Intelligent Violence Detection: An AI Driven Approach for Enhanced Surveillance System

Violence Alert System is an AI-powered surveillance system for real-time detection of violent attacks and threats. Through the use of advanced machine learning techniques, the system integrates human detection, violence recognition, and new weapon detection to enhance public safety. Real-time human detection is achieved with the use of Faster R-CNN architecture, with MobileNetV2 used for detecting violent behavior. Integration of weapon detection enhances threat analysis by detecting guns and knives in videos. The system gives real-time alert via Telegram, with the images being time-stamped with location details, thus enabling timely response by law enforcement agencies. Image and face detection enhancement using MTCNN enables more accurate identification, with Firebase Cloud Firestore enabling secure storage and retrieval of data. With the implementation of multi-layered threat assessment, the Violence Alert System offers an effective and scalable solution for active public security surveillance in public places, schools, and business segments.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-05-10
DOI
https://doi.org/10.36948/ijfmr.2025.v07i03.44243
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Intelligent Violence Detection: An AI Driven Approach for Enhanced Surveillance System

Komal Jadhav, Sarvesh Padwal, Rohan Sardesai, Akhilesh Huddar et al.
International Journal For Multidisciplinary Research
Advanced Malware Detection Techniques
article

Intelligent Violence Detection: An AI Driven Approach for Enhanced Surveillance System

Komal Jadhav, Sarvesh Padwal, Rohan Sardesai, Akhilesh Huddar, Ahilya Sarnaik
article en

Abstract

Violence Alert System is an AI-powered surveillance system for real-time detection of violent attacks and threats. Through the use of advanced machine learning techniques, the system integrates human detection, violence recognition, and new weapon detection to enhance public safety. Real-time human detection is achieved with the use of Faster R-CNN architecture, with MobileNetV2 used for detecting violent behavior. Integration of weapon detection enhances threat analysis by detecting guns and knives in videos. The system gives real-time alert via Telegram, with the images being time-stamped with location details, thus enabling timely response by law enforcement agencies. Image and face detection enhancement using MTCNN enables more accurate identification, with Firebase Cloud Firestore enabling secure storage and retrieval of data. With the implementation of multi-layered threat assessment, the Violence Alert System offers an effective and scalable solution for active public security surveillance in public places, schools, and business segments.

International Journal For Multidisciplinary ResearchVol. 7(3)
Openalex Percentile: Top 88%
Advanced Malware Detection Techniques
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