CN111402347A - New crown pneumonia epidemic situation prevention and control system based on Internet of things - Google Patents
New crown pneumonia epidemic situation prevention and control system based on Internet of things Download PDFInfo
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Abstract
The invention is suitable for the technical field of computers, and particularly relates to a new coronary pneumonia epidemic prevention and control system based on the Internet of things, which comprises a new coronary pneumonia colloidal gold kit provided with a detection line sensor and a server side; the new coronary pneumonia colloidal gold kit provided with the detection line sensor is used for detecting new coronary pneumonia of a user, acquiring a detection line result through the detection line sensor and uploading the detection line result to the server; and the server is used for determining the diagnosis result of the user according to the detection line result. The prevention and control system provided by the embodiment of the invention utilizes the new coronary pneumonia colloidal gold kit which has the advantages of rapidness, simplicity, convenience, high stability, low price, self-detection and the like as a new coronary pneumonia detection tool, and is matched with the detection line sensor arranged in the kit, so that the detection line result can be obtained and uploaded to a server side, on one hand, a user can conveniently and rapidly detect the new coronary pneumonia, and on the other hand, the centralized management of the new coronary pneumonia detection result is realized.
Description
Technical Field
The invention belongs to the technical field of computers, and particularly relates to a new coronary pneumonia epidemic situation prevention and control system based on the Internet of things.
Background
The new coronavirus (2019-nCoV) is a new strain of coronavirus which has extremely strong infectivity and can cause fever, cough, dyspnea and even death of an infected person. The incubation period of pneumonia caused by the new coronavirus infection is 1-14 days, and the infected person has obvious infectivity in the whole course of disease, so that early and timely diagnosis can effectively control the infection of the disease and is helpful for giving medical support to the patient in advance to improve the disease outcome.
The current screening for new coronavirus pneumonia requires a comprehensive judgment of the results of clinical symptoms, blood routine, CT examination or nucleic acid examination. CT inspection and nucleic acid inspection all need independent place, expensive equipment and professional personnel, consequently can't satisfy the demand of screening to the crowd on a large scale at present to the testing result needs professional doctor to accomplish, has reduced detection efficiency, can't obtain medical explanation and medical advice in time behind the testing result that obtains, and the result can't be preserved for a long time, can't provide data for subsequent research.
Therefore, the existing new coronavirus pneumonia also has the technical problems that the detection means are difficult to popularize and the detection data are difficult to analyze in a centralized way.
Disclosure of Invention
The embodiment of the invention aims to provide a new coronavirus pneumonia epidemic prevention and control system based on the Internet of things, and aims to solve the technical problems that the existing new coronavirus pneumonia is difficult to popularize in detection means and difficult to intensively analyze detection data.
The embodiment of the invention is realized in such a way that the new coronary pneumonia epidemic prevention and control system based on the Internet of things comprises a new coronary pneumonia colloidal gold kit provided with a detection line sensor and a server side;
the new coronary pneumonia colloidal gold kit provided with the detection line sensor is used for detecting new coronary pneumonia of a user, acquiring a detection line result through the detection line sensor and uploading the detection line result to the server;
and the server is used for determining the diagnosis result of the user according to the detection line result.
As a preferred embodiment of the present invention, the present invention further includes an identity binding end, and the identity binding end is configured to acquire user identity information, establish a corresponding relationship with the acquired detection line result, and upload the result to the server.
As another preferred embodiment of the present invention, the present invention further includes a positioning end, and the positioning end is configured to acquire user location information, establish a corresponding relationship with the acquired user identity information, and upload the user location information to the service end.
As another preferred embodiment of the present invention, the detection line sensor is an image sensor, and the detection line result is an image including a detection line.
As another preferred embodiment of the present invention, the detection lines include a quality control detection line, an IgM antibody detection line, and an IgG antibody detection line.
As another preferred embodiment of the present invention, the step of the server side determining the diagnosis result of the user according to the image containing the detection line specifically includes:
determining gray values of a plurality of detection lines in an image containing the detection lines;
carrying out noise reduction processing on gray values of a plurality of 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;
and determining the diagnosis result of the user according to the gray values of the plurality of detection lines subjected to the noise reduction processing.
