Innovative Forest Fire Detection Using LoRa Wireless Network for Long-Range and Real-Time Monitoring

detection tool based on wireless technology that can send information in real-time without an internet network. This system helps related parties detect and respond to fires more quickly and efficiently. Methodology: This study employs an experimental research method, using tools such as Arduino, LoRa, DHT11, MQ2 sensors, and ESP32 Wi-Fi modules. Data collection methods include observation, interviews, and literature review. Software used includes Arduino IDE, Sublime, and Windows 10. Prototyping is applied for system design, with unit, system, and integrity testing for system validation. Data analysis is qualitative, with a focus on real-time monitoring. Main Findings: The LoRa forest fire detection system works well, sending temperature, humidity, and smoke data to the website. Tests show that the device can work at a distance of up to 1 km. The fire status only appears if the temperature is above 40°C, humidity is above 10%, and smoke is above 2670 ppm. At close range, the device successfully detects fires, while at further distances, the safe status is displayed. Novelty/Originality of this study: This study introduces a forest fire detection system using LoRa wireless communication, combining real-time monitoring of temperature, humidity, and smoke. The integration of Arduino-based sensors with LoRa for long-range data transmission offers an innovative approach. This research advances existing fire detection technologies by improving coverage and real-time data transmission, enhancing the accuracy and reliability of wildfire monitoring systems.

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Institutions

Publication Details

Journal
Journal of Educational Technology and Learning Creativity
Published
2025-05-02
DOI
https://doi.org/10.37251/jetlc.v3i1.1627
Citations
2
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
2.61
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article

Innovative Forest Fire Detection Using LoRa Wireless Network for Long-Range and Real-Time Monitoring

Nur Shahirah Sulaiman, Christopher Fulton, Nur Adelianthi, Pinky Jee B. Albarico
2 citations
Journal of Educational Technology and Learning Creativity
Fire Detection and Safety Systems
2.61
article

Innovative Forest Fire Detection Using LoRa Wireless Network for Long-Range and Real-Time Monitoring

Nur Shahirah Sulaiman, Christopher Fulton, Nur Adelianthi, Pinky Jee B. Albarico
article en
2 citations

Abstract

detection tool based on wireless technology that can send information in real-time without an internet network. This system helps related parties detect and respond to fires more quickly and efficiently. Methodology: This study employs an experimental research method, using tools such as Arduino, LoRa, DHT11, MQ2 sensors, and ESP32 Wi-Fi modules. Data collection methods include observation, interviews, and literature review. Software used includes Arduino IDE, Sublime, and Windows 10. Prototyping is applied for system design, with unit, system, and integrity testing for system validation. Data analysis is qualitative, with a focus on real-time monitoring. Main Findings: The LoRa forest fire detection system works well, sending temperature, humidity, and smoke data to the website. Tests show that the device can work at a distance of up to 1 km. The fire status only appears if the temperature is above 40°C, humidity is above 10%, and smoke is above 2670 ppm. At close range, the device successfully detects fires, while at further distances, the safe status is displayed. Novelty/Originality of this study: This study introduces a forest fire detection system using LoRa wireless communication, combining real-time monitoring of temperature, humidity, and smoke. The integration of Arduino-based sensors with LoRa for long-range data transmission offers an innovative approach. This research advances existing fire detection technologies by improving coverage and real-time data transmission, enhancing the accuracy and reliability of wildfire monitoring systems.

Journal of Educational Technology and Learning CreativityVol. 3(1)
University of Macau (MO), Northern State University (US), Islamic University (BD), Universitas Islam Makassar (ID), Northern University of Malaysia (MY)
Openalex Percentile: Top 12%
Fire Detection and Safety Systems
2.61
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Innovative Forest Fire Detection Using LoRa Wireless Network for Long-Range and Real-Time Monitoring — Nur Shahirah Sulaiman, Christopher Fulton, et al. · Journal of Educational Technology and Learning Creativity (2025) | TGRS Research Map | TGRS