Enterprise Production Safety Intelligent Monitoring System Based On Deep Convolution Neural Network

With the continuous development of the security industry,the demand for the production safety of enterprises has been growing day by day.The status examination of the enterprise operators has become an urgent problem that needs to be solved urgently in the production of an enterprise.In the past ten years,deep learning has made a major breakthrough in the field of artificial intelligence.Deep convolutional neural network as an important part of the depth of learning in face recognition,pedestrian detection and other fields have achieved excellent results.This article mainly explores the specific application of deep learning technology in the field of safety monitoring.Aiming at the safety problems of the operators in the real-time monitoring,the deep convolution neural network model is built by collecting and establishing the deep learning datasets,and the object tracking is used to complete the real-time on-line detection of the abnormal conditions of the workers in the monitoring.Finally,an enterprise production safety intelligent monitoring system is designed to meet the actual production requirements.The main contributions of this paper are as follows:(1)In this paper,the Faster-RCNN and object tracking method are respectively simulated in production safety monitoring.The advantages and disadvantages of the two methods in production safety monitoring are analyzed.A set of Faster-RCNN and object tracking method are designed Target extraction and analysis method.(2)Fetching a sample of fainting from all the videos in the fall data set of the University of Montreal and collecting a large number of image samples of standing walking in the enterprise production workshop and manually labeling thousands of samples to establish the Faster-RCNN Model Training Sample Set.(3)large and more accurate data set is an important condition to enhance the recognition rate of the deep learning model.In different workshops,the clothing characteristics of the workers who are often active in each workshop are also different.In order to improve the robustness of the system,In this paper,we design a method to automatically update the depth learning training sample set.(4)Based on the labview platform,it integrates the functions of image acquisition,target extraction,event alarm and human-computer interaction to complete the functional requirements of the enterprise production safety intelligent monitoring system.