CN111312358A - Self-service medicine supermarket-based medicine purchase guiding method and system and readable storage medium - Google Patents
Self-service medicine supermarket-based medicine purchase guiding method and system and readable storage medium Download PDFInfo
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- CN111312358A CN111312358A CN202010071419.1A CN202010071419A CN111312358A CN 111312358 A CN111312358 A CN 111312358A CN 202010071419 A CN202010071419 A CN 202010071419A CN 111312358 A CN111312358 A CN 111312358A
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
- G16H20/13—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered from dispensers
Abstract
The invention relates to a self-service medicine supermarket-based medicine purchase guiding method, a self-service medicine supermarket-based medicine purchase guiding system and a readable storage medium, wherein the method comprises the following steps: establishing a database according to the medicine purchasing information, continuously overlapping the stored information in the database along with the increase of the medicine purchasing information, and screening and updating the database information; acquiring image information through image acquisition, extracting characteristics of medicine purchasing personnel, acquiring medicine purchasing record information according to the image information and the characteristics of the medicine purchasing personnel, matching database information, and recommending screen display type medicine information; comparing the medicine purchasing transaction information with the recommended screen display type medicine information to obtain deviation information, and correcting the recommended screen display type medicine information according to the deviation information to obtain correction information; and reversely correcting the medicine information corresponding to the N bits before the recommended screen display type medicine information is sorted according to the correction information, and updating the database information.
Description
Technical Field
The invention relates to a medicine purchase guiding method, in particular to a medicine purchase guiding method and system based on a self-service medicine supermarket and a readable storage medium.
Background
The existing medicine selling mode is mostly adopted through a pharmacy or a hospital, the problems that medicine selling in the pharmacy is difficult to guarantee at night, medicine selling salespeople at night is not professional, medicine selling in 24 hours cannot be guaranteed and the like exist, the medicine selling of a patient at night is inconvenient and untimely, treatment time is delayed, life health is damaged, the medicine selling is difficult for inpatients to purchase, old patients are abundant, self-help medicine purchasing is difficult, medicine use is not guided by people and the like in the general direction of medical improvement, after the medicine is cancelled in a hospital department, a plurality of medicines which are urgently needed are difficult to obtain, and life can be endangered if treatment is not timely.
In order to realize accurate control on a self-service medicine supermarket, a system matched with the self-service medicine supermarket needs to be developed for control, medicine purchasing personnel are accurately guided to purchase medicines through the system, however, in the control process, the optimal screen display medicine information is recommended according to image acquisition, and the rapidity of data transmission is realized.
Disclosure of Invention
The invention overcomes the defects of the prior art and provides a medicine purchase guiding method based on a self-service medicine supermarket.
In order to achieve the purpose, the invention adopts the technical scheme that: a medicine purchase guiding method based on a self-service medicine supermarket comprises the following steps:
establishing a database according to the medicine purchasing information, continuously overlapping the stored information in the database along with the increase of the medicine purchasing information, and screening and updating the database information;
acquiring image information through image acquisition, extracting characteristics of medicine purchasing personnel, acquiring medicine purchasing record information according to the image information and the characteristics of the medicine purchasing personnel, matching database information, and recommending screen display type medicine information;
comparing the medicine purchasing transaction information with the recommended screen display type medicine information to obtain deviation information, and correcting the recommended screen display type medicine information according to the deviation information to obtain correction information;
and reversely correcting the medicine information corresponding to the N bits before the recommended screen display type medicine information is sorted according to the correction information, and updating the database information.
Preferably, the characteristics of the drug buyer at least comprise one or two or more of age, gender and stature.
Preferably, a database is established according to the medicine purchasing information, the information stored in the database is continuously overlapped along with the increase of the medicine purchasing information, and the database information is screened and updated, and the method specifically comprises the following steps:
generating medicine purchasing transaction information according to the medicine purchasing information, and comparing the medicine purchasing transaction information with original data in a database to obtain a medicine purchasing information deviation rate;
if the deviation rate of the medicine purchasing information is larger than a preset deviation rate threshold value, replacing original data;
and when the medicine purchasing times reach a preset value, covering and updating the database information to obtain new database information.
Preferably, image information is acquired through image acquisition, and the characteristics of medicine purchasing personnel are extracted, specifically:
the method comprises the following steps of collecting human face features, obtaining human face images, and generating a human face image set S, specifically:
S＝{Γ1,Γ2,Γ3,……,ΓMwherein Γ isnRepresenting the face image information acquired each time, wherein n is more than or equal to 1 and less than or equal to M;
comparing the face image set, and calculating an average image psi, specifically:
comparing the collected face image with the average image, and calculating the image difference
The method specifically comprises the following steps: phii＝Γi-ψ；
Comparing the average image difference value with a preset image difference value;
if the average image information is less than the preset image difference value, recommending screen display type medicine information according to the average image information and the medicine purchasing record information;
if the difference value is larger than the preset image difference value, recommending screen display type medicine information according to the collected face image and the characteristics of medicine purchasing personnel, recording the medicine transaction record information into a database, and updating the database information.
Preferably, the method further comprises the following steps:
acquiring screen display type medicine information and medicine purchasing transaction information;
comparing the screen display type medicine information with the medicine purchasing transaction information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
if the correction information is larger than the preset correction information, the screen display type medicine information is corrected reversely through the correction information.
