Blockchain-based clinic epidemic monitoring method, device, medium and equipment

Abstract

The application discloses a clinic epidemic situation monitoring method and device based on a blockchain, a medium and equipment, and belongs to the technical field of blockchains. The method comprises the following steps: monitoring a doctor in a clinic to obtain a monitoring video of a patient during a treatment process; converting the monitoring video into monitoring audio; detecting whether the patient has symptoms of an epidemic disease according to the monitoring audio; if the patient has symptoms of the epidemic disease, generating epidemic situation monitoring content according to the monitoring video or the monitoring audio; storing clinic information of the clinic, identity information of the patient and the epidemic situation monitoring content in a blockchain connected to the clinic; and sending a notification message to an epidemic prevention center so that the epidemic prevention center monitors the patient according to the notification message. The application automatically monitors the epidemic situation of the clinic, saves manpower, avoids the problems of missing reports, hidden reports and tampering with monitoring videos, and avoids wasting disk space. Sending the notification message to the epidemic prevention center can improve the response speed to the epidemic situation.

Description

Technical Field

[0001] This application relates to the field of blockchain technology, and in particular to a blockchain-based method, apparatus, medium and equipment for epidemic monitoring in clinics. Background Technology

[0002] Due to epidemic prevention and control, the epidemic prevention center needs to monitor in real time whether there are patients with colds and fevers visiting the clinic, so as to monitor the epidemic situation in the clinic.

[0003] In this technology, the epidemic prevention center can install surveillance cameras near the doctor's desk at each clinic. Staff can then monitor the footage in real time. If someone with a cold or fever is detected in the video, the specific clinic can be located, and the patient can be monitored. Each day after get off work, the clinic needs to transmit the day's surveillance video to the epidemic prevention center for future review.

[0004] Arranging for employees to watch surveillance videos is not only a waste of manpower, but also may result in missed or concealed reports due to human error. There is also the possibility of tampering with the content of the surveillance videos, which could affect the accuracy of epidemic monitoring. In addition, saving all the surveillance videos would waste a lot of disk space. Summary of the Invention

[0005] This application provides a blockchain-based method, apparatus, medium, and equipment for epidemic monitoring in clinics. It addresses the problems of wasting manpower, affecting the accuracy of epidemic monitoring, and wasting significant disk space when monitoring the epidemic by manually watching surveillance videos. The technical solution is as follows:

[0006] On the one hand, a blockchain-based method for epidemic monitoring in clinics is provided, the method comprising:

[0007] The process of doctors in a clinic treating patients is monitored, and surveillance video is obtained.

[0008] Convert the surveillance video into surveillance audio;

[0009] The monitoring audio is used to detect whether the patient has symptoms of an infectious disease.

[0010] If the patient seeking medical treatment has symptoms of an infectious disease, then epidemic monitoring content is generated based on the monitoring video or the monitoring audio.

[0011] The clinic information, the patient's identity information, and the epidemic monitoring content are stored in a blockchain connected to the clinic.

[0012] A notification message is sent to the epidemic prevention center so that the epidemic prevention center can monitor the patients seeking medical treatment based on the notification message.

[0013] In one possible implementation, the method further includes: setting keywords based on the symptoms that appear after infection with the disease;

[0014] The step of detecting whether the patient has symptoms of infection based on the monitoring audio includes: detecting whether the monitoring audio contains the keyword; if the monitoring audio contains the keyword, then it is determined that the patient has symptoms of infection.

[0015] In one possible implementation, generating epidemic monitoring content based on the surveillance video includes:

[0016] Obtain the time when the keyword appears in the monitored audio;

[0017] Centered on the time of occurrence, video segments of predetermined duration are extracted from the surveillance video, both forward and backward, to obtain video clips describing the symptoms;

[0018] The video clip can be identified as content for epidemic monitoring, or the hash value of the video clip can be identified as content for epidemic monitoring.