As another preferred embodiment of the present invention, the step of training and generating the image denoising model specifically includes:
obtaining a training sample; the training sample comprises gray values of a plurality of sample detection lines and corresponding diagnosis results;
constructing an initialized image noise reduction model, wherein the image noise reduction model comprises an error parameter to be determined and a threshold parameter;
and training the error parameters and the threshold parameters included in the image noise reduction model according to the training samples.
As another preferred embodiment of the present invention, the server is further configured to determine an epidemic propagation trend according to the diagnosis result of the user and a preset epidemic propagation model.
According to the new coronary pneumonia epidemic prevention and control system based on the Internet of things, the new coronary pneumonia colloidal gold kit which has the advantages of being fast, simple, convenient, high in stability, low in price, capable of self-detecting and the like is used as a new coronary pneumonia detection tool, meanwhile, the detection line sensor installed in the kit is matched, detection line results can be obtained and uploaded to the server, the server can collect detection results of self-detection of all users in a statistics mode and determine diagnosis results of all users, on one hand, popularization of new coronary pneumonia detection is achieved, the users can conveniently and fast achieve detection at home, on the other hand, centralized management of the new coronary pneumonia detection results is achieved, and the new coronary pneumonia epidemic prevention and control system has profound significance for sorting, analyzing, disclosing and predicting of subsequent data.
Drawings
Fig. 1 is a schematic structural diagram of a new coronary pneumonia epidemic situation prevention and control system based on the internet of things according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of another new coronary pneumonia epidemic situation prevention and control system based on the internet of things according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of another new coronary pneumonia epidemic situation prevention and control system based on the internet of things according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating steps provided by an embodiment of the present invention for determining a diagnostic result of a user;
fig. 5 is a flowchart of steps for training a generated image noise reduction model according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, a schematic structural diagram of a new coronary pneumonia epidemic prevention and control system based on the internet of things provided by the embodiment of the present invention is described in detail as follows.
In the embodiment of the present invention, the new coronary pneumonia epidemic prevention and control system includes a new coronary pneumonia colloidal gold kit 120 with a detection line sensor 110 and a server 130.
In the embodiment of the present invention, the new coronary pneumonia colloidal gold kit 120 is used for detecting new coronary pneumonia for a user.
In the embodiment of the present invention, the detection line sensor 110 is configured to acquire a detection line result and upload the acquired detection line result to the server.
In a preferred embodiment of the present invention, the detecting line sensor is an image sensor, and the detecting line result is an image including the detecting line. Furthermore, the detection line includes matter accuse detection line, IgM antibody detection line and IgG antibody detection line, and the validity that this detection can be reflected in the matter accuse detection line indicates that this detection is effective when the matter accuse detection line colouration, and when the matter accuse detection line does not colourize, indicates that this detection is invalid, and when detecting effectively, IgM antibody detection line and IgG antibody detection line can reflect user's diagnosis result, whether infect.
In the embodiment of the present invention, the server 130 may be a server having data storage and data processing functions, or may be a cloud server, and the server is configured to determine a diagnosis result of a user according to the detection line result. Obviously, the server can collect the detection line results uploaded by a plurality of users and centrally manage the diagnosis results.
As a preferred embodiment of the present invention, when the detection line sensor is an image sensor, the server determines the diagnosis result of the user according to the uploaded image including the detection line, please refer to fig. 4 and the explanation thereof.
As a preferred embodiment of the present invention, the server 130 is further configured to determine an epidemic propagation trend according to the diagnosis result of the user and a preset epidemic propagation model.
According to the new coronary pneumonia epidemic prevention and control system based on the Internet of things, the new coronary pneumonia colloidal gold kit which has the advantages of being fast, simple, convenient, high in stability, low in price, capable of self-detecting and the like is used as a new coronary pneumonia detection tool, meanwhile, the detection line sensor installed in the kit is matched, detection line results can be obtained and uploaded to the server, the server can collect detection results of self-detection of all users in a statistics mode and determine diagnosis results of all users, on one hand, popularization of new coronary pneumonia detection is achieved, the users can conveniently and fast achieve detection at home, on the other hand, centralized management of the new coronary pneumonia detection results is achieved, and the new coronary pneumonia epidemic prevention and control system has profound significance for sorting, analyzing, disclosing and predicting of subsequent data.
