Detection of Emergency Situations for Elevator Passengers

This paper introduces an example of AI(Artificial Intelligence) engine implementation for detecting events related to emergency situations such as collapse and assault, especially for elevator passengers. In contrast to the security cameras installed in a relatively open-space environment, those cameras installed in an elevator environment are likely to capture subjects from a high angle and at a relatively close distance. In an elevator environment, sometimes, only a part of subject may be captured. In addition to that, a part or whole of subject may be reflected in the wall or mirror and, moreover, those reflected things may be also captured. Considering those differences, to implement the above AI engine, the authors of this paper picked action/video recognition methods. And, the authors also built a prototype-level data-set to train and evaluate the related neural network models. This paper describes the tasks and methods to implement the above AI engine and also shows some demonstration results.