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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM52504

Object Detection Enabled Security Camera with Email and Sound Alert

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM52504

Volume:

9 |

9 |

Sep 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM52504

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SDR

Sushma D R1

DTVK

Dr. T. Vijaya Kumar2

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Abstract

The demand for sophisticated security solutions has surged due to evolving security threats. This research introduces an advanced intelligent surveillance system that leverages deep learning and computer vision to automate threat detection and provide immediate alerts. Utilizing the YOLO (You Only Look Once) architecture for real-time object detection, combined with OpenCV for video processing and TensorFlow for model optimization, the system offers automated threat classification, dual-alert mechanisms (local sound alarms and email notifications), and customizable detection settings. A web-based interface developed using Flask facilitates user interaction, while MySQL manages detection logs, user preferences, and system analytics. The system demonstrates significant improvements in response time, detection accuracy, and operational efficiency over traditional CCTV systems, making it ideal for residential, commercial, and industrial security applications.

KEYWORDS

Intelligent surveillance deep learning computer vision threat detection YOLO automated security real-time monitoring object detection.

Cite This Article

Sushma D R1, Dr. T. Vijaya Kumar2, "Object Detection Enabled Security Camera with Email and Sound Alert," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 9, Sep 2025. https://doi.org/10.55041/IJSREM52504

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Publication Date

8/8/2025

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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