Preferably, the drug purchase transaction information and the recommended screen display type drug information are compared to obtain deviation information, and the recommended screen display type drug information is corrected according to the deviation information to obtain correction information, which specifically includes:
dividing the characteristics of the drug buyer into N different subregions;
calculating the characteristic value of the medicine purchasing personnel in each subarea to obtain characteristic similarity information,
comparing the feature similarity information in each different sub-region to obtain a feature similarity difference rate;
classifying the subareas smaller than the characteristic similarity information difference rate threshold value into the areas of the same category;
acquiring medicine purchasing transaction information of areas of the same category;
calculating correction parameters according to the medicine purchasing transaction information;
and obtaining correction information according to the correction parameters.
The second aspect of the present invention also provides a self-service medicine supermarket-based medicine purchase guidance system, which includes: the system comprises a memory and a processor, wherein the memory comprises a medicine purchasing guiding method program of a self-service medicine supermarket, and the medicine purchasing guiding method program of the self-service medicine supermarket realizes the following steps when being executed by the processor:
establishing a database according to the medicine purchasing information, continuously overlapping the stored information in the database along with the increase of the medicine purchasing information, and screening and updating the database information;
acquiring image information through image acquisition, extracting characteristics of medicine purchasing personnel, acquiring medicine purchasing record information according to the image information and the characteristics of the medicine purchasing personnel, matching database information, and recommending screen display type medicine information;
comparing the medicine purchasing transaction information with the recommended screen display type medicine information to obtain deviation information, and correcting the recommended screen display type medicine information according to the deviation information to obtain correction information;
and reversely correcting the medicine information corresponding to the N bits before the recommended screen display type medicine information is sorted according to the correction information, and updating the database information.
Preferably, image information is acquired through image acquisition, and the characteristics of medicine purchasing personnel are extracted, specifically:
the method comprises the following steps of collecting human face features, obtaining human face images, and generating a human face image set S, specifically:
S＝{Γ1,Γ2,Γ3,……,ΓMwherein Γ isnRepresenting the face image information acquired each time, wherein n is more than or equal to 1 and less than or equal to M;
comparing the face image set, and calculating an average image psi, specifically:
comparing the collected face image with the average image, and calculating the image difference
The method specifically comprises the following steps: phii＝Γi-ψ；
Comparing the average image difference value with a preset image difference value;
if the average image information is less than the preset image difference value, recommending screen display type medicine information according to the average image information and the medicine purchasing record information;
if the difference value is larger than the preset image difference value, recommending screen display type medicine information according to the collected face image and the characteristics of medicine purchasing personnel, recording the medicine transaction record information into a database, and updating the database information.
Preferably, the drug purchase transaction information and the recommended screen display type drug information are compared to obtain deviation information, and the recommended screen display type drug information is corrected according to the deviation information to obtain correction information, which specifically includes:
dividing the characteristics of the drug buyer into N different subregions;
calculating the characteristic value of the medicine purchasing personnel in each subarea to obtain characteristic similarity information,
comparing the feature similarity information in each different sub-region to obtain a feature similarity difference rate;
classifying the subareas smaller than the characteristic similarity information difference rate threshold value into the areas of the same category;
acquiring medicine purchasing transaction information of areas of the same category;
calculating correction parameters according to the medicine purchasing transaction information;
and obtaining correction information according to the correction parameters.
A third aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a program of a medication guiding method for a self-service medicine supermarket, and when the program of the medication guiding method for the self-service medicine supermarket is executed by a processor, the steps of the medication guiding method for the self-service medicine supermarket are implemented.
The invention solves the defects in the background technology, and has the following beneficial effects:
(1) through image acquisition face information, match with database information to accurate acquisition recommends the screen display medicine information classification, when guiding the personnel of buying the medicine, quick accurate guide of buying the medicine.
(2) When recommending screen display type medicines, deviation correction can be carried out according to final transaction information of medicine purchasing personnel, updating and replacing of database information are carried out, when next medicine purchasing is carried out, it is guaranteed that medicines finally selected by the medicine purchasing personnel are located in recommended screen display type medicine information, and meanwhile, the medicines are located in the medicine type, which is ranked at the front, of the recommended screen display, and accurate positioning of the medicine purchasing personnel is achieved.
(3) The database information is reversely corrected through the correction information, namely, the optimal recommended screen display type medicine information is obtained through real-time analysis, the system is updated according to the correction information, the autonomous learning capacity of the system is improved, and the database information is updated and covered after medicine transaction is carried out for a preset number of times, so that better targeted guidance is provided for medicine purchasing personnel, and the medicine selection accuracy of the medicine purchasing personnel is greatly improved.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a flow chart of a guiding method for guiding drug purchase based on a self-service medicine supermarket, which is disclosed by the invention;
FIG. 2 illustrates a flow diagram of a method of updating database information;
FIG. 3 illustrates a flow chart of a method of modifying on-screen type drug information;
FIG. 4 shows a flow chart of a method of obtaining correction information;
FIG. 5 is a block diagram of a self-service supermarket-based medication guidance system according to the present invention;
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Fig. 1 shows a flow chart of a medicine purchase guiding method based on a self-service medicine supermarket.
