Development and Optimization of IoT-Based Weighing Rain Gauge

Abstract

Climate change significantly impacts the hydrologic cycle, altering water movement through land, oceans, and the atmosphere. The Philippines, an agricultural nation, experiences significant effects from the intensification of El Niño and La Niña events due to climate change. This highlights the need for accurate rainfall monitoring, which is crucial for everything from agricultural planning to flood control. This study aimed to develop and optimize an IoT-based weighing rain gauge to enhance the data’s accuracy and reliability. The design process involved analyzing existing rainfall data using the hydrological concept of return period and probability of non-occurrence while adhering to the World Meteorological Organization standards. Powered by a lithium-ion battery rechargeable by a solar panel, the system measures water in grams, converts it to millimeters, and stores it in the cloud. The fabrication employed 3D modeling and printing for efficient prototyping. Calibration used hysteresis and linear regression analysis to minimize errors, ensuring 99.999 % data accuracy. Validation in a laboratory setting showed that the prototype had 99.98 % accuracy, outperforming the commercial gauge’s 98.66 %. Standard deviation analysis indicated higher precision for the prototype. ANOVA confirmed no significant differences between the devices, validating the prototype’s reliability. Potential improvements include applying artificial intelligence to enhance performance.