A hospital calling system based on face recognition

Abstract

The present invention discloses a hospital calling system based on face recognition, and relates to the technical field of face recognition. The present invention comprises: a hospital reservation information acquisition module, a patient face punching module, a department calling adjustment unit and a local database. The present invention verifies the face information of each patient to ensure that the patient who sees a doctor offline and the patient who registers online are the same person, thereby reducing the secondary sale of reserved medical resources. The face recognition technology is used to monitor in real time the sorted signed-in patients of each department of the hospital. When calling the signed-in patients, if the signed-in patients do not see a doctor within the initial waiting time, the additional allowed waiting time of the signed-in patients is analyzed according to the time point and location of the patients in the hospital, thereby improving the utilization efficiency of medical resources. At the same time, a re-calling service is provided for these patients who miss the calling, and they are intelligently sorted, thereby ensuring the patient's satisfaction and improving the trust of the hospital.

Description

Technical Field

[0001] The present invention relates to the technical field of face recognition, and in particular to a hospital calling system based on face recognition. Background Art

[0002] After patients register for medical treatment in a hospital, due to the limited capacity of the hospital, when there are a large number of patients, they often have to wait for a long time for their number to be called. It is also easy for them to miss the call because they leave temporarily or do not hear the call, and have to queue again. Facial recognition technology can accurately locate the position of each patient in the hospital, so as to better coordinate the hospital's calling service. Therefore, it is necessary to add facial recognition technology to the hospital's calling service.

[0003] The prior art, such as the invention patent application with announcement number: CN112184980B, discloses a hospital intelligent calling system, which includes: a server and a calling module; the server is used to generate a queue number; the server is also used to receive a calling instruction; the calling module is used to obtain and play the calling number from the server; and also includes a verification module, which is used to collect the patient's queue number; the verification module is also used to play a personal information input prompt, and the server is used to determine the patient's queue number according to the queue list and the patient's personal information. The technical solution of this invention can effectively verify the patient's identity.

[0004] Prior art, such as the invention patent application with announcement number: CN118379824A, discloses a multi-scenario intelligent queuing and calling system based on the Internet of Things, and the system includes: This invention can apply the Internet of Things technology to the queuing and calling system, realize real-time data sharing and interaction in various business scenarios, break the information island phenomenon, and use the Internet of Things and Internet technology to support remote services and management, facilitate enterprises to operate and maintain across regions and time, and make intelligent predictions on patients' arrival time, service needs, etc., to achieve more accurate scheduling and queuing optimization, improve service efficiency and patient satisfaction, reduce patient waiting time, and provide strong support for business improvement and innovation of enterprises, helping enterprises make more scientific decisions.

[0005] It can be seen from the above scheme that the current hospital calling system lacks certain attention to adjusting the calling time for each patient according to the relevant data such as the check-in time of each patient. After each patient punches in and takes a number in the hospital department, they generally need to wait for a long time. When some patients are called, sometimes these patients cannot respond to the call due to urgent matters such as going to the toilet. The traditional calling system calls numbers through a fixed time, which is prone to the problem of long-term calling but no one answering, resulting in the problem that the doctor is idle, but the outside patients cannot come in for treatment, reducing the efficiency of medical resource utilization. At the same time, there is a lack of attention to the re-calling service for patients who have not seen the doctor in time. Sometimes some patients will return to the hospital department after missing the call. If they are queued in front of all patients at this time, it is easy to cause some patients who have been waiting for a long time to become irritable, thereby increasing the patient's dissatisfaction and reducing the trust of the hospital. Summary of the invention

[0006] The purpose of the present invention is to provide a hospital calling system based on face recognition, which solves the problems existing in the background technology.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solution: The present invention provides a hospital call number system based on face recognition, including: a hospital appointment information acquisition module, used to obtain the department for each patient's appointment.

