Real-time vehicle occupation status detection system by integrating cloud computation and machine learning

In the past decades, with the rapid development of computer technology, machine learning and machine vision have been applied to many field for automatic detection purpose. However, most applications are based on CNN network or DNN network, in which the computation cost is very high. In this research, we focused on the application of real-time vehicle occupation status detection. An intelligent parking management system based on machine vision and machine learning was developed. With this system, detection of vehicle occupation status can be realized only using cameras, and the computation speed is very fast. The effectiveness of this system was tested by two actual parking lots, which have already applied this system.