WO2021184411A1 - 一种基于物联网的新冠肺炎疫情防控系统 - Google Patents

一种基于物联网的新冠肺炎疫情防控系统 Download PDF

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WO2021184411A1
WO2021184411A1 PCT/CN2020/081698 CN2020081698W WO2021184411A1 WO 2021184411 A1 WO2021184411 A1 WO 2021184411A1 CN 2020081698 W CN2020081698 W CN 2020081698W WO 2021184411 A1 WO2021184411 A1 WO 2021184411A1
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detection line
server
control system
internet
system based
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French (fr)
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吴刚
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吴刚
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/70—Denoising; Smoothing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/80—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning

Definitions

  • the invention belongs to the field of computer technology, and in particular relates to a new crown pneumonia epidemic prevention and control system based on the Internet of Things.
  • the new coronavirus (2019-nCoV) is a new strain of coronavirus that is extremely contagious and can cause fever, cough, difficulty breathing, and even death in the infected person.
  • the incubation period of pneumonia caused by the new coronavirus infection is 1-14 days.
  • the infected person is obviously contagious throughout the course of the disease. Therefore, early and timely diagnosis can effectively control the infection of the disease and help to give patients medical support in advance. The outcome of the disease.
  • the existing new coronavirus pneumonia still has technical problems that the detection methods are difficult to popularize and the detection data is difficult to centrally analyze.
  • the purpose of the embodiments of the present invention is to provide a novel coronavirus pneumonia epidemic prevention and control system based on the Internet of Things, which aims to solve the existing technical problems of the existing novel coronavirus pneumonia that the detection methods are difficult to popularize and the detection data are difficult to centrally analyze.
  • the embodiment of the present invention is implemented in this way, a new crown pneumonia epidemic prevention and control system based on the Internet of Things, including a new crown pneumonia colloidal gold kit installed with a detection line sensor and a server;
  • the new coronary pneumonia colloidal gold kit installed with a detection line sensor is used to detect a user for new coronary pneumonia, and obtain the detection line result through the detection line sensor, and upload it to the server;
  • the server is used to determine the diagnosis result of the user according to the result of the detection line.
  • the identity binding terminal is used to obtain user identity information, establish a corresponding relationship with the obtained detection line result, and upload it to the server .
  • it further includes a positioning terminal configured to obtain user location information, establish a corresponding relationship with the obtained user identity information, and upload it to the server.
  • the detection line sensor is an image sensor, and the detection line result is an image containing the detection line.
  • the test line includes a quality control test line, an IgM antibody test line, and an IgG antibody test line.
  • the step of the server for determining the diagnosis result of the user according to the image containing the detection line specifically includes:
  • the user's diagnosis result is determined according to the gray values of the multiple detection lines after the noise reduction process.
  • the step of training and generating the image noise reduction model specifically includes:
  • the training samples include gray values of multiple sample detection lines and corresponding diagnosis results;
  • the image noise reduction model including error parameters to be determined and threshold parameters;
  • the server is also used to determine the spreading trend of the epidemic according to the diagnosis result of the user and a preset spreading model of the epidemic.
  • the embodiment of the present invention provides a new crown pneumonia epidemic prevention and control system based on the Internet of Things, which uses a new crown pneumonia colloidal gold kit that has the advantages of rapidity, simplicity, high stability, low cost, self-detection, etc., as a new crown pneumonia new crown pneumonia detection tool
  • the detection line sensor installed in the kit
  • the server can collect statistics and determine the diagnosis results of each user and determine the diagnosis results of each user.
  • the new crown The popularity of pneumonia detection allows users to quickly and conveniently achieve detection at home.
  • it realizes the centralized management of new coronary pneumonia detection results, which is of far-reaching significance for subsequent data collation, analysis, disclosure, and prediction.
  • FIG. 1 is a schematic structural diagram of a new crown pneumonia epidemic prevention and control system based on the Internet of Things provided by an embodiment of the present invention
  • FIG. 2 is a schematic structural diagram of another new crown pneumonia epidemic prevention and control system based on the Internet of Things provided by an embodiment of the present invention
  • FIG. 3 is a schematic structural diagram of another new crown pneumonia epidemic prevention and control system based on the Internet of Things provided by an embodiment of the present invention
  • FIG. 4 is a flowchart of steps for determining a diagnosis result of a user according to an embodiment of the present invention
  • Fig. 5 is a flowchart of steps for training a noise reduction model generated by an image provided by an embodiment of the present invention.
