In recent years, campus security accidents frequently occur. The establishment of a set of campus security systems based on artificial intelligence can allow schools, parents, and relevant government departments to make timely warnings and respond to emergencies, effectively protecting the safety of children, which has become an important task in the construction of the current campus security system. This paper designs a smart campus security system based on computer vision and Internet of Things communication technology. The system is mainly analyzed by a vision algorithm, and the campus crowd detection system is designed. The YOLO algorithm based on the DarkNet53 network is mainly used to separate pedestrians from the background for pedestrian detection. Through perspective transformation technology, the center coordinate of the image pedestrian is converted into a three-dimensional coordinate, and the crowd detection and the crowd danger action detection alarm are realized.