Performance Evaluation of ESP32 Sensors for Blynk-Based Smart Home Monitoring

Abstract

This study presents a quantitative analytical evaluation of an integrated ESP32-based smart home system for environmental monitoring, hazard detection, and proximity sensing connected via the Blynk cloud platform. The prototype incorporates a DHT11 sensor for ambient temperature and relative humidity, an MQ-2 semiconductor sensor for LPG leak detection, and an HC-SR04 ultrasonic sensor for distance measurement. Experimental evaluation across repeated continuous trials demonstrated reliable real-time data acquisition and multi-channel alert delivery via Blynk push notifications and automated emails. Statistical analysis against reference instruments revealed high accuracy for the DHT11 sensor, achieving a Mean Absolute Error (MAE) of 1.05°C (RMSE = 1.15°C) for temperature and an MAE of 1.15% (RMSE = 1.27%) for relative humidity, both well within commercial manufacturer tolerances. The HC-SR04 ultrasonic sensor operated accurately over a 5 to 60 cm distance range with an overall MAE of 0.92 cm (RMSE = 0.96 cm). Overall, the proposed system delivers a robust, cost-effective solution for smart residential monitoring and serves as a highly practical instructional trainer kit for IoT and electrical engineering education.