Intelligent medicine box based on Internet of Things and control method thereof

Abstract

The invention relates to the technical field of intelligent medicine boxes, in particular to an intelligent medicine box based on the Internet of Things and a control method of the intelligent medicine box. Similar medicine taking data matched with the personal medicine taking data are searched in the comparison medicine taking data set in real time, a first medicine taking risk value and a second medicine taking risk value are obtained through calculation, and a comprehensive medicine taking risk value is calculated through fusion; and according to the comprehensive medicine taking risk value, performing user medicine taking time interval early warning, generating a medicine taking historical map of the user, and feeding back the medicine taking historical map to the user side and the doctor side. The problems that in the prior art, due to the data island phenomenon, medicine use information and medical records of patients are scattered, and the medical information sharing efficiency is low are solved; and a risk assessment method for medicine taking reminding depends on single historical data and lacks wide comparison data support, so that the assessment result is one-sided, and the problem that comprehensive assessment of the medicine taking condition of the patient is not facilitated exists.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent medicine boxes, and is an intelligent medicine box based on the Internet of Things and a control method thereof. Background Art

[0002] As an innovative model combining IoT technology with medical services, the smart ward forms an intelligent environment of information sharing and efficient operation through the integration of network and information technology equipment, collects and analyzes patient health information in real time, and provides personalized medical services. The functions of the smart ward include real-time monitoring of patients' vital signs, efficient management of medical resources, data sharing and analysis, and patient interaction and feedback, aiming to improve patient safety and medical operation efficiency. As an important part of the smart ward, the smart medicine box realizes the whole process management and monitoring of medical prescription medication through accurate medication reminders, real-time data collection and scientific risk assessment, greatly improving the safety and effectiveness of medication. The smart medicine box can remind patients to take medication on time, automatically record the time and status of medication, and improve medication compliance; collect and upload patients' personal medication data in real time, and seamlessly connect with the monitoring system of the smart ward, so that doctors can obtain patients' medication status at any time; through data analysis, scientific risk assessment of patients' medication status is carried out to timely discover potential medication risks.

[0003] Although existing technologies have made certain progress in the application of smart medicine boxes and smart wards, they still face some shortcomings: the data island phenomenon leads to the dispersion of patients' medication information and medical records, reducing the efficiency of information sharing; the risk assessment method relies on single historical data and lacks extensive comparative data support, which may lead to one-sided assessment results and is not conducive to a comprehensive assessment of patients' medication; the data analysis and access of smart medicine boxes is relatively simple, and artificial intelligence algorithms are not fully applied to provide truly personalized medication guidance; the operating interface is complex and inconvenient to operate, which may lead to operational errors for patients, affecting the effectiveness of medication and health management; smart medicine boxes are mostly based on one-way information transmission, lack of interaction with patients, and cannot promptly answer patients' questions or provide personalized support. Summary of the invention

[0004] The technical problem to be solved by the present invention is that in the prior art, the data island phenomenon leads to the dispersion of patients' medication information and medical records, and the efficiency of medical information sharing is low; and the risk assessment method of medication reminders relies on single historical data and lacks extensive comparative data support, which leads to one-sided assessment results and is not conducive to a comprehensive assessment of patients' medication situation. A smart medicine box based on the Internet of Things and a control method thereof are proposed.

[0005] In order to achieve the above object, the technical solution of a control method of a smart medicine box based on the Internet of Things of the present invention comprises the following steps: S1: Enter the initial information of the medication currently taken by the user and the interval between first medications through the smart medicine box; S2: The user's personal medication data is recorded in real time through the smart medicine box, and the medication data of other users in the same department in the smart ward where the user is located are simultaneously obtained to form a comparative medication data set; S3: Searching in real time in the comparison medication data set for similar medication data that matches the personal medication data, importing the personal medication data and the similar medication data into the first medication risk assessment strategy, and calculating and obtaining the first medication risk value; S4: Real-time monitoring of the user's physical status data during the use of the smart medicine box through an Internet device, and importing the user's physical status data into the second medication risk assessment strategy to calculate and obtain the second medication risk value; S5: Calculate the comprehensive medication risk value based on the first medication risk value and the second medication risk value; S6: Based on the comprehensive medication risk value, the user's medication time interval warning is issued, the user's medication history map is generated, and the medication history map is fed back to the user end and the doctor end.

