Intelligent medicine box control system and method

Abstract

The application provides an intelligent medicine box control system and method, relates to the technical field of medicine box control, and combines and connects medicine boxes and establishes a transmission channel to obtain an intelligent medicine box, acquires a medicine box control network according to the intelligent medicine box and a mobile phone APP; analyzes medicine management according to the medicine box control network, and then analyzes the medicine box control to obtain medicine box control analysis data; and analyzes and warns according to the medicine box control analysis data, obtains medicine abnormal warning information, and realizes flexible combination of the intelligent medicine box and deep linkage control of software and hardware.

Description

Technical Field

[0001] This invention proposes an intelligent pillbox control system and method, which relates to the field of digital control technology, specifically to the field of intelligent pillbox control technology. Background Technology

[0002] Existing smart pillboxes mostly use a fixed number of compartments, making it impossible to flexibly adjust the structure according to the type of medication and frequency of use. There is a lack of linkage mechanisms between the compartments, allowing only independent storage of medications, making it difficult to adapt to complex medication scenarios involving multiple medications and multiple time periods. Most products only support simple time reminders, relying on users to manually enter medication information, lacking AI-assisted recognition and coding binding capabilities, which easily leads to information errors and mismatches between medications and compartments. Furthermore, existing pillboxes lack medication feedback collection and anomaly warning mechanisms, making it impossible to monitor users' actual medication dispensing behavior, difficult to identify missed doses or incorrect doses, and mostly rely on physical connections between compartments for data transmission, resulting in poor hardware layout flexibility. These shortcomings prevent existing products from forming a closed-loop medication management system, increasing user medication risks and failing to meet the safe medication needs of the elderly, those living alone, and those with chronic diseases. Summary of the Invention

[0003] This invention provides an intelligent pillbox control system and method to solve the above-mentioned problems: This invention proposes an intelligent pillbox control system and method, the method comprising: S1. Combine and connect the pillboxes and establish a transmission channel to obtain a smart pillbox. Obtain the pillbox control network based on the smart pillbox and the mobile APP. S2. Perform drug management analysis based on the drug box control network, and then perform drug box control analysis to obtain drug box control analysis data; S3. Based on the medicine box control analysis data, conduct comparative analysis and early warning of medication control status feedback to obtain medication abnormality early warning information.

[0004] Further, S1 includes: Obtain multiple small boxes, and connect them in series or parallel to obtain a combination of small boxes; Multiple small boxes are combined, stacked, and connected in space to obtain a medicine box assembly; Establish medicine box channels between multiple small boxes in the medicine box assembly to achieve intelligent assembly; A smart medicine box is obtained by setting up sensors and a controller in a smart combination; the sensors include pressure sensors. The smart pillbox is connected and interacts with a mobile app to obtain a pillbox control network.

[0005] Furthermore, the step of intelligently connecting and interacting with a mobile app to obtain a pillbox control network includes: The smart pillbox is used to identify and locate drug information to obtain drug identification and location information; Encode the drug identification and location information to obtain drug identification and location coding information; The smart pillbox transmits the drug identification and positioning code information to the mobile APP to obtain the first connection and interaction information. Transmit information from the mobile app to the smart pillbox to obtain second-connection interaction information; The first connection interaction information and the second connection interaction information are mapped and synchronized to obtain the medicine box control network.

[0006] Further, S2 includes: Drug information is entered and stored according to the drug box control network to obtain drug entry and storage information; Based on the drug entry and storage information, drug management data analysis is performed to obtain drug management analysis data; Based on drug management analysis data, conduct drug box control analysis to obtain drug box control analysis data; The medicine box control sequence is generated based on the medicine box control analysis data, and medicine box control information is obtained based on the medicine box control sequence.

[0007] Furthermore, the step of performing drug management data analysis based on drug entry and storage information to obtain drug management analysis data includes: Obtain preset medication information and extract medication features to obtain medication feature extraction data; The medication feature extraction data is matched with the drug information of each small box in the drug box control network to obtain drug information matching data. Based on the extracted medication features, the corresponding boxes of the drug information matching data are associated to obtain medication association combination data. Obtain preset medication plan data, and generate a medication control list based on the preset medication plan data and medication association combination data; The medication control list is the data for drug management analysis.

[0008] Furthermore, the step of performing drug box control analysis based on drug management analysis data to obtain drug box control analysis data includes: Based on drug management analysis data, extract the corresponding dosing time, dosing interval, related drug combinations and small box interval codes for each drug to obtain drug extraction information; Based on the drug extraction information, select the small boxes corresponding to drugs that need to be taken during the same medication period, have related effects, or need to be taken in sequence, and determine which small boxes need to be connected. The controller controls the series or parallel connection of the boxes to be connected, configures the signal linkage channels between the boxes, and obtains the connection control data. Based on the connectivity control data and the spatial overlay layout of the medicine box combination, a coordinate system for the position of the small box is established, and the physical location, interval affiliation and signal association of each small box that needs to be connected are marked, and a summary location table of medicine connectivity is generated. Based on the drug connectivity summary location table, the target drug flip-top box corresponding to each medication time period is located, and a flip-top control strategy is configured for each target box. The controller issues flip-top control commands and collects real-time flip-top status data of the small box to generate medicine box control analysis data. Further, S3 includes: Obtain medicine box feedback information based on the medicine box control information; Analyze the medication feedback status based on the information from the medicine box to obtain medication feedback status data; Compare and analyze the medication feedback status data with the medicine box control information to obtain medication comparison analysis data; Determine the types of abnormal data based on the comparative analysis of medication use data; By comparing and contrasting abnormal data, anomalies can be located and anomaly warning control can be triggered to obtain medication anomaly warning information.

