Belt-pulley looseness is a crucial factor in ensuring the safe operation of machinery used in industrial applications, such as compressors and fans. Traditionally, belt looseness has been inspected using contact-based current and vibration sensors. However, these methods are time-consuming and require manual attachment of the sensors. In order to overcome the limitations of these traditional methods, we propose a remote diagnosis method for detecting belt looseness using a smartphone. By utilizing a four-mirror system, the smartphone can construct a stereo system that enables 3D reconstruction of the object. This allows us to reconstruct the 3D trajectory of the belt and diagnose the level of looseness. To further enhance the accuracy of our proposed system, we have developed a calibration algorithm specifically designed for the four-mirror system. In our actual experiment, we successfully diagnosed four levels of belt looseness. As the level of looseness increased, we observed a curved shape in the 3D trajectory of the belt, along with noticeable quantitative differences. To quantitatively analyze these differences, we introduced a measure called the residual, which reflects the curvilinearity of the 3D trajectory. Our findings confirmed a significant correlation between the residual and the level of belt looseness.