Weapon detection and crowd management using existing CCTV, AI and ML

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Mohammed Tajuddin Azam; Sridhar Gummalla; Shaikh Shakeer Basha

Weapon detection and crowd management using existing CCTV, AI and ML

Authors: Mohammed Tajuddin Azam, Sridhar Gummalla, Shaikh Shakeer Basha

Unique Paper ID: 182727
Volume: 12
Issue: 2
PageNo: 2935-2939

Keywords: CCTV AI ML Weapon detection crowd management

Abstract:
In the world with the population the increase in crime rate has been evolved as well. To prevent crimes and for our safety it is important to have a device which help in recognizing the criminals. As urban security is constantly evolving the machine learning (ML) can be a game changing solution. Motivated by real-world challenges where conventional surveillance methods often fall short, our project aims to transform urban safety through innovative technological solutions. Our approach harness the potential of ML, involve YOLO which stands for “YOU ONLY LOOK ONCE” algorithm. With risks everywhere security is always an important aspect and due to rise in crime rate in a crowded events or suspicious area with less activity. With the growing demand for the protection of safety, security and personal property deploying video surveillance systems capable of recognizing and interpreting scenes and anomalous events plays a vital role in intelligent monitoring. This paper implement automatic gun or weapon detection using a faster region based convolution neural network algorithms. This paper works when in a crowd there are any weapon detected it can manage the crowd and locate any weapon if detected.

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Cite This Article

ISSN: 2349-6002
Volume: 12
Issue: 2
PageNo: 2935-2939

Weapon detection and crowd management using existing CCTV, AI and ML

Available:https://ijirt.org/article?manuscript=182727

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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