Abstract:
The UB Forest, located on the slopes of Mount Arjuno, is a significant educational and research area with rich agricultural
lands and diverse plant species. Traditional methods of microclimate data collection in this area have relied on manual sensor inspection
by local farmers. This study introduces a novel approach by integrating Internet of Things (IoT) technology, particularly employing
Long Range (LoRa) communication, to overcome the limitations of conventional WiFi networks in remote data access. The
implementation uses ESP32 modules for data transmission and reception, focusing on establishing a LoRa network compatible with
the Message Queuing Telemetry Transport for Sensor Networks (MQTT-SN) protocol. This enhances data exchange efficiency and
reliability. The system is engineered to transmit 11 distinct microclimate data parameters bi-minutely from two nodes. Preliminary
testing reveals a maximum transmission range of 300 meters. However, the data loss rate is significant, averaging 50%, which reduces
to 15% at a distance of 100 meters. Signal strength is strongest at -94 dBm for 100 meters and -121 dBm for 300 meters. These results,
while promising, fall short of the LoRa Alliance's expected performance metrics, which suggest effective operational distances of up
to 2km under optimal conditions. This research demonstrates the potential and challenges of integrating IoT and LoRa technology in
agricultural and environmental monitoring. The findings underscore the need for further optimization to achieve the range and
reliability required for effective remote monitoring in rural and forested environments. This study sets a foundation for future
enhancements in sensor network design and deployment strategies, aiming to improve data accuracy and accessibility for agricultural
and environmental research.
