Roller coasters have long been one of the most popular attractions in amusement parks on account of their unique sense of speed and thrilling experience. The lifting chain, a core component of the roller coaster, is responsible for the entire vehicle system’s traction work, and the quality of its performance is directly related to the safe operation of the roller coaster and the comfort of the passengers. However, the wear problem of the lifting chain is particularly prominent with long-term high-speed operation and frequent changes in load, while in the existing lubrication systems, the commonly used method of regular manual oiling lacks real-time monitoring of the actual operating conditions of the chain, making it difficult to adapt to variable working environments and workloads, thereby increasing the risk of equipment failure. In addition, the excessive use of lubricants is plausible to lead to environmental pollution and unnecessary resource waste. To address the above issues, an intelligent monitoring system is proposed. This intelligent monitoring system incorporates advanced sensors to continuously track the lifting chain’s operational state, including key parameters like the surrounding humidity and wind speed, thereby achieving accurate prediction of lubrication needs. The system dynamically adjusts the lubrication strategy based on real-time data, ensuring that the lifting chain can receive just the right amount of lubrication under different environmental conditions, significantly improving the efficiency of lubricant use and reducing waste. Moreover, the introduction of an intelligent monitoring system will greatly reduce the cost of manual maintenance, improve the safety and accuracy of maintenance work, and provide a more reliable guarantee for the safe operation of roller coasters (Woodcock in Saf Sci 62:466–474, 2014).