  • FIG. 1 it is a schematic structural diagram of a new crown pneumonia epidemic prevention and control system based on the Internet of Things provided by an embodiment of the present invention, which is described in detail as follows.
  • the new coronary pneumonia epidemic prevention and control system includes a new coronary pneumonia colloidal gold kit 120 installed with a detection line sensor 110 and a server 130.
  • the neo-coronary pneumonia colloidal gold kit 120 is used to perform neo-coronary pneumonia detection on users.
  • the detection line sensor 110 is used to obtain a detection line result, and upload the obtained detection line result to the server.
  • the detection line sensor is an image sensor, then the detection line result at this time is an image containing the detection line.
  • the test line includes quality control test line, IgM antibody test line and IgG antibody test line.
  • the quality control test line can reflect the effectiveness of this test. When the quality control test line is colored, it indicates that the test is effective. When the quality control test line does not show color, it indicates that the test is invalid. When the test is effective, the IgM antibody test line and IgG antibody test line can reflect the user's diagnosis result and whether it is infected.
  • the server 130 may be a server with data storage and data processing functions, or a cloud server, and the server is used to determine the diagnosis result of the user according to the result of the detection line.
  • the server can collect the detection line results uploaded by several users, and centrally manage the diagnosis results.
  • the server determines the user's diagnosis result according to the uploaded image containing the detection line, please refer to FIG. 4 and its explanation for details.
  • the server 130 is also used to determine the spreading trend of the epidemic according to the diagnosis result of the user and a preset spreading model of the epidemic.
  • the embodiment of the present invention provides a new crown pneumonia epidemic prevention and control system based on the Internet of Things, which uses a new crown pneumonia colloidal gold kit that has the advantages of rapidity, simplicity, high stability, low cost, self-detection, etc., as a new crown pneumonia new crown pneumonia detection tool
  • the detection line sensor installed in the kit
  • the server can collect statistics and determine the diagnosis results of each user and determine the diagnosis results of each user.
  • the new crown The popularity of pneumonia detection allows users to quickly and conveniently achieve detection at home.
  • it realizes the centralized management of new coronary pneumonia detection results, which is of far-reaching significance for subsequent data collation, analysis, disclosure, and prediction.
  • FIG. 2 another system for preventing and controlling a new crown pneumonia epidemic based on the Internet of Things provided by an embodiment of the present invention is described in detail as follows.
  • the difference from the new crown pneumonia epidemic prevention and control system based on the Internet of Things shown in FIG. 1 is that it also includes an identity binding terminal 210;
  • the identity binding terminal 210 is used to obtain user identity information, establish a corresponding relationship with the obtained detection line result, and upload it to the server.
  • the identity binding terminal 210 is usually a mobile device, such as a mobile phone, a smart watch, etc., any device that can obtain the user’s identity information, and further uses QR code scanning and facial recognition. Identification and other technologies realize the binding of identities, and the present invention does not limit the specific equipment and technologies that realize the binding of identities.
  • the identity binding terminal should correspond to the COVID-19 colloidal gold kit one-to-one, that is, under normal circumstances, every COVID-19 colloidal gold kit should correspond to an identity binding terminal.
  • FIG. 3 Another system for preventing and controlling a new crown pneumonia epidemic based on the Internet of Things provided by an embodiment of the present invention is described in detail as follows.
  • the difference from the new crown pneumonia epidemic prevention and control system based on the Internet of Things shown in FIG. 1 is that it also includes a positioning terminal 310;
  • the positioning terminal 310 is configured to obtain user location information, establish a corresponding relationship with the obtained user identity information, and upload it to the server.
  • the positioning terminal 310 is similar to the identity binding terminal 210, and is usually a mobile device, and may be any device with a GPS positioning function, such as a mobile phone, a smart watch, and so on.
  • the same device can also be used to achieve identity binding and positioning at the same time, that is, it can be the identity binding terminal and the positioning terminal at the same time.
  • the positioning terminal should also correspond to the identity binding terminal one-to-one, that is, under normal circumstances, each identity binding terminal should correspond to a positioning terminal.
