Implementation of LoRa-Based Remote Monitoring System for Precision Mango Farming

Abstract

This study investigated the effectiveness of a LoRa-based remote monitoring system for enhancing precision mango farming. The main objective was to evaluate how real-time environmental data collected from soil. air. and light sensors can support improved cultivation practices. A sensor network was deployed in a commercial mango orchard in Chachoengsao. Thailand, focusing on two areas: one managed with good agricultural practices, and the other with conventional methods. Ten mango trees were randomly selected from these areas for sensor installation to monitor environmental conditions. Data were collected hourly from July 2023 to April 2024. transmitted to a cloud-based MQTT broker, and visualized using a web dashboard. The study hypothesizes that sensor-guided interventions, such as optimized irrigation and pruning, lead to better environmental conditions and higher fruit yield. The results confirmed that trees under good practices, where the soil effectively retained rainwater, showed higher moisture retention. In contrast, some trees subjected to conventional practices exhibited lower retention rates. These findings support the potential of IoT-based LoRa systems to enable data-driven sustainable mango cultivation.