Development of LoRa Multipoint Network Integrated with MQTT-SN Protocol for Microclimate Data Logging in UB Forest

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.