  • the distribution map of the new coronary pneumonia can be determined, which is of great significance to the establishment of the subsequent spreading model of the epidemic.
  • FIG. 4 it is a flowchart of steps for determining a diagnosis result of a user according to an embodiment of the present invention, which specifically includes the following steps:
  • Step S402 Determine the gray values of multiple detection lines in the image containing the detection lines.
  • the detection line considering whether the detection line is colored or not to determine the detection result, it is necessary to determine the gray values of multiple detection lines in the image containing the detection line.
  • Step S404 Perform noise reduction processing on the gray values of multiple detection lines in the image based on a preset image noise reduction model.
  • the preset image noise reduction model is generated in advance based on linear regression algorithm training. Taking into account the errors in the acquisition process, the image noise reduction model can perform noise reduction processing on the gray values of multiple detection lines, so as to obtain more accurate results.
  • Step S406 Determine the diagnosis result of the user according to the gray values of the multiple detection lines after the noise reduction processing.
  • the detection line is colored based on the gray value of multiple detection lines and the preset threshold value.
  • the detection line is displayed Color; when the gray value of the detection line is lower than the preset threshold, the detection line is not colored. Furthermore, judging whether the user is infected by the color development of the detection line belongs to the conventional technical means of those skilled in the art, and will not be repeated here.
  • FIG. 5 it is a flowchart of steps for training and generating an image noise reduction model provided by an embodiment of the present invention, which specifically includes the following steps:
  • Step S502 Obtain training samples.
  • the training sample includes gray values of multiple sample detection lines and corresponding diagnosis results.
  • Step S504 Construct an initialized image noise reduction model.
