Violence Detection using Deep Learning

Abstract: Violent incidents threaten public safety and current surveillance systems still suffer from latencies, false positives, and very little meaningful response. This paper proposes an automated and adaptive, real-time detection of violence system by fusing YOLOv8-based detection of humans and lethal weapon localization with a MobileNetV2 classifier. An adaptive image enhancement task takes into account lighting differences. A temporal filter requires that a positive report must be maintained for 30 consecutive frames prior to triggering an alert. Upon confirmation, an image with a timestamp and geolocation metadata is sent to a Telegram bot.