Automatic Collection and Management System of Computer Room Assets based on Convolutional Neural Networks

For solving the problems existing in assets information collection and management in offline computer room, such as long time consuming, low reliability, high cost and difficult to manage assets in different places, convolution neural network was introduced into the field of device information automatic collection in this paper. The device classifier model based on convolution neural network was put forward and applied to the automatic collection and storage system. In addition, the DIC application system used for the mobile side and the CRMS system for the server side were implemented by using the architecture that separated the server and the client. The results reveal that this system has great potential to improve the way of information collection and management of device in the room, thus gathering info more effective.