Bearing failure is one of the main causes of operational disruptions in mechanical systems due to the lack of continuous condition monitoring. Early detection of vibration and temperature increases is essential to prevent downtime and reduce maintenance costs. This study aims to design and develop a bearing condition monitoring prototype based on the Internet of Things (IoT) using the Research and Development (R&D) approach. The system employs an Arduino Uno and NodeMCU ESP8266 as the main controllers, a piezoelectric sensor to detect vibration, and an MLX90614 infrared sensor to measure the bearing surface temperature. The measured data are transmitted in real time to the ThingSpeak platform for remote visualization and analysis. Experimental testing over three hours showed an average vibration of 7.25 Hz and an average temperature of 35.87 °C, where the condition indicators on the LED and LCD operated according to the predefined thresholds. The system successfully provided early warnings of potential bearing failure through continuous parameter monitoring. The novelty of this research lies in the integration of low-cost multi-sensor technology with the ThingSpeak platform for real-time, end-to-end bearing condition monitoring, supporting the concept of predictive maintenance.
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