[0006] Specifically, S1 includes the following specific steps: S11: The user performs the first registration and initialization operation of the smart medicine box, extracts the initial drug information in the user's doctor's order through the smart ward database, and verifies whether the drugs stored in the drug storage bin of the smart medicine box correspond to the initial drug information; S12: When the user takes medicine for the first time through the smart medicine box, the timestamp of the user's first medication is captured through the smart medicine box; S13: When the user takes the next medication, it is marked that the user has completed the first medication, the interval time of the first medication is recorded, and the last medication record is updated in real time on the smart medicine box display panel.

[0007] Specifically, in S2, the comparative medication data set includes: the cumulative medication times data of other users in the same department in the smart ward where the user is located, the age data of other users, the weight data of other users, and the body active enzyme quantity data of other users.

[0008] Specifically, S3 includes the following specific steps: S31: Extract a comparative medication data set, use the drug type in the initial information of the user's current medication as a search tag, and search in real time in the comparative medication data set for similar medication data that matches the personal medication data, wherein the similar medication data overlaps with the initial information of the user's current medication in terms of drug types greater than or equal to two.

[0009] Specifically, S3 also includes the following specific steps: S32: Importing personal medication data and similar medication data into the first medication risk assessment strategy to calculate and obtain the first medication risk value , wherein the calculation strategy of the first medication risk value is: ; Among them, M is the total number of similar medication data, and m is a subscript, indicating the mth similar medication data; Indicates the cumulative number of times other users took medicine in the mth similar medication data; Indicates the cumulative number of times the user has taken medication; i is a subscript, indicating the type of data. When i=1, 2, and 3, they correspond to the age data of other users, the weight data of other users, and the number of active enzymes of other users, respectively. represents the coefficient of the i-th type of data; They respectively represent the data volume of the i-th type of data in the similar medication data of other users and the user's personal medication data.

[0010] Further, This part calculates the ratio of the cumulative number of medications taken by other users in the mth similar medication data to the cumulative number of medications taken by the user himself. The higher the ratio, the more times other users have taken medications in the similar medication data relative to the user's own medication times, and the higher the potential medication risk. Further, The ratio of the age, weight and number of active enzymes of other users in similar medication data to the corresponding data of the user himself was calculated and weighted by the data proportion coefficient; Furthermore, the squaring process enhances the differences in data proportions, making the data with larger differences have a greater impact on the risk value. At the same time, the square root process balances the impact of different data types and makes the overall impact smoother.

[0011] Specifically, in S4, the body state data includes: body representation data and body activity data, wherein the body activity data includes the sleep time, sedentary time and active time of the user after taking the medicine this time; the body representation data includes: body heart rate average data, body blood pressure average data, body temperature average data, body blood oxygen saturation average data and body respiratory rate average data; In S4, the second medication risk assessment strategy is specifically: ; in, is the risk value for the second dose; n is a subscript, indicating the nth medication process; Indicates the cumulative number of times the user has taken medication; is a subscript, indicating the type of physical activity data. The time corresponds to the sleeping time, sitting time and active time of the user after taking the medicine for the nth time; is a subscript, indicating the type of body representation data, The times correspond to the average heart rate data, the average blood pressure data, the average body temperature data, the average blood oxygen saturation data and the average breathing rate data of the user after taking the medicine for the nth time; Respectively represent Data and The proportion coefficient of the data; Respectively represent Data and The amount of data of the type; Respectively, in the user During the second medication, Data and The average value of the data; Indicates the user's During the second medication, The maximum and minimum values ​​of the data; Indicates the user's During the second medication, The maximum and minimum values ​​of the data.

