Research on the design of personal intelligent epidemic prevention products by integrating digital twin models and edge computing frameworks
In this era of blurred concepts and serious homogenization of anti-epidemic products.In order to improve the experi-ence effect of epidemic prevention products and meet the needs of the public.After researching and analyzing the existing epidemic prevention products,the study purposefully introduces the digital twin model and edge computing framework to analyze and redefine the monitoring data,and finally proposes a new intelligent monitoring mask.The experimental results show that the average value of blood oxygen content detection error of the research-designed smart mask is about 0.4,and the average value of heart rate error is a-bout 0.35.In the comparative test,it is found that the blood oxygen content and heart rate monitoring of individuals wearing the mask tend to be normalized.Compared to the same type of smart masks,the new smart mask designed by the study has a maximum filtration efficiency of 97％,while the respiratory resistance is below normal,ranging from 80-260 Pa.Tests after three weeks of use found the smart mask to have a maximum wear and tear of only 60％.The remaining battery life was retained at a maximum of 40 hours and comfort was still up to 65％.After the comprehensive scoring,the new mask has the highest average safety score of 8.5.In summary,this study provides new ideas and methods for the design and research of smart epidemic prevention products.
万方数据
维普