As shown in fig. 1, a first aspect of the present invention provides a medication purchase guidance method based on a self-service medicine supermarket, including:
s102, establishing a database according to the medicine purchasing information, continuously overlapping the stored information in the database along with the increase of the medicine purchasing information, and screening and updating the database information;
s104, acquiring image information through image acquisition, extracting characteristics of medicine purchasing personnel, acquiring medicine purchasing record information according to the image information and the characteristics of the medicine purchasing personnel, matching database information, and recommending screen display type medicine information;
s106, comparing the medicine purchase transaction information with the recommended screen display type medicine information to obtain deviation information, and correcting the recommended screen display type medicine information according to the deviation information to obtain correction information;
and S108, reversely correcting the medicine information corresponding to N bits before the recommended screen display type medicine information is sorted according to the correction information, and updating the database information.
The medicine is an over-the-counter medicine, medicine purchasing is divided into self-medicine purchasing, namely medicine purchasing for the self-medicine purchasing or medicine purchasing for a substitute, and medicine purchasing for other people, the two medicine purchasing modes can be guided by guiding information, including image acquisition, voice recognition or case scanning, etiology analysis from cases, and accurate medicine recommendation.
The system can not only recommend single medicine, but also realize medicine combination recommendation, when the combination medicine is recommended, after the medicine purchasing is guided for a plurality of times, according to the medicine purchasing transaction information, comparing the information of the recommended screen display type medicine combination, if two medicines are recommended to be combined, such as amoxicillin and compound paracetamol capsules, roxithromycin and gankang, the two combinations are used for treating cold, but the medicine purchasing personnel does not select the combination as shown in the medicine purchasing transaction record, but the amoxicillin and the Gankang are purchased separately, the medicine information is recombined through the deviation information, the amoxicillin and the Gankang form a new screen display medicine combination, the database is updated at the same time, and the two combinations are only examples, and do not limit the names of the drugs, the types of the combinations, or the types of the drugs, and multiple drug combinations can be performed in actual use.
And arranging the medicine combinations 5-10 th before the purchase times are ranked after carrying out multiple guide transactions according to a month period, screening database information, and refreshing or replacing the medicine combinations 5-10 th before the purchase times are ranked in the last month so as to achieve real-time update of medicine recommendation.
According to the embodiment of the invention, the characteristics of the medicine buyer at least comprise one or two or more of age, gender and stature.
It should be noted that, when selling medicine, buying medicine for oneself, image acquisition can be used to perform all-round characteristic analysis on the medicine purchasing personnel, the medicine purchasing intention of the medicine purchasing personnel is obtained through characteristic analysis, and when recommending medicine through age analysis, the best medicine suitable for the age group is recommended, for example, the medicine is recommended in the age of 15-20 years, the medicine information is recommended in combination with the body growth of teenagers, the medicine is recommended in the age of 20-40 years, the body quality is better, medicines with strong functions and quick treatment can be recommended, and the medicine purchasing population is 40-60 years, so that selective recommendation needs to be performed in combination with the body quality of the medicine purchasing personnel, and people with different sexes also have differences in the recommended medicine, and factors including body contour, weight, bone size and the like, but not only include the two types, different weights, bearing capacity to medicine, and medicine dosage are different, therefore, the screen display medicine information can be selectively recommended according to the multiple factors, when the medicine purchasing personnel definitely know the name of the medicine to be purchased, the name of the medicine can be directly spoken out through voice recognition, when the system recommends the screen display medicine information, the screen display is directly recommended, the middle recognition process is reduced, the medicine purchasing guide efficiency is improved, the user experience is increased, when the medicine purchasing personnel does not clearly know the name of the medicine to be purchased, the sick symptoms and expressions can be spoken out according to the voice, and when necessary, cases can be provided for scanning, so that the system can more accurately recommend and guide the medicine.
Specifically, when buying medicine for others, the medicine buying personnel can speak out ill symptoms and expressions according to voice, if necessary, a case can be provided for scanning, when buying medicine for themselves, the medicine buying personnel can select two modes of image acquisition and voice recognition to be matched, human body characteristics and face images can be acquired through image acquisition, illness state characteristics are simply analyzed, the symptoms and expressions spoken by voice are combined, more convenient description is provided, diagnosis is carried out, and medicine purchase guidance is carried out according to symptoms.
In addition, under the condition that only the color of the medicine box is known, the drug producing area or the manufacturer is known, the drug purchasing personnel can understand that the medicine is purchased with semi-purpose property, and can also screen the database information according to the requirement of the drug purchasing personnel through the limitation condition of the specification of the drug purchasing personnel and then recommend the medicine, so that the drug purchasing guidance is more humanized.
According to the embodiment of the invention, a database is established according to the medicine purchasing information, the information stored in the database is continuously overlapped along with the increase of the medicine purchasing information, and the database information is screened and updated, which specifically comprises the following steps:
generating medicine purchasing transaction information according to the medicine purchasing information, and comparing the medicine purchasing transaction information with original data in a database to obtain a medicine purchasing information deviation rate;
if the deviation rate of the medicine purchasing information is larger than a preset deviation rate threshold value, replacing original data;
and when the medicine purchasing times reach a preset value, covering and updating the database information to obtain new database information.