[0008] The patient face check-in module is used to screen each signed-in patient and obtain the check-in time of each signed-in patient. According to the department of each patient's appointment, the department of each signed-in patient's appointment is extracted, and the signed-in patients of each department of the hospital are mapped. The signed-in patients of each department of the hospital are sorted according to the order of the check-in time points from front to back, so as to obtain the sorted signed-in patients of each department of the hospital.

[0009] The department call adjustment unit is used to screen the patients to be analyzed in each department of the hospital, and analyze the allowed waiting time for each patient to be analyzed in each department of the hospital, so as to screen the patients who have not been treated in each department of the hospital and provide re-calling services for them.

[0010] The department calling number adjustment unit includes: a queuing calling number module and a re-calling number module.

[0011] The queuing and calling module is used to screen the patients to be analyzed in each department of the hospital and analyze the allowed waiting time of the patients to be analyzed in each department of the hospital.

[0012] The re-calling module is used to screen the patients who have not visited the hospital, and based on them, screen the inquiring patients in the hospital, and screen the re-called patients in the hospital, evaluate the patients who have not visited the hospital after the re-called patients return, analyze the ranking position of the re-called patients in the hospital, and send the ranking position of the re-called patients in the hospital to the corresponding re-called patients.

[0013] The beneficial effects of the present invention are as follows: (1) The hospital appointment information acquisition module of the present invention is used to obtain the appointment information of each patient in the hospital, thereby facilitating subsequent analysis.

[0014] (2) The patient face check-in module of the present invention verifies the facial information of each patient to ensure that the patient who sees the doctor offline is the same person as the patient who registers online, thereby reducing the secondary sale of scheduled medical resources. At the same time, each patient is sorted according to the check-in time point to ensure that each patient queues for treatment in a fair and orderly manner.

[0015] (3) The department call adjustment unit of the present invention uses facial recognition technology to monitor in real time the sorted signed-in patients of various departments of the hospital, obtain the time and location of their appearance in the hospital, and when calling the signed-in patients, if the signed-in patients have not been treated within the initial waiting time, the additional allowed waiting time of the signed-in patients is analyzed according to the time and location of their appearance in the hospital, thereby reducing the incidence of the problem that doctors are idle but outside patients cannot come in for treatment, improving the efficiency of the use of medical resources, and at the same time, re-calling services are provided for these patients who have missed the call, and they are intelligently arranged into the sorted signed-in patients who have not been treated in various departments of the hospital after the corresponding re-called patients return, thereby ensuring patient satisfaction and improving the trust of the hospital. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a schematic diagram of the system module of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Reference Figure 1 As shown, the present invention provides a hospital calling number system based on face recognition, including: a hospital appointment information acquisition module, a patient face punching module, a department calling number adjustment unit and a local database.

[0020] It should be noted that the hospital appointment information acquisition module is connected to the patient face punching module, the patient face punching module is connected to the department call number adjustment unit, and the local database is connected to the department call number adjustment unit.

[0021] It should also be noted that the local database is used to store the end time of the working time period of the department for each target patient's appointment, the initial waiting time of the target department, the images taken by the hospital's cameras, the locations of the consultation entrances of each department of the hospital, the increase in the allowable waiting time corresponding to the unit distance of each department of the hospital, the allowable waiting time adjustment value corresponding to each historical default coefficient interval, the reference allowable waiting time of each department of the hospital, the check-in status of each historical appointment of each in-hospital patient in each department of the hospital, the historical default coefficient adjustment value corresponding to each check-in status, the estimated departure location of the hospital, the lower limit and upper limit of the allowable waiting time for unidentified patients in the hospital, the allowable waiting time decrease value corresponding to the unit waiting time of each department of the hospital, the appropriate waiting time, and the waiting annoyance coefficient threshold.

[0022] The hospital appointment information acquisition module is used to obtain the department for each patient's appointment.

[0023] In a specific embodiment, the department booked by each patient is obtained by a specific method as follows: after each patient makes an appointment on a hospital appointment terminal by face entry, the department booked by each patient is obtained through the hospital appointment terminal.

[0024] The hospital appointment information acquisition module of the present invention is used to obtain the appointment information of each patient in the hospital, so as to facilitate subsequent analysis.