As shown in fig. 2, another new crown pneumonia epidemic situation prevention and control system based on the internet of things provided by the embodiment of the present invention is described in detail as follows.
In the embodiment of the present invention, the system is different from the new crown pneumonia epidemic situation prevention and control system based on the internet of things shown in fig. 1 in that the system further includes an identity binding end 210;
the identity binding end 210 is configured to obtain user identity information, establish a corresponding relationship with the obtained detection line result, and upload the detection line result to the server.
In the embodiment of the present invention, the identity binding end 210 is generally a mobile device, such as a mobile phone, a smart watch, and the like, and any device that can acquire identity information of a user may be used, and further, technologies such as two-dimensional code scanning and face recognition are used to implement identity binding.
In the embodiment of the present invention, it is obvious that the identity binding end should correspond to the new coronary pneumonia colloidal gold kit one to one, that is, in general, each new coronary pneumonia colloidal gold kit should correspond to one identity binding end.
In the embodiment of the invention, the identity binding end is set, and the binding relationship is established with the obtained detection line result, so that the supervision of the risk user can be further conveniently realized.
As shown in fig. 3, a detailed description of another new crown pneumonia epidemic situation prevention and control system based on the internet of things is provided as follows.
In the embodiment of the present invention, the system is different from the new crown pneumonia epidemic situation prevention and control system based on the internet of things shown in fig. 1 in that the system further includes a positioning end 310;
the positioning terminal 310 is configured to obtain user location information, establish a corresponding relationship with the obtained user identity information, and upload the user location information to the server.
In the embodiment of the present invention, the positioning terminal 310, similar to the identity binding terminal 210, is generally a mobile device, and may be any device having a GPS positioning function, such as a mobile phone, a smart watch, and the like. Of course, as an optimization, the identity binding and the positioning can also be simultaneously realized by using the same equipment, that is, the identity binding end and the positioning end can be simultaneously realized.
In the embodiment of the present invention, it is obvious that the positioning end should also correspond to the identity binding end one to one, that is, in general, each identity binding end should correspond to one positioning end.
In the embodiment of the invention, the positioning end is further arranged, and the obtained user position information is bound with the user identity information and the detection result, so that the distribution map of the new coronary pneumonia can be determined, and the method has important significance for establishing a propagation model of a subsequent epidemic situation.
As shown in fig. 4, a flowchart of the steps for determining the diagnosis result of the user according to the embodiment of the present invention specifically includes the following steps:
in step S402, the gray values of a plurality of detection lines in an image containing the detection lines are determined.
In the embodiment of the present invention, the detection result is determined in consideration of whether or not the detection lines are colored, and therefore, it is necessary to determine the gradation values of the plurality of detection lines in the image including the detection lines. Preferably, considering that there is a large error in acquiring only a single detection result in one detection process, the detection results may be acquired several times in one detection process to acquire multiple images, that is, to acquire the gray value arrays of multiple detection lines.
Step S404, noise reduction processing is carried out on the gray values of the detection lines in the image based on a preset image noise reduction model.
In the embodiment of the invention, the preset image noise reduction model is generated by training based on a linear regression algorithm in advance. In consideration of errors in the acquisition process, the image noise reduction model can be used for carrying out noise reduction on the gray values of the multiple detection lines, so that a more accurate result is obtained.
Step S406, determining the diagnosis result of the user according to the gray values of the plurality of detection lines after the noise reduction processing.
In the embodiment of the invention, obviously, whether the detection lines are colored or not can be determined based on the gray values of the detection lines and the preset threshold value, and when the gray values of the detection lines are higher than the preset threshold value, the detection lines are colored; when the gray value of the detection line is lower than a preset threshold value, the detection line is not colored. Whether the user is infected or not is further judged by the color development of the detection line, which belongs to the conventional technical means of the technical personnel in the field and is not described herein again.
As shown in fig. 5, a flowchart of the steps of generating an image noise reduction model for training provided by the embodiment of the present invention specifically includes the following steps:
step S502, obtaining a training sample.
