Sistem Fire Alarm Berbasis Mikrokontroler ESP32
DOI:
https://doi.org/10.30649/je.v7i2.156Keywords:
Fire Alarm System, Smoke Detector, Microcontroller ESP32, IoT Monitoring, Industrial SafetyAbstract
An early fire detection system is a critical component in the implementation of occupational safety and health, particularly in mining environments that present a high risk of fire hazards. PT Putra Perkasa Abadi, as a mining service company, requires a smoke detector monitoring system capable of operating in real time, providing accurate information, and supporting effective fire prevention measures. However, field implementation still encounters several challenges, including limited manual monitoring, sensor performance degradation due to dust accumulation, and the absence of a centralized and continuous smoke detector reporting system. This study aims to design and develop a microcontroller-based smoke detector monitoring system that is capable of automatically monitoring sensor conditions, providing early fire warnings, and recording periodic changes in sensor status. The proposed system utilizes a microcontroller as the main data processing unit, a smoke detector sensor to identify the presence of smoke, and a communication module to display sensor status through an LCD and digital interface. System testing was conducted directly in the operational environment of PT Putra Perkasa Abadi Site BIB to evaluate the reliability and performance of the system under real working conditions. The results indicate that the developed monitoring system is able to provide accurate readings of smoke detector conditions and transmit sensor status information in real time with fast and stable responses. The implementation of this system improves monitoring effectiveness and minimizes the risk of delayed fire detection. Therefore, the proposed system can serve as an alternative solution to enhance occupational safety systems and support fire prevention programs in the mining industry.
References
T. Nguyen, A. Pham, and D. Tran, “Performance Evaluation of Photoelectric and Ionization Smoke Detectors in Industrial Environments,” IEEE Sens. J., vol. 22, no. 10, pp. 11852–11860, 2022.
M. Setiawan, “Analisis Sistem Deteksi Kebakaran Berbasis Mikrokontroler,” Jurnal Teknologi Elektro, vol. 14, no. 2, pp. 45–52, 2020.
T. Nguyen and J. Lee, “Vision-based Early Fire Detection using Deep Learning and Multi-Sensor Fusion,” IEEE Access, vol. 11, pp. 11820–11832, 2023.
R. Wibowo and F. Anggrainy, “Implementasi Sensor Asap Nirkabel untuk Sistem Peringatan Kebakaran,” Jurnal Sistem Informasi dan Kecerdasan Buatan, vol. 5, no. 1, pp. 22–30, 2021.
N. Faqih and M. Maizana, “Perancangan Modul Relay 5V Berbasis Mikrokontroler untuk Sistem Kontrol Otomatis,” Jurnal Teknik Elektro, vol. 6, no. 2, pp. 41–48, 2024.
S. Hakim, “Hybrid CO & Smoke Sensor for Fire Detection,” Int. Journal of Safety Systems, 2022.
R. Wibowo and F. Anggrainy, “Implementasi Alarm Industri Berbasis Mikrokontroler,” Jurnal Sistem Informasi Industri, 2021.
R. Wibowo and F. Anggrainy, “Implementasi Sensor Asap Berbasis IoT untuk Sistem Deteksi Kebakaran,” Jurnal Sistem Informasi dan Kecerdasan Buatan, vol. 5, no. 1, pp. 22–30, 2021.
A. Muttaqin, S. Rahman, and R. Firmansyah, “Evaluasi Sensor Photoelectric untuk Lingkungan Industri Berdebu,” in Prosiding Seminar Nasional Instrumentasi, 2023, pp. 101–108.
Y. Zhao and K. Lee, “Embedded System Testing Methodologies for Real-Time Applications,” IEEE Transactions on Industrial Electronics, vol. 69, no. 5, pp. 5512–5521, 2022.
A. Rahman, Y. Hakim, and L. Darmawan, “Industrial IoT-based Fire Detection and Notification System using MQTT Protocol,” IEEE Internet Things J., vol. 10, no. 4, pp. 2420–2431, 2023.
M. Nurjaya and S. Elisa, “Konfigurasi GPIO dan Implementasi ESP32 pada Sistem Monitoring,” Jurnal Teknologi dan Komputasi, vol. 8, no. 1, pp. 55–63, 2023.
D. Patel and K. Sharma, “Low-Power Wireless Fire Alarm System for Remote Industrial Sites using LoRa Communication,” International Journal of Wireless Networks and Applications, vol. 14, no. 3, pp. 91–102, 2024.