[0025] The patient face punch-in module is used to screen each signed-in patient and obtain the sign-in time point of each signed-in patient, extract the department of each signed-in patient's appointment based on the department of each patient's appointment, map each signed-in patient of each department of the hospital, and sort each signed-in patient of each department of the hospital according to the order of the sign-in time point from front to back, so as to obtain the sorted signed-in patients of each department of the hospital.

[0026] In a specific embodiment, the check-in time of each signed-in patient is obtained by a specific method: the check-in time of each signed-in patient is obtained through a hospital appointment clock-in terminal.

[0027] In a specific embodiment, the specific analysis method for screening each signed-in patient is as follows: if a patient signs in with his / her face at a hospital appointment clock-in terminal, the patient is marked as a target patient, thereby screening each target patient, obtaining the appointment face image, sign-in face image and sign-in time point of each target patient, performing image comparison, and determining whether the target patient himself / herself has signed in. If so, the end time point of the working time period of the department for which each target patient has made an appointment is obtained. If the sign-in time point of a target patient is after the end time point of the working time period of the department for which the appointment has been made, a timeout reminder is given to the target patient. Otherwise, the target patient is marked as a signed-in patient, thereby screening each signed-in patient.

[0028] In a specific embodiment, the method for obtaining the appointment facial image, check-in facial image and check-in time point of each target patient is as follows: obtaining the appointment facial image of each target patient through a hospital appointment terminal, and obtaining the check-in facial image and check-in time point of each target patient through a hospital appointment punch-in terminal.

[0029] In a specific embodiment, the determination of whether each target patient has signed in himself is made by using existing image recognition technology and combining the appointment face image and sign-in face image of each target patient to determine whether each target patient has signed in himself.

[0030] In a specific embodiment, the end time point of the working time period of the department with which each target patient has made an appointment is obtained by a specific method of obtaining the end time point of the working time period of the department with which each target patient has made an appointment from a local database.

[0031] The patient face punch-in module of the present invention verifies the facial information of each patient to ensure that the patient who sees the doctor offline and the patient who registers online are the same person, thereby reducing the secondary sale of scheduled medical resources. At the same time, each patient is sorted according to the check-in time point to ensure that each patient queues for medical treatment in a fair and orderly manner.

[0032] The department call adjustment unit is used to screen the patients to be analyzed in each department of the hospital, and analyze the allowed waiting time for each patient to be analyzed in each department of the hospital, so as to screen the patients who have not been treated in each department of the hospital and provide re-calling service for them.

[0033] The department call adjustment unit of the present invention monitors the sorted signed-in patients of various departments of the hospital in real time through face recognition technology, obtains the time and location of their appearance in the hospital, and when calling the signed-in patients, if the signed-in patients have not seen a doctor within the initial waiting time, the additional allowed waiting time of the signed-in patients is analyzed according to the time and location of their appearance in the hospital, thereby reducing the occurrence rate of the problem that doctors are idle but outside patients cannot come in for treatment, improving the efficiency of the use of medical resources, and at the same time, providing a re-calling service for these patients who have missed the call, and intelligently arranging them into the sorted signed-in patients who have not seen a doctor in various departments of the hospital after the corresponding re-called patients return, thereby ensuring patient satisfaction and improving the trust of the hospital.

[0034] In a specific embodiment of the present invention, the department calling number adjustment unit includes: a queuing calling number module and a re-calling number module.

[0035] The queuing and calling module is used to screen the patients to be analyzed in each department of the hospital and analyze the allowed waiting time of the patients to be analyzed in each department of the hospital.

[0036] The re-calling module is used to screen the patients who have not visited the hospital, and based on them, screen the inquiring patients in the hospital, and screen the re-called patients in the hospital, evaluate the patients who have not visited the hospital after the re-called patients return, analyze the ranking position of the re-called patients in the hospital, and send the ranking position of the re-called patients in the hospital to the corresponding re-called patients.

