IrriGaia: IoT-Integrated Robotic System for Comparative Analysis of Mist and Drip Irrigation

This study evaluates the performance of IoT-based mist and drip irrigation systems for Thai basil (Ocimum basilicum var. thyrsiflora) cultivation in a controlled indoor environment. We developed a prototype system that integrates ESP32 microcontrollers, capacitive soil moisture sensors, water flow sensors, and energy meters to automate irrigation scheduling and data collection. IoT integration facilitated real-time monitoring, automated control, optimized the irrigation schedules and resource management and enabled the remote visualization in the cloud dashboard. We found that the mist irrigation system demonstrated 33% less water consumption than the drip irrigation system but consumed 55% more energy due to continuous operation. Conversely, the drip irrigation system exhibited superior energy efficiency, making it more suitable for large-scale operations. These findings highlight the potential of IoT-enabled robotic irrigation systems to enhance sustainability and resource efficiency in agriculture. Researchers' future works will explore scalability to diverse crops and environments, as well as the integration of renewable energy sources.