It should be noted that, as long as a medicine is purchased in the system, all medicine purchasing information is stored in the database, data analysis, classification and screening are performed, information with high medicine purchasing similarity can be stored in the same area, when medicine combination is performed and screen display type medicine recommendation is performed, the operation time of the database is reduced, when the system is operated for the first time, original information is in the database, the original information can be understood as screen display type medicine recommendation performed according to common symptoms, when medicine purchasing transaction information is generated, the medicine purchasing information is compared with the information in the original database to obtain a recommended medicine information rate, and when the recommended medicine information deviation rate is greater than a preset deviation rate, the database information is updated through deviation medicine purchasing transaction information to perform updating coverage or replacement of the original database information; and when the deviation rate of the recommended medicine information is smaller than the preset deviation rate, screening the original data, and selecting the optimal recommended medicine information.
FIG. 2 illustrates a flow diagram of a method of updating database information;
according to the embodiment of the invention, image information is acquired through image acquisition, and the characteristics of medicine purchasing personnel are extracted, which specifically comprises the following steps:
s202, collecting human face features, acquiring human face images, and generating a human face image set S, which specifically comprises the following steps:
S＝{Γ1,Γ2,Γ3,……,ΓMwherein Γ isnRepresenting the face image information acquired each time, wherein n is more than or equal to 1 and less than or equal to M;
s204, comparing the face image set, and calculating an average image psi, specifically:
s206, comparing the collected face image with the average image, and calculating the image difference value
The method specifically comprises the following steps: phii＝Γi-ψ；
S208, comparing the average image difference value with a preset image difference value;
s210, if the difference value is smaller than the preset image difference value, recommending screen display type medicine information according to the average image information and the medicine purchasing record information;
s212, if the difference value is larger than the preset image difference value, recommending screen display type medicine information according to the collected face image and the characteristics of the medicine purchasing personnel, recording the medicine transaction record information into a database, and updating the database information.
It should be noted that, when image acquisition is performed, the face image is acquired from the face set by analyzing the face image, similarity information is analyzed, face information closest to the acquired face image is obtained through the similarity information, and screen display type medicine combination information is recommended through the closest face information, so that the method is more dependent.
In addition, the face image set is compared, an average image is calculated, all the collected images are compared with the average image, an image difference value is calculated, a preset image difference value is set, if the image difference value is smaller than the preset image difference value, the similarity is higher, the recommended screen display type medicine information is analyzed through the average image information and the medicine purchasing record information, and therefore the recommended medicine information is quicker and more accurate, the collected image information does not need to be compared with all the images in the face image set one by one, and only the comparison with the average image is needed.
In this way, a situation exists, that is, when the similarity is low, it indicates that there is no face image with high similarity in the face set, which indicates that the medicine purchasing person belongs to the medicine purchasing through the system for the first time, it needs to perform recommended screen display type medicine combination by the collected face image and the characteristics of the medicine purchasing person in combination with symptom description, and when the medicine purchasing person generates a medicine purchasing record, it performs medicine purchasing analysis and selected medicine analysis, whether new medicine transaction information is generated, and records the medicine purchasing information in the database, and at the same time, reversely corrects the medicine combination information, or refreshes the information in the database.
FIG. 3 illustrates a flow chart of a method of modifying on-screen type drug information;
according to the embodiment of the invention, the method further comprises the following steps:
s302, screen display type medicine information and medicine purchasing transaction information are obtained;
s304, comparing the information of the screen display type medicines with the information of the medicine purchasing transaction to obtain a deviation rate;
s306, judging whether the deviation rate is larger than a preset deviation rate threshold value or not;
and S308, if the correction information is larger than the preset correction information, reversely correcting the screen display type medicine information.
It should be noted that when purchasing medicines, no selection is made from the recommended screen display medicines, or medicines are selected after the recommended screen display medicines are ranked, which indicates that the recommended screen display medicines are relatively accurate and have a large deviation from the needs of the medicine purchasing staff, the screen display medicines need to be corrected through correction information, and through big data analysis, the common medicine information and the common medicines in the medicine purchasing transaction record, which are relatively high in demand, are reordered when screen display recommendation is performed, so that it is ensured that when purchasing medicines are selected, the medicines selected are located in the medicines 5-10 before the recommended screen display medicines information ranking, and the accuracy of the recommended medicines is ensured through continuous correction.
FIG. 4 shows a flow chart of a method of obtaining correction information;
according to the embodiment of the invention, the deviation information is obtained by comparing the medicine purchase transaction information with the recommended screen display type medicine information, and the recommended screen display type medicine information is corrected according to the deviation information to obtain the correction information, which specifically comprises the following steps:
s402, dividing the characteristics of the medicine buyer into N different subregions;
s404, calculating characteristic values of medicine purchasing personnel in each subarea to obtain characteristic similarity information;
s406, comparing the feature similarity information in each different sub-region to obtain a feature similarity difference rate;
s408, classifying the sub-regions smaller than the feature similarity information difference rate threshold into regions of the same category;
s410, acquiring medicine purchasing transaction information of areas of the same category;
and S412, calculating a correction parameter according to the medicine purchasing transaction information, and obtaining correction information according to the correction parameter.
