INNOVATIVE IOT-BASED STRATEGY FOR WATER QUALITY CONTROL IN HYDROPONIC PLANTS USING MEDIAN FILTER AND LINEAR QUADRATIC ESTIMATION

Controlling water quality in hydroponic farming is essential but challenging. IoT sensors help monitor water conditions, but the data they produce is often inaccurate and water quality control becomes ineffective. This research uses an innovative approach in remote monitoring and controlling water quality in hydroponic systems through the integration of Internet of Things (IoT) technology for real-time data collection and data processing algorithms. The proposed strategy is to use a Median Filter combined with Linear Quadratic Estimation to produce more precise water quality control for hydroponic plants. Median Filter effectively reduces the noise from data obtained from sensors, while Linear Quadratic Estimation is used to predict the state of water quality of hydroponic plans. Experimental results show that the proposed system achieves mean absolute error (MAE), and root mean square error (RMSE) values below 1% for both PPM and pH measurements. This indicates that sensor data can be effectively processed, and the estimation of water quality changes closely reflects the actual conditions of the water. The approach using these two methods can ensure that the water quality of hydroponic plants becomes more stable and controlled, thus having an impact on the fertility and health of the plants and increasing better yields.