In an embodiment of the present invention, the training samples include gray values of a plurality of sample detection lines and corresponding diagnosis results.
Step S504, an initialized image noise reduction model is built.
In an embodiment of the present invention, the image noise reduction model includes an error parameter to be determined and a threshold parameter. The error parameters follow a normal distribution with a mean value of 0.
Step S506, training the error parameters and the threshold parameters included in the image noise reduction model according to the training samples.
In the embodiment of the invention, the values of the error parameter and the threshold parameter included in the image noise reduction model can be determined based on a linear regression algorithm and in combination with the training sample, so that the image noise reduction model is trained and generated.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (8)
1. A new coronary pneumonia epidemic situation prevention and control system based on the Internet of things is characterized by comprising a new coronary pneumonia colloidal gold kit provided with a detection line sensor and a server side;
the new coronary pneumonia colloidal gold kit provided with the detection line sensor is used for detecting new coronary pneumonia of a user, acquiring a detection line result through the detection line sensor and uploading the detection line result to the server;
and the server is used for determining the diagnosis result of the user according to the detection line result.
2. The system for preventing and controlling the new crown pneumonia epidemic situation based on the internet of things according to claim 1, characterized by further comprising an identity binding end;
and the identity binding end is used for acquiring user identity information, establishing a corresponding relation with the acquired detection line result and uploading the detection line result to the server end.
3. The system for preventing and controlling the new crown pneumonia epidemic situation based on the internet of things according to claim 2, characterized by further comprising a positioning end;
and the positioning end is used for acquiring user position information, establishing a corresponding relation with the acquired user identity information and uploading the user identity information to the server.
4. The system of claim 1, wherein the detection line sensor is an image sensor, and the detection line result is an image containing a detection line.
5. The Internet of things-based new crown pneumonia epidemic prevention and control system of claim 4, wherein the detection lines comprise a quality control detection line, an IgM antibody detection line and an IgG antibody detection line.
6. The system of claim 4, wherein the step of the server side determining the diagnosis result of the user according to the image containing the detection line specifically comprises:
determining gray values of a plurality of detection lines in an image containing the detection lines;
carrying out noise reduction processing on gray values of a plurality of 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;
and determining the diagnosis result of the user according to the gray values of the plurality of detection lines subjected to the noise reduction processing.
7. The system according to claim 6, wherein the step of training and generating the image noise reduction model specifically comprises:
obtaining a training sample; the training sample comprises gray values of a plurality of sample detection lines and corresponding diagnosis results;
constructing an initialized image noise reduction model, wherein the image noise reduction model comprises an error parameter to be determined and a threshold parameter;
and training the error parameters and the threshold parameters included in the image noise reduction model according to the training samples.
8. The system according to claim 1, wherein the server is further configured to determine an epidemic propagation trend according to a diagnosis result of the user and a preset epidemic propagation model.
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| CN202010203131.5A CN111402347A (en) | 2020-03-20 | 2020-03-20 | New crown pneumonia epidemic situation prevention and control system based on Internet of things |
| PCT/CN2020/081698 WO2021184411A1 (en) | 2020-03-20 | 2020-03-27 | Covid-19 pandemic prevention and control system based on internet of things |