[0019] In one possible implementation, generating epidemic monitoring content based on the monitoring audio includes:

[0020] Obtain the time when the keyword appears in the monitored audio;

[0021] Centered on the time of occurrence, audio segments of predetermined duration are extracted from the monitoring audio, both forward and backward, to obtain audio segments containing descriptions of the symptoms;

[0022] Epidemic monitoring content is generated based on the audio clips.

[0023] In one possible implementation, generating epidemic monitoring content based on the audio segment includes:

[0024] The audio clip was identified as part of epidemic monitoring content, or...

[0025] The hash value of the audio clip is used to determine the content of the epidemic monitoring; or,

[0026] The audio clip is converted into text, and the text is identified as content related to epidemic monitoring.

[0027] In one possible implementation, the method further includes:

[0028] Obtain the prescription issued by the doctor to the patient.

[0029] If a medicine for treating the disease is detected in the prescription, the prescription, the clinic information, and the patient's identity information are stored in the blockchain as evidence.

[0030] A notification message is sent to the epidemic prevention center so that the epidemic prevention center can monitor the patients seeking medical treatment based on the notification message.

[0031] In one possible implementation, the method further includes:

[0032] Obtain the biometric information of the patients and the user codes obtained through big data analysis;

[0033] If it is determined from the biometric information and the user code that the patient has symptoms of an infectious disease, then the biometric information, the user code, the clinic information, and the patient's identity information are stored in the blockchain as evidence.

[0034] A notification message is sent to the epidemic prevention center so that the epidemic prevention center can monitor the patients seeking medical treatment based on the notification message.

[0035] On the one hand, a blockchain-based epidemic monitoring device for clinics is provided, the device comprising:

[0036] The monitoring module is used to monitor the process of doctors in the clinic receiving patients and obtain monitoring video.

[0037] A conversion module is used to convert the surveillance video into surveillance audio;

[0038] The detection module is used to detect whether the patient has symptoms of infectious disease based on the monitoring audio.

[0039] The generation module is used to generate epidemic monitoring content based on the monitoring video or the monitoring audio if the patient has symptoms of infection.

[0040] The evidence storage module is used to store the clinic information, the patient's identity information, and the epidemic monitoring content in a blockchain connected to the clinic.

[0041] The notification module is used to send notification messages to the epidemic prevention center so that the epidemic prevention center can monitor the patients seeking medical treatment based on the notification messages.

[0042] On the one hand, a computer-readable storage medium is provided, wherein at least one instruction is stored in the storage medium, the at least one instruction being loaded and executed by a processor to implement the blockchain-based clinic epidemic monitoring method described above.

[0043] On one hand, a computer device is provided, the computer device including a processor and a memory, the memory storing at least one instruction, the instruction being loaded and executed by the processor to implement the blockchain-based clinic epidemic monitoring method as described above.

[0044] The beneficial effects of the technical solutions provided in this application include at least the following:

[0045] By converting surveillance video into audio, when a patient is detected exhibiting symptoms of infectious disease, epidemic monitoring content is generated based on the video or audio. The clinic's information, the patient's identity information, and the epidemic monitoring content are stored on a blockchain connected to the clinic. This enables automated monitoring of the epidemic situation at the clinic, saving manpower, preventing underreporting, concealment, and tampering with surveillance video, and avoiding wasted disk space. Furthermore, by sending notification messages to the epidemic prevention center, the center can monitor patients based on these notifications, improving the speed of epidemic response.

[0046] By storing video or audio clips on the blockchain, or by storing the hash values ​​of video or audio clips on the blockchain, or by converting audio clips into text and storing the text on the blockchain, disk space can be further avoided compared to storing the entire day's surveillance video on the blockchain. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a flowchart of a blockchain-based clinic epidemic monitoring method provided in one embodiment of this application;

[0049] Figure 2 This is a flowchart of a blockchain-based clinic epidemic monitoring method provided in one embodiment of this application;

[0050] Figure 3 This is a structural block diagram of a blockchain-based clinic epidemic monitoring device provided in one embodiment of this application;

[0051] Figure 4 This is a structural block diagram of a blockchain-based clinic epidemic monitoring device provided in one embodiment of this application. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0053] Please refer to Figure 1 This document illustrates a flowchart of a blockchain-based epidemic monitoring method for clinics, according to an embodiment of this application. This blockchain-based epidemic monitoring method for clinics may include:

[0054] Step 101: Monitor the doctor's process of seeing patients in the clinic and obtain the monitoring video.