[0037] In a specific embodiment, the specific analysis method for screening the patients to be analyzed in each department of the hospital is as follows: during the working hours of each department of the hospital, the sorted signed-in patients in each department of the hospital are called in sequence, a department is randomly selected as the target department, and the initial waiting time of the target department is obtained from the local database. If, after calling the number of a signed-in patient in the target department of the hospital, the signed-in patient does not see a doctor in time within the initial waiting time of the target department, the signed-in patient will be marked as a patient to be analyzed, thereby screening the patients to be analyzed in the target department of the hospital and screening the patients to be analyzed in each department of the hospital.

[0038] In a specific embodiment of the present invention, the allowed waiting time of each patient to be analyzed in each department of the hospital is analyzed, and the specific analysis method is: obtaining the calling time point of each patient to be analyzed in each department of the hospital from the hospital calling terminal, and adding it to the initial waiting time of the corresponding department, so as to calculate the current analysis time point of each patient to be analyzed in each department of the hospital.

[0039] The images captured by the hospital's cameras are obtained from the local database, and through face recognition, the time point when each patient to be analyzed in each department of the hospital last appeared in the captured image is obtained, and it is marked as the target time point of each patient to be analyzed in each department of the hospital, and the position where each patient to be analyzed in each department of the hospital last appeared in the captured image is obtained, and it is marked as the target position of each patient to be analyzed in each department of the hospital.

[0040] If the target time point of a patient to be analyzed in a certain department of the hospital is consistent with the current analysis time point, the patient to be analyzed is marked as an in-hospital patient, thereby screening the in-hospital patients in various departments of the hospital; otherwise, the patient to be analyzed is marked as an unidentified in-hospital patient, thereby screening the unidentified in-hospital patients in various departments of the hospital.

[0041] Calculate the allowed waiting time of each in-hospital patient in each department of the hospital, evaluate the allowed waiting time of each unidentified in-hospital patient in each department of the hospital, and summarize the allowed waiting time of each patient to be analyzed in each department of the hospital.

[0042] In a specific embodiment, the time point when each patient to be analyzed in each department of the hospital last appeared in the captured image is obtained by the following specific method: the existing face recognition technology is relatively mature. After each patient to be analyzed in each department of the hospital signs in, real-time monitoring is performed through the existing face recognition technology to obtain the time point when each patient to be analyzed in each department of the hospital last appeared in the captured image.

[0043] In a specific embodiment, the position of each patient to be analyzed in each department of the hospital that last appeared in the captured image is obtained by the following specific method: the existing face recognition technology is relatively mature. After each patient to be analyzed in each department of the hospital signs in, real-time monitoring is performed through the existing face recognition technology to obtain the position of each patient to be analyzed in each department of the hospital that last appeared in the captured image.

[0044] In a specific embodiment of the present invention, the calculation method of the allowed waiting time of each in-hospital patient in each department of the hospital is as follows: according to the target position of each patient to be analyzed in each department of the hospital, the target position of each in-hospital patient in each department of the hospital is extracted, the position of the consultation port of each department of the hospital is obtained from the local database, and the distance value a between the position of the consultation port of each department of the hospital and the target position of each in-hospital patient is calculated. xn , where x represents the number of each department, x=1,2,…,y, y is a positive integer greater than 2, and n represents the number of patients in each hospital, n=1,2,…,m, m is a positive integer greater than 2.

[0045] Obtain the allowed waiting time increase value b corresponding to the unit distance of each department of the hospital from the local database x , calculate the allowed waiting time increase β of each patient in each department of the hospital xn =a xn *b x .

[0046] Assess the historical dishonesty coefficient of each in-hospital patient in each department of the hospital.

[0047] Obtain the allowed waiting time adjustment parameter value corresponding to each historical default coefficient interval from the local database, and map it to obtain the allowed waiting time adjustment parameter value f for each in-hospital patient in each department of the hospital xn .

[0048] It should be noted that the larger the historical default coefficient is, the larger the corresponding allowed waiting time adjustment parameter value is.