It should be noted that, the medicine information is divided into N sub-areas, medicine distinguishing is performed according to the characteristic value of the medicine information in each sub-area, two or more kinds of medicines with high similarity can be classified into the same type area, in the process of medicine transaction, different medicine purchasing information is obtained through the medicine transaction record information, the medicine purchasing information is stored in the database and updated in the database, when a medicine purchasing person does not select the medicine in the screen display medicine information, the recommended screen display medicine information needs to be corrected, correction parameters are determined through the medicine purchasing information, and the screen display medicine information is corrected through the parameters, so that screen display medicine information can be more accurately recommended next time.
FIG. 5 shows a block diagram of a self-service drug supermarket-based drug purchase guidance system;
the second aspect of the invention provides a self-service medicine supermarket-based medicine purchase guiding system, which comprises: the system comprises a memory and a processor, wherein the memory comprises a medicine purchasing guiding method program of a self-service medicine supermarket, and the medicine purchasing guiding method program of the self-service medicine supermarket realizes the following steps when being executed by the processor:
establishing a database according to the medicine purchasing information, continuously overlapping the stored information in the database along with the increase of the medicine purchasing information, and screening and updating the database information;
acquiring image information through image acquisition, extracting characteristics of medicine purchasing personnel, acquiring medicine purchasing record information according to the image information and the characteristics of the medicine purchasing personnel, matching database information, and recommending screen display type medicine information;
comparing the medicine purchasing transaction information with the recommended screen display type medicine information to obtain deviation information, and correcting the recommended screen display type medicine information according to the deviation information to obtain correction information;
and reversely correcting the medicine information corresponding to the N bits before the recommended screen display type medicine information is sorted according to the correction information, and updating the database information.
It should be noted that, as long as a medicine is purchased in the system, all medicine purchasing information is stored in the database, data analysis, classification and screening are performed, information with high medicine purchasing similarity can be stored in the same area, when medicine combination is performed and screen display type medicine recommendation is performed, the operation time of the database is reduced, when the system is operated for the first time, original information is in the database, the original information can be understood as screen display type medicine recommendation performed according to common symptoms, when medicine purchasing transaction information is generated, the medicine purchasing information is compared with the information in the original database to obtain a recommended medicine information rate, and when the recommended medicine information deviation rate is greater than a preset deviation rate, the database information is updated through deviation medicine purchasing transaction information to perform updating coverage or replacement of the original database information; and when the deviation rate of the recommended medicine information is smaller than the preset deviation rate, screening the original data, and selecting the optimal recommended medicine information.
In addition, the medicine purchasing guiding system adopts an AT89C51 singlechip data acquisition unit and a central processing unit for data processing, storage and control, the data acquisition unit is communicated with the sensor through an IIC protocol, the acquisition units are communicated through RS485 interfaces, the data acquisition unit temporarily stores data in an internal RAM, the acquisition units of all modules acquire uploaded data AT the same time, and the non-delay precision of the data is ensured, wherein the model of the singlechip can be selected by technicians in the field according to actual needs, such as selection of ATMEGA48 or AT89C52, and the like.
In addition, AT89C51 provides standard functions of 4 kbyte Flash memory, 256 bytes on-chip data memory (00H-7FH is on-chip RAM, 80H-FFH is special function register SFR), 32I/O port lines, two 16-bit timing/counters, a 5-vector two-stage interrupt structure, a full-duplex serial communication port, an on-chip oscillator and a clock circuit, and AT the same time, AT89C51 can be reduced to 0Hz static logic operation and support two software selectable power-saving operating modes. The idle mode stops the CPU from operating, but allows the RAM, timer/counter, serial port and interrupt system to continue operating. The power down mode saves the contents of the RAM but the oscillator stops and disables all other components until the next hardware reset.
In addition, the medicines are non-prescription medicines, the medicine purchasing is divided into self-medicine purchasing, namely medicine purchasing for self, medicine purchasing for substitute and medicine purchasing for other people, the two medicine purchasing modes can be guided by guiding information, including image acquisition, voice recognition or case scanning, etiology analysis from cases and accurate medicine recommendation, the intention of medicine purchasing can be obtained through the modes, relevant medicine information is searched from a database through the intention information of medicine purchasing, medicine combinations with the largest transaction times or the first few medicines can be extracted from the purchase transaction information for recommendation, allergic medicines or medicines which are not suitable to be used can be obtained through self-description or human body characteristic scanning of a medicine purchasing person in the recommendation process, and the allergic medicines are automatically filtered when screen display information is recommended, so that the user experience is improved.
The system can not only recommend single medicine, but also realize medicine combination recommendation, when the combination medicine is recommended, after the medicine purchasing is guided for a plurality of times, according to the medicine purchasing transaction information, comparing the information of the recommended screen display type medicine combination, if two medicines are recommended to be combined, such as amoxicillin and compound paracetamol capsules, roxithromycin and gankang, the two combinations are used for treating cold, but the medicine purchasing personnel does not select the combination as shown in the medicine purchasing transaction record, but the amoxicillin and the Gankang are purchased separately, the medicine information is recombined through the deviation information, the amoxicillin and the Gankang form a new screen display medicine combination, the database is updated at the same time, and the two combinations are only examples, and do not limit the names of the drugs, the types of the combinations, or the types of the drugs, and multiple drug combinations can be performed in actual use.
And arranging the medicine combinations 5-10 th before the purchase times are ranked after carrying out multiple guide transactions according to a month period, screening database information, and refreshing or replacing the medicine combinations 5-10 th before the purchase times are ranked in the last month so as to achieve real-time update of medicine recommendation.
