Smart Surveillance using Arcface & Motion Analysis with Alert System

T, Kaviyarasan; P, Mohamed faiz; J, Mathavan; K, Mathanraj

doi:https://doi.org/10.55041/ijsmt.v2i4.266

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SMART SURVEILLANCE USING ARCFACE & MOTION ANALYSIS WITH ALERT SYSTEM

AUTHORS:

Kaviyarasan T

Mohamed faiz P

Mathavan J

Mathanraj K

Mentor

Affiliation

Department of Computer Science and Engineering,MIET Engineering College, Tiruchirappalli – 620007

DOI: 10.55041/ijsmt.v2i4.266

CC BY 4.0 License:

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract

This paper presents an intelligent smart surveillance system that integrates motion analysis and deep learning-based facial recognition for real-time security monitoring. Traditional CCTV systems rely heavily on human observation, leading to inefficiency and missed threats. The proposed system utilizes Gaussian Mixture Model (GMM) for anomaly detection, object tracking for movement analysis, and ArcFace for robust facial recognition under challenging conditions such as occlusion and low illumination. The system generates real-time alerts for suspicious activities and unknown individuals. This approach significantly enhances detection accuracy, reduces false alarms, and minimizes human intervention, making it suitable for modern surveillance applications.

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✓ All ethical standards met

This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.

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