Research And Application Of The Elderly Fall Detection Method Based On Video Surveillance

As people’s living standards improve,they pay more and more attention to their health.Donkey-hide gelatin as a medicinal food is becoming increasingly popular due to its obvious efficacy and great medicinal value for people’s health.In traditional Chinese medicine,it is often used as a tonic.Most of the Donkey-hide gelatin manufacturers in China are manually operated,and the complex production process makes it difficult to ensure its quality.If the quality does not meet the standard,it will pose a huge threat to human health.Automating the Donkey-hide gelatin production line not only improves production efficiency but also ensures the reliability and consistency of the operation,thereby effectively improving product quality.To improve the automation level of Donkey-hide gelatin production,this paper analyzes its process mechanism and control requirements,and develops the Donkey-hide gelatin production distributed control system and foam image feature analysis system.The main research contents are as follows:(1)Based on the process mechanism of Donkey-hide gelatin production and the current research status at home and abroad,the overall scheme of the Donkey-hide gelatin production line automation system is proposed,including the Donkey-hide gelatin production DCS system and the foam image feature analysis system.(2)The process flow of the Donkey-hide gelatin production line is studied,and the upper computer uses Freelance2019,and the lower computer uses AC800 F for the Donkey-hide gelatin production process automatic control system.The functions of equipment start and stop,analog quantity automatic adjustment,fault alarm,process monitoring,etc.,are realized.In addition,a control platform is built for the foam image feature analysis system.(3)To solve the problem of automatic control of the foam lifting process,computer vision technology is used to analyze foam images,and the image is preprocessed based on the bilateral filtering Retinex theory image enhancement algorithm.The color feature and texture feature of the image are extracted using the color histogram and gray-level co-occurrence matrix,respectively.The texture feature vector value is used to judge the quality of the gelatin solution,solving the problem of difficult judgment of the quality of gelatin solution in the lifting process.The foam image is segmented based on the Otsu threshold segmentation method,and the foam lifting progress is judged in combination with the color feature,solving the problem of incomplete foam extraction leading to a decrease in the quality of the gelatin solution.An image feature analysis system is developed to provide online guidance for Donkey-hide gelatin foam lifting.(4)The Donkey-hide gelatin production distributed control system and foam image feature analysis system are verified by simulation.In the DCS control system,a simulation control platform is built and connected to a simulation controller to simulate the production situation on-site to verify the feasibility of the system.In MATLAB R2018 B software,the foam image feature analysis system is verified,and the accuracy of the system is verified by analyzing the foam image feature.The results show that the Donkey-hide gelatin production distributed control system and foam image feature analysis system have improved the overall automation level of Donkey-hide gelatin production,realized the intelligence of Donkey-hide gelatin production,and are conducive to improving Donkey-hide gelatin production efficiency and product quality.