A Comparative Study Of HC-SR04 and HY-SRF05 Ultrasonic Sensors For Automated Height Measurement Based On IoT - Kusuma, Mohan Henry; Banu Santoso (Lembaga Penelitian dan Pengabdian Mayarakat (LPPM) Universitas PGRI Yogyakarta, 2025)
The inefficiency and potential for operator error in manual height measurements limit data reliability in health and fitness monitoring. To address this, we developed an automated IoT-based system to compare the performance of HC-SR04 and HY-SRF05 ultrasonic sensors. The system architecture is built on a NodeMCU ESP8266 microcontroller, which sends measurement data to a cloud-based Firebase platform for real-time storage and historical analysis, all visualized on a dynamic ReactJS dashboard. The evaluation involved 30 human subjects with heights ranging from 100 to 200 cm. The analysis revealed a mean absolute error of 0.20 cm (0.131%) for HY-SRF05 and 0.233 cm (0.16%) for HC-SR04. Crucially, statistical testing found no significant difference in accuracy between the two sensors (T-test, p > 0.05). The study concludes that both low-cost sensors are highly capable and statistically equivalent for this application. The complete IoT system demonstrates a robust solution for deploying affordable, scalable, and accurate automated height measurement tools, offering a significant improvement over traditional methods.