[0009] Furthermore, the step of analyzing medication feedback status based on the medicine box feedback information to obtain medication feedback status data includes: Based on the preset medication time cycle and reminder time nodes, the medicine box feedback information is divided into time sequence feedback information in different time segments; The preset medication execution standards in the medicine box control information are retrieved based on the timing feedback information; The information is matched one by one based on the time-series feedback information and the medication implementation standards; During the matching process, it is determined whether the flipping action, medicine retrieval behavior and reminder response in each time segment meet the preset requirements, and the time sequence status determination information is obtained. Feature extraction is performed on the temporal state determination information to extract the core features corresponding to the determination results of each time segment; The extracted core features are standardized, encoded, and stored in a structured manner to obtain temporal state feature extraction information; The extracted temporal state features are the medication feedback state data.

[0010] Further, according to claim 7, the intelligent pillbox control method is characterized in that, the step of comparing and analyzing the medication feedback status data with the pillbox control information to obtain medication comparison analysis data includes: By comparing medication feedback status data with medicine box control data from multiple dimensions, multi-dimensional comparison data is obtained. The multi-dimensional comparison data is compared with the corresponding multi-dimensional comparison threshold to obtain the multi-dimensional comparison results. Based on the results of multi-dimensional comparison, normal and abnormal information in each dimension are determined.

[0011] Furthermore, the system includes: The pillbox network establishment module is used to combine and connect pillboxes and establish a transmission channel to obtain smart pillboxes. The module also obtains the pillbox control network based on the smart pillboxes and the mobile APP. The medicine box management and control analysis module is used to perform medicine management analysis based on the medicine box control network, and then perform medicine box control analysis to obtain medicine box control analysis data. The control status feedback and early warning module is used to perform comparative analysis and early warning of medication control status based on the medicine box control analysis data, and to obtain early warning information of medication abnormalities.

[0012] The beneficial effects of this invention are as follows: This method solves the technical problems of traditional medicine box fixed structures being unable to adapt to multiple medicines, only providing reminders without feedback, and failing to provide early warnings for abnormal medication use; it realizes intelligent management and control of the entire medication process, breaks down the data barriers between hardware and software, and upgrades the medicine box from a single storage tool to a full-process medication management system; it improves the accuracy and safety of medication management, adapts to complex medication scenarios involving multiple medicines and multiple time periods; it reduces the risk of missed or incorrect doses due to user memory bias or operational errors, and is especially suitable for elderly, single-living, and chronic disease users, improving the convenience of medication use and the monitoring efficiency of family members. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of a smart pillbox control method. Detailed Implementation

[0014] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0015] In one embodiment of the present invention, an intelligent pillbox control system and method are proposed, the method comprising: S1. Combine and connect the pillboxes and establish a transmission channel to obtain a smart pillbox. Obtain the pillbox control network based on the smart pillbox and the mobile APP. S2. Perform drug management analysis based on the drug box control network, and then perform drug box control analysis to obtain drug box control analysis data; S3. Based on the medication box control analysis data, perform medication control status feedback comparison analysis and early warning to obtain medication abnormality early warning information, such as... Figure 1 As shown, The working principle and technical effects of the above solution are as follows: This method establishes a stable hardware and software control network by linking a modular pillbox with an app, enabling data communication between the pillbox and the terminal. Based on this network, drug information is entered and analyzed, and pillbox control strategies are generated, ensuring precise matching between pillbox actions and medication needs. By collecting feedback data from the pillbox and comparing it with preset control information, medication anomalies are accurately identified and alerts are triggered, forming a closed-loop management system. For example, an elderly user needs to take three chronic disease medications daily (divided into three doses, including before / after meals). This method allows for flexible pillbox combinations, precise medication reminders, and timely notification of any abnormalities to family members, all without relying on the user's memory.

[0016] This method solves the technical problems of traditional medicine boxes, such as their fixed structure being unable to accommodate multiple medications, providing only reminders without feedback, and failing to warn of abnormal medication use. It achieves intelligent management of the entire medication process, breaking down the data barriers between hardware and software, and upgrading the medicine box from a single storage tool to a full-process medication management system. It improves the accuracy and safety of medication management, adapting to complex medication scenarios involving multiple medications and multiple time periods. It reduces the risk of missed or incorrect doses due to user memory bias or operational errors, and is particularly suitable for elderly, single-living, and chronically ill users, improving the convenience of medication use and the efficiency of family monitoring.

