This study investigated the development of an Internet of Things (IoT) based lubricant level monitoring system. Monitoring lubricant levels is essential for maintaining the reliability, efficiency, and longevity of industrial machinery. Conventional lubricant level inspection methods are often manual, time-consuming, and unsuitable for continuous monitoring. To address this limitation, this study develops the system integrates a Light Detection and Ranging (LiDAR) LiDAR sensors and IoT technology using an ESP32 microcontroller for real-time lubricant level measurement and remote data monitoring. The proposed system continuously measures lubricant levels and transmits the collected data through an IoT platform, enabling users to access monitoring information remotely. Laboratory tests were carried out using two Petronas products. They are base oil, known as ETRO 6+ and product, termed as Syntium 800 10W-40. Five measurement tests were performed for each lubricant to evaluate the stability and consistency of the monitoring system. The collected data were analysed using statistical parameters, including mean and standard deviation. The test results showed stable performance with standard deviations of 10.6 mm and 9.27 mm, respectively. The proposed system offers a practical solution for predictive maintenance applications. Future work should focus on evaluating the system under actual industrial environments involving vibration, temperature fluctuations, and other operational disturbances to further validate its industrial applicability and long term reliability. These findings indicate that the developed LiDAR-IoT monitoring system is capable of providing accurate and continuous lubricant level monitoring under controlled laboratory conditions.