Transformative solution for violence identification

Registration ID: IJNRD_216578

Published ID: IJNRD2404574

DOI: Click Here to Get

Venkatachalam G

Closed-circuit television (CCTV), Human violence, deep learning, Machine learning, Transfer learning.

The average yearly death toll from acts of human aggression worldwide is 7.9 per 10,000 individuals. The majority of these acts of violence against people occur suddenly or in remote places.One of the most interesting and difficult study areas in computer vision is violence recognition. Finding violence using surveillance cameras in public and private spaces is one of its unique uses. We demand that these violent incidents be immediately under control. They must conduct a thorough search for automated violence detection systems because human operators are required to monitor the surveillance video screen, which frequently results in mistakes and neglects to identify the occurrence of unexpected events. One of the main obstacles to halting these activities is the information delay in this case. In this work, the detecting technique is employed to thrive on this issue. One of the best computer vision algorithms is the one that uses CCTV to detect moving things. These days, CCTV cameras are installed on every street and are quite useful for case solving. Certain deep learning algorithms are applied in computer vision to anticipate and identify actions and attributes in videos. When police arrive at dangerous locations in real time, they analyse CCTV footage and begin an investigation before moving further. The purpose of this study is to consciously identify violent crimes seen on CCTV. Several uses for gathered video features are made possible by the use of computer vision and machine learning techniques, one of which is safety monitoring. The effectiveness of violent event detection is determined by how accurate and efficient it is. We describe a unique architecture for video surveillance camera-based violence detection in this study. The Yolo v8 models identify the usage of weapons in the incident, as well as the violent act. These deep learning models constitute the basis of the work and are utilised to create a video detection system. Real-time software or an application programming interface (API) can be created using this concept. According to the study's findings, the suggested model has a 74% accuracy

Published Paper   E-Certificate

Venkatachalam G (April-2024). Transformative solution for violence identification. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), f605-f612. https://ijnrd.org/papers/IJNRD2404574.pdf

Volume 9 Issue 4, April-2024

Pages : f605-f612

Paper Reg. ID: IJNRD_216578

Published Paper Id: IJNRD2404574

Downloads: 000121978

Research Area: Computer Science & Technology 

Country: Coimbatore, Tamil nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404574.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404574

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 | IJNRD.ORG | IJNRD.COM | IJPUB.ORG

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

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse fields. Its goal is to promote global scientific information exchange among researchers, developers, engineers, academicians, and practitioners. IJNRD serves as a platform where educators and professionals can share research evidence, models of best practice, and innovative ideas, contributing to academic growth and industry relevance.

Indexing Coverage includes Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar (AI-Powered Research Tool), Microsoft Academic, Academia.edu, arXiv.org, ResearchGate, CiteSeerX, ResearcherID (Thomson Reuters), Mendeley, DocStoc, ISSUU, Scribd, and many more recognized academic repositories.

How to submit the paper?

By Our website

Click Here to Submit Paper Online

By Mail

Send your paper to editor@ijnrd.org

Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.

Subject Category: Research Area

Call for Paper: More Details