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CN113868677B - Distributed blockchain information technology verification system - Google Patents

Distributed blockchain information technology verification system Download PDF

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Publication number
CN113868677B
CN113868677B CN202111034743.7A CN202111034743A CN113868677B CN 113868677 B CN113868677 B CN 113868677B CN 202111034743 A CN202111034743 A CN 202111034743A CN 113868677 B CN113868677 B CN 113868677B
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module
face recognition
priority
doctor
identity
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CN113868677A (en
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刘云
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Shandong Quwei Network Technology Co ltd
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Shandong Quwei Network Technology Co ltd
Suzhou Tuohanju Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/604—Tools and structures for managing or administering access control systems
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/45—Structures or tools for the administration of authentication
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
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    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The invention discloses a distributed blockchain information technology verification system which comprises a data module, a camera module and a face recognition module, wherein the camera module is electrically connected with the face recognition module, the data module is used for counting and summarizing data information of people, the camera module is used for scanning and shooting conditions in a region, the face recognition module is used for recognizing the face information of the people and matching with identities, the data module comprises an identity data statistics module, a priority calculation module and a priority judgment module, the camera module comprises an identity recognition module and a camera unit, the priority calculation module is electrically connected with the priority judgment module, the identity recognition module is electrically connected with the identity data statistics module, and the face recognition module comprises a wake-up module, an image analysis module, an image signal receiving and transmitting module, an operation power distribution module and an identity matching module.

Description

Distributed blockchain information technology verification system
Technical Field
The invention relates to the technical field of information verification, in particular to a distributed block chain based information technology verification system.
Background
In hospitals, once the identity of a medical practitioner is falsified or replaced, quite serious medical consequences are very likely to occur, and thus authentication of a doctor is very necessary. However, the working time of the doctor is very precious, and how to achieve the purpose of saving time by adjusting the order of identity verification of the doctor is a problem to be solved. Therefore, it is necessary to design a distributed blockchain information technology based verification system that saves resources and improves efficiency.
Disclosure of Invention
The invention aims to provide a distributed block chain information technology based verification system to solve the problems in the background technology.
In order to solve the technical problems, the invention provides a distributed block chain information technology-based verification system which comprises a data module, a camera module and a face recognition module, wherein the camera module is electrically connected with the face recognition module;
The data module is used for counting and summarizing data information of people, the camera module is used for scanning and shooting conditions in the area, and the face recognition module is used for recognizing face information of people and matching with identities.
According to the technical scheme, the data module comprises an identity data statistics module, a priority calculation module and a priority judgment module, the camera module comprises an identity recognition module and a camera unit, the priority calculation module is electrically connected with the priority judgment module, and the identity recognition module is electrically connected with the identity data statistics module;
The identity data statistics module is used for storing identity information of doctors and the number of patients registered on the same day, the priority calculation module is used for calculating priority indexes of the doctors according to the job title of the doctors and the number of the patients registered on the same day, the priority judgment module is used for judging the priority of the doctors according to the priority indexes of the doctors, the identity recognition module is used for reading the identity information and the priority data provided by the doctors, and the camera shooting unit is used for shooting a monitoring area.
According to the technical scheme, the face recognition module comprises a wake-up module, an image analysis module, an image signal receiving and transmitting module, an operation force distribution module and an identity matching module, wherein the identity recognition module is electrically connected with the wake-up module, the camera shooting unit is electrically connected with the image analysis module, the operation force distribution module is electrically connected with the image signal receiving and transmitting module, and the identity matching module is electrically connected with the identity data statistics module;
the image signal receiving and transmitting module is used for sending or receiving a face image to be processed, the computing power distribution module is used for distributing face recognition tasks, and the identity matching module is used for matching the recognized face information with the identity information of a person.
According to the technical scheme, the main working flow of the system is as follows:
S0, arranging a plurality of identity recognition modules and face recognition modules in each important area of the hospital, wherein the identity recognition modules and face recognition modules are used for recognizing and verifying identity information of doctors and patients;
s1, when no person enters the area, the face recognition module stops working;
s2, when someone applies to enter an important area, the system reads the identity information and the priority data of a doctor or the identity information of a patient through the identity recognition module and performs face recognition, and when the face recognition is performed, the higher the priority of the doctor is, the earlier the face recognition verification is performed;
S3, after the face recognition task is finished, the face recognition module is not closed immediately, and when no person enters the area again for a period of time, the face recognition module stops working.
