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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM59099

YOLO - BASED EARLY FIRE DETECTION USING DEEP LEARNING AND PROTECTION SYSTEM

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM59099

Volume:

10 |

4 |

April 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM59099

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

TP

Thellamekala Poojitha¹

CRSS²

Chakka Rathna Sai Sindhuja ²

SS

Somu Soumya³

VCS

Vennapusa Chandra Shekar⁴

GBS

Gopalam Bhanu Sree⁵

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Abstract

This project presents a smart fire detection and protection system using YOLO and Deep Learning techniques. It utilizes Computer Vision to identify fire and smoke in real-time through camera input. A Raspberry Pi acts as the main controller, integrating data from various sensors to improve detection accuracy. The system also includes GPS and GSM modules to send alert messages with location details. This ensures quick response and effective monitoring. Overall, the system provides a reliable solution for real-time fire detection and safety management.

KEYWORDS

YOLO FireDetection DeepLearning ComputerVision Raspberrypi Sensors GPS GSM Real-time monitoring.

Cite This Article

Thellamekala Poojitha¹, Chakka Rathna Sai Sindhuja ², Somu Soumya³, Vennapusa Chandra Shekar⁴, Gopalam Bhanu Sree⁵, "YOLO - BASED EARLY FIRE DETECTION USING DEEP LEARNING AND PROTECTION SYSTEM," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, April 2026. https://doi.org/10.55041/IJSREM59099

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Publication Date

7/3/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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

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