and Optimization Technology in Intelligent Video Surveillance

With the public Internet becoming more unstable due to issues like network congestion and line outages, ensuring the quality of large-scale real-time communications is becoming a significant concern. The real-time streaming processing and optimization methods for intelligent video surveillance systems are the main topics of this study. It offers a dynamic routing and distribution network technology developed to address transmission issues brought on by unstable public Internet links. Transmission quality is significantly increased by the system's optimisation of data transfer between servers through the use of dynamic path design and real-time quality detection. The study shows increased transmission stability and efficiency by contrasting static direct connections with dynamic routing. The dynamic obstacle avoidance capabilities of the system is validated by experimental simulations of network breakdowns. Furthermore, the effectiveness of different video encoders and streaming transport methods is assessed. According to the findings, content-aware coding beats rate-control and resolution-adjustment approaches in terms of video transmission quality, achieving an average Peak Signal-to-Noise Ratio (PSNR) of 38.2 dB. The present study offers significant perspectives on enhancing real-time streaming services and contributes to the advancement of intelligent video surveillance systems in the future.