[0017] In one embodiment of the present invention, S1 includes: Obtain multiple small boxes, connect them in series or in parallel to obtain a box combination; the small boxes have a flip-top function and structure; Multiple small boxes are combined, stacked, and connected in space to obtain a medicine box assembly; Establish medicine box channels between multiple small boxes in the medicine box assembly to achieve intelligent assembly; The smart combination is equipped with sensors and controllers to obtain a smart pillbox; the sensors include pressure sensors; for example: 20 pills are placed in a square, and the medication is preset to be taken three times a day, two pills each time. After taking the pills, the weight will be reduced. This is mainly to prevent the elderly from forgetting whether they have taken the pills or not, and to accurately measure whether they have taken one or two pills, and to provide voice alarm reminders. The smart pillbox is connected and interacts with a mobile app to obtain a pillbox control network.

[0018] Examples of smart pillboxes: Pressure sensors are installed in each compartment (square) of the smart pillbox, and the sensors are connected to the pillbox controller to ensure that the sensors can collect the weight data of the medicines in the box in real time.

[0019] Medication parameters can be preset via a mobile app, including the initial quantity of medicine in the box (e.g., 20 tablets), the number of times to take the medicine per day (e.g., 3 times), and the dosage per dose (e.g., 2 tablets), and synchronized to the medicine box control network.

[0020] The pressure sensor detects the weight of the medicine inside the box in real time, records the weight change data, and transmits the data to the controller.

[0021] The controller determines whether the elderly person has taken medication and whether the amount of medication taken at one time meets the requirements (such as whether they have taken 1 or 2 tablets) based on preset medication parameters and weight change data.

[0022] If any abnormality is detected, such as failure to take medication, insufficient dosage, or excessive dosage, the controller will trigger the medicine box's voice alarm module to issue a voice reminder, informing the elderly person of the current medication abnormality and the correct procedure.

[0023] The working principle and technical effects of the above technical solution are as follows: This method completes the construction of a smart pillbox and control network through modular combination and software and hardware adaptation. First, multiple independent small boxes with flip-top structures are obtained. According to the types of medications used by the user (e.g., 6 small boxes are needed for 6 types of medications), they are connected in series or parallel to form a basic small box combination. Then, according to space requirements, the small box combination is stacked vertically or horizontally to achieve flexible expansion in 6 / 9 / 12 ranges. At the same time, a signal transmission channel is established between the combined small boxes to ensure data communication between the small boxes, forming a smart combination. Sensors (detecting flip-top action and small box status) and controllers (receiving / sending commands) are configured for this combination to complete the hardware formation of the smart pillbox. Through communication methods such as Bluetooth, Wi-Fi, and Fi, bidirectional connection and data interaction between the smart pillbox and the mobile APP are realized, and a pillbox control network covering hardware status, drug information, and control commands is built. For example, if a user needs to take nine medications daily, the nine small boxes from three sets of six boxes can be connected in series and spatially stacked to establish signal channels between the boxes. After configuring sensors and controllers and binding them to an app, a control network capable of managing nine medication units can be formed. The channels can be connected using splicing methods, etc. This method solves the technical problems of traditional smart pillboxes, which have fixed structures, limited number of compartments, and cannot adapt to the needs of multiple medications, and whose compartments can only work independently without any linkage. It achieves modularization and scalability of the pillbox structure, supports flexible adjustment of the compartment combination according to the number of medications, and adapts to the personalized medication scenarios of different users. It improves the intelligence level and data interoperability of the pillbox hardware, lowers the usage threshold of the pillbox in multi-medication scenarios, and avoids the problems of mixed medications and disordered medication retrieval caused by insufficient number of compartments.

[0024] In one embodiment of the present invention, the step of intelligently connecting and interacting with a mobile APP to obtain a pillbox control network includes: The smart pillbox is used to identify and locate drug information to obtain drug identification and location information; Encode the drug identification and location information to obtain drug identification and location coding information; The smart pillbox transmits the drug identification and positioning code information to the mobile APP to obtain the first connection and interaction information. Transmit information from the mobile app to the smart pillbox to obtain second-connection interaction information; The first connection interaction information and the second connection interaction information are mapped and synchronized to obtain the medicine box control network.

[0025] The working principle and technical effects of the above technical solution are as follows: This method achieves deep hardware and software linkage through four steps: identification, encoding, transmission, and synchronization, thus constructing a stable medicine box control network. The identification module mounted on the medicine box (or APP photo recognition) collects information and locates the medicines placed in each small box, clarifying the name, specifications, and other information of the medicine corresponding to each small box, forming medicine identification and location information. This information is uniquely encoded, binding the medicine information with the small box interval number and location information to generate medicine identification and location encoding information, ensuring the uniqueness and accuracy of data transmission. The encoded information is transmitted from the smart medicine box to the mobile APP through the communication module, forming the first connection interaction information, completing the data upload from hardware to software. Simultaneously, the medication rules and user information preset on the APP are transmitted to the smart medicine box, forming the second connection interaction information, completing the data distribution from software to hardware. The two sets of interaction information are mapped and synchronized to establish a one-to-one correspondence between medicine information, small box status, and APP commands, constructing a closed-loop medicine box control network. For example: When medicine is placed in small box 1, it is identified and located and coded as XQ01, ASPL, 0.1g. After being transmitted to the APP, the APP transmits the rule of taking one tablet every morning at 8:00 to the medicine box, and synchronously binds the code and the medication rule to complete the network construction.

