Autonomous Blazebot : A real-time fire detection and SMS alert system using AI and GSM technology

Mohd Nasir, Faarih Farhan and Eugene Tan, Wei Ren and A Rahman, Khairul Azlan and Mohamed Noor, Ahamad Zaki (2025) Autonomous Blazebot : A real-time fire detection and SMS alert system using AI and GSM technology. Jurnal Kejuruteraan, 37 (6). 3063 - 3074. ISSN 0128-0198

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Abstract

Indoor fire incidents pose a significant threat to both life and property, particularly in areas that are not regularly monitored or are isolated. Traditional fire detection systems, which typically rely on smoke, temperature, or gas sensors, tend to be passive, prone to false alarms, and incapable of providing intelligent, real-time alerts to users in remote locations. This paper addresses these challenges by introducing the development of an autonomous Blazebot for fire detection and alert systems using GSM technology. The proposed system integrates a lightweight YOLOv8n (You Only Look Once version 8 nano) deep learning model, deployed on a Raspberry Pi 4, to continuously recognize flames visually through a USB camera. Once a flame is confirmed, the system sends an alert signal to an Arduino Mega 2560, which then activates a SIM900 GSM module to send SMS notifications to designated recipients. The system successfully identified flame sources with a minimum size of 2500 pixels at distances up to 350 cm, achieving optimal accuracy between 200 and 250 cm. The average delay for SMS transmission was recorded at 10.01 seconds after detection. These findings demonstrate the viability of a costeffective, real-time, vision-based fire detection and communication system suitable for settings without internet access or constant human oversight.

Item Type:	Article
Uncontrolled Keywords:	Fire-fighting robot, SMS alert; YOLOv8n, Real-time vision, Hazard response, Fire detection
Divisions:	Faculty of Artificial Intelligence and Cyber Security
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	23 Feb 2026 02:02
Last Modified:	23 Feb 2026 02:02
URI:	http://eprints.utem.edu.my/id/eprint/29492
Statistic Details:	View Download Statistic

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