ARCHIVES

This research presents a comprehensive study on a low-cost LoRa-based wireless sensor network for early forest fire detection. The goal is to develop a scalable, energy-efficient, and long-range monitoring system capable of identifying early fire signatures, including abnormal temperature rise, smoke concentration, and humidity drops. The study focuses on system design, component integration, communication reliability, and field validation. The proposed model demonstrates low power consumption (under 150 mW), long communication range (up to 2.8 km in field tests), and low deployment cost, making it highly suitable for large forest environments. With global forest fire disturbances reaching record highs in 2023 and 2024 — 2.2 times higher globally than the 2002–2022 average — the urgency for scalable, affordable early-warning systems has never been greater. This work addresses that gap through a real-world validated IoT architecture.