According to the above technical solution, in the step S2, the priority calculation rule of the doctor is:
The higher the doctor's job level in the medical system, the higher the importance of this doctor is represented, the more patients registered on the same day the system will handle, the more patients waiting for doctor's doctor the system will handle it preferentially, so doctor's priority order is calculated by doctor's job level and the number of patients registered on the same day, specifically:
X=μp+λυq
Wherein X is a priority index, the greater X is, the higher the doctor's priority, mu is the weight of the hospital class in the priority index, v is the weight of the number of patients registered in the same day in the priority index, p is the name of the doctor, q is the number of patients registered in the same day by the doctor, and lambda is an adjustment coefficient.
According to the above technical solution, in the step S2, the method for calculating the weight of the priority is as follows:
In the period of relatively more patients in a hospital, the weight of the registration number of the doctor in the same day in the priority order calculation is properly increased, and the weight of the job level of the doctor in the priority order calculation is properly reduced;
In the period of relatively less patients in the hospital, the weight of the job level of the doctor in the priority order calculation is properly increased, the weight of the registration number of the doctor on the same day in the priority order calculation is properly reduced,
Mu+v=100%, and can be obtained
Wherein x is the total number of advanced hanging numbers of hospitals on the same day, and x 0 is the total number of advanced hanging numbers of hospitals on average each day.
According to the technical scheme, the operating principle of the operation force distribution module is as follows:
Because the number of times that the patient comes to the hospital is less, the human face recognition is complex, the time spent is long, the number of times that the doctor comes to the hospital is more, the human face recognition is simple, and the time spent is short, so the operation power occupied when the human face recognition is carried out on the patient and the doctor is different;
The system monitors the number of people in the area through the camera module, the system judges that the number of people wearing the white coat is doctor number, the rest is patient number, when doctors in the area are more, the calculation power occupied by each person is less, when patients in the area are more, the calculation power occupied by each person is more,
The calculation power occupied by each patient for face recognition is M, the calculation power occupied by each doctor for face recognition is N, the number of patients in a certain area is M, the number of doctors is N, and the total occupied calculation power is
Y=mM+nN
The computing power distribution module distributes the person to each face recognition module according to the computing power required by each region to execute the face recognition person.
According to the technical scheme, the main working mode of the face recognition module is as follows:
When the face recognition module finishes the recognition task, in order to save the time required for restarting the face recognition module when someone applies for entering immediately, the face recognition module waits for responding for a period of time t 2 and enters dormancy after t 2;
If a certain face recognition module works and other face recognition modules rest or wait for responding, the face recognition module in the work can send the face recognition task to other face recognition modules which do not perform face recognition work, and the face recognition task is distributed according to the respective operation capacity, so that a plurality of face recognition are cooperatively analyzed.
According to the technical scheme, the working modes of the face recognition module are divided into the following three modes:
When a certain face recognition module does not work, that is, no person applies for entering an important area in at least time t 2, the computing function of the face recognition module can be completely distributed to other face recognition modules;
When a certain face recognition module is started, namely an existing person applies to enter an important area, the computing function of the face recognition module is fully occupied;
When a certain face recognition module enters a waiting response mode, namely, within the time t 2 after the face recognition work is completed, the computing function of the face recognition module can be partially distributed to other face recognition modules.
According to the above technical scheme, the distribution principle of the residual computing power of the face recognition module is as follows:
the residual operation force for processing other information tasks in real time is proportionally increased along with the time after completing the tasks until the face recognition module is triggered to be closed, wherein the residual operation force is all the operation force, specifically
Wherein A is the calculation power for processing other information tasks in real time, N 0 is the total calculation power, N 1 is the calculation power occupied when waiting for response, t 2 is the preset response time, t is the time for waiting for response, and t E [0, t 2).
