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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM41709

LRCN-Based Surveillance System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM41709

Volume:

9 |

2 |

Feb 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM41709

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

LM

Lethiciya Mary

AS

Asha Sonal

V

Vaishnav

SS

Sri Sanjeevi

MMAD

Mr Mohamed Athfan D

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Abstract

A Surveillance and Alert System is designed to detect violent activities and fire spread within a surveillance environment, promptly alerting the concerned authority. Today, CCTV surveillance is the most fundamental and impactful security feature a premise can have. Being a well-known method of preventing and identifying undesirable activities, CCTV systems are commonly deployed in various premises. For instance, a college campus may have CCTV installed in diverse structures, such as dormitories, classrooms, canteens, sports complexes, auditoriums, etc. However, manually searching through recorded video after an incident occurs is a time-consuming process. The aim of this project is to develop a Long-term Recurrent Convolutional Network (LRCN) system for environments like academic campuses to monitor CCTV footage and detect violent activities, such as fighting, and fire incidents. The system will create alerts through calls and messages via email, including the video of the detected activity, which will be sent to the respective authority.

KEYWORDS

Violence Detection Alert Generation LRCN Fire detection Non-violence

Cite This Article

Lethiciya Mary, Asha Sonal, Vaishnav, Sri Sanjeevi, Mr Mohamed Athfan D, "LRCN-Based Surveillance System," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 2, Feb 2025. https://doi.org/10.55041/IJSREM41709

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Publication Date

2/21/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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0

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2

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5

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Conflict of Interest

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

Funding Information

No funding information available for this research.

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