According to the embodiment of the invention, image information is acquired through image acquisition, and the characteristics of medicine purchasing personnel are extracted, which specifically comprises the following steps:
the method comprises the following steps of collecting human face features, obtaining human face images, and generating a human face image set S, specifically:
S＝{Γ1,Γ2,Γ3,……,ΓMwherein Γ isnRepresenting the face image information acquired each time, wherein n is more than or equal to 1 and less than or equal to M;
comparing the face image set, and calculating an average image psi, specifically:
comparing the collected face image with the average image, and calculating the image difference
The method specifically comprises the following steps:
Φi＝Γi-ψ；
comparing the average image difference value with a preset image difference value;
if the average image information is less than the preset image difference value, recommending screen display type medicine information according to the average image information and the medicine purchasing record information;
if the difference value is larger than the preset image difference value, recommending screen display type medicine information according to the collected face image and the characteristics of medicine purchasing personnel, recording the medicine transaction record information into a database, and updating the database information.
It should be noted that, when image acquisition is performed, the face image is acquired from the face set by analyzing the face image, similarity information is analyzed, face information closest to the acquired face image is obtained through the similarity information, and screen display type medicine combination information is recommended through the closest face information, so that the method is more dependent.
In addition, the face image set is compared, an average image is calculated, all the collected images are compared with the average image, an image difference value is calculated, a preset image difference value is set, if the image difference value is smaller than the preset image difference value, the similarity is higher, the recommended screen display type medicine information is analyzed through the average image information and the medicine purchasing record information, and therefore the recommended medicine information is quicker and more accurate, the collected image information does not need to be compared with all the images in the face image set one by one, and only the comparison with the average image is needed.
In this way, a situation exists, that is, when the similarity is low, it indicates that there is no face image with high similarity in the face set, which indicates that the medicine purchasing person belongs to the medicine purchasing through the system for the first time, it needs to perform recommended screen display type medicine combination by the collected face image and the characteristics of the medicine purchasing person in combination with symptom description, and when the medicine purchasing person generates a medicine purchasing record, it performs medicine purchasing analysis and selected medicine analysis, whether new medicine transaction information is generated, and records the medicine purchasing information in the database, and at the same time, reversely corrects the medicine combination information, or refreshes the information in the database.
According to the embodiment of the invention, the deviation information is obtained by comparing the medicine purchase transaction information with the recommended screen display type medicine information, and the recommended screen display type medicine information is corrected according to the deviation information to obtain the correction information, which specifically comprises the following steps:
dividing the characteristics of the drug buyer into N different subregions;
calculating the characteristic value of the medicine purchasing personnel in each subarea to obtain characteristic similarity information,
comparing the feature similarity information in each different sub-region to obtain a feature similarity difference rate;
classifying the subareas smaller than the characteristic similarity information difference rate threshold value into the areas of the same category;
acquiring medicine purchasing transaction information of areas of the same category;
calculating correction parameters according to the medicine purchasing transaction information;
and obtaining correction information according to the correction parameters.
It should be noted that, the medicine information is divided into N sub-areas, medicine distinguishing is performed according to the characteristic value of the medicine information in each sub-area, two or more kinds of medicines with high similarity can be classified into the same type area, in the process of medicine transaction, different medicine purchasing information is obtained through the medicine transaction record information, the medicine purchasing information is stored in the database and updated in the database, when a medicine purchasing person does not select the medicine in the screen display medicine information, the recommended screen display medicine information needs to be corrected, correction parameters are determined through the medicine purchasing information, and the screen display medicine information is corrected through the parameters, so that screen display medicine information can be more accurately recommended next time.
In addition, when purchasing medicines, the medicines are not selected from the recommended screen display medicines or the medicines after the recommended screen display medicines are ranked are selected, so that the accuracy of the recommended screen display medicines is poor, the deviation from the needs of medicine purchasing personnel is large, screen display medicines need to be corrected through correction information, and through big data analysis, the information of common medicines and common medicines in the purchase transaction records are rearranged during screen display recommendation, so that the medicines selected during the medicine purchasing selection are located in the 5-10 th position before the recommended screen display medicines are ranked, and the accuracy of the recommended medicines is guaranteed through continuous correction.
The characteristics of the medicine buyer at least comprise one or two or more of age, gender and figure outline.
It should be noted that, when selling medicine, buying medicine for oneself, image acquisition can be used to perform all-round characteristic analysis on the medicine purchasing personnel, the medicine purchasing intention of the medicine purchasing personnel is obtained through characteristic analysis, and when recommending medicine through age analysis, the best medicine suitable for the age group is recommended, for example, the medicine is recommended in the age of 15-20 years, the medicine information is recommended in combination with the body growth of teenagers, the medicine is recommended in the age of 20-40 years, the body quality is better, medicines with strong functions and quick treatment can be recommended, and the medicine purchasing population is 40-60 years, so that selective recommendation needs to be performed in combination with the body quality of the medicine purchasing personnel, and people with different sexes also have differences in the recommended medicine, and factors including body contour, weight, bone size and the like, but not only include the two types, different weights, bearing capacity to medicine, and medicine dosage are different, therefore, the screen display medicine information can be selectively recommended according to the multiple factors, when the medicine purchasing personnel definitely know the name of the medicine to be purchased, the name of the medicine can be directly spoken out through voice recognition, when the system recommends the screen display medicine information, the screen display is directly recommended, the middle recognition process is reduced, the medicine purchasing guide efficiency is improved, the user experience is increased, when the medicine purchasing personnel does not clearly know the name of the medicine to be purchased, the sick symptoms and expressions can be spoken out according to the voice, and when necessary, cases can be provided for scanning, so that the system can more accurately recommend and guide the medicine.