[0012] Furthermore, by comprehensively considering the user's activity data during different medication processes, including sleep, sedentary, and active, as well as physiological data, including heart rate, blood pressure, body temperature, blood oxygen, and respiratory rate, and the deviation from their average values, a comprehensive assessment of medication risk is achieved. By weighting and accumulating the medication risk value of each item, it is ensured that the difference and importance of data deviations are reasonably reflected, thereby calculating an accurate second medication risk value.

[0013] Specifically, in S5, the calculation strategy of the comprehensive medication risk value is: ; Among them, S is the comprehensive medication risk value; They are the risk value proportion coefficient of the first medication and the risk value proportion coefficient of the second medication respectively; For exponential operation.

[0014] Furthermore, the calculation of the comprehensive medication risk value converts the linear risk value into a nonlinear risk value by performing an exponential operation on the first medication risk value and the second medication risk value. Through the exponential operation, the risk value curve that may have been relatively flat can be made steeper. Especially in the case of high risk values, this conversion can more sensitively reflect the impact of high risks. The function has the characteristic of monotonically increasing and can amplify the difference in values. Especially when the risk value is large, the exponential operation can significantly amplify the impact of the risk value, making the high risk value occupy a larger proportion in the comprehensive risk value.

[0015] Specifically, S6 includes the following specific steps: S61: According to the comprehensive medication risk value, an early warning is issued for the time interval between medications taken by the user; S62: Preset a medication risk threshold. When the comprehensive medication risk value is continuously lower than the medication risk threshold, it is determined that the user is taking medication normally and risk monitoring continues; When the comprehensive medication risk value is greater than or equal to the medication risk threshold for the first time, the patient is reminded that there is a medication risk; When the comprehensive medication risk value is greater than the medication risk threshold in three consecutive monitoring periods, a patient medication risk reminder is sent directly to the doctor and a follow-up consultation suggestion pops up.

[0016] In addition, the present invention provides an Internet of Things-based smart medicine box, comprising a medicine box body and a controller, wherein the controller comprises: Initial information collection module, comparative medication data set construction module, first medication risk value assessment module, second medication risk value assessment module, comprehensive medication risk value calculation module, historical medication feedback module; The initial information collection module collects and stores the initial information of the medicine currently taken by the user and the interval time of the first medication through the smart medicine box; The comparative medication data set construction module records the user's personal medication data in real time through the smart medicine box, and simultaneously obtains the medication data of other users in the same department in the smart ward where the user is located, to form a comparative medication data set; The first medication risk value assessment module is used to search in real time in the comparison medication data set for similar medication data that matches the personal medication data, import the personal medication data and the similar medication data into the first medication risk assessment strategy, and calculate and obtain the first medication risk value; The second medication risk value assessment module monitors the user's physical state data in real time during the use of the smart medicine box through an Internet device, imports the user's physical state data into the second medication risk assessment strategy, and calculates and obtains the second medication risk value; The comprehensive medication risk value calculation module calculates the comprehensive medication risk value by integrating the first medication risk value and the second medication risk value; The historical medication feedback module dynamically adjusts the interval time for the next medication according to the comprehensive medication risk value, generates a medication history map for the user, and feeds back the medication history map to the user end and the doctor end.

[0017] A computer-readable storage medium stores instructions, and when a computer reads the instructions, the computer executes the control method of a smart medicine box based on the Internet of Things.

[0018] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the control method of a smart medicine box based on the Internet of Things is implemented.