[0055] In this embodiment, a surveillance camera can be installed in the doctor's office or near the doctor's desk. This camera records the doctor's consultation process with patients in real time and sends the resulting video stream to a computer. The computer can extract a fixed-length video stream from the real-time video stream to obtain a single surveillance video; alternatively, the computer can extract a video stream of a single patient from the live video stream to obtain a separate surveillance video.

[0056] Step 102: Convert the surveillance video into surveillance audio.

[0057] Computer equipment can extract audio from surveillance videos to obtain surveillance audio.

[0058] Step 103: Detect whether the patient exhibits symptoms of infectious disease based on the monitoring audio. During doctor's consultations, patients are typically asked to describe their symptoms, which will then appear in the doctor-patient conversation. Based on this, keywords can be pre-defined according to the symptoms of infectious disease infection, and the monitoring audio can be checked for the presence of these keywords. If the monitoring audio contains the keywords, the patient is confirmed to have symptoms of infectious disease infection; if it does not contain the keywords, the patient is confirmed not to have symptoms of infectious disease infection. At least one keyword can be included, and its content must be related to a specific infectious disease.

[0059] When detecting whether an audio segment contains keywords, one approach is to first convert the audio segment into text and then detect whether the text contains keywords; another approach is to obtain the speech of the keywords and then detect whether the audio segment contains that speech.

[0060] Step 104: If the patient seeking medical treatment has symptoms of an infectious disease, generate epidemic monitoring content based on the monitoring video or audio.

[0061] To avoid wasting disk space by uploading the complete surveillance video of the day, this embodiment can generate epidemic monitoring content based on the surveillance video or surveillance audio.

[0062] (1) When generating epidemic monitoring content based on surveillance video, the computer device can obtain the time when the keyword appears in the surveillance audio; take the time of appearance as the center, cut out a video of a predetermined duration forward and backward in the surveillance video to obtain a video segment describing the symptoms; determine the video segment as epidemic monitoring content, or determine the hash value of the video segment as epidemic monitoring content.

[0063] The scheduled duration can be pre-set and can be changed. For example, if the scheduled duration is 5 minutes, the computer device can extract video clips 10 minutes before and after the keywords.

[0064] In this embodiment, the computer device can directly store video clips on the blockchain. To further save on-chain disk space, the computer device can store video clips locally only, calculate the hash value of the video clips, and store the hash value on the blockchain.

[0065] (2) When generating epidemic monitoring content based on monitoring audio, the computer device can obtain the time when the keywords appear in the monitoring audio; take the time of appearance as the center, extract audio segments of predetermined duration forward and backward in the monitoring audio to obtain audio segments containing descriptions of symptoms; and generate epidemic monitoring content based on the audio segments.

[0066] The scheduled duration can be pre-set and can be changed. For example, if the scheduled duration is 8 minutes, the computer device can extract audio segments 16 minutes before and after the keywords.

[0067] Specifically, generating epidemic monitoring content based on audio clips can include: identifying the audio clip as epidemic monitoring content, or identifying the hash value of the audio clip as epidemic monitoring content; or converting the audio clip into text and identifying the text as epidemic monitoring content.

[0068] In this embodiment, the computer device can directly store audio segments on the blockchain. To further save on-chain disk space, the computer device can store the audio segments locally and calculate their hash values, then store the hash values ​​on the blockchain; alternatively, the computer device can store the converted text of the audio segments on the blockchain.

[0069] Step 105: Store the clinic's information, the patients' identity information, and the epidemic monitoring data in the blockchain connected to the clinic.

[0070] Clinic information can include the clinic's name, location, etc.

[0071] The patient's identity information can include name, ID card information, phone number, etc., so that the epidemic prevention center can contact the patient.

