Abstract:

In today’s era of digital connectivity, live video streaming has evolved into a cornerstone for real-time communication, education, entertainment, and remote collaboration. Despite the wide availability of commercial platforms like YouTube Live, Twitch, and Facebook Live, these solutions are often resource-heavy, closed-source, and unsuitable for lightweight or institution-level deployments. HyperCast bridges this gap by introducing a web-based, low-latency live streaming platform integrated with intelligent moderation and sentiment based analysis. Built using Flask, OpenCV, and Socket.IO, HyperCast enables real-time, browser-accessible streaming and two-way communication with minimal computational overhead. The platform integrates Natural Language Processing (NLP) techniques for sentiment scoring using the VADER analyzer and an explicit-language filter for ethical moderation. Additionally, it employs OS-level resource scheduling for maintaining efficient streaming performance under varying load conditions [1][2][3]. Experimental results show an average frame rate of 30 FPS with sub 200 ms latency and 87% sentiment classification accuracy.