System

Abstract

To provide a system integrally performs information provision on medicine, interaction check, assistance in health management, and pharmacy guidance.SOLUTION: A system comprises a medicine information collection unit, a medicine information provision unit, a check unit, an interaction information provision unit, a measurement unit, a management unit, a pharmacy information collection unit, and a guidance unit. The medicine information collection unit collects information on medicine. The medicine information provision unit provides a user with medicine information to be administered to the user. The check unit checks the interaction of a plurality of kinds of medicine when the medicine to be administered includes a plurality of kinds. The interaction information provision unit provides the user with the result of check by the check unit. The measurement unit measures information pertaining to the body of the user. The management unit provides the user with concrete information or advice regarding health on the basis of measured information. The pharmacy information collection unit collects information in a pharmacy. The guidance unit conducts concrete guidance in the pharmacy on the basis of collected information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including a description and related instruction sentence regarding the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology did not integrate functions such as providing drug information, checking drug interactions, health management support, and pharmacy guidance, resulting in low convenience for users.

[0005] The system according to the embodiment aims to provide drug information, drug interaction checks, health management support, and pharmacy guidance in an integrated manner. [Means for solving the problem]

[0006] The system according to the embodiment includes a drug information collecting unit, a drug information providing unit, a check unit, an interaction information providing unit, a measurement unit, a management unit, a pharmacy information collecting unit, and a guidance unit. The drug information collecting unit collects drug information. The drug information providing unit provides the user with information on drugs to be taken by the user based on the information collected by the drug information collecting unit. When the user is to take multiple drugs, the check unit checks interactions between the multiple drugs based on the information collected by the drug information collecting unit. The interaction information providing unit provides the user with the check result by the check unit. The measurement unit measures information about the user's body. The management unit provides the user with specific information or advice about health based on the information measured by the measurement unit. The pharmacy information collecting unit collects information within the pharmacy. The guidance unit provides specific guidance within the pharmacy based on the information collected by the pharmacy information collecting unit. Effect of the Invention

[0007] The system according to the embodiment can provide drug information, check for drug interactions, support health management, and provide pharmacy guidance in an integrated manner. [Brief description of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7]FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., voice and / or text). Display 40A displays visible information such as text and images according to instructions from processor 46. Speaker 40B outputs voice according to instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0024] As shown in Fig. 2, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific process program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Also, the data processing device 12 may be a server device, or may be a terminal device (e.g., a mobile phone, a robot, a home appliance, etc.) owned by a user. Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The agent system according to the embodiment of the present invention is a system that provides and explains medicines, checks drug interactions, supports health management, and provides pharmacy guidance. This agent system collects information about medicines and provides it to the user. Next, when a user is taking multiple medicines, it checks drug interactions and provides the results to the user. In addition, it measures the user's physical information and provides health information and advice. In addition, it collects information about the pharmacy and provides guidance about the pharmacy. For example, it collects information such as the type of medicine, its effect, how to take it, and side effects. This makes it possible to provide the user with appropriate drug information. Next, when a user is taking multiple medicines, it checks drug interactions. For example, when multiple medicines are taken at the same time, if there is a risk of side effects or interactions, the agent can warn the user and encourage the user to consult a doctor or pharmacist. In addition, it measures the user's physical information. For example, it measures information such as height, weight, blood pressure, and blood sugar level. This makes it possible to grasp the user's health condition and provide appropriate advice. In addition, it collects information about the pharmacy and provides guidance about the pharmacy. For example, it can provide guidance about products and services in the pharmacy, guidance about facilities, and guidance about waiting times. This allows the agent system to efficiently provide and explain medicines, check for drug interactions, support health management, and guide users to pharmacies, improving user convenience. For example, the agent can provide health information and health quizzes to make effective use of waiting time at the pharmacy. It is also possible to provide customized information based on the user's past medical history. Furthermore, by having an interface that visually displays the risk of interactions, it is possible to provide information to the user in an easy-to-understand manner. This allows the agent system to efficiently provide and explain medicines, check for drug interactions, support health management, and guide users to pharmacies.

