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International Journal of Advanced Technology and Engineering Exploration (IJATEE)

ISSN (Print):2394-5443    ISSN (Online):2394-7454
Volume-10 Issue-108 November-2023
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Paper Title : Enhancing peatland fire prevention: an incremental LoRa and mobile-based early warning system
Author Name : Diki Arisandi, Amir Syamsuadi and Liza Trisnawati
Abstract :

Peatland fires present a significant threat in Indonesia, arising from human activities or adverse weather conditions. An early warning system using long-range (LoRa) and mobile technology can help avert peatland fires through continuous environmental monitoring and rapid detection of fire risks. This study develops an incremental LoRa and mobile-based early warning system for peatlands. Temperature, humidity, and other environmental data are gathered by strategically placed node sensors and gateways in high-risk areas. The sensors transmit data to a cloud server for storage and analysis. Web and mobile platforms provide easy accessibility to view sensor readings and alerts. The system is designed using an incremental integration approach, seamlessly combining LoRa technology and mobile monitoring for enhanced real-time anomaly detection in peatlands. Telecommunication signal strength mapping and user testing help refine sensor placement and system usability. Evaluation of the mobile-based LoRa system demonstrates promising results. Users positively acknowledged the intuitiveness and utility of the web and mobile applications. The system achieved high task success rates exceeding 85%, low error rates under 15%, and reasonable task completion times during testing. This result indicates effectiveness in enabling early fire risk detection and response coordination. However, fluctuations in sensor reading accuracy compared to field measurements and limited telecommunication coverage in remote regions impacted system reliability. While significant progress has been made, challenges remain regarding consistent sensor accuracy and connectivity coverage. Future efforts should focus on integrating industrial-grade sensors and machine-learning techniques for improved data analytics and autonomous decision-making. Enhancing the system's accuracy and early detection capabilities will strengthen peatland fire prevention and mitigate risks from human activities and climate change impacts. With further development, the mobile-based LoRa system shows promise as an accessible, inexpensive, and scalable solution for early warning and coordinated action against peatland fires.

Keywords : Peatland fires, LoRa technology, Early warning system, Environmental monitoring, Mobile technology.
Cite this article : Arisandi D, Syamsuadi A, Trisnawati L. Enhancing peatland fire prevention: an incremental LoRa and mobile-based early warning system. International Journal of Advanced Technology and Engineering Exploration. 2023; 10(108):1368-1391. DOI:10.19101/IJATEE.2023.10101900.
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