[0019] Compared with the prior art, the technical effects of the present invention include: significantly improving the safety and compliance of patients' medication by integrating real-time health monitoring, data analysis and risk assessment. The solution can promptly remind users to take medications on time, automatically record and synchronize personal medication data, and compare it with the medication data of other patients in the smart ward, thereby generating reliable risk assessment results. On this basis, personalized risk management is carried out by comprehensively considering the individual's physical condition and historical medication records to ensure that doctors and patients can quickly obtain important health information. At the same time, the technology also promotes the efficient management of medical resources and information sharing, realizes real-time interaction and feedback during the patient's medication process, thereby improving the overall quality of medical services and patient satisfaction, and strongly supports the construction and development of smart wards. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them: Figure 1 It is a flow chart of a control method of a smart medicine box based on the Internet of Things of the present invention; Figure 2 This is a schematic diagram of the structure of a smart medicine box based on the Internet of Things of the present invention; Figure 3 This is a scene example diagram of a control method of a smart medicine box based on the Internet of Things of the present invention. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0022] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0023] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0024] Embodiment 1 like Figure 1 As shown, a control method of a smart medicine box based on the Internet of Things according to an embodiment of the present invention includes the following specific steps: S1: Enter the initial information of the medication currently taken by the user and the interval between first medications through the smart medicine box; S1 includes the following specific steps: S11: The user performs the first registration and initialization operation of the smart medicine box, extracts the initial drug information in the user's doctor's order through the smart ward database, and verifies whether the drugs stored in the drug storage bin of the smart medicine box correspond to the initial drug information; S12: When the user takes medicine for the first time through the smart medicine box, the timestamp of the user's first medication is captured through the smart medicine box; S13: When the user takes the next medication, it is marked that the user has completed the first medication, the interval time of the first medication is recorded, and the last medication record is updated in real time on the smart medicine box display panel.

[0025] S2: The user's personal medication data is recorded in real time through the smart medicine box, and the medication data of other users in the same department in the smart ward where the user is located are simultaneously obtained to form a comparative medication data set; In S2, the comparative medication data set includes: the cumulative medication times data of other users in the same department in the smart ward where the user is located, the age data of other users, the weight data of other users, and the body active enzyme quantity data of other users.

[0026] S3: Searching in real time in the comparison medication data set for similar medication data that matches the personal medication data, importing the personal medication data and the similar medication data into the first medication risk assessment strategy, and calculating and obtaining the first medication risk value; S3 includes the following specific steps: S31: Extract a comparative medication data set, use the drug type in the initial information of the user's current medication as a search tag, and search in real time in the comparative medication data set for similar medication data that matches the personal medication data, wherein the similar medication data overlaps with the initial information of the user's current medication in terms of drug types greater than or equal to two.

[0027] S3 also includes the following specific steps: S32: Importing personal medication data and similar medication data into the first medication risk assessment strategy to calculate and obtain the first medication risk value , wherein the calculation strategy of the first medication risk value is: ; Among them, M is the total number of similar medication data, and m is a subscript, indicating the mth similar medication data; Indicates the cumulative number of times other users took medicine in the mth similar medication data; Indicates the cumulative number of times the user has taken medication; i is a subscript, indicating the type of data. When i=1, 2, and 3, they correspond to the age data of other users, the weight data of other users, and the number of active enzymes of other users, respectively. represents the coefficient of the i-th type of data; They respectively represent the data volume of the i-th type of data in the similar medication data of other users and the user's personal medication data.

[0028] S4: Real-time monitoring of the user's physical status data during the use of the smart medicine box through an Internet device, and importing the user's physical status data into the second medication risk assessment strategy to calculate and obtain the second medication risk value; In S4, the body state data includes: body representation data and body activity data, wherein the body activity data includes the sleep time, sedentary time and active time of the user after taking the medicine this time; the body representation data includes: body heart rate average data, body blood pressure average data, body temperature average data, body blood oxygen saturation average data and body respiratory rate average data; In S4, the second medication risk assessment strategy is specifically: ; in, is the risk value for the second dose; n is a subscript, indicating the nth medication process; Indicates the cumulative number of times the user has taken medication; is a subscript, indicating the type of physical activity data. The time corresponds to the sleeping time, sitting time and active time of the user after taking the medicine for the nth time; is a subscript, indicating the type of body representation data, The times correspond to the average heart rate data, the average blood pressure data, the average body temperature data, the average blood oxygen saturation data and the average breathing rate data of the user after taking the medicine for the nth time; Respectively represent Data and The proportion coefficient of the data; Respectively represent Data and The amount of data of the type; Respectively, in the user During the second medication, Data and The average value of the data; Indicates the user's During the second medication, The maximum and minimum values ​​of the data; Indicates the user's During the second medication, The maximum and minimum values ​​of the data.