[0072] The epidemic monitoring content is the information generated in step 104, which can be video clips, audio clips, hash values, or text.

[0073] Step 106: Send a notification message to the epidemic prevention center so that the epidemic prevention center can monitor the patients seeking medical treatment based on the notification message.

[0074] Computer devices can send instant messaging messages or emails to the epidemic prevention center. In this embodiment, the specific form of the notification message is not limited.

[0075] Upon receiving a notification message, the epidemic prevention center can obtain clinic information and identity information from the message. If the on-chain evidence is a video or audio clip, the center can retrieve it based on the clinic and identity information. After reviewing the clip and confirming the patient's symptoms, the center can monitor the patient. If the on-chain evidence is a hash value, the center can obtain the video or audio clip from a computer, calculate its hash value, and compare the result with the hash value on the chain. If they match, the local video or audio clip has not been tampered with. After reviewing the clip and confirming the patient's symptoms, the center can monitor the patient. If the on-chain evidence is text, the center can obtain the audio clip from a computer, extract the text, and compare it with the text on the chain. If they match, the local audio clip has not been tampered with. After listening to the audio clip and confirming the patient's symptoms, the center can monitor the patient.

[0076] In summary, the blockchain-based clinic epidemic monitoring method provided in this application converts surveillance video into audio. When a patient is detected to have symptoms of infectious disease, epidemic monitoring content is generated based on the surveillance video or audio. The clinic's information, the patient's identity information, and the epidemic monitoring content are stored in a blockchain connected to the clinic. This enables automatic monitoring of the epidemic in the clinic, saving manpower, avoiding underreporting, concealment, and tampering with surveillance video, and preventing wasted disk space. Furthermore, by sending notification messages to the epidemic prevention center, enabling the center to monitor patients based on these messages, the response speed to the epidemic is improved.

[0077] By storing video or audio clips on the blockchain, or by storing the hash values ​​of video or audio clips on the blockchain, or by converting audio clips into text and storing the text on the blockchain, disk space can be further avoided compared to storing the entire day's surveillance video on the blockchain.

[0078] Please refer to Figure 2This document illustrates a flowchart of a blockchain-based epidemic monitoring method for clinics, according to an embodiment of this application. This blockchain-based epidemic monitoring method for clinics may include:

[0079] Step 201: Obtain the patient's biometric information and user code obtained through big data analysis; if the patient is found to have symptoms of infectious disease based on the biometric information and user code, store the biometric information, user code, clinic information, and patient's identity information in the blockchain; send a notification message to the epidemic prevention center so that the epidemic prevention center can monitor the patient based on the notification message.

[0080] Biometric information can include body temperature information, human body test reports, etc.

[0081] Computer equipment can detect biometric information and user codes, and the specific detection methods can be set according to the specific epidemic.

[0082] If the patient is determined to have no symptoms of infectious disease based on biometric information and user code, the patient is allowed to enter the clinic for treatment, and step 202 is executed.

[0083] If a patient is determined to have symptoms of an infectious disease based on biometric information and a user code, the computer device stores the biometric information, user code, clinic information, and patient identity information on a blockchain. A notification message is then sent to the epidemic prevention center, enabling the center to monitor the patient. The clinic information may include the clinic name and location. The patient's identity information may include their name, ID card information, and phone number, allowing the epidemic prevention center to contact the patient.

[0084] After receiving the notification message, the epidemic prevention center can obtain clinic information and identity information from the notification message, and then obtain biometric information and user code from the blockchain based on the clinic information and identity information. After determining that the patient has symptoms of infection based on the biometric information and user code, the center can monitor the patient.

[0085] Step 202: Monitor the doctor's consultation process with patients in the clinic to obtain surveillance video.

[0086] Step 203: Convert the surveillance video into surveillance audio.

[0087] Step 204: Detect whether the patient has symptoms of infection based on the monitoring audio.

[0088] Step 205: If the patient seeking medical treatment has symptoms of infection with the epidemic, generate epidemic monitoring content based on the monitoring video or monitoring audio.

