INTELLIGENT VIDEO CONTENT FILTERING SYSTEM USING AL

Abstract

Intelligent video content filtering systems are important for ensuring safe and appropriate content across digital platforms such as social media, online streaming services, educational websites, and mobile applications. Traditional content moderation systems rely on human reviewers to continuously monitor large volumes of video data, which can lead to fatigue, inconsistency, and missed detection of inappropriate or harmful content. As a result, sensitive material such as violence, explicit scenes, or unsafe activities may not be identified in time.

To address this problem, this project proposes an Intelligent Video Content Filtering System using Artificial Intelligence and deep learning models such as CNN and YOLO (You Only Look Once). The system processes video streams and analyze frames in real time to detect inappropriate content such as violence, explicit visuals, or harmful activities. Detected elements are highlighted with bounding boxes and classified based on predefined categories, making it easier to identify and filter unsafe content.