  • the image noise reduction model includes an error parameter to be determined and a threshold parameter.
  • the error parameter obeys a normal distribution with a mean value of 0.
  • Step S506 Training the error parameters and threshold parameters included in the image noise reduction model according to the training samples.
  • the values of the error parameters and threshold parameters included in the image noise reduction model can be determined based on the linear regression algorithm and combined with training samples, thereby training and generating the image noise reduction model.

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Abstract

本发明适用于计算机技术领域，尤其涉及一种基于物联网的新冠肺炎疫情防控系统，包括安装有检测线传感器的新冠肺炎胶体金试剂盒以及服务端；所述安装有检测线传感器的新冠肺炎胶体金试剂盒，用于对用户进行新冠肺炎检测，并通过所述检测线传感器获取检测线结果，并上传至所述服务端；所述服务端，用于根据所述检测线结果确定用户的诊断结果。本发明实施例提供的防控系统利用具有快速、简便、稳定性高、廉价、可自我检测等优点的新冠肺炎胶体金试剂盒作为新冠肺炎新冠肺炎检测工具，同时配合安装在试剂盒内部的检测线传感器，能够获取检测线结果并上传至服务端，一方面用户可以方便快捷的进行检测，另一方面实现了新冠肺炎检测结果的集中管理。

Description

一种基于物联网的新冠肺炎疫情防控系统 技术领域
本发明属于计算机技术领域，尤其涉及一种基于物联网的新冠肺炎疫情防控系统。
 背景技术
新冠状病毒（2019-nCoV）是一种具有极强的传染性，可导致感染者出现发热、咳嗽、呼吸困难，甚至死亡的冠状病毒新毒株。新冠状病毒感染导致的肺炎潜伏期为1-14天，感染者在整个病程中均具有明显的传染性，因此早期、及时地诊断可有效控制疾病的传染，并有助于提前给予患者医疗支持改善其疾病结局。
目前对于新冠状病毒肺炎的筛查需要综合临床症状、血常规、CT检查或核酸检查的结果进行判断。CT检查和核酸检查均需要独立的场所、昂贵的设备及专业的人员，因此无法满足目前对大范围人群进行筛查的需求，并且检测结果需要专业医生完成，降低了检测效率，获得的检测结果后无法及时获得医学解释及医疗建议，结果无法长期保存，无法为后续的研究提供数据。
 技术问题
现有的新冠状病毒肺炎还存在着检测手段难以普及、检测数据难以集中分析的技术问题。
 技术解决方案
本发明实施例的目的在于提供一种基于物联网的新冠肺炎疫情防控系统，旨在解决现有的新冠状病毒肺炎还存在的检测手段难以普及、检测数据难以集中分析的技术问题。
本发明实施例是这样实现的，一种基于物联网的新冠肺炎疫情防控系统，包括安装有检测线传感器的新冠肺炎胶体金试剂盒以及服务端；
所述安装有检测线传感器的新冠肺炎胶体金试剂盒，用于对用户进行新冠肺炎检测，并通过所述检测线传感器获取检测线结果，并上传至所述服务端；
所述服务端，用于根据所述检测线结果确定用户的诊断结果。
作为本发明的一个优选实施例，还包括身份绑定端，所述身份绑定端，用于获取用户身份信息，并与获取的所述检测线结果建立对应关系，并上传至所述服务端。
作为本发明的另一个优选实施例，还包括定位端，所述定位端，用于获取用户位置信息，并与获取的所述用户身份信息建立对应关系，并上传至所述服务端。
作为本发明的另一个优选实施例，所述检测线传感器为图像传感器，所述检测线结果为包含检测线的图像。
作为本发明的另一个优选实施例，所述检测线包括质控检测线、IgM抗体检测线以及IgG抗体检测线。
作为本发明的另一个优选实施例，所述服务端用于根据所述包含检测线的图像确定用户的诊断结果的步骤具体包括：
确定包含检测线的图像中多条检测线的灰度值；
基于预设的图像降噪模型对所述图像中多条检测线的灰度值进行降噪处理；所述预设的图像降噪模型是预先基于线性回归算法训练生成的；
根据降噪处理后的多条检测线的灰度值确定用户的诊断结果。
作为本发明的另一个优选实施例，训练生成所述图像降噪模型的步骤具体包括：
获取训练样本；所述训练样本包括多条样本检测线的灰度值以及对应的诊断结果；
构建初始化的图像降噪模型，所述图像降噪模型包括待确定的误差参数以及阈值参数；
根据所述训练样本对所述图像降噪模型中包括的误差参数以及阈值参数进行训练。
作为本发明的另一个优选实施例，所述服务端还用于根据用户的诊断结果以及预设的疫情传播模型确定疫情的传播趋势。