[0026] This method solves the technical problems of traditional smart pillboxes that only have simple Bluetooth connections with the APP, resulting in data transmission without coded binding, easy information errors, and no precise correlation between the medicine and the position of the pillbox. It achieves precise mapping and synchronization of medicine information, pillbox position, and APP commands, ensuring the accuracy and stability of data transmission. It improves the depth and reliability of hardware and software linkage, allowing the pillbox to accurately respond to APP commands and the APP to obtain the pillbox status in real time. It reduces the error rate in the data transmission process and avoids problems such as incorrect medication reminders and confusion in the medicine dispensing location caused by information errors.

[0027] In one embodiment of the present invention, S2 includes: Drug information is entered and stored according to the drug box control network to obtain drug entry and storage information; Based on the drug entry and storage information, drug management data analysis is performed to obtain drug management analysis data; Based on drug management analysis data, conduct drug box control analysis to obtain drug box control analysis data; The medicine box control sequence is generated based on the medicine box control analysis data, and medicine box control information is obtained based on the medicine box control sequence.

[0028] The working principle and technical effects of the above technical solution are as follows: This method is based on a medicine box control network and constructs a medication data processing flow of information input, data analysis, and control strategy generation. Information such as drug name, dosage, and administration time is entered into the system through manual input via an APP or photo recognition (with AI-assisted information extraction). This information is then bound to the medicine box via its code, forming the drug input storage information. This information is then classified, matched, and correlated to filter valid data and generate drug management analysis data, clarifying the control logic for each drug. Based on the drug management analysis data and the hardware characteristics of the medicine box, the linkage method of the medicine box and the timing of the flip-top control are analyzed to generate medicine box control analysis data. An ordered medicine box control sequence is generated based on the control analysis data (e.g., triggering a flip-top reminder for medicine box 1 at 8:00 AM and simultaneously locking other medicine boxes), and the sequence is converted into executable medicine box control information and sent to the medicine box controller. For example: Enter the medication (1 tablet each at 8 am and 8 pm daily, taken after meals) and store it. After analysis, determine that the small box 2 is bound to the medication, generate a control sequence that triggers the small box 2 to remind you at 8 am and 8 pm, and provides feedback on the status after the box is opened, and convert it into control information to be sent out.

[0029] This method solves the technical problems of traditional smart pillboxes, which can only store drug information and cannot perform in-depth analysis of the information, and whose control instructions are not well-planned and can only provide single reminders. It realizes the standardized management of drug information and the precise generation of pillbox control strategies, making the pillbox actions highly compatible with medication needs. It improves the processing efficiency of medication data and the executability of control instructions. It reduces the complexity of medication management in multi-drug scenarios and avoids problems such as reminder errors and disordered drug dispensing caused by chaotic control logic.

[0030] In one embodiment of the present invention, the step of performing drug management data analysis based on drug entry and storage information to obtain drug management analysis data includes: Obtain preset medication information and extract medication features to obtain medication feature extraction data; The medication feature extraction data is matched with the drug information of each small box in the drug box control network to obtain drug information matching data. Based on the extracted medication features, the corresponding boxes of the drug information matching data are associated to obtain medication association combination data. Obtain preset medication plan data, and generate a medication control list based on the preset medication plan data and medication association combination data; The medication control list is the data for drug management analysis.

[0031] The working principle and technical effects of the above technical solution are as follows: This method completes the construction of drug management analysis data through feature extraction, information matching, association combination, and list generation. It acquires preset medication information (including basic drug information, user medication habits, safe medication standards, etc.), extracts medication feature data, covering core features such as drug name, specifications, administration time, administration interval, and pre- / post-meal requirements; it matches the extracted feature data with each small box in the drug box control network one by one, clarifying the drugs and corresponding information that each small box can be matched with, forming drug information matching data to avoid mismatches between drugs and small boxes; based on the medication feature data, it performs association processing on the successfully matched small boxes, combining small boxes corresponding to drugs with the same medication time period and pharmacodynamic correlation (such as synergistic effects, contraindication avoidance) to form medication association combination data; it acquires preset medication plan data (user's daily / weekly medication schedule), and combines it with the medication association combination data to generate a medication control list containing drug, small box binding relationship, medication time period, association combination, and administration requirements, which serves as drug management analysis data. For example: In the preset medication information, medication a (at 8 am, before meals) and medication b (at 8 am, before meals) are associated medications. After extracting features, they are matched with small boxes 1 and 2, and the associated combination is the 8 am medication group. Combined with the preset plan, a list is generated, which clearly defines the corresponding medications bound to the two small boxes and the synchronous reminder at 8 am.