[0089] Step 206: Store the clinic's information, the patients' identity information, and the epidemic monitoring data in the blockchain connected to the clinic.

[0090] Step 207: Send a notification message to the epidemic prevention center so that the epidemic prevention center can monitor the patients seeking medical treatment based on the notification message.

[0091] The implementation process of steps 202-207 is the same as that of steps 101-106, and will not be described again here.

[0092] Step 208: Obtain the prescription issued by the doctor to the patient; if a drug for treating the epidemic is detected in the prescription, store the prescription, clinic information and patient identity information in the blockchain; send a notification message to the epidemic prevention center so that the epidemic prevention center can monitor the patient according to the notification message.

[0093] Computer equipment can analyze prescriptions, and the specific analysis methods can be set according to the specific epidemic situation.

[0094] If the prescription determines that the patient does not have symptoms of an infectious disease, the process ends.

[0095] If a patient is determined to have symptoms of an infectious disease based on a prescription, the prescription, clinic information, and patient's identity information are stored on a blockchain. A notification message is then sent to the epidemic prevention center so that the center can monitor the patient. The clinic information can include the clinic name and location. The patient's identity information can include their name, ID card information, and phone number, enabling the epidemic prevention center to contact the patient.

[0096] After receiving the notification message, the epidemic prevention center can obtain clinic information and identity information from the notification message, retrieve the prescription from the blockchain based on the clinic information and identity information, and monitor the patient after confirming that the patient has symptoms of infection based on the prescription.

[0097] In summary, the blockchain-based clinic epidemic monitoring method provided in this application converts surveillance video into audio. When a patient is detected to have symptoms of infectious disease, epidemic monitoring content is generated based on the surveillance video or audio. The clinic's information, the patient's identity information, and the epidemic monitoring content are stored in a blockchain connected to the clinic. This enables automatic monitoring of the epidemic in the clinic, saving manpower, avoiding underreporting, concealment, and tampering with surveillance video, and preventing wasted disk space. Furthermore, by sending notification messages to the epidemic prevention center, enabling the center to monitor patients based on these messages, the response speed to the epidemic is improved.

[0098] By storing video or audio clips on the blockchain, or by storing the hash values ​​of video or audio clips on the blockchain, or by converting audio clips into text and storing the text on the blockchain, disk space can be further avoided compared to storing the entire day's surveillance video on the blockchain.

[0099] Please refer to Figure 3 The diagram illustrates a structural block diagram of a blockchain-based clinic epidemic monitoring device according to an embodiment of this application. The blockchain-based clinic epidemic monitoring device includes:

[0100] The monitoring module 310 is used to monitor the process of doctors in the clinic receiving patients and obtain monitoring video.

[0101] Conversion module 320 is used to convert surveillance video into surveillance audio;

[0102] The detection module 330 is used to detect symptoms of infectious diseases in patients visiting the hospital based on the monitoring audio.

[0103] The generation module 340 is used to generate epidemic monitoring content based on monitoring video or monitoring audio if the patient has symptoms of infection.

[0104] The evidence storage module 350 is used to store clinic information, patient identity information, and epidemic monitoring content in a blockchain connected to the clinic.

[0105] The notification module 360 ​​is used to send notification messages to the epidemic prevention center so that the center can monitor patients based on the notification messages.

[0106] Please refer to Figure 4 In an optional embodiment, the device further includes:

[0107] Module 370 is used to set keywords based on the symptoms that appear after infection with the disease.

[0108] The detection module 330 is also used to detect whether the monitoring audio contains keywords; if the monitoring audio contains keywords, it is determined that the patient has symptoms of infection.

[0109] In an optional embodiment, the generation module 340 is further configured to:

[0110] Obtain the time when keywords appear in the monitored audio;

[0111] Centered on the moment of occurrence, video clips of predetermined duration are extracted from the surveillance video, both forward and backward, to obtain video segments describing the symptoms;

[0112] The video clip can be identified as content for epidemic monitoring, or the hash value of the video clip can be identified as content for epidemic monitoring.