Compared with the prior art, the invention has the beneficial effects that by sequencing the priorities of doctors, doctors with heavier tasks and stronger capacity can pass face recognition authentication preferentially, the working efficiency is improved, the computing power of the face recognition module is distributed according to the number of the doctors and the patients, the computing power resource can be fully utilized, and the waste is avoided.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic view of the overall modular structure of the present invention;
Detailed Description
The following description of the technical solutions in the embodiments of the present invention will be clear and complete, and it is obvious that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in figure 1, the invention provides a distributed block chain information technology-based verification system, which comprises a data module, a camera module and a face recognition module, wherein the camera module is electrically connected with the face recognition module;
the data module is used for counting and summarizing the data information of the person, the camera module is used for scanning and shooting the condition in the area, and the face recognition module is used for recognizing the face information of the person and matching with the identity;
The data module comprises an identity data statistics module, a priority calculation module and a priority judgment module, the camera module comprises an identity recognition module and a camera unit, the priority calculation module is electrically connected with the priority judgment module, and the identity recognition module is electrically connected with the identity data statistics module;
The system comprises an identity data statistics module, a priority calculation module, a priority judgment module, an identity recognition module, a camera unit and a monitoring area, wherein the identity data statistics module is used for storing identity information of a doctor and the number of patients registered on the same day;
The face recognition module comprises a wake-up module, an image analysis module, an image signal receiving and transmitting module, an operation force distribution module and an identity matching module, wherein the identity recognition module is electrically connected with the wake-up module, the camera shooting unit is electrically connected with the image analysis module, the operation force distribution module is electrically connected with the image signal receiving and transmitting module, and the identity matching module is electrically connected with the identity data statistics module;
The system comprises a wake-up module, an image signal receiving and transmitting module, an image signal processing module, an operation power distribution module, an identity matching module and a user identification module, wherein the wake-up module is used for waking up the human face recognition module, the image analysis module is used for analyzing human faces in shot images, the image signal receiving and transmitting module is used for sending or receiving human face images to be processed, the operation power distribution module is used for distributing human face recognition tasks, and the identity matching module is used for matching the recognized human face information with the identity information of a person;
the main working flow of the system is as follows:
S0, arranging a plurality of identity recognition modules and face recognition modules in each important area of the hospital, wherein the identity recognition modules and face recognition modules are used for recognizing and verifying identity information of doctors and patients;
s1, when no person enters the area, the face recognition module stops working;
s2, when someone applies to enter an important area, the system reads the identity information and the priority data of a doctor or the identity information of a patient through the identity recognition module and performs face recognition, and when the face recognition is performed, the higher the priority of the doctor is, the earlier the face recognition verification is performed;
s3, after the face recognition task is finished, the face recognition module is not closed immediately, and when no person enters the area for a period of time, the face recognition module stops working;
Through the steps, doctors are subjected to priority ranking, so that the doctors with heavier tasks and stronger capabilities can pass face recognition authentication preferentially, the working efficiency is improved, the computing power of the face recognition module is distributed according to the number of the doctors and the patients, the computing power resources can be fully utilized, and the waste is avoided;