 有益效果
本发明实施例提供的一种基于物联网的新冠肺炎疫情防控系统，利用具有快速、简便、稳定性高、廉价、可自我检测等优点的新冠肺炎胶体金试剂盒作为新冠肺炎新冠肺炎检测工具，同时配合安装在试剂盒内部的检测线传感器，能够获取检测线结果，并上传至服务端，服务端可以统计收集各个用户自行检测的检测结果并确定各个用户的诊断结果，一方面实现了新冠肺炎检测的普及，用户可以居家方便快捷的实现检测，另一方面实现了新冠肺炎检测结果的集中管理，对于后续数据的整理、分析、公开、预测具有深远的意义。
 附图说明
图1为本发明实施例提供的一种基于物联网的新冠肺炎疫情防控系统的结构示意图；
图2为本发明实施例提供的另一种基于物联网的新冠肺炎疫情防控系统的结构示意图；
图3为本发明实施例提供的又一种基于物联网的新冠肺炎疫情防控系统的结构示意图；
图4为本发明实施例提供的确定用户的诊断结果的步骤流程图；
图5为本发明实施例提供的训练生成图像降噪模型的步骤流程图。
 本发明的实施方式
为了使本发明的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
如图1所示，为本发明实施例提供的一种基于物联网的新冠肺炎疫情防控系统的结构示意图，详述如下。
在本发明实施例中，所述新冠肺炎疫情防控系统包括安装有检测线传感器110的新冠肺炎胶体金试剂盒120以及服务端130。
在本发明实施例中，所述新冠肺炎胶体金试剂盒120用于对用户进行新冠肺炎检测。
在本发明实施例中，所述检测线传感器110用于获取检测线结果，并将获取的检测线结果上传至所述服务端。
作为本发明的一个优选实施例中，所述检测线传感器为图像传感器，则此时检测线结果为包含检测线的图像。进一步的，检测线包括质控检测线、IgM抗体检测线以及IgG抗体检测线，质控检测线可以反映本次检测的有效性，当质控检测线显色时，表明本次检测有效，而质控检测线不显色时，表明本次检测无效，在检测有效时，IgM抗体检测线以及IgG抗体检测线可以反映用户的诊断结果，是否感染。
在本发明实施例中，所述服务端130可以是具有数据存储以及数据处理功能的服务器，也可以是云服务器，所述服务端用于根据所述检测线结果确定用户的诊断结果。显然，所述服务端可以收集若干个用户上传的检测线结果，并集中对诊断结果进行管理。
作为本发明的一个优选实施例，当检测线传感器为图像传感器，服务端根据上传的包含检测线的图像确定用户的诊断结果的步骤请具体参阅图4及其解释说明。
作为本发明的一个优选实施例，所述服务端130还用于根据用户的诊断结果以及预设的疫情传播模型确定疫情的传播趋势。
本发明实施例提供的一种基于物联网的新冠肺炎疫情防控系统，利用具有快速、简便、稳定性高、廉价、可自我检测等优点的新冠肺炎胶体金试剂盒作为新冠肺炎新冠肺炎检测工具，同时配合安装在试剂盒内部的检测线传感器，能够获取检测线结果，并上传至服务端，服务端可以统计收集各个用户自行检测的检测结果并确定各个用户的诊断结果，一方面实现了新冠肺炎检测的普及，用户可以居家方便快捷的实现检测，另一方面实现了新冠肺炎检测结果的集中管理，对于后续数据的整理、分析、公开、预测具有深远的意义。
如图2所示，为本发明实施例提供的另一种基于物联网的新冠肺炎疫情防控系统，详述如下。
在本发明实施例中，与图1所示出的一种基于物联网的新冠肺炎疫情防控系统的区别在于，还包括身份绑定端210；
所述身份绑定端210，用于获取用户身份信息，并与获取的所述检测线结果建立对应关系，并上传至所述服务端。
在本发明实施例中，所述身份绑定端210通常为移动设备，例如手机、智能手表等等，凡是能够获取到用户的身份信息的设备均可，并进一步利用二维码扫描、人脸识别等技术实现身份的绑定，本发明对具体实现身份绑定的设备以及技术均不作限制。
在本发明实施例中，显然身份绑定端应当与新冠肺炎胶体金试剂盒一一对应，即通常情况下，每一份新冠肺炎胶体金试剂盒都应当对应有一个身份绑定端。
在本发明实施例中，通过设置身份绑定端，并与获取的检测线结果建立绑定关系，能够进一步方便实现对风险用户的监管。
如图3所示，为本发明实施例提供的又一种基于物联网的新冠肺炎疫情防控系统，详述如下。
在本发明实施例中，与图1所示出的一种基于物联网的新冠肺炎疫情防控系统的区别在于，还包括定位端310；
所述定位端310，用于获取用户位置信息，并与获取的所述用户身份信息建立对应关系，并上传至所述服务端。
在本发明实施例中，所述定位端310与所述身份绑定端210相似，通常为移动设备，可以是具有GPS定位功能的任意设备，例如手机、智能手表等等。当然，作为优选，也可以利用同一款设备同时实现身份绑定以及定位，即可以同时为身份绑定端和定位端。
在本发明实施例中，显然定位端也应当与身份绑定端一一对应，即通常情况下，每一个身份绑定端都应当对应有一个定位端。
在本发明实施例中，通过进一步设置定位端，并将获取的用户位置信息与用户身份信息以及检测结果绑定，能够确定新冠肺炎的分布地图，对后续疫情的传播模型的建立具有重要意义。
如图4所示，为本发明实施例提供的确定用户的诊断结果的步骤流程图，具体包括以下步骤：
步骤S402，确定包含检测线的图像中多条检测线的灰度值。
