Real-Time Weapon Detection Using YOLOv8 for Enhanced Safety

TL;DR

This paper introduces a YOLOv8-based AI system for real-time weapon detection, significantly improving safety in public spaces by accurately identifying firearms and edged weapons in video streams.

Contribution

The study develops and evaluates a highly accurate, efficient deep learning model for real-time weapon detection using YOLOv8, trained on a comprehensive dataset.

Findings

High precision and recall in weapon detection

Real-time processing speed suitable for surveillance

Robust differentiation between weapon and non-weapon objects

Abstract

This research paper presents the development of an AI model utilizing YOLOv8 for real-time weapon detection, aimed at enhancing safety in public spaces such as schools, airports, and public transportation systems. As incidents of violence continue to rise globally, there is an urgent need for effective surveillance technologies that can quickly identify potential threats. Our approach focuses on leveraging advanced deep learning techniques to create a highly accurate and efficient system capable of detecting weapons in real-time video streams. The model was trained on a comprehensive dataset containing thousands of images depicting various types of firearms and edged weapons, ensuring a robust learning process. We evaluated the model's performance using key metrics such as precision, recall, F1-score, and mean Average Precision (mAP) across multiple Intersection over Union (IoU) thresholds, revealing a significant capability to differentiate between weapon and non-weapon classes with minimal error. Furthermore, we assessed the system's operational efficiency, demonstrating that it can process frames at high speeds suitable for real-time applications. The findings indicate that our YOLOv8-based weapon detection model not only contributes to the existing body of knowledge in computer vision but also addresses critical societal needs for improved safety measures in vulnerable environments. By harnessing the power of artificial intelligence, this research lays the groundwork for developing practical solutions that can be deployed in security settings, ultimately enhancing the protective capabilities of law enforcement and public safety agencies.