[0049] Obtain the reference allowed waiting time g for each department of the hospital from the local database x , calculate the allowed waiting time δ of each patient in each department of the hospital xn =g x -f xn +β xn .

[0050] In a specific embodiment of the present invention, the historical dishonesty coefficient of each in-hospital patient in each department of the hospital is evaluated, and the specific evaluation method is: the check-in status of each historical appointment of each in-hospital patient in each department of the hospital and the historical dishonesty coefficient adjustment parameter value corresponding to each check-in status are obtained from the local database, and the historical dishonesty coefficient adjustment parameter value c of each historical appointment of each in-hospital patient in each department of the hospital is mapped. xni , where i represents the number of each historical reservation, i=1,2,…,j, and j is a positive integer greater than 2.

[0051] Evaluate the historical dishonesty coefficient of each patient in each department of the hospital .

[0052] It should be noted that the sign-in status includes: signed in, not signed in, and timed sign-in.

[0053] In a specific embodiment of the present invention, the allowed waiting time of each unidentified patient in each department of the hospital is evaluated, and the specific evaluation method is: based on the target position of each patient to be analyzed in each department of the hospital, the target position of each unidentified patient in each department of the hospital is extracted.

[0054] The lower limit and upper limit A of the allowed waiting time for each estimated hospital departure location and unidentified patients in the hospital are obtained from the local database.

[0055] If the target position of an unidentified patient in a department of the hospital is consistent with the estimated position of leaving the hospital, the lower limit of the allowed waiting time will be used as the allowed waiting time for the unidentified patient in the hospital. Otherwise, the unidentified patient in the hospital will be marked as a patient in the blind spot of the hospital, thereby screening the patients in the blind spots of various departments of the hospital.

[0056] Based on the method of calculating the increase in the allowed waiting time for each in-hospital patient in each department of the hospital, the decrease in the allowed waiting time for each blind spot patient in each department of the hospital is calculated in the same way. xp , where p represents the number of the blind area of ​​each viewing angle, p=1,2,…,q, and q is a positive integer greater than 2.

[0057] Calculate the decrease in the allowed waiting time C of patients in blind spots of each visual angle in each department of the hospital due to the disappearance of the target in the visual field xp , calculate the allowed waiting time Φ for patients in each blind spot of each department of the hospital xp =AB xp -C xp .

[0058] Summarize the allowed waiting time for unidentified patients in each department of the hospital.

[0059] In a specific embodiment of the present invention, the calculation method of the reduction in the allowed waiting time for patients in each visual blind spot of each department of the hospital due to the disappearance of the target field of vision is as follows: based on the target time point of each patient to be analyzed in each department of the hospital, the target time point of each patient in the visual blind spot of each department of the hospital is extracted.

[0060] According to the current analysis time point of each patient to be analyzed in each department of the hospital, the current analysis time point of each blind spot patient in each department of the hospital is extracted, and the target time point of each blind spot patient in each department of the hospital is subtracted from it to calculate the disappearance time h of each blind spot patient in each department of the hospital xp .

[0061] Obtain the allowed waiting time reduction value k corresponding to the unit waiting time of each department of the hospital from the local database x Calculate the decrease in the waiting time allowed for patients in each blind area of ​​each department of the hospital due to the disappearance of the target in the visual field C xp =h xp *k x .

[0062] In a specific embodiment, the screening of the non-patients in each department of the hospital is carried out by a specific screening method as follows: if a patient to be analyzed in a department of the hospital has not been treated within the allowed waiting time, the patient to be analyzed is marked as a non-patient, thereby screening the non-patients in each department of the hospital.

[0063] In a specific embodiment, the inquiring patients of each department of the hospital are screened by a specific screening method: if a non-treated patient is detected by facial recognition in a department of the hospital during working hours as appearing in the hospital, the non-treated patient is marked as an inquiring patient, thereby screening the inquiring patients of each department of the hospital.