in the above step S2, the doctor' S priority calculation rule is:
The higher the doctor's job level in the medical system, the higher the importance of this doctor is represented, the more patients registered on the same day the system will handle, the more patients waiting for doctor's doctor the system will handle it preferentially, so doctor's priority order is calculated by doctor's job level and the number of patients registered on the same day, specifically:
X=μp+λυq
wherein X is a priority index, the greater X is, the higher the doctor's priority, mu is the weight of the hospital class in the priority index, v is the weight of the number of patients registered in the same day in the priority index, p is the name of the doctor, q is the number of patients registered in the same day by the doctor, and lambda is an adjustment coefficient;
in the step S2, the method for calculating the weight of the priority is as follows:
In the period of relatively more patients in a hospital, the weight of the registration number of the doctor in the same day in the priority order calculation is properly increased, and the weight of the job level of the doctor in the priority order calculation is properly reduced;
In the period of relatively less patients in the hospital, the weight of the job level of the doctor in the priority order calculation is properly increased, the weight of the registration number of the doctor on the same day in the priority order calculation is properly reduced,
Mu+v=100%, and can be obtained
Wherein x is the total number of advanced hanging numbers of the hospitals on the same day, and x 0 is the total number of advanced hanging numbers of the hospitals on average each day;
the operating principle of the operational force distribution module is as follows:
Because the number of times that the patient comes to the hospital is less, the human face recognition is complex, the time spent is long, the number of times that the doctor comes to the hospital is more, the human face recognition is simple, and the time spent is short, so the operation power occupied when the human face recognition is carried out on the patient and the doctor is different;
The system monitors the number of people in the area through the camera module, the system judges that the number of people wearing the white coat is doctor number, the rest is patient number, when doctors in the area are more, the calculation power occupied by each person is less, when patients in the area are more, the calculation power occupied by each person is more,
The calculation power occupied by each patient for face recognition is M, the calculation power occupied by each doctor for face recognition is N, the number of patients in a certain area is M, the number of doctors is N, and the total occupied calculation power is
Y=mM+nN
The computing power distribution module distributes the characters to each face recognition module according to the computing power required by each area to execute the face recognition of the characters;
the main working mode of the face recognition module is as follows:
When the face recognition module finishes the recognition task, in order to save the time required for restarting the face recognition module when someone applies for entering immediately, the face recognition module waits for responding for a period of time t 2 and enters dormancy after t 2;
If a certain face recognition module works and other face recognition modules rest or wait for responding, the face recognition module in the work can send the face recognition task to other face recognition modules which do not perform face recognition work, and the face recognition task is distributed according to the respective operation capacity, so that a plurality of face recognition are cooperatively analyzed;
the working modes of the face recognition module are divided into the following three modes:
When a certain face recognition module does not work, that is, no person applies for entering an important area in at least time t 2, the computing function of the face recognition module can be completely distributed to other face recognition modules;
When a certain face recognition module is started, namely an existing person applies to enter an important area, the computing function of the face recognition module is fully occupied;
When a certain face recognition module enters a waiting response mode, namely in the time t 2 after finishing face recognition work, the computing function of the face recognition module can be partially distributed to other face recognition modules;
The distribution principle of the residual computing power of the face recognition module is as follows:
the residual operation force for processing other information tasks in real time is proportionally increased along with the time after completing the tasks until the face recognition module is triggered to be closed, wherein the residual operation force is all the operation force, specifically
Wherein A is the calculation power for processing other information tasks in real time, N 0 is the total calculation power, N 1 is the calculation power occupied when waiting for response, t 2 is the preset response time, t is the time for waiting for response, and t E [0, t 2).
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that the above-mentioned embodiments are merely preferred embodiments of the present invention, and the present invention is not limited thereto, but may be modified or substituted for some of the technical features thereof by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (7)

1.一种基于分布式的区块链信息技术验证系统，其特征在于：包括数据模块、摄像模块、人脸识别模块，所述摄像模块与人脸识别模块电连接；1. A distributed blockchain information technology verification system, characterized in that it includes a data module, a camera module, and a face recognition module, wherein the camera module is electrically connected to the face recognition module; 所述数据模块用于统计并汇总人的数据信息，所述摄像模块用于扫描和拍摄区域内的状况，所述人脸识别模块用于识别人的人脸信息并与身份进行匹配；The data module is used to count and summarize the data information of people, the camera module is used to scan and shoot the conditions in the area, and the face recognition module is used to recognize the face information of people and match them with their identities; 所述数据模块包括身份数据统计模块、优先级计算模块、优先级判断模块，所述摄像模块包括身份识别模块、摄像单元，所述优先级计算模块与优先级判断模块电连接，所述身份识别模块与身份数据统计模块电连接；The data module includes an identity data statistics module, a priority calculation module, and a priority judgment module. The camera module includes an identity recognition module and a camera unit. The priority calculation module is electrically connected to the priority judgment module, and the identity recognition module is electrically connected to the identity data statistics module. 所述身份数据统计模块用于存储医生的身份信息与当天挂号的病人数量，所述优先级计算模块用于根据医生的职称与当天挂号的病人数量计算出医生的优先级指数，所述优先级判断模块用于根据医生的优先级指数判断医生的优先级，所述身份识别模块用于读取医生所提供的身份信息和优先级数据，所述摄像单元用于对监测区域进行拍摄；The identity data statistics module is used to store the identity information of the doctor and the number of patients registered on the same day, the priority calculation module is used to calculate the priority index of the doctor according to the doctor's title and the number of patients registered on the same day, the priority judgment module is used to judge the priority of the doctor according to the doctor's priority index, the identity recognition module is used to read the identity information and priority data provided by the doctor, and the camera unit is used to shoot the monitoring area; 所述人脸识别模块包括唤醒模块、图像分析模块、图像信号收发模块、运算力分配模块、身份匹配模块，所述身份识别模块与唤醒模块电连接，所述摄像单元与图像分析模块电连接，所述运算力分配模块与图像信号收发模块电连接，所述身份匹配模块与身份数据统计模块电连接；The face recognition module includes a wake-up module, an image analysis module, an image signal transceiver module, a computing power allocation module, and an identity matching module. The identity recognition module is electrically connected to the wake-up module, the camera unit is electrically connected to the image analysis module, the computing power allocation module is electrically connected to the image signal transceiver module, and the identity matching module is electrically connected to the identity data statistics module; 所述唤醒模块用于唤醒人脸识别模块，所述图像分析模块用于对拍摄到的图像中的人脸进行分析，所述图像信号收发模块用于发送或接收待处理的人脸图像，所述运算力分配模块用于对人脸识别任务进行分配，所述身份匹配模块用于将识别出的人脸信息与人的身份信息进行匹配；The wake-up module is used to wake up the face recognition module, the image analysis module is used to analyze the face in the captured image, the image signal transceiver module is used to send or receive the face image to be processed, the computing power allocation module is used to allocate the face recognition task, and the identity matching module is used to match the recognized face information with the person's identity information; 该系统的主要工作流程为：The main workflow of the system is: S0、在医院的每个重要区域都设置多个身份识别模块与人脸识别模块，用于识别与验证医生、病人的身份信息；S0. Multiple identity recognition modules and face recognition modules are set up in each important area of the hospital to identify and verify the identity information of doctors and patients; S1、当没有人进入区域时，人脸识别模块停止工作；S1. When no one enters the area, the face recognition module stops working; S2、当有人申请进入重要区域时，系统通过身份识别模块读取了医生的身份信息与优先级数据或者病人的身份信息，并进行人脸识别，在人脸识别时，医生的优先级越高，越先进行人脸识别的验证；S2. When someone applies to enter an important area, the system reads the doctor's identity information and priority data or the patient's identity information through the identity recognition module and performs face recognition. During face recognition, the higher the doctor's priority, the earlier the face recognition verification is performed; S3、在人脸识别任务完成后，人脸识别模块不会立刻关闭，一段时间都没有人再进入区域时，人脸识别模块停止工作。