[0032] This method solves the technical problems of traditional smart pillboxes, such as the lack of precise matching between medicines and pillboxes, and the lack of combined management of related medications, which easily leads to misplaced medicines and chaotic order of taking related medications. It achieves precise binding of medicines and pillboxes and combined management of related medications, making medication arrangements more logical and standardized; it improves the precision of medicine management; and it reduces the risk of incorrect or missed doses caused by disordered medicine placement and improper management of related medications, especially suitable for chronic disease users who need to take multiple related medications at the same time.

[0033] In one embodiment of the present invention, the step of performing drug box control analysis based on drug management analysis data to obtain drug box control analysis data includes: Based on drug management analysis data, extract the corresponding dosing time, dosing interval, related drug combinations and small box interval codes for each drug to obtain drug extraction information; Based on the drug extraction information, select the small boxes corresponding to drugs that need to be taken during the same medication period, have related effects, or need to be taken in sequence, and determine which small boxes need to be connected. The controller controls the series or parallel connection of the boxes to be connected, configures the signal linkage channels between the boxes, and obtains the connection control data. Based on the connectivity control data and the spatial overlay layout of the medicine box combination, a coordinate system for the position of the small box is established, and the physical location, interval affiliation and signal association of each small box that needs to be connected are marked, and a summary location table of medicine connectivity is generated. Based on the drug connectivity summary location table, the target drug flip-top box corresponding to each medication time period is located, and a flip-top control strategy is configured for each target box. The controller issues flip-top control commands and collects real-time flip-top status data of the small box to generate medicine box control analysis data. The working principle and technical effect of the above technical solution are as follows: This method is based on drug management analysis data and constructs a drug box control and analysis process that includes information extraction, small box screening, connectivity control, positioning and labeling, strategy configuration, and data generation. Extract the dosing time, dosing interval, related drug combinations, and box interval codes for each drug from the medication control list to clarify the core control information of each drug and form drug extraction information. Based on the extracted information, select the boxes corresponding to drugs that need to be taken during the same medication period, have related effects, or need to be taken in sequence, and determine the boxes that need to be connected to ensure that the associated boxes can work together. Use the controller to connect the boxes in series or parallel, configure the signal linkage channels between the boxes to realize status communication and synchronous response, and form connection control data. Combine the spatial layout of the boxes to establish a box position coordinate system, mark the physical location, interval, and signal association of each box that needs to be connected, and generate a drug connection summary positioning table to clarify the control scope and association logic. Based on the positioning table, lock the target box for each medication period and configure personalized flip-top control strategies (including sensor trigger sensitivity, status feedback after flipping, unlocking permissions for each period, etc.). Use the controller to issue flip-top control commands, collect the flip-top status data of the boxes in real time, and integrate all control data to form drug box control analysis data. For example: If small box 1 and small box 2 (related to medication) need to be taken at 8 am, the controller will connect the two small boxes in parallel to establish a signal channel, mark the position coordinates, configure a strategy with moderate trigger sensitivity (suitable for elderly operation) and synchronous feedback to the APP after the lid is opened, issue instructions and collect status, and generate control analysis data.

[0034] This method solves the technical problems of traditional smart pillboxes, such as independent operation of individual pillboxes without linkage control, fixed flip-top strategies that cannot adapt to different users, inaccurate positioning of pillboxes, and disordered control command issuance. It achieves collaborative linkage and precise positioning of associated pillboxes, as well as the configuration of personalized flip-top control strategies to adapt to different users' operating habits and medication needs. It improves the accuracy and flexibility of pillbox control, ensuring that control commands can be executed efficiently and orderly. It reduces the difficulty of operating the pillboxes, avoiding problems such as difficulty in retrieving medication and operational errors caused by incompatible control strategies and lack of linkage between pillboxes, thus improving the medication experience.

[0035] In one embodiment of the present invention, S3 includes: Obtain medicine box feedback information based on the medicine box control information; Analyze the medication feedback status based on the information from the medicine box to obtain medication feedback status data; Compare and analyze the medication feedback status data with the medicine box control information to obtain medication comparison analysis data; Determine the types of abnormal data based on the comparative analysis of medication use data; By comparing and contrasting abnormal data, anomalies can be located and anomaly warning control can be triggered to obtain medication anomaly warning information.