[0029] The agent system according to the embodiment includes a drug information collecting unit, a drug information providing unit, a check unit, an interaction information providing unit, a measurement unit, a management unit, a pharmacy information collecting unit, and a guidance unit. The drug information collecting unit collects drug information. The drug information collecting unit collects information such as the type of drug, effects, how to take the drug, and side effects. The drug information collecting unit can acquire information from a database. The drug information collecting unit can also measure information using a sensor. The drug information providing unit provides information on drugs to be taken by the user based on the information collected by the drug information collecting unit. The drug information providing unit provides information by, for example, a screen display, voice guidance, or email transmission. When there are multiple drugs to be taken by the user, the check unit checks interactions between multiple drugs based on the information collected by the drug information collecting unit. The check unit checks interactions using, for example, an algorithm. The interaction information providing unit provides the check result by the check unit to the user. The interaction information providing unit provides information by, for example, a screen display, voice guidance, or email transmission. The measurement unit measures information about the user's body. The measurement unit measures information such as height, weight, blood pressure, and blood sugar level. The measurement unit can measure information using a sensor. The management unit provides health information or advice based on the information measured by the measurement unit. The management unit provides information by, for example, a screen display, voice guidance, or email transmission. The pharmacy information collection unit collects information within the pharmacy. The pharmacy information collection unit collects information on products, services, and facilities within the pharmacy. The pharmacy information collection unit can acquire information from a database. The guidance unit provides guidance within the pharmacy based on the information collected by the pharmacy information collection unit. The guidance unit provides guidance by, for example, a screen display, voice guidance, or email transmission. As a result, the agent system according to the embodiment can efficiently provide and explain medicines, check for drug interactions, support health management, and guide the pharmacy.

[0030] The drug information collecting unit collects drug information. The drug information collecting unit collects information such as the type of drug, its effects, how to take it, and side effects. Specifically, the drug information collecting unit can acquire information from a pharmaceutical database or an electronic medical record system of a medical institution. This makes it possible to always hold the latest drug information and provide it to the user. The drug information collecting unit can also measure information using a sensor. For example, a drug ingredient analysis sensor can be used to measure the ingredients and concentration of a drug in real time and add the information to the database. Furthermore, the drug information collecting unit can also collect information from reliable medical information sites and academic papers on the Internet and update the database. This allows the drug information collecting unit to build a foundation for collecting comprehensive drug information from a wide range of information sources and providing it to users.

[0031] The drug information providing unit provides information on the drug to be taken by the user based on the information collected by the drug information collecting unit. The drug information providing unit provides information by, for example, a screen display, voice guidance, or email transmission. Specifically, when a user accesses the drug information providing unit using a smartphone or tablet, detailed information on the drug is displayed on the screen. This includes the name of the drug, its effects, how to take it, side effects, and precautions. In addition, by using the voice guidance function, the information can be provided in an easy-to-understand manner even for visually impaired people and the elderly. Furthermore, if the user wishes, it is also possible to send drug information by email or SMS so that the information can be checked at any time. In this way, the drug information providing unit can quickly and accurately provide the drug information required by the user and support appropriate drug use.

[0032] The checking unit checks interactions between multiple drugs based on the information collected by the drug information collecting unit when the user is taking multiple drugs. The checking unit checks interactions using, for example, an algorithm. Specifically, the checking unit implements an algorithm that evaluates the risk of interactions based on the ingredients and mechanism of action of drugs. This algorithm is built based on interaction information obtained from existing pharmaceutical databases and academic papers, and detects potential interactions for combinations of drugs taken by the user. For example, it can detect cases where the effectiveness of a specific drug decreases or side effects increase when used in combination with other drugs, and issue a warning to the user. In this way, the checking unit can support the user in taking drugs safely and minimize the risks of drug interactions.

[0033] The interaction information providing unit provides the user with the check result by the checking unit. The interaction information providing unit provides information by, for example, a screen display, voice guidance, email transmission, or the like. Specifically, the risk of an interaction detected by the checking unit is notified to the user's device in real time. Detailed information on the interaction and recommended measures are displayed on the screen, and are provided in a format that is easy for the user to understand. By using the voice guidance function, information can be provided that is easy to understand for visually impaired people and the elderly. It is also possible to send interaction information by email or SMS so that the user can check it at any time. Furthermore, the interaction information providing unit provides information that is useful when the user consults a doctor or pharmacist, and supports the user in receiving appropriate advice. In this way, the interaction information providing unit can quickly and accurately grasp information on drug interactions and support the user in taking medicines safely.

