Development of groundwater level sensor for internet of things-based peatland fire monitoring

Abstract

Monitoring groundwater levels in peatlands is crucial for mitigating forest and land fires, which frequently occur in tropical regions. Current peatland groundwater level monitoring systems generally have limitations in their sensing range. Additionally, the lack of electricity and internet infrastructure around the monitoring sites presents another challenge. To address these issues, in this study, we developed a groundwater level sensor based on a float integrated with an optocoupler as a rotary encoder to monitor changes in water levels in real-time. The system is connected to an internet of things (IoT) platform through a LoRa communication module, powered by solar panels, enabling continuous wireless data transmission over a large range. To overcome the sensing range limitation, we developed a rotary encoder with a pulley driven by a long rope. Testing was conducted using transparent pipes with varying water levels to evaluate the sensor's performance. Experimental results showed that the sensor could measure water levels with a resolution of ±3.33 mm. This research provides a technique for measuring groundwater levels with an extended measurement range. Additionally, it produces a peatland fire risk monitoring system based on groundwater level parameters. It is expected can support peatland fire mitigation efforts more efficiently and effectively.