S3. After the face recognition task is completed, the face recognition module will not be shut down immediately. When no one enters the area for a period of time, the face recognition module will stop working. 2.根据权利要求1所述的一种基于分布式的区块链信息技术验证系统，其特征在于：上述步骤S2中，医生的优先级计算规则为：2. A distributed blockchain information technology verification system according to claim 1, characterized in that: in the above step S2, the priority calculation rule of the doctor is: 医疗系统中医生的职称级别越高，代表此医生的重要性越高，系统会对其优先处理，医疗系统中医生的当天挂号病人数量越多，代表有更多的病人在等待医生看病，系统也会优先对其处理，因此医生的优先级顺序由医生的职称级别和当天挂号的病人数量来计算，具体为：The higher the professional title of a doctor in the medical system, the more important the doctor is, and the system will give priority to him. The more patients a doctor has registered on the same day, the more patients are waiting to see the doctor, and the system will give priority to him. Therefore, the priority order of doctors is calculated by the professional title of the doctor and the number of patients registered on the same day, as follows: X＝μp+λυqX＝μp+λυq 其中X为优先级指数，X越大，医生的优先级越高，μ为院内等级占优先级指数的权重，υ为当天挂号的病人数量占优先级指数的权重，p为医生的职称，q为此医生当天挂号的病人数量，λ为调节系数。Where X is the priority index. The larger X is, the higher the priority of the doctor. μ is the weight of the hospital grade in the priority index. υ is the weight of the number of patients registered on the same day in the priority index. p is the doctor's title. q is the number of patients registered by this doctor on the same day. λ is the adjustment coefficient. 3.根据权利要求2所述的一种基于分布式的区块链信息技术验证系统，其特征在于：上述步骤S2中，优先级的权重计算的方法如下：3. A distributed blockchain information technology verification system according to claim 2, characterized in that: in the above step S2, the method for calculating the priority weight is as follows: 在医院病人数相对较多的时期，适当提高医生的当During periods when the number of patients in hospitals is relatively high, it is appropriate to increase the salaries of doctors. 天挂号数量在优先级顺序计算中的权重，适当降低医生的职称级别在优先级顺序计算中的权重；The weight of the number of daily registrations in the priority order calculation should be appropriately reduced, and the weight of the doctor's professional title level in the priority order calculation should be appropriately reduced; 在医院病人数相对较少的时期，适当提高医生的职称级别在优先级顺序计算中的权重，适当降低医生的当天挂号数量在优先级顺序计算中的权重，During periods when the number of patients in hospitals is relatively small, the weight of the doctor's professional title in the priority calculation should be appropriately increased, and the weight of the number of doctors' daily registrations in the priority calculation should be appropriately reduced. 又有μ+υ＝100％，可得And μ+υ＝100%, we can get 其中x为当天医院的总提前挂号数，x0为平均每日医院的总提前挂号数。Where x is the total number of advance registrations in the hospital on that day, and x0 is the average total number of advance registrations in the hospital per day. 4.根据权利要求3所述的一种基于分布式的区块链信息技术验证系统，其特征在于：所述运算力分配模块的工作原理为：4. According to claim 3, a distributed blockchain information technology verification system is characterized in that: the working principle of the computing power allocation module is: 由于病人来医院的次数较少，进行人脸识别较为复杂，需要花费的时间较长，医生来医院的次数较多，进行人脸识别较为简单，需要花费的时间较短，因此对病人与医生进行人脸识别时所占用的运算力也不同；Since patients come to the hospital less frequently, face recognition is more complicated and takes longer time, while doctors come to the hospital more frequently, face recognition is simpler and takes less time. Therefore, the computing power used for face recognition of patients and doctors is different. 系统将通过摄像模块监测区域内的人员数量，系统判定穿白色大褂的人数为医生人数，其余人数为病人人数，当区域内医生更多时，平均每人所占用的运算力更少，当区域内病人更多时，平均每人所占用的运算力更多，The system will monitor the number of people in the area through the camera module. The system determines that the number of people wearing white coats is the number of doctors, and the rest are the number of patients. When there are more doctors in the area, the average computing power occupied by each person is less. When there are more patients in the area, the average computing power occupied by each person is more. 每名病人进行人脸识别所占用的运算力为M，每名医生进行人脸识别所占用的运算力为N，某块区域内病人人数为m，医生人数为n，则总占用运算力为The computing power occupied by each patient for face recognition is M, and the computing power occupied by each doctor for face recognition is N. The number of patients in a certain area is m, and the number of doctors is n. The total computing power occupied is Y＝mM+nNY＝mM+nN 运算力分配模块会根据每个区域执行人脸识别人物所需的运算力对每个人脸识别模块进行人物分配。The computing power allocation module allocates characters to each face recognition module according to the computing power required to perform face recognition of characters in each area. 5.