[0029] S5: Calculate the comprehensive medication risk value based on the first medication risk value and the second medication risk value; like Figure 3 As shown, in this embodiment, the first medication risk value and the second medication risk value are transmitted to the data analysis central server via a wireless network, and the comprehensive medication risk value is calculated by the data analysis central server; In S5, the calculation strategy of the comprehensive medication risk value is: ; Among them, S is the comprehensive medication risk value; They are the risk value proportion coefficient of the first medication and the risk value proportion coefficient of the second medication respectively; For exponential operation.

[0030] S6: Based on the comprehensive medication risk value, the user's medication time interval warning is issued, the user's medication history map is generated, and the medication history map is fed back to the user end and the doctor end.

[0031] S6 includes the following specific steps: S61: According to the comprehensive medication risk value, an early warning is issued for the time interval between medications taken by the user; S62: Preset a medication risk threshold. When the comprehensive medication risk value is continuously lower than the medication risk threshold, it is determined that the user is taking medication normally and risk monitoring continues; When the comprehensive medication risk value is greater than or equal to the medication risk threshold for the first time, the patient is reminded that there is a medication risk; When the comprehensive medication risk value is greater than the medication risk threshold in three consecutive monitoring periods, a patient medication risk reminder is sent directly to the doctor and a follow-up consultation suggestion pops up.

[0032] Embodiment 2 like Figure 2 and Figure 3 As shown, an IoT-based smart medicine box according to an embodiment of the present invention includes a medicine box body and a controller, wherein the controller includes: Initial information collection module, comparative medication data set construction module, first medication risk value assessment module, second medication risk value assessment module, comprehensive medication risk value calculation module, historical medication feedback module; The initial information collection module collects and stores the initial information of the medicine currently taken by the user and the interval time of the first medication through the smart medicine box; The comparative medication data set construction module records the user's personal medication data in real time through the smart medicine box, and simultaneously obtains the medication data of other users in the same department in the smart ward where the user is located, to form a comparative medication data set; The first medication risk value assessment module is used to search in real time in the comparison medication data set for similar medication data that matches the personal medication data, import the personal medication data and the similar medication data into the first medication risk assessment strategy, and calculate and obtain the first medication risk value; The second medication risk value assessment module monitors the user's physical state data in real time during the use of the smart medicine box through an Internet device, imports the user's physical state data into the second medication risk assessment strategy, and calculates and obtains the second medication risk value; The comprehensive medication risk value calculation module calculates the comprehensive medication risk value by integrating the first medication risk value and the second medication risk value; The historical medication feedback module dynamically adjusts the interval time for the next medication according to the comprehensive medication risk value, generates a medication history map for the user, and feeds back the medication history map to the user end and the doctor end.

[0033] Embodiment 3 This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned control method of the smart medicine box based on the Internet of Things by calling the computer program stored in the memory.

[0034] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, and the computer program is loaded and executed by the processor to implement a control method of a smart medicine box based on the Internet of Things provided by the above method embodiment. The electronic device may also include other components for realizing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0035] Embodiment 4 This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon; When the computer program runs on a computer device, the computer device executes the above-mentioned control method of a smart medicine box based on the Internet of Things.