[0064] In a specific embodiment, the screening of the re-called patients in each department of the hospital, the specific screening method is: inquiring each inquired patient in each department of the hospital through text messages, judging whether each inquired patient in each department of the hospital needs to punch in and be called again, if an inquired patient in a department of the hospital needs to punch in and be called again, then the inquired patient is marked as a re-called patient, thereby screening the re-called patients in each department of the hospital.

[0065] In a specific embodiment, the evaluation of the signed-in patients who have not seen the doctor after being sorted after each re-called patient returns, the specific evaluation method is: if a sorted signed-in patient of a department of the hospital has not seen the doctor after a re-called patient returns, then the signed-in patient is marked as a signed-in patient who has not seen the doctor, thereby screening the signed-in patients who have not seen the doctor after being sorted after each re-called patient returns in each department of the hospital.

[0066] In a specific embodiment of the present invention, the ranking position of each re-called patient in each department of the hospital is analyzed, and the specific analysis method is: based on the check-in time point of each signed-in patient, the check-in time points of each patient who has not visited the hospital and signed in after the ranking of each re-called patient returns are extracted and filtered.

[0067] Obtain the agreed calling time of each patient who is called again in each department of the hospital from the hospital calling terminal, subtract the check-in time of each patient who has not been seen and signed in after the ranking of each department of the hospital, and obtain the waiting time l of each patient who has not been seen and signed in after the ranking of each patient who is called again in each department of the hospital. xrt, where r represents the number of each patient who is called again, r=1,2,…,s, s is a positive integer greater than 2, and t represents the number of each patient who has not signed in for treatment, t=1,2,…,u, u is a positive integer greater than 2.

[0068] Obtain the appropriate waiting time D from the local database and calculate the waiting annoyance coefficient of each department of the hospital after the patients who have not signed in for treatment have returned to the order of the patients who have been called again. .

[0069] The waiting annoyance coefficient threshold is obtained from the local database, and the ranking position of each patient who is called again in each department of the hospital is counted.

[0070] In a specific embodiment, the ranking position of each re-called patient in each department of the hospital is counted, and the specific statistical method is as follows: if the waiting annoyance coefficient of the first non-attended signed-in patient in a certain department of the hospital after a re-called patient returns is greater than the waiting annoyance coefficient threshold, then the waiting annoyance coefficient of the second non-attended signed-in patient in the department of the hospital after the re-called patient returns is compared with the waiting annoyance coefficient threshold, and so on, until the waiting annoyance coefficient of a non-attended signed-in patient in the department of the hospital after the re-called patient returns is less than the waiting annoyance coefficient threshold, then the ranking position of the re-called patient is placed before the non-attended signed-in patient, thereby counting the ranking positions of each re-called patient in each department of the hospital.