[0036] The working principle and technical effects of the above technical solution are as follows: This method constructs a full-process monitoring and early warning system for medication based on feedback collection, status analysis, comparison and judgment, and anomaly early warning. According to the medicine box control information, sensors collect real-time feedback information from the medicine box, including the opening action of the small box, the opening time, the reminder response status, and the sensor operating status. The collected feedback information is analyzed in detail to determine whether the user's medication behavior meets the preset control requirements, generating medication feedback status data to accurately depict the actual medication situation. The feedback status data is compared and analyzed comprehensively with the preset medicine box control information (such as preset opening time, target small box, reminder response time limit, etc.) to identify the differences between actual medication use and preset requirements, forming medication comparison analysis data. Based on the comparison data, the anomaly type is determined (such as failure to take medication on time, taking the wrong small box, no response to reminders, etc.), and the comparison anomaly type data is identified. The anomaly type data is precisely located, clarifying the small box, time point, and cause of the anomaly, triggering the corresponding anomaly early warning control (such as APP pop-up, ringtone reminder, synchronous notification to family members, etc.), generating medication anomaly early warning information. For example: If the preset time is 8:00 AM to open the lid of small box 1 for medication, and the feedback information shows that the lid has not been opened by 9:00 AM, it is determined to be an abnormality of not picking up medication on time. The location of small box 1 and the abnormal time of 9:00 AM are located, triggering an emergency reminder on the APP and a notification on the family's end.

[0037] This method solves the technical problems of traditional smart pillboxes, which can only issue reminders but cannot collect medication feedback, identify abnormal medication behavior, or provide accurate early warnings and location information after anomalies occur. It achieves full-process monitoring of medication behavior, accurate anomaly identification and early warning, forming a closed-loop management system of reminders, feedback, and early warnings. It improves medication safety and monitoring effectiveness, allowing users and their families to keep track of medication status in real time and handle abnormalities promptly. It reduces the risk of missed doses, incorrect doses, and other abnormal medication use, providing a safety guarantee, especially for elderly people living alone and users without self-monitoring capabilities.

[0038] In one embodiment of the present invention, the step of analyzing medication feedback status based on the feedback information from the medicine box to obtain medication feedback status data includes: Based on the preset medication time cycle and reminder time nodes, the medicine box feedback information is divided into time sequence feedback information in different time segments; The preset medication execution standards in the medicine box control information are retrieved based on the timing feedback information; The information is matched one by one based on the time-series feedback information and the medication implementation standards; During the matching process, it is determined whether the flipping action, medicine retrieval behavior and reminder response in each time segment meet the preset requirements, and the time sequence status determination information is obtained. Feature extraction is performed on the temporal state determination information to extract the core features corresponding to the determination results of each time segment; The extracted core features are standardized, encoded, and stored in a structured manner to obtain temporal state feature extraction information; The extracted time-series state features are the medication feedback state data, which is bound one-to-one with the small box interval code, drug information, and medication rules in the medicine box control network.

[0039] The working principle and technical effect of the above technical solution are as follows: This method achieves accurate generation of medication feedback status data through time-series segmentation and refined matching. Based on preset medication time cycles (e.g., daily, weekly) and reminder time nodes (e.g., 8 AM, 8 PM), the collected medicine box feedback information is split into time segments, corresponding to the time-series feedback information for each medication period, ensuring the timeliness and relevance of the analysis. For the time-series feedback information of each time segment, the corresponding preset medication execution standards (e.g., target box, opening time limit, reminder response requirements, etc.) are retrieved from the medicine box control information. The time-series feedback information is compared and matched with the preset execution standards one by one to verify the actual medication behavior within each time segment. During the matching process, it is determined whether the opening action within each time segment has occurred. The system determines whether the actions of taking or retrieving medication correspond to the target box and whether the reminder response is within the time limit, generating time-series status judgment information that includes three categories of results: meeting the standard, deviating from the standard, and no feedback. Core features are extracted from this judgment information, including the time node of deviation from the standard, the duration of no feedback, the number and time of flip-top triggers, and the reminder response delay. These extracted core features are standardized, encoded, and structured for storage, forming time-series status feature extraction information. This information is bound to the box interval code, drug information, and medication rules in the medicine box control network to ensure data traceability and correlation, thus forming medication feedback status data. For example, daily feedback information is divided into three time segments: 8 AM, 12 PM, and 8 PM. In the 8 AM segment, the feedback for box 1 has a 10-minute delay in flipping the box. After matching the standard, this is determined to be a deviation from the standard, and the extracted features are encoded, stored, and bound to box 1 and the aspirin medication rules.

[0040] This method addresses the technical problems of traditional smart pillboxes, which can only record medication feedback information in a simple way, lacking the ability to perform time-series and refined analysis, and whose feedback data is unrelated to drugs, pillboxes, and medication rules, thus failing to accurately depict medication status. It achieves time-series and refined analysis and structured storage of medication feedback information, accurately capturing the details of medication behavior at each time period; improves the usability and traceability of medication status data; reduces the error rate of medication status analysis, and avoids abnormal misjudgments caused by disorganized and unrelated information.

[0041] According to an embodiment of the present invention, a smart pillbox control method according to claim 7, characterized in that the step of comparing and analyzing medication feedback status data with pillbox control information to obtain medication comparison analysis data includes: By comparing medication feedback status data with medicine box control data from multiple dimensions, multi-dimensional comparison data is obtained. The multi-dimensional comparison data is compared with the corresponding multi-dimensional comparison threshold to obtain the multi-dimensional comparison results. Based on the results of multi-dimensional comparison, normal and abnormal information in each dimension are determined.

