<![CDATA[Single-phase induction motors are widely used in industrial support systems such as compressors, cooling fans, and pumps. Bearing deterioration can alter motor vibration and operating current and may reduce equipment reliability. This study develops an Internet of Things-based condition-monitoring prototype for a 1/4 horsepower single-phase induction motor using an MPU6050 accelerometer, an ACS712 current sensor, an ESP32 microcontroller, a liquid crystal display, and a Firebase realtime database. Sensor data are processed by the ESP32, displayed locally, and transmitted through a wireless network for remote observation. Tests were conducted for 100 seconds under normal and abnormal bearing conditions, with three repetitions for each condition. The average Y-axis acceleration reading changed from -8 LSB in the normal condition to -372 LSB in the abnormal condition, indicating a measurable shift in the recorded vibration level for the tested configuration. The ACS712 provided current readout and the ESP32 successfully transmitted monitoring data to Firebase. The prototype therefore supports early condition monitoring, while generalized fault classification and current-based discrimination require further validation.]]>
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