[0071] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A hospital calling system based on face recognition, characterized in that: include: Hospital appointment information acquisition module, used to obtain the appointment department of each patient; The patient face punch-in module is used to screen each signed-in patient and obtain the sign-in time of each signed-in patient. According to the department of each patient's appointment, the department of each signed-in patient's appointment is extracted, and each signed-in patient of each department of the hospital is mapped. The signed-in patients of each department of the hospital are sorted according to the order of the sign-in time points from the front to the back, so as to obtain the sorted signed-in patients of each department of the hospital; The department call adjustment unit is used to screen the patients to be analyzed in each department of the hospital, and analyze the allowed waiting time for each patient to be analyzed in each department of the hospital, so as to screen the patients who have not been treated in each department of the hospital and provide re-calling service for them; The department calling number adjustment unit includes: a queuing calling number module and a re-calling number module; The queuing module is used to screen the patients to be analyzed in each department of the hospital and analyze the allowed waiting time of each patient to be analyzed in each department of the hospital; The specific analysis method for each patient to be analyzed in each department of the screening hospital is as follows: During the working hours of each department of the hospital, the number of each registered patient in each department of the hospital is called in sequence, a department is randomly selected as the target department, and the initial waiting time of the target department is obtained from the local database. If a registered patient in the target department of the hospital is called, and the registered patient does not see a doctor in time within the initial waiting time of the target department, the registered patient is marked as a patient to be analyzed, thereby screening the patients to be analyzed in the target department of the hospital and screening the patients to be analyzed in each department of the hospital; The specific analysis method of the allowed waiting time of each patient to be analyzed in each department of the analysis hospital is as follows: Obtain the calling time point of each patient to be analyzed in each department of the hospital from the hospital calling terminal, and add it to the initial waiting time of the corresponding department, so as to calculate the current analysis time point of each patient to be analyzed in each department of the hospital; Obtain images captured by the hospital's camera from the local database, and through face recognition, obtain the time point when each patient to be analyzed in each department of the hospital last appeared in the captured image, and mark it as the target time point of each patient to be analyzed in each department of the hospital, obtain the position where each patient to be analyzed in each department of the hospital last appeared in the captured image, and mark it as the target position of each patient to be analyzed in each department of the hospital; If the target time point of a patient to be analyzed in a certain department of the hospital is consistent with the current analysis time point, the patient to be analyzed is marked as an in-hospital patient, thereby screening the in-hospital patients of various departments of the hospital; otherwise, the patient to be analyzed is marked as an unidentified in-hospital patient, thereby screening the unidentified in-hospital patients of various departments of the hospital; Calculate the allowed waiting time of each in-hospital patient in each department of the hospital, evaluate the allowed waiting time of each unidentified in-hospital patient in each department of the hospital, and summarize the allowed waiting time of each patient to be analyzed in each department of the hospital; The specific calculation method for calculating the allowed waiting time of each in-hospital patient in each department of the hospital is as follows: According to the target position of each patient to be analyzed in each department of the hospital, the target position of each in-hospital patient in each department of the hospital is extracted, the location of the consultation port of each department of the hospital is obtained from the local database, and the distance value a between the location of the consultation port of each department of the hospital and the target position of each in-hospital patient is calculated. xn , where x represents the number of each department, n=1,2,…,m, and m is a positive integer greater than 2; Obtain the allowed waiting time increase value b corresponding to the unit distance of each department of the hospital from the local database x , calculate the allowed waiting time increase β of each patient in each department of the hospital xn =a xn *b x ; Evaluate the historical dishonesty coefficient of each in-hospital patient in each department of the hospital; Obtain the allowed waiting time adjustment parameter value corresponding to each historical default coefficient interval from the local database, and map it to obtain the allowed waiting time adjustment parameter value f for each in-hospital patient in each department of the hospital xn ; Obtain the reference allowed waiting time g for each department of the hospital from the local database x , calculate the allowed waiting time δ of each patient in each department of the hospital xn =g x -f xn +β xn ; The specific evaluation method of the allowed waiting time of unidentified patients in each department of the evaluation hospital is as follows: According to the target position of each patient to be analyzed in each department of the hospital, the target position of each unidentified patient in each department of the hospital is extracted; Obtain the lower limit and upper limit A of the allowed waiting time for each estimated leaving hospital location and unidentified patients in the hospital from the local database; If the target position of an unidentified patient in a department of the hospital is consistent with the estimated position of leaving the hospital, the lower limit of the allowed waiting time will be used as the allowed waiting time for the unidentified patient in the hospital. Otherwise, the unidentified patient in the hospital will