Design of a Miniature Sensor and Algorithm for Real-Time Interpretation of Micro-Nutrient Data

The increasing demand for sustainable agricultural practices has led to the adoption of hydroponics, a method of growing plants in nutrient-rich solutions without soil. This method is particularly effective in controlled environments where resource efficiency is paramount. However, the success of hydroponic systems depends heavily on precise nutrient management, especially for micro-nutrients, which are crucial for plant health and productivity. Traditional methods of nutrient monitoring are often labor-intensive and lack the real-time responsiveness needed for optimal nutrient control. This study addresses the challenge of real-time nutrient management in hydroponic systems by developing a miniature sensor system integrated with Internet of Things (IoT) technology. The proposed system is designed to detect micro-nutrient concentrations accurately and transmit data in real-time to a cloud platform for continuous monitoring and automated control. Advanced algorithms are employed for data processing and calibration, ensuring high accuracy in detecting micro-nutrient levels. The system was tested in a controlled hydroponic environment, where it demonstrated high accuracy with minimal error margins, validated by a consistently low Mean Absolute Error (MAE). The integration of IoT allowed for seamless data transmission and real-time analysis, enabling immediate adjustments to nutrient levels as needed. This research contributes to the advancement of precision agriculture by providing an effective solution for real-time nutrient management in hydroponic systems, potentially improving crop yields and resource efficiency.