[0036] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0037] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0038] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0039] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0040] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0041] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0042] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0043] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0044] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0045] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0046] In summary, compared with the prior art, the technical effects of the present invention are as follows: By integrating real-time health monitoring, data analysis and risk assessment, the safety and compliance of patients' medication has been significantly improved. The solution can promptly remind users to take medication on time, automatically record and synchronize personal medication data, and compare it with the medication data of other patients in the smart ward to generate reliable risk assessment results. On this basis, personalized risk management is carried out by comprehensively considering personal physical condition and historical medication records to ensure that doctors and patients can quickly obtain important health information. At the same time, this technology also promotes the efficient management and information sharing of medical resources, realizes real-time interaction and feedback during the patient's medication process, thereby improving the overall quality of medical services and patient satisfaction, and strongly supports the construction and development of smart wards.

[0047] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A control method for a smart medicine box based on the Internet of Things, characterized in that: The method comprises the following specific steps: S1: Enter the initial information of the medication currently taken by the user and the interval between first medications through the smart medicine box; S2: The user's personal medication data is recorded in real time through the smart medicine box, and the medication data of other users in the same department in the smart ward where the user is located are simultaneously obtained to form a comparative medication data set; S3: Searching in real time in the comparison medication data set for similar medication data that matches the personal medication data, importing the personal medication data and the similar medication data into the first medication risk assessment strategy, and calculating and obtaining the first medication risk value; S4: Real-time monitoring of the user's physical status data during the use of the smart medicine box through an Internet device, and importing the user's physical status data into the second medication risk assessment strategy to calculate and obtain the second medication risk value; S5: Calculate the comprehensive medication risk value based on the first medication risk value and the second medication risk value; S6: Based on the comprehensive medication risk value, the user's medication time interval warning is issued, the user's medication history map is generated, and the medication history map is fed back to the user end and the doctor end.

2. The control method of a smart medicine box based on the Internet of Things according to claim 1 is characterized in that: S1 includes the following specific steps: S11: The user performs the first registration and initialization operation of the smart medicine box, extracts the initial drug information in the user's doctor's order through the smart ward database, and verifies whether the drugs stored in the drug storage bin of the smart medicine box correspond to the initial drug information; S12: When the user takes medicine for the first time through the smart medicine box, the timestamp of the user's first medication is captured through the smart medicine box; S13: When the user takes the next medication, it is marked that the user has completed the first medication, the interval time of the first medication is recorded, and the last medication record is updated in real time on the smart medicine box display panel.

3. The control method of a smart medicine box based on the Internet of Things according to claim 2 is characterized in that: In S2, the comparative medication data set includes: the cumulative medication times data of other users in the same department of the smart ward where the user is located, the age data of other users, the weight data of other users, and the body active enzyme quantity data of other users.

4. The control method of the smart medicine box based on the Internet of Things according to claim 3 is characterized in that: S3 includes the following specific steps: S31: Extract a comparative medication data set, use the drug type in the initial information of the user's current medication as a search tag, and search in real time in the comparative medication data set for similar medication data that matches the personal medication data, wherein the similar medication data overlaps with the initial information of the user's current medication in terms of drug types greater than or equal to two.

5. The control method of the smart medicine box based on the Internet of Things according to claim 4 is characterized in that: S3 also includes the following specific steps: S32: Importing personal medication data and similar medication data into the first medication risk assessment strategy to calculate and obtain the first medication risk value , wherein the calculation strategy of the first medication risk value is: ； Among them, M is the total number of similar medication data, and m is a subscript, indicating the mth similar medication data; Indicates the cumulative number of times other users took medicine in the mth similar medication data; Indicates the cumulative number of times the user has taken medication; i is a subscript, indicating the type of data. When i=1, 2, and 3, they correspond to the age data of other users, the weight data of other users, and the number of active enzymes of other users, respectively. represents the coefficient of the i-th type of data; They respectively represent the data volume of the i-th type of data in the similar medication data of other users and the user's personal medication data.

