Development of an IoT-Based Digital Pressure Meter for Suction Pump Pressure Testing and Automated Data Logging

Abstract

A suction pump requires periodic vacuum-pressure verification to support consistent performance assessment and reliable documentation. This study developed an Internet of Things (IoT)-based Digital Pressure Meter (DPM) that displays pressure in mmHg, Pascal (Pa), and bar and transmits measurement records to Google Sheets. The device integrated an Arduino Mega 2560, an MPX5050DP pressure sensor, a DHT22 sensor, a TFT LCD, and an ESP8266 module. Testing was performed at 0, 50, 100, 150, and 200 mmHg with five repetitions at each point and comparison against a Fluke DPM4. The analysis included mean, standard deviation, coefficient of variation, bias, mean absolute percentage error (MAPE), and linear regression. Across the four non-zero points, the relative error against the set pressure ranged from 1.75% to 4.02%, with a MAPE of 2.68%; the coefficient of variation ranged from 0.40% to 2.95%. The relationship between set pressure and device output was y = 0.9735x + 1.0804 with R² = 0.9996. Relative differences from the reference-device means ranged from 1.12% to 5.02%, averaging 2.61%. The IoT system successfully stored pressure, timestamp, serial number, temperature, and humidity; however, decimal formatting for bar values was inconsistent in Google Sheets. The prototype demonstrated strong linearity and repeatability as a pressure-testing and documentation aid. Further work should establish measurement uncertainty, hysteresis, long-term stability, and metrological traceability before the device is used as a calibration standard.