[0042] The working principle and technical effect of the above technical solution are as follows: This method achieves accurate identification of medication abnormalities through multi-dimensional comparison and threshold judgment. A multi-dimensional comparison system is established, covering the time dimension (actual flip-top time vs. preset reminder time), location dimension (actual dispensing box vs. preset target box), behavior dimension (flip-top frequency vs. preset medication usage frequency), and hardware dimension (sensor trigger status vs. preset control commands). Medication feedback status data and box control information are compared one by one according to their respective dimensions, calculating the difference between the actual value and the preset value for each dimension to form multi-dimensional comparison data. For each comparison dimension, a corresponding comparison threshold is preset (e.g., a 15-minute threshold for the time dimension and a perfect match threshold for the location dimension). The multi-dimensional comparison data is compared with the corresponding threshold to determine whether the differences in each dimension exceed the acceptable range, forming a multi-dimensional comparison result. Based on the comparison result, each dimension is divided into normal information (difference within the threshold) and abnormal information (difference exceeding the threshold), clarifying the medication compliance of each dimension. For example: The preset threshold for the time dimension is 15 minutes. The feedback data shows a delay of 20 minutes. Exceeding the threshold is judged as an anomaly in the time dimension. The feedback for the location dimension shows that the medicine box is consistent with the preset value, which is judged as normal. Finally, comparative analysis data including time anomalies and location normalities are formed.

[0043] This method addresses the technical problem of traditional smart pillboxes, which can only compare medication feedback from a single dimension and lack clear threshold standards, leading to vague anomaly judgments and low accuracy. It enables multi-dimensional and standardized comparison of medication feedback and control information, and clarifies the quantitative standards for anomaly judgment. It improves the accuracy and standardization of anomaly identification, and can accurately distinguish different types of medication deviations. It reduces the probability of false positives and false negatives, ensuring that medication anomalies can be identified in a timely and accurate manner, and further safeguarding medication safety.

[0044] According to one embodiment of the present invention, the system includes: The pillbox network establishment module is used to combine and connect pillboxes and establish a transmission channel to obtain smart pillboxes. The module also obtains the pillbox control network based on the smart pillboxes and the mobile APP. The medicine box management and control analysis module is used to perform medicine management analysis based on the medicine box control network, and then perform medicine box control analysis to obtain medicine box control analysis data. The control status feedback and early warning module is used to perform comparative analysis and early warning of medication control status based on the medicine box control analysis data, and to obtain early warning information of medication abnormalities.

[0045] The working principle and technical effects of the above solution are as follows: This method establishes a stable hardware and software control network by linking a modular pillbox with an app, enabling data communication between the pillbox and the terminal. Based on this network, drug information is entered and analyzed, and pillbox control strategies are generated, ensuring precise matching between pillbox actions and medication needs. By collecting feedback data from the pillbox and comparing it with preset control information, medication anomalies are accurately identified and alerts are triggered, forming a closed-loop management system. For example, an elderly user needs to take three chronic disease medications daily (divided into three doses, including before / after meals). This method allows for flexible pillbox combinations, precise medication reminders, and timely notification of any abnormalities to family members, all without relying on the user's memory.

[0046] This method solves the technical problems of traditional medicine boxes, such as their fixed structure being unable to accommodate multiple medications, providing only reminders without feedback, and failing to warn of abnormal medication use. It achieves intelligent management of the entire medication process, breaking down the data barriers between hardware and software, and upgrading the medicine box from a single storage tool to a full-process medication management system. It improves the accuracy and safety of medication management, adapting to complex medication scenarios involving multiple medications and multiple time periods. It reduces the risk of missed or incorrect doses due to user memory bias or operational errors, and is particularly suitable for elderly, single-living, and chronically ill users, improving the convenience of medication use and the efficiency of family monitoring.

[0047] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for controlling an intelligent pillbox, characterized in that, The method includes: S1. Combine and connect the pillboxes and establish a transmission channel to obtain a smart pillbox. Obtain the pillbox control network based on the smart pillbox and the mobile APP. S2. Perform drug management analysis based on the drug box control network, and then perform drug box control analysis to obtain drug box control analysis data; S3. Based on the medicine box control analysis data, conduct comparative analysis and early warning of medication control status feedback to obtain medication abnormality early warning information.

2. The intelligent pillbox control method according to claim 1, characterized in that, S1 includes: Obtain multiple small boxes, and connect them in series or parallel to obtain a combination of small boxes; Multiple small boxes are combined, stacked, and connected in space to obtain a medicine box assembly; Establish medicine box channels between multiple small boxes in the medicine box assembly to achieve intelligent assembly; A smart medicine box is obtained by setting up sensors and a controller in a smart combination; the sensors include pressure sensors. The smart pillbox is connected and interacts with a mobile app to obtain a pillbox control network.