6. The control method of the smart medicine box based on the Internet of Things according to claim 5 is characterized in that: In S4, the body state data includes: body representation data and body activity data, wherein the body activity data includes the sleep time, sedentary time and active time of the user after taking the medicine this time; the body representation data includes: body heart rate average data, body blood pressure average data, body temperature average data, body blood oxygen saturation average data and body respiratory rate average data; In S4, the second medication risk assessment strategy is specifically: ； in, is the risk value for the second dose; n is a subscript, indicating the nth medication process; Indicates the cumulative number of times the user has taken medication; is a subscript, indicating the type of physical activity data. The time corresponds to the sleeping time, sitting time and active time of the user after taking the medicine for the nth time; is a subscript, indicating the type of body representation data, The times correspond to the average heart rate data, the average blood pressure data, the average body temperature data, the average blood oxygen saturation data and the average breathing rate data of the user after taking the medicine for the nth time; Respectively represent Data and The proportion coefficient of the data; Respectively represent Data and The amount of data of the type; Respectively, in the user During the second medication, Data and The average value of the data; Indicates the user's During the second medication, The maximum and minimum values ​​of the data; Indicates the user's During the second medication, The maximum and minimum values ​​of the data.

7. The control method of the smart medicine box based on the Internet of Things according to claim 6 is characterized in that: In S5, the calculation strategy of the comprehensive medication risk value is: ； Among them, S is the comprehensive medication risk value; They are the risk value proportion coefficient of the first medication and the risk value proportion coefficient of the second medication respectively; For exponential operation.

8. The control method of the smart medicine box based on the Internet of Things according to claim 7 is characterized in that: S6 includes the following specific steps: S61: According to the comprehensive medication risk value, an early warning is issued for the time interval between medications taken by the user; S62: Preset a medication risk threshold. When the comprehensive medication risk value is continuously lower than the medication risk threshold, it is determined that the user is taking medication normally and risk monitoring continues; When the comprehensive medication risk value is greater than or equal to the medication risk threshold for the first time, the patient is reminded that there is a medication risk; When the comprehensive medication risk value is greater than the medication risk threshold in three consecutive monitoring periods, a patient medication risk reminder is sent directly to the doctor and a follow-up consultation suggestion pops up.

9. A smart medicine box based on the Internet of Things, which is used to implement the control method of a smart medicine box based on the Internet of Things as claimed in any one of claims 1 to 8, characterized in that: The smart medicine box includes a medicine box body and a controller, wherein the controller includes: Initial information collection module, comparative medication data set construction module, first medication risk value assessment module, second medication risk value assessment module, comprehensive medication risk value calculation module, historical medication feedback module; The initial information collection module collects and stores the initial information of the medicine currently taken by the user and the interval time of the first medication through the smart medicine box; The comparative medication data set construction module records the user's personal medication data in real time through the smart medicine box, and simultaneously obtains the medication data of other users in the same department in the smart ward where the user is located, to form a comparative medication data set; The first medication risk value assessment module is used to search in real time in the comparison medication data set for similar medication data that matches the personal medication data, import the personal medication data and the similar medication data into the first medication risk assessment strategy, and calculate and obtain the first medication risk value; The second medication risk value assessment module monitors the user's physical state data in real time during the use of the smart medicine box through an Internet device, imports the user's physical state data into the second medication risk assessment strategy, and calculates and obtains the second medication risk value; The comprehensive medication risk value calculation module calculates the comprehensive medication risk value by integrating the first medication risk value and the second medication risk value; The historical medication feedback module dynamically adjusts the interval time for the next medication according to the comprehensive medication risk value, generates a medication history map for the user, and feeds back the medication history map to the user end and the doctor end.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, a control method for a smart medicine box based on the Internet of Things as described in any one of claims 1 to 8 is implemented.

11. An electronic device, characterized in that: include: A memory for storing instructions; A processor is used to execute the instruction so that the device performs the operation of implementing the control method of a smart medicine box based on the Internet of Things as described in any one of claims 1-8.

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