[0113] In an optional embodiment, the generation module 340 is further configured to:

[0114] Obtain the time when keywords appear in the monitored audio;

[0115] Centered on the moment of occurrence, audio segments of predetermined duration are extracted from the monitoring audio, both forward and backward, to obtain audio segments containing descriptions of symptoms;

[0116] Epidemic monitoring content is generated based on audio clips.

[0117] In an optional embodiment, the generation module 340 is further configured to:

[0118] The audio clip was identified as part of the epidemic monitoring content, or...

[0119] The hash value of the audio clip is used to determine the content of the epidemic monitoring; or,

[0120] The audio clips were converted into text, and the text was then identified as content for epidemic monitoring.

[0121] In an optional embodiment, the device further includes:

[0122] Module 380 is used to retrieve prescriptions issued by doctors to patients.

[0123] The evidence storage module 350 is also used to store the prescription, clinic information and patient identity information in the blockchain if a drug for treating an epidemic is detected in the prescription.

[0124] The notification module 360 ​​is also used to send notification messages to the epidemic prevention center so that the epidemic prevention center can monitor patients based on the notification messages.

[0125] In an optional embodiment, the acquisition module 380 is further configured to acquire the biometric information of the patient and the user code obtained through big data analysis.

[0126] The evidence storage module 350 is also used to store the biometric information, user code, clinic information and patient identity information in the blockchain if it is determined that the patient has symptoms of infectious disease based on biometric information and user code.

[0127] The notification module 360 ​​is also used to send notification messages to the epidemic prevention center so that the epidemic prevention center can monitor patients based on the notification messages.

[0128] In summary, the blockchain-based clinic epidemic monitoring device provided in this application converts surveillance video into audio. When a patient is detected to have symptoms of infectious disease, epidemic monitoring content is generated based on the surveillance video or audio. The clinic's information, the patient's identity information, and the epidemic monitoring content are stored in a blockchain connected to the clinic. This enables automatic monitoring of the clinic's epidemic situation, saving manpower, avoiding underreporting, concealment, and tampering with surveillance video, and preventing wasted disk space. Furthermore, by sending notification messages to the epidemic prevention center, enabling the center to monitor patients based on these messages, the response speed to the epidemic is improved.

[0129] By storing video or audio clips on the blockchain, or by storing the hash values ​​of video or audio clips on the blockchain, or by converting audio clips into text and storing the text on the blockchain, disk space can be further avoided compared to storing the entire day's surveillance video on the blockchain.

[0130] One embodiment of this application provides a computer-readable storage medium storing at least one instruction, which is loaded and executed by a processor to implement the blockchain-based clinic epidemic monitoring method described above.

[0131] One embodiment of this application provides a computer device including a processor and a memory, wherein the memory stores at least one instruction, which is loaded and executed by the processor to implement the blockchain-based clinic epidemic monitoring method described above.

[0132] It should be noted that the above-described embodiment of the blockchain-based clinic epidemic monitoring device is only an example of the division of the functional modules described above when performing blockchain-based clinic epidemic monitoring. In practical applications, the functions described above can be assigned to different functional modules as needed, that is, the internal structure of the blockchain-based clinic epidemic monitoring device can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the blockchain-based clinic epidemic monitoring device and the blockchain-based clinic epidemic monitoring method embodiment provided above belong to the same concept, and their specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0133] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0134] The above description is not intended to limit the embodiments of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of the embodiments of this application.

