A multi-terminal pushing method for emergency information in a smart city based on deep learning. (1st March 2022)

• Record Type: Journal Article
• Authors: Xie, Zheng; Su, Xin
• Is Part Of: International journal of information technology and management. Volume 21:Number 1(2022)
• Page Start: 80
• Page End: 96
• Publication Date: 2022-03-01
• Subjects: deep learning -- smart city -- emergency information -- multi-terminal -- push -- case reasoning; Management information systems -- Periodicals; Information technology -- Periodicals; Management -- Data processing -- Periodicals; 658.403805
• Languages: English
• ISSNs: 1461-4111

Abstract

In order to overcome the problems of large information identification error and high error rate in traditional emergency information push methods, a multi-terminal push method of emergency information in a smart city based on deep learning is proposed. The convolution neural network based on deep learning is used to identify the real-time collection results of intelligent city operation monitoring information, and the combination of softmax loss function and centre loss function is used to reduce the identification error. Through the process of retrieval, adaptation and detection of crisis cases, crisis types are determined and emergency decision-making is selected. Based on XMPP protocol, a multi-terminal push network of emergency information is constructed to push monitoring information and emergency decision to each push terminal. The experimental results show that the information recognition rate of the proposed method is higher than 99%, and the emergency information push result has high precision.