3. The intelligent pillbox control method according to claim 2, characterized in that, The process of intelligently connecting and interacting with a mobile app to obtain a pillbox control network includes: The smart pillbox is used to identify and locate drug information to obtain drug identification and location information; Encode the drug identification and location information to obtain drug identification and location coding information; The smart pillbox transmits the drug identification and positioning code information to the mobile APP to obtain the first connection and interaction information. Transmit information from the mobile app to the smart pillbox to obtain second-connection interaction information; The first connection interaction information and the second connection interaction information are mapped and synchronized to obtain the medicine box control network.

4. The intelligent pillbox control method according to claim 1, characterized in that, S2 includes: Drug information is entered and stored according to the drug box control network to obtain drug entry and storage information; Based on the drug entry and storage information, drug management data analysis is performed to obtain drug management analysis data; Based on drug management analysis data, conduct drug box control analysis to obtain drug box control analysis data; The medicine box control sequence is generated based on the medicine box control analysis data, and medicine box control information is obtained based on the medicine box control sequence.

5. The intelligent pillbox control method according to claim 4, characterized in that, The process of analyzing drug management data based on drug entry and storage information to obtain drug management analysis data includes: Obtain preset medication information and extract medication features to obtain medication feature extraction data; The medication feature extraction data is matched with the drug information of each small box in the drug box control network to obtain drug information matching data. Based on the extracted medication features, the corresponding boxes of the drug information matching data are associated to obtain medication association combination data. Obtain preset medication plan data, and generate a medication control list based on the preset medication plan data and medication association combination data; The medication control list is the data for drug management analysis.

6. The intelligent pillbox control method according to claim 4, characterized in that, The step of performing drug box control analysis based on drug management analysis data to obtain drug box control analysis data includes: Based on drug management analysis data, extract the corresponding dosing time, dosing interval, related drug combinations and small box interval codes for each drug to obtain drug extraction information; Based on the drug extraction information, select the small boxes corresponding to drugs that need to be taken during the same medication period, have related effects, or need to be taken in sequence, and determine which small boxes need to be connected. The controller controls the series or parallel connection of the boxes to be connected, configures the signal linkage channels between the boxes, and obtains the connection control data. Based on the connectivity control data and the spatial overlay layout of the medicine box combination, a coordinate system for the position of the small box is established, and the physical location, interval affiliation and signal association of each small box that needs to be connected are marked, and a summary location table of medicine connectivity is generated. Based on the drug connectivity summary location table, the target drug flip-top box corresponding to each medication time period is located, and a flip-top control strategy is configured for each target box. The controller issues flip-top control commands, collects real-time flip-top status data of the small box, and generates box control analysis data.

7. The intelligent pillbox control method according to claim 1, characterized in that, S3 includes: Obtain medicine box feedback information based on the medicine box control information; Analyze the medication feedback status based on the information from the medicine box to obtain medication feedback status data; Compare and analyze the medication feedback status data with the medicine box control information to obtain medication comparison analysis data; Determine the types of abnormal data based on the comparative analysis of medication use data; By comparing and contrasting abnormal data, anomalies can be located and anomaly warning control can be triggered to obtain medication anomaly warning information.

8. The intelligent pillbox control method according to claim 7, characterized in that, The step of analyzing medication feedback status based on the feedback information from the medicine box to obtain medication feedback status data includes: Based on the preset medication time cycle and reminder time nodes, the medicine box feedback information is divided into time sequence feedback information in different time segments; The preset medication execution standards in the medicine box control information are retrieved based on the timing feedback information; The information is matched one by one based on the time-series feedback information and the medication implementation standards; During the matching process, it is determined whether the flipping action, medicine retrieval behavior and reminder response in each time segment meet the preset requirements, and the time sequence status determination information is obtained. Feature extraction is performed on the temporal state determination information to extract the core features corresponding to the determination results of each time segment; The extracted core features are standardized, encoded, and stored in a structured manner to obtain temporal state feature extraction information; The extracted temporal state features are the medication feedback state data.

9. The intelligent pillbox control method according to claim 7, characterized in that, The step of comparing and analyzing medication feedback status data with medicine box control information to obtain medication comparison analysis data includes: By comparing medication feedback status data with medicine box control data from multiple dimensions, multi-dimensional comparison data is obtained. The multi-dimensional comparison data is compared with the corresponding multi-dimensional comparison threshold to obtain the multi-dimensional comparison results. Based on the results of multi-dimensional comparison, normal and abnormal information in each dimension are determined.

10. A smart pillbox control system, characterized in that, The system includes: The pillbox network establishment module is used to combine and connect pillboxes and establish a transmission channel to obtain smart pillboxes. The module also obtains the pillbox control network based on the smart pillboxes and the mobile APP. The medicine box management and control analysis module is used to perform medicine management analysis based on the medicine box control network, and then perform medicine box control analysis to obtain medicine box control analysis data. The control status feedback and early warning module is used to perform comparative analysis and early warning of medication control status based on the medicine box control analysis data, and to obtain early warning information of medication abnormalities.

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