Claims

1. A blockchain-based method for monitoring an epidemic in a clinic, characterized in that, The method comprises: monitoring a doctor in a clinic to receive a patient, obtaining a monitoring video; converting the monitoring video into monitoring audio; detecting whether the patient has symptoms of an infectious disease according to the monitoring audio; if the patient has symptoms of an infectious disease, generating epidemic monitoring content according to the monitoring video or the monitoring audio; storing clinic information of the clinic, identity information of the patient, and the epidemic monitoring content in a blockchain connected with the clinic; sending a notification message to an epidemic prevention center to enable the epidemic prevention center to monitor the patient according to the notification message; The method further comprises: setting a keyword according to symptoms appearing after infection with an infectious disease, the keyword contains at least one, and its content is related to a specific infectious disease; The method further comprises: detecting whether the keyword is contained in the monitoring audio; if the keyword is contained in the monitoring audio, it is determined that the patient has symptoms of an infectious disease; The method further comprises: obtaining the time when the keyword appears in the monitoring audio; taking the time as the center, respectively cutting a predetermined length of video forward and backward in the monitoring video to obtain a video segment describing the symptoms; and determining the video segment as the epidemic monitoring content; The method further comprises: obtaining the time when the keyword appears in the monitoring audio; taking the time as the center, respectively cutting a predetermined length of audio forward and backward in the monitoring audio to obtain an audio segment containing a description of the symptoms; and determining the audio segment as the epidemic monitoring content.

2. The blockchain-based method for monitoring an epidemic in a clinic according to claim 1, wherein, The method comprises: determining the hash value of the video segment as the epidemic monitoring content.

3. The blockchain-based method for monitoring an epidemic in a clinic according to claim 1, wherein, The method further comprises: determining the hash value of the audio segment as the epidemic monitoring content; or converting the audio segment into text, and determining the text as the epidemic monitoring content.

4. The blockchain-based method for monitoring an epidemic in a clinic according to any one of claims 1 to 3, wherein, The method further comprises: obtaining a prescription issued by the doctor to the patient; if a drug for treating the infectious disease is detected in the prescription, storing the prescription, clinic information of the clinic, and identity information of the patient in the blockchain; sending a notification message to an epidemic prevention center to enable the epidemic prevention center to monitor the patient according to the notification message.

5. The blockchain-based method for monitoring an epidemic in a clinic according to any one of claims 1 to 3, wherein, The method further comprises: obtaining biological information of the patient and a user code obtained through big data analysis; if it is determined that the patient has symptoms of an infectious disease according to the biological information and the user code, storing the biological information, the user code, clinic information of the clinic, and identity information of the patient in the blockchain; sending a notification message to an epidemic prevention center to enable the epidemic prevention center to monitor the patient according to the notification message. 6.A blockchain-based clinic epidemic monitoring device, characterized in that, The device comprises: a monitoring module for monitoring a doctor in a clinic to receive a patient, obtaining a monitoring video; a conversion module for converting the monitoring video into monitoring audio; detecting, by a detection module, whether the patient has symptoms of an infectious disease according to the monitoring audio; generating, by a generation module, epidemic monitoring content according to the monitoring video or the monitoring audio if the patient has symptoms of an infectious disease; storing, by a storage module, clinic information of the clinic, identity information of the patient, and the epidemic monitoring content in a blockchain connected to the clinic; sending, by a notification module, a notification message to an epidemic prevention center to enable the epidemic prevention center to monitor the patient according to the notification message; The device further comprises a setting module for setting keywords according to symptoms that appear after infection with an infectious disease, the keywords comprising at least one and being related to specific infectious diseases in content; The detection module is further configured to detect whether the keywords are included in the monitoring audio, and determine that the patient has symptoms of an infectious disease if the keywords are included in the monitoring audio. The generation module is further configured to obtain a time of appearance of the keywords in the monitoring audio, obtain video segments describing the symptoms by respectively cutting forward and backward a predetermined length of video in the monitoring video with the time of appearance as the center, and determine the video segments as the epidemic monitoring content. The generation module is further configured to obtain a time of appearance of the keywords in the monitoring audio, obtain audio segments describing the symptoms by respectively cutting forward and backward a predetermined length of audio in the monitoring audio with the time of appearance as the center, and determine the audio segments as the epidemic monitoring content.

7. A computer-readable storage medium, characterized in that, The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the epidemic monitoring method of the clinic based on the blockchain as claimed in any one of claims 1 to 5.

8. A computer device, comprising: The computer device comprises a processor and a memory, and the memory stores at least one instruction, which is loaded and executed by the processor to implement the epidemic monitoring method of the clinic based on the blockchain as claimed in any one of claims 1 to 5.

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