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.