Specifically, when buying medicine for others, the medicine buying personnel can speak out ill symptoms and expressions according to voice, if necessary, a case can be provided for scanning, when buying medicine for themselves, the medicine buying personnel can select two modes of image acquisition and voice recognition to be matched, human body characteristics and face images can be acquired through image acquisition, illness state characteristics are simply analyzed, the symptoms and expressions spoken by voice are combined, more convenient description is provided, diagnosis is carried out, and medicine purchase guidance is carried out according to symptoms.
In addition, under the condition that only the color of the medicine box is known, the drug producing area or the manufacturer is known, the drug purchasing personnel can understand that the medicine is purchased with semi-purpose property, and can also screen the database information according to the requirement of the drug purchasing personnel through the limitation condition of the specification of the drug purchasing personnel and then recommend the medicine, so that the drug purchasing guidance is more humanized.
A third aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a program of a medication guiding method for a self-service medicine supermarket, and when the program of the medication guiding method for the self-service medicine supermarket is executed by a processor, the steps of the medication guiding method for the self-service medicine supermarket are implemented.
Through image acquisition face information, match with database information to accurate acquisition recommends the screen display medicine information classification, when guiding the personnel of buying the medicine, quick accurate guide of buying the medicine.
When recommending screen display type medicines, deviation correction can be carried out according to final transaction information of medicine purchasing personnel, updating and replacing of database information are carried out, when next medicine purchasing is carried out, it is guaranteed that medicines finally selected by the medicine purchasing personnel are located in recommended screen display type medicine information, and meanwhile, the medicines are located in the medicine type, which is ranked at the front, of the recommended screen display, and accurate positioning of the medicine purchasing personnel is achieved.
The database information is reversely corrected through the correction information, namely, the optimal recommended screen display type medicine information is obtained through real-time analysis, the system is updated according to the correction information, the autonomous learning capacity of the system is improved, and the database information is updated and covered after medicine transaction is carried out for a preset number of times, so that better targeted guidance is provided for medicine purchasing personnel, and the medicine selection accuracy of the medicine purchasing personnel is greatly improved.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A medicine purchase guiding method based on a self-service medicine supermarket is characterized by comprising the following steps:
establishing a database according to the medicine purchasing information, continuously overlapping the stored information in the database along with the increase of the medicine purchasing information, and screening and updating the database information;
acquiring image information through image acquisition, extracting characteristics of medicine purchasing personnel, acquiring medicine purchasing record information according to the image information and the characteristics of the medicine purchasing personnel, matching database information, and recommending screen display type medicine information;
comparing the medicine purchasing transaction information with the recommended screen display type medicine information to obtain deviation information, and correcting the recommended screen display type medicine information according to the deviation information to obtain correction information;
and reversely correcting the medicine information corresponding to the N bits before the recommended screen display type medicine information is sorted according to the correction information, and updating the database information.
2. The self-service medicine supermarket-based medicine purchase guiding method according to claim 1, wherein the method comprises the following steps: the characteristics of the medicine buyer at least comprise one or two or more of age, gender and figure outline.
3. The self-service medicine supermarket-based medicine purchase guiding method according to claim 2, wherein the method comprises the following steps: the method comprises the following steps of establishing a database according to medicine purchasing information, continuously superposing the stored information in the database along with the increase of the medicine purchasing information, and screening and updating the database information, and specifically comprises the following steps:
generating medicine purchasing transaction information according to the medicine purchasing information, and comparing the medicine purchasing transaction information with original data in a database to obtain a medicine purchasing information deviation rate;
if the deviation rate of the medicine purchasing information is larger than a preset deviation rate threshold value, replacing original data;
and when the medicine purchasing times reach a preset value, covering and updating the database information to obtain new database information.
4. The self-service medicine supermarket-based medicine purchase guiding method according to claim 3, wherein the method comprises the following steps:
image information is acquired through image acquisition, and the characteristics of medicine purchasing personnel are extracted, and the method specifically comprises the following steps:
the method comprises the following steps of collecting human face features, obtaining human face images, and generating a human face image set S, specifically:
S＝{Γ1,Γ2,Γ3,……,ΓMwherein Γ isnRepresenting the face image information acquired each time, wherein n is more than or equal to 1 and less than or equal to M;
comparing the face image set, and calculating an average image psi, specifically:
comparing the collected face image with the average image, and calculating the image difference
The method specifically comprises the following steps:
Φi＝Γi-ψ；
comparing the average image difference value with a preset image difference value;
if the average image information is less than the preset image difference value, recommending screen display type medicine information according to the average image information and the medicine purchasing record information;
if the difference value is larger than the preset image difference value, recommending screen display type medicine information according to the collected face image and the characteristics of medicine purchasing personnel, recording the medicine transaction record information into a database, and updating the database information.