根据权利要求4所述的一种基于分布式的区块链信息技术验证系统，其特征在于：所述人脸识别模块的主要工作方式为：5. A distributed blockchain information technology verification system according to claim 4, characterized in that the main working mode of the face recognition module is: 人脸识别模块在没有人申请进入重要区域时进入休眠状态，当身份识别模块检测到有人申请进入重要区域时，唤醒人脸识别模块，模块启动需要等待时间t1；当人脸识别模块完成识别任务后，为了节约立刻又有人申请进入而重新启动需要的时间，人脸识别模块会等待响应一段时间t2，在t2时间之后进入休眠；The face recognition module enters a dormant state when no one applies to enter an important area. When the identity recognition module detects that someone applies to enter an important area, the face recognition module is awakened. The module needs to wait for a time t1 to start. When the face recognition module completes the recognition task, in order to save the time required for restarting when someone applies to enter immediately, the face recognition module will wait for a response for a period of time t2 , and enter a dormant state after t2 . 若某个人脸识别模块在工作，而其他有的人脸识别模块在休息或等待响应时，该工作中的人脸识别模块会将人脸识别任务发送给其他未进行人脸识别工作的人脸识别模块，按照各自的运算能力进行人脸识别任务的分配，使多个人脸识别进行协同分析。If a face recognition module is working while other face recognition modules are resting or waiting for a response, the working face recognition module will send the face recognition task to other face recognition modules that are not performing face recognition work, and allocate the face recognition tasks according to their respective computing capabilities, so that multiple face recognitions can perform collaborative analysis. 6.根据权利要求5所述的一种基于分布式的区块链信息技术验证系统，其特征在于：所述人脸识别模块的工作模式分为以下三种：6. According to claim 5, a distributed blockchain information technology verification system is characterized in that: the working modes of the face recognition module are divided into the following three types: 当某个人脸识别模块未进行工作，即已经至少有时间t2内没有人申请进入重要区域时，则该人脸识别模块的计算功能可以完全分配给其他人脸识别模块；When a face recognition module is not working, that is, no one has applied to enter the important area for at least time t 2 , the calculation function of the face recognition module can be fully allocated to other face recognition modules; 当某个人脸识别模块启动，即已有人申请进入重要区域时，该人脸识别模块的计算功能已被完全占用；When a face recognition module is activated, that is, someone has applied to enter an important area, the computing function of the face recognition module has been fully occupied; 当某个人脸识别模块进入等待响应模式，即在完成人脸识别工作后的t2时间内，其人脸识别模块的计算功能可以部分分配给其他人脸识别模块。When a face recognition module enters the waiting response mode, that is, within t2 time after completing the face recognition work, the computing function of its face recognition module can be partially allocated to other face recognition modules. 7.根据权利要求6所述的一种基于分布式的区块链信息技术验证系统，其特征在于：所述人脸识别模块的剩余计算力的分配原则为：7. A distributed blockchain information technology verification system according to claim 6, characterized in that: the allocation principle of the remaining computing power of the face recognition module is: 实时处理其他信息任务的剩余运算力随着完成任务后的时间成正比增加，直到触发人脸识别模块关闭时，剩余运算力为其全部运算力，具体为The remaining computing power for real-time processing of other information tasks increases in direct proportion to the time after the task is completed, until the face recognition module is triggered to shut down, and the remaining computing power is its full computing power, specifically 其中A为实时处理其他信息任务的运算力，N0为总体运算力，N1为在等待响应时占用的运算力，t2为预先设定的响应时间，t为等待响应的时间，t∈[0，t2)。Where A is the computing power for real-time processing of other information tasks, N 0 is the overall computing power, N 1 is the computing power occupied when waiting for a response, t 2 is the pre-set response time, t is the time to wait for a response, t ∈ [0, t 2 ).
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Publication number Priority date Publication date Assignee Title
CN107992786A (en) * 2016-10-27 2018-05-04 中国科学院沈阳自动化研究所 A kind of people streams in public places amount statistical method and system based on face

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060116557A1 (en) * 2004-11-30 2006-06-01 Alere Medical Incorporated Methods and systems for evaluating patient data
US7729928B2 (en) * 2005-02-25 2010-06-01 Virtual Radiologic Corporation Multiple resource planning system
CN105989653B (en) * 2015-02-13 2019-12-03 中兴通讯股份有限公司 A medical information processing method, device, medical consultation system and self-service terminal
CN106600500A (en) * 2017-03-07 2017-04-26 佛山市融信通企业咨询服务有限公司 Hospital registration method for automatically determining priority grade of seeing doctor
CN106934906A (en) * 2017-03-07 2017-07-07 佛山市融信通企业咨询服务有限公司 A kind of Hospital register system of the medical priority level of automatic decision
CN107330301A (en) * 2017-08-25 2017-11-07 遵义博文软件开发有限公司 Managing medical information platform based on recognition of face
CN109658581B (en) * 2019-02-19 2021-07-02 中国人民解放军陆军军医大学第一附属医院 Hospital's intelligence system of arranging numbers of seeing a doctor
CN110570942A (en) * 2019-07-26 2019-12-13 华中科技大学 An intelligent medical treatment method and corresponding device

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107992786A (en) * 2016-10-27 2018-05-04 中国科学院沈阳自动化研究所 A kind of people streams in public places amount statistical method and system based on face

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