Real-Time Anomaly Detection Surveillance System

Real-Time Anomaly Detection Surveillance System

Registration ID: IJNRD_199627

Published ID: IJNRD2306358

DOI: Click Here to Get

Chhabil Nagar , Hemant , Nakul Kaushik , Nayan Tuteja , Rachana Sharma

Anomaly Detection , CNN

Abstract— Today's age put a significant amount of emphasis on monitoring systems. It has received a lot of research recently due to its connection to picture understanding and video analysis. More effective tools that can extract high information content are introduced into the system when artificial intelligence, deep learning, and machine learning are integrated to address the issues with standard style. Most anomaly detection tools focus on indoor surveillance and activity monitoring, which help identify abnormal behavior by watching the live stream footage. The most important of them all is the detection of human nature. It is the most strange behavior, which makes it difficult to assess whether it is normal or suspicious. This study demonstrates how in-depth learning can be used to spot odd behaviour on college or high school campuses. Employing consecutive camera frames obtained from a video, the monitoring is done. We will use our model to find the abnormal behaviour in the extracted camera frames. As soon as an anomaly is found, the stream is saved, alerting the relevant people. Therefore, we only need to save the portion of the video where the anomaly is occurring, rather than recording the entire feed. The system is composed of two parts. In the first section, features will be computed from the live video stream, and the classifier will use those features to forecast the anomaly in the second section. The proposed system can recognize the anomalies with a loss of 4.795. Keywords— LSTM, CNN, Autoencoders, Reconstruction error, Regularity Score

Published Paper   E-Certificate

"Real-Time Anomaly Detection Surveillance System", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 6, page no.d566-d572, June-2023, Available :https://ijnrd.org/papers/IJNRD2306358.pdf

Volume 8 Issue 6, June-2023

Pages : d566-d572

Paper Reg. ID: IJNRD_199627

Published Paper Id: IJNRD2306358

Downloads: 000121142

Research Area: Engineering

Country: Greater Noida West, Uttar Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2306358.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2306358

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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