[0034] The measurement unit measures information about the user's body. The measurement unit measures information such as height, weight, blood pressure, and blood glucose level. Specifically, the measurement unit measures this information in real time using a wearable device worn by the user or a home health management device. For example, a smart watch or fitness tracker can be used to continuously monitor heart rate and blood pressure and collect data. In addition, home devices such as a blood glucose meter and a weight scale can be used to periodically obtain data and transmit it to the measurement unit. This allows the measurement unit to build a foundation for constantly understanding the user's health condition and providing appropriate advice and warnings as necessary. Furthermore, the measurement unit can store the collected data in a cloud server and cooperate with other systems and medical institutions to realize more advanced health management.

[0035] The management unit provides information or advice on health based on the information measured by the measurement unit. The management unit provides information by, for example, a screen display, voice guidance, or email transmission. Specifically, the management unit analyzes the data transmitted from the measurement unit and evaluates the user's health condition. For example, the management unit monitors fluctuations in blood pressure and blood sugar levels, and issues a warning to the user when an abnormality is detected. The management unit also provides advice on diet and exercise according to the health condition, and supports the user in maintaining his or her health. Furthermore, the management unit can grasp trends in the health condition and predict future risks by storing the user's health data for the long term and comparing it with past data. This allows the management unit to play an important role in helping the user maintain their health and prevent and detect diseases early.

[0036] The pharmacy information collecting unit collects information within the pharmacy. The pharmacy information collecting unit collects, for example, information on products, services, and facilities within the pharmacy. Specifically, the pharmacy information collecting unit can obtain information from the inventory management system and POS system of the pharmacy and update it in real time. This makes it possible to always grasp the latest inventory status, prices, and sale information of products within the pharmacy. In addition, information on services and facilities provided within the pharmacy can be collected and provided to the user. For example, information such as health consultations and vaccination schedules performed within the pharmacy, and the presence or absence of barrier-free facilities is collected and provided in a form that is easy for the user to use. This allows the pharmacy information collecting unit to support users in efficiently using the pharmacy and contribute to improving the pharmacy's services.

[0037] The guidance unit provides guidance within the pharmacy based on the information collected by the pharmacy information collection unit. The guidance unit provides guidance, for example, by a method such as a screen display, voice guidance, or email transmission. Specifically, when a user visits a pharmacy and accesses the guidance unit using a smartphone or tablet, a map of the pharmacy, product locations, and service locations are displayed. This allows the user to quickly find the desired product or service. In addition, the voice guidance function can be used to provide guidance that is easy to understand for visually impaired people and elderly people. Furthermore, it is also possible to transmit sale information and campaign information within the pharmacy by email or SMS, allowing the user to efficiently obtain information. In this way, the guidance unit can support the user to use the pharmacy comfortably and contribute to promoting the use of the pharmacy.

[0038] The drug information collecting unit can collect information on the type, effect, method of taking, and side effects of the drug. The types of drugs include, for example, prescription drugs, over-the-counter drugs, generic drugs, etc. The effects include, for example, therapeutic effects, the presence or absence of side effects, etc. The method of taking the drug includes, for example, the number of times to take the drug, the time to take the drug, and the dosage. The side effects include, for example, the frequency of occurrence, the severity, etc. In this way, by collecting information on the type, effect, method of taking the drug, and side effects, it is possible to provide appropriate drug information to the user. A part or all of the above-mentioned processing in the drug information collecting unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information collecting unit can input information on the type, effect, method of taking the drug, and side effects into AI, and the AI ​​can collect the information.

[0039] The measurement unit can measure the height, weight, blood pressure, and blood glucose level of the user. For example, a measuring device is used to measure the height. For example, a weight scale is used to measure the weight. For example, a blood pressure monitor is used to measure the blood glucose level. For example, a blood glucose meter is used to measure the blood glucose level. In this way, by measuring the height, weight, blood pressure, and blood glucose level of the user, the user's health condition can be understood and appropriate advice can be provided. A part or all of the above-mentioned processing in the measurement unit may be performed, for example, using AI, or may be performed without using AI. For example, the measurement unit can input data on the user's height, weight, blood pressure, and blood glucose level to AI, which can analyze the data.

[0040] The pharmacy information collection unit can collect information on products, services, and facilities in the pharmacy. Product information includes, for example, product names, prices, and inventory status. Service information includes, for example, the types of services provided, terms of use, and the like. Facility information includes, for example, the location of the facility, available hours, and the like. In this way, by collecting information on products, services, and facilities in the pharmacy, it is