Monitoring and Control System Watering Orchid Plants Based on Weather Data

Abstract

Orchid farming faces challenges in efficient water management, often relying on less accurate visual judgments. This research aims to design a weather data-based orchid watering system, monitored and controlled remotely via smartphone. Using a Research and Development (R&D) methodology, the system's performance was tested through soil moisture and temperature sensors. Sensor data were compared with measuring instrument data for accuracy and evaluated across different planting media: vermicompost, coconut fiber, and charcoal. Results showed the DHT22 sensor's temperature (average 33.87°C) was slightly higher than weather.com data (average 32.6°C). Both sources displayed similar humidity patterns, with higher humidity in the morning and lower in the afternoon. The DHT22 sensor recorded an average humidity of 52.58%, compared to 53.4% from weather.com, with a temperature standard deviation of ±0.59 and humidity of ±0.51, indicating good consistency. The soil moisture sensor closely matched the soil meter, with an average difference of 1.3% and a standard deviation of ±0.59. Orchid leaf growth in the first week increased from 10 cm to 10.2 cm in fertiliser and coconut fiber media and to 10.3 cm in charcoal media. In the second week, growth increased to 10.5 cm across all media. Charcoal media was the most effective in accelerating growth in the first week, making it the best choice among the tested media.

Keyword: Monitoring and Control System, Plant Watering, and Orchid Plant Growth.