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| CN202010203131.5A CN111402347A (en) | 2020-03-20 | 2020-03-20 | New crown pneumonia epidemic situation prevention and control system based on Internet of things |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111816323A (en) * | 2020-07-27 | 2020-10-23 | 广州驰兴通用技术研究有限公司 | Smart city management method and system based on Internet of things |
| CN111999288A (en) * | 2020-08-31 | 2020-11-27 | 北京连接时代科技有限公司 | Pathogen and antibody detection system for mobile terminal |
| CN112164471A (en) * | 2020-09-17 | 2021-01-01 | 吉林大学 | New crown epidemic situation comprehensive evaluation method based on classification regression model |
| WO2022021664A1 (en) * | 2020-07-30 | 2022-02-03 | 山东大学 | Method and system for rapidly detecting covid-19 |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114898892B (en) * | 2021-12-30 | 2024-02-13 | 北京福乐云科技有限公司 | Infection risk control method for basic medical community medical institution based on Internet of things system |
Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103248681A (en) * | 2013-04-27 | 2013-08-14 | 北京福乐云检测科技有限公司 | Colloidal gold method detection cloud platform based on mobile terminal reading |
| CN103245780A (en) * | 2013-04-27 | 2013-08-14 | 北京福乐云检测科技有限公司 | Colloidal gold anti-counterfeiting tracing cloud platform |
| CN103259855A (en) * | 2013-04-27 | 2013-08-21 | 北京福乐云检测科技有限公司 | Cloud platform of infectious disease and chronic disease detecting and monitoring pre-warning system |
| CN105787944A (en) * | 2016-03-04 | 2016-07-20 | 红塔烟草（集团）有限责任公司楚雄卷烟厂 | Leaf laying table handle monitoring device based on industrial camera and monitoring method |
| CN205427956U (en) * | 2016-03-04 | 2016-08-03 | 红塔烟草（集团）有限责任公司楚雄卷烟厂 | Spread leaf platform tobacco leaf pendulum monitoring device based on industry camera |
| CN107121542A (en) * | 2017-04-28 | 2017-09-01 | 厦门大学 | A kind of immunity-chromatography test strip quantitative detection system and method based on mobile phone |
| CN107315990A (en) * | 2017-05-04 | 2017-11-03 | 深圳市美好幸福生活安全系统有限公司 | A kind of pedestrian detection algorithm based on XCS LBP features and cascade AKSVM |
| CN107423736A (en) * | 2017-04-20 | 2017-12-01 | 深圳可思美科技有限公司 | A kind of noise-reduction method and device for detecting skin symptom |
| CN207366573U (en) * | 2017-11-13 | 2018-05-15 | 深圳市博卡生物技术有限公司 | Respiratory pathogen IgM antibody detection kit |
| CN108305247A (en) * | 2018-01-17 | 2018-07-20 | 中南大学湘雅三医院 | A method of tissue hardness is detected based on CT gray value of images |
| CN108475544A (en) * | 2015-11-12 | 2018-08-31 | 卡尤迪医学检验实验室（北京）有限公司 | Method and system for disease surveillance and assessment |
| CN109287589A (en) * | 2018-11-26 | 2019-02-01 | 广东智源信息技术有限公司 | A kind of fast slowdown monitoring mosquito luring lamp of mosquito quantity based on image recognition |
| CN109959750A (en) * | 2019-04-09 | 2019-07-02 | 浙江大学 | Fat-soluble natural products thin layer quantitative image recognition detection method |
| CN110044901A (en) * | 2019-04-30 | 2019-07-23 | 重庆康巨全弘生物科技有限公司 | A kind of reagent card gray analysis system |
| CN110069598A (en) * | 2019-03-12 | 2019-07-30 | 北京睿企信息科技有限公司 | A kind of smart mediation method and system |
| CN110646354A (en) * | 2019-08-28 | 2020-01-03 | 东华大学 | Color testing device and method for cotton fibers |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111378568A (en) * | 2013-09-06 | 2020-07-07 | 赛拉诺斯知识产权有限责任公司 | Systems and methods for detecting infectious diseases |
| US9152761B2 (en) * | 2014-01-10 | 2015-10-06 | Heartflow, Inc. | Systems and methods for identifying medical image acquisition parameters |
| CN109727681A (en) * | 2017-10-30 | 2019-05-07 | 戚本昊 | Disease epidemic situation prevention monitoring survey system |
| CN109752976A (en) * | 2017-11-01 | 2019-05-14 | 杭州沃朴物联科技有限公司 | A kind of chicken cultivation management system for internet of things with antifalsification label |
| CN109596617B (en) * | 2018-12-20 | 2022-05-17 | 广州蚁群信息科技有限公司 | Movable traceable system for detecting echinococcosis |
-
2020
- 2020-03-20 CN CN202010203131.5A patent/CN111402347A/en active Pending
- 2020-03-27 WO PCT/CN2020/081698 patent/WO2021184411A1/en active Application Filing
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103245780A (en) * | 2013-04-27 | 2013-08-14 | 北京福乐云检测科技有限公司 | Colloidal gold anti-counterfeiting tracing cloud platform |
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