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  Published Paper Details:

  Paper Title

A Survey on YOLOv8-based Anomaly and Violence Detection for Intelligent Surveillance.

  Authors

  Krushna Bhati,  Kaustubh Bhore,  Mahesh Mane,  Santosh Panpatil,  Pankaj Dhage

  Keywords

YOLOv8, Anomaly Detection, Violence Detection, Intelligent Surveillance, Deep Learning, Real-Time Monitoring

  Abstract


Ensuring public safety requires surveillance systems that can detect abnormal and violent activities in real-time. Traditional CCTV monitoring depends on human attention and often leads to delayed response or oversight. To address this, deep learning-based models have become crucial. This survey highlights the capabilities of YOLOv8, an advanced object detection model, for anomaly and violence detection. YOLOv8 offers higher accuracy, faster inference, and improved feature representation compared to earlier YOLO versions, making it suitable for intelligent surveillance. The study reviews its applications, datasets, challenges, and performance considerations, concluding that YOLOv8 provides an effective framework for real-time automated monitoring and security enhancement.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2511225

  Paper ID - 296283

  Page Number(s) - b785-b790

  Pubished in - Volume 13 | Issue 11 | November 2025

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Krushna Bhati,  Kaustubh Bhore,  Mahesh Mane,  Santosh Panpatil,  Pankaj Dhage,   "A Survey on YOLOv8-based Anomaly and Violence Detection for Intelligent Surveillance.", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 11, pp.b785-b790, November 2025, Available at :http://www.ijcrt.org/papers/IJCRT2511225.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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