The Role of Precise Environmental Monitoring in Precision Agriculture for Climate Change Mitigation: A Sensor Calibration Approach

Unmaintained soil moisture can hinder plant growth. Thus, automatic soil moisture control is a solution to this problem. Soil moisture sensors can measure soil moisture and activate the pump system automatically. However, sensor readings are inaccurate without proper calibration and can disrupt the system’s function for controlling the plant environment. Therefore, a calibration of each sensor is necessary before implementation. This study mainly demonstrated a simple linear regression calibration method for soil moisture, air temperature, and humidity sensors before use. In addition, validate the potential for precision agriculture to enhance seedling growth compared to the manual method. The calibration results for soil moisture sensors, air temperature, and humidity showed an increase in accuracy of 0.26%, 0.29%, and 0.36%, respectively. Furthermore, applying this soil moisture control system in precision agriculture was tested by comparing green bean seedling yields’ wet weight and height at 80% and 50% moisture levels and with manual watering. The experimental results showed that planting using this moisture control system resulted in better seedling growth than manual watering. This study finds that precision agriculture produces crops up to twice as much as the manual method, yet has low human capital costs to improve profitability. Findings suggest that automated irrigation improves seedling growth, potentially enhancing sustainability in precision agriculture. By refining sensor accuracy, this approach not only supports efficient resource management but also contributes to higher crop yields and to climate change mitigation by reducing water use.