DBSCAN算法的学校新冠肺炎数据采集云平台设计

Design of school COVID⁃19 data acquisition cloud platform based on DBSCAN algorithm

自全国新型冠状病毒感染的肺炎疫情出现以来,在教育主管部门指导下,各学校防疫工作科学有序开展。面对爆发增长的病例数字,如何快速、准确地收集校学生健康状况数据是防疫工作的重中之重。师生出行或状态状况等数据若采用传统的微信群、QQ群收集方式会导致时间久、效率低,而且难免错漏。利用信息化平台发布填写任务,能够让师生在规定时间内填写当天健康信息、历史出行记录、家庭成员健康状况等。对于海量的数据,通过手工筛选问题数据工作量巨大。平台基于DBSCAN算法对海量数据进行分析,找出孤立点,挖掘异常数据,减少数据筛选工作量,提高定位精度,助力学校疫情防控。系统在湖北、江苏、安徽、江西、广东和河北等百所学校进行了使用,产生了良好的社会效益和经济效益。

Since the outbreak of COVID⁃19 in China,the epidemic prevention work in schools has been carried out scientifically and orderly under the guidance of the competent authorities for education.In the face of the increasing number of the cases,how to quickly and accurately collect the health data of school students is the top priority of epidemic prevention work.If the traditional WeChat group and QQ group are used to collect the data of travel condition or status quo of teachers and students,it will lead to a long time consumption,low efficiency,and inevitable errors and omissions.The information platform is used to release the filling task,so that teachers and students can fill in the forms of their health information,historical travel records,and health status of their family members within the specified time.For massive data,the workload of manually filtering problem data is huge.The platform is based on DBSCAN algorithm to analyze massive data,so as to find out the isolated point,mine the abnormal data,reduce the workload of data screening,improve the positioning accuracy,and help epidemic prevention and control of schools.The system has been used in hundreds of schools in Hubei,Jiangsu,Anhui,Jiangxi,Guangdong and Hebei provinces,and has produced good social and economic benefits.