Design and Implementation of a Smart Garden System for Monitoring and Automatic Watering of Maidenhair Fern Using the Blynk Platform

Abstract

Maidenhair fern (Adiantum tenerum Sw.) is an ornamental plant with high economic value but is highly sensitive to environmental conditions, especially soil moisture, which must be maintained within 50%–80% for optimal growth. Improper cultivation, including poor drainage and fluctuating soil moisture, can cause leaf wilting, root rot, and plant death. This study uses a system design and experimental testing approach to develop a smart garden system for monitoring and automatic watering of maidenhair fern using the Blynk platform. The system integrates an ESP32 microcontroller, soil moisture sensor, relay module, water pump, and Wi-Fi connectivity for real-time monitoring and remote control. Soil moisture conditions were classified as dry (0–49%), moist (50–80%), and wet (80–100%). Results show that the pump activates below 50% and deactivates above 80%, with dry soil (42%–49%) increasing to wet levels (89%–95%) after irrigation. Relay testing confirmed that a high input consistently turns the pump on under dry conditions, while a low input turns it off under moist or wet conditions. Multi-day performance tests demonstrated stable, reliable operation, with real-time data displayed on both LCD and the Blynk application. These findings indicate that the smart garden system effectively regulates soil moisture, simplifies maintenance of maidenhair fern, and provides a practical foundation for IoT-based smart agriculture applications.Maidenhair fern (Adiantum tenerum Sw.) is an ornamental plant with high economic value but is highly sensitive to environmental conditions, especially soil moisture, which must be maintained within 50%–80% for optimal growth. Improper cultivation, including poor drainage and fluctuating soil moisture, can cause leaf wilting, root rot, and plant death. This study uses a system design and experimental testing approach to develop a smart garden system for monitoring and automatic watering of maidenhair fern using the Blynk platform. The system integrates an ESP32 microcontroller, soil moisture sensor, relay module, water pump, and Wi-Fi connectivity for real-time monitoring and remote control. Soil moisture conditions were classified as dry (0–49%), moist (50–80%), and wet (80–100%). Results show that the pump activates below 50% and deactivates above 80%, with dry soil (42%–49%) increasing to wet levels (89%–95%) after irrigation. Relay testing confirmed that a high input consistently turns the pump on under dry conditions, while a low input turns it off under moist or wet conditions. Multi-day performance tests demonstrated stable, reliable operation, with real-time data displayed on both LCD and the Blynk application. These findings indicate that the smart garden system effectively regulates soil moisture, simplifies maintenance of maidenhair fern, and provides a practical foundation for IoT-based smart agriculture applications.