be marked as a blind spot patient, thereby screening the blind spot patients in each department of the hospital; Based on the method of calculating the increase in the allowed waiting time for each in-hospital patient in each department of the hospital, the decrease in the allowed waiting time for each blind spot patient in each department of the hospital is calculated in the same way. xp , where p represents the number of the blind area of ​​each viewing angle, p=1,2,…,q, q is a positive integer greater than 2; Calculate the decrease in the allowable waiting time C of patients in blind areas of each visual angle in each department of the hospital due to the loss of visual field xp , calculate the allowed waiting time Φ for patients in each blind spot of each department of the hospital xp =AB xp -C xp ; Summarize the allowed waiting time for unidentified patients in each department of the hospital; The specific calculation method for calculating the decrease in the allowed waiting time of patients in blind spots of each visual angle in each department of the hospital due to loss of visual field is as follows: According to the target time points of each patient to be analyzed in each department of the hospital, the target time points of patients in the blind spots of each visual angle in each department of the hospital are extracted; According to the current analysis time point of each patient to be analyzed in each department of the hospital, the current analysis time point of each blind spot patient in each department of the hospital is extracted, and the target time point of each blind spot patient in each department of the hospital is subtracted from it to calculate the disappearance time h of each blind spot patient in each department of the hospital xp ; Obtain the allowed waiting time reduction value k corresponding to the unit waiting time of each department of the hospital from the local database x Calculate the decrease in the allowed waiting time C of patients in blind spots of each visual angle in each department of the hospital due to the loss of visual field xp =h xp *k x ; The re-calling module is used to screen the patients who have not been treated in each department of the hospital, and based on the screening of the inquiring patients in each department of the hospital, and screen the re-called patients in each department of the hospital, evaluate the patients who have not been treated and signed in in each department of the hospital after the re-called patients return to the ranking, analyze the ranking position of each re-called patient in each department of the hospital, and send the ranking position of each re-called patient in each department of the hospital to the corresponding re-called patient; The specific screening method for the untreated patients in each department of the screening hospital is as follows: If a patient to be analyzed in a department of a hospital does not see a doctor within the allowed waiting time, the patient to be analyzed is marked as a non-patient, thereby screening non-patients in various departments of the hospital; The specific analysis method of analyzing the ranking position of each re-called patient in each department of the hospital is as follows: According to the sign-in time of each signed-in patient, the sign-in time of each patient who has not signed in for treatment is extracted and filtered after the sorting of each re-called patient in each department of the hospital; Obtain the agreed calling time of each patient who is called again in each department of the hospital from the hospital calling terminal, subtract the check-in time of each patient who has not been seen and signed in after the ranking of each department of the hospital, and obtain the waiting time l of each patient who has not been seen and signed in after the ranking of each patient who is called again in each department of the hospital. xrt , where r represents the number of each patient who is called again, r=1,2,…,s, s is a positive integer greater than 2, and t represents each patient who has not signed in for treatment, t=1,2,…,u, u is a positive integer greater than 2; Obtain the appropriate waiting time D from the local database and calculate the waiting annoyance coefficient of each department of the hospital after the patients who have not signed in for treatment have returned to the order of the patients who have been called again. ; Obtain the waiting annoyance coefficient threshold from the local database, and count the ranking positions of each patient who has been called again in each department of the hospital; The specific statistical method for the ranking position of each patient who has been called again in each department of the statistical hospital is as follows: If the waiting annoyance coefficient of the first non-attended signed-in patient in a certain department of the hospital after a re-called patient returns is greater than the waiting annoyance coefficient threshold, then the waiting annoyance coefficient of the second non-attended signed-in patient in the department of the hospital after the re-called patient returns is compared with the waiting annoyance coefficient threshold, and so on, until the waiting annoyance coefficient of a non-attended signed-in patient in the department of the hospital after the re-called patient returns is less than the waiting annoyance coefficient threshold, then the ranking position of the re-called patient is placed before the non-attended signed-in patient, thereby counting the ranking positions of each re-called patient in each department of the hospital.

2. According to claim 1, a hospital calling system based on face recognition is characterized in that: The specific evaluation method for evaluating the historical dishonesty coefficient of each in-hospital patient in each department of the hospital is as follows: The check-in status of each historical appointment of each in-hospital patient in each department of the hospital and the historical untrustworthiness coefficient adjustment parameter value corresponding to each check-in status are obtained from the local database, and the historical untrustworthiness coefficient adjustment parameter value c of each historical appointment of each in-hospital patient in each department of the hospital is mapped. xni , where i represents the number of each historical reservation, i=1,2,…,j, j is a positive integer greater than 2; Evaluate the historical dishonesty coefficient of each patient in each department of the hospital .

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