在本发明实施例中，考虑到通过检测线显色与否来判断检测结果，因此，需要确定包含检测线的图像中多条检测线的灰度值。作为优选，考虑到一次检测过程中，仅仅获取单次检测结果存在较大的误差，可以在一次检测过程中采集若干次检测结果，获取多张图像，即获取多条检测线的灰度值数组。
步骤S404，基于预设的图像降噪模型对所述图像中多条检测线的灰度值进行降噪处理。
在本发明实施例中，所述预设的图像降噪模型是预先基于线性回归算法训练生成的。考虑到采集过程中的误差，通过图像降噪模型能够对多条检测线的灰度值进行降噪处理，从而获得更加准确地结果。
步骤S406，根据降噪处理后的多条检测线的灰度值确定用户的诊断结果。
在本发明实施例中，显然基于多条检测线的灰度值与预设的阈值判断就可以确定检测线是否显色，当检测线的灰度值高于预设的阈值，该检测线显色；当检测线的灰度值低于预设的阈值，该检测线未显色。而进一步通过检测线的显色与否判断用户是否感染属于本领域技术人员的常规技术手段，在此不做赘述。
如图5所示，为本发明实施例提供的训练生成图像降噪模型的步骤流程图，具体包括以下步骤：
步骤S502，获取训练样本。
在本发明实施例中，所述训练样本包括多条样本检测线的灰度值以及对应的诊断结果。
步骤S504，构建初始化的图像降噪模型。
在本发明实施例中，所述图像降噪模型包括待确定的误差参数以及阈值参数。所述误差参数服从均值为0的正态分布。
步骤S506，根据所述训练样本对所述图像降噪模型中包括的误差参数以及阈值参数进行训练。
在本发明实施例中，基于线性回归算法并结合训练样本就可以确定图像降噪模型中包括的误差参数以及阈值参数的值，从而训练生成图像降噪模型。
应该理解的是，虽然本发明各实施例的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，各实施例中的至少一部分步骤可以包括多个子步骤或者多个阶段，这些子步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些子步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
以上所述实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本发明的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对本发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干变形和改进，这些都属于本发明的保护范围。因此，本发明专利的保护范围应以所附权利要求为准。
以上所述仅为本发明的较佳实施例而已，并不用以限制本发明，凡在本发明的精神和原则之内所作的任何修改、等同替换和改进等，均应包含在本发明的保护范围之内。

Claims (8)

  1. 一种基于物联网的新冠肺炎疫情防控系统，其特征在于，包括安装有检测线传感器的新冠肺炎胶体金试剂盒以及服务端；
    所述安装有检测线传感器的新冠肺炎胶体金试剂盒，用于对用户进行新冠肺炎检测，并通过所述检测线传感器获取检测线结果，并上传至所述服务端；
    所述服务端，用于根据所述检测线结果确定用户的诊断结果。
  2. 根据权利要求1所述的一种基于物联网的新冠肺炎疫情防控系统，其特征在于，还包括身份绑定端；
    所述身份绑定端，用于获取用户身份信息，并与获取的所述检测线结果建立对应关系，并上传至所述服务端。
  3. 根据权利要求2所述的一种基于物联网的新冠肺炎疫情防控系统，其特征在于，还包括定位端；
    所述定位端，用于获取用户位置信息，并与获取的所述用户身份信息建立对应关系，并上传至所述服务端。
  4. 根据权利要求1所述的一种基于物联网的新冠肺炎疫情防控系统，其特征在于，所述检测线传感器为图像传感器，所述检测线结果为包含检测线的图像。
  5. 根据权利要求4所述的一种基于物联网的新冠肺炎疫情防控系统，其特征在于，所述检测线包括质控检测线、IgM抗体检测线以及IgG抗体检测线。
  6. 根据权利要求4所述的一种基于物联网的新冠肺炎疫情防控系统，其特征在于，所述服务端用于根据所述包含检测线的图像确定用户的诊断结果的步骤具体包括：
    确定包含检测线的图像中多条检测线的灰度值；
    基于预设的图像降噪模型对所述图像中多条检测线的灰度值进行降噪处理；所述预设的图像降噪模型是预先基于线性回归算法训练生成的；
    根据降噪处理后的多条检测线的灰度值确定用户的诊断结果。
  7. 根据权利要求6所述的一种基于物联网的新冠肺炎疫情防控系统，其特征在于，训练生成所述图像降噪模型的步骤具体包括：
    获取训练样本；所述训练样本包括多条样本检测线的灰度值以及对应的诊断结果；
    构建初始化的图像降噪模型，所述图像降噪模型包括待确定的误差参数以及阈值参数；
    根据所述训练样本对所述图像降噪模型中包括的误差参数以及阈值参数进行训练。
  8. 根据权利要求1所述的一种基于物联网的新冠肺炎疫情防控系统，其特征在于，所述服务端还用于根据用户的诊断结果以及预设的疫情传播模型确定疫情的传播趋势。
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