5. The self-service medicine supermarket-based medicine purchase guiding method according to claim 1, wherein the method comprises the following steps:
further comprising:
acquiring screen display type medicine information and medicine purchasing transaction information;
comparing the screen display type medicine information with the medicine purchasing transaction information to obtain a deviation rate;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
if the correction information is larger than the preset correction information, the screen display type medicine information is corrected reversely through the correction information.
6. The self-service medicine supermarket-based medicine purchase guiding method according to claim 1, wherein the method comprises the following steps: comparing the medicine purchase transaction information with the recommended screen display type medicine information, acquiring deviation information, correcting the recommended screen display type medicine information according to the deviation information to obtain correction information, and specifically comprising the following steps:
dividing the characteristics of the drug buyer into N different subregions;
calculating the characteristic value of the medicine purchasing personnel in each subarea to obtain characteristic similarity information,
comparing the feature similarity information in each different sub-region to obtain a feature similarity difference rate;
classifying the subareas smaller than the characteristic similarity information difference rate threshold value into the areas of the same category;
acquiring medicine purchasing transaction information of areas of the same category;
calculating correction parameters according to the medicine purchasing transaction information;
and obtaining correction information according to the correction parameters.
7. The utility model provides a purchase medicine guide system based on self-service medicine supermarket which characterized in that, this system includes: the system comprises a memory and a processor, wherein the memory comprises a medicine purchasing guiding method program of a self-service medicine supermarket, and the medicine purchasing guiding method program of the self-service medicine supermarket realizes the following steps when being executed by the processor:
establishing a database according to the medicine purchasing information, continuously overlapping the stored information in the database along with the increase of the medicine purchasing information, and screening and updating the database information;
acquiring image information through image acquisition, extracting characteristics of medicine purchasing personnel, acquiring medicine purchasing record information according to the image information and the characteristics of the medicine purchasing personnel, matching database information, and recommending screen display type medicine information;
comparing the medicine purchasing transaction information with the recommended screen display type medicine information to obtain deviation information, and correcting the recommended screen display type medicine information according to the deviation information to obtain correction information;
and reversely correcting the medicine information corresponding to the N bits before the recommended screen display type medicine information is sorted according to the correction information, and updating the database information.
8. The self-service supermarket for guiding medicine purchase according to claim 7, wherein:
image information is acquired through image acquisition, and the characteristics of medicine purchasing personnel are extracted, and the method specifically comprises the following steps:
the method comprises the following steps of collecting human face features, obtaining human face images, and generating a human face image set S, specifically:
S＝{Γ1,Γ2,Γ3,……,ΓMwherein Γ isnRepresenting the face image information acquired each time, wherein n is more than or equal to 1 and less than or equal to M;
comparing the face image set, and calculating an average image psi, specifically:
comparing the collected face image with the average image, and calculating the image difference
The method specifically comprises the following steps:
Φi＝Γi-ψ；
comparing the average image difference value with a preset image difference value;
if the average image information is less than the preset image difference value, recommending screen display type medicine information according to the average image information and the medicine purchasing record information;
if the difference value is larger than the preset image difference value, recommending screen display type medicine information according to the collected face image and the characteristics of medicine purchasing personnel, recording the medicine transaction record information into a database, and updating the database information.
9. The self-service supermarket for guiding medicine purchase according to claim 7, wherein: comparing the medicine purchase transaction information with the recommended screen display type medicine information, acquiring deviation information, correcting the recommended screen display type medicine information according to the deviation information to obtain correction information, and specifically comprising the following steps:
dividing the characteristics of the drug buyer into N different subregions;
calculating the characteristic value of the medicine purchasing personnel in each subarea to obtain characteristic similarity information,
comparing the feature similarity information in each different sub-region to obtain a feature similarity difference rate;
classifying the subareas smaller than the characteristic similarity information difference rate threshold value into the areas of the same category;
acquiring medicine purchasing transaction information of areas of the same category;
calculating correction parameters according to the medicine purchasing transaction information;
and obtaining correction information according to the correction parameters.
10. A computer-readable storage medium characterized by: the computer readable storage medium comprises a program of a medication guiding method for a self-service medicine supermarket, when the program of the medication guiding method for the self-service medicine supermarket is executed by a processor, the steps of the medication guiding method for the self-service medicine supermarket according to any one of claims 1 to 6 are realized.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111949889A (en) * | 2020-09-16 | 2020-11-17 | 苏州众智诺成信息科技有限公司 | Sharing platform intelligent recommendation method and system based on big data and readable storage medium |
| CN114596593A (en) * | 2022-05-10 | 2022-06-07 | 慧医谷中医药科技(天津)股份有限公司 | Health-preserving data recommendation method and system based on image processing |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111949889A (en) * | 2020-09-16 | 2020-11-17 | 苏州众智诺成信息科技有限公司 | Sharing platform intelligent recommendation method and system based on big data and readable storage medium |
| CN114596593A (en) * | 2022-05-10 | 2022-06-07 | 慧医谷中医药科技(天津)股份有限公司 | Health-preserving data recommendation method and system based on image processing |
| CN114596593B (en) * | 2022-05-10 | 2022-07-29 | 慧医谷中医药科技(天津)股份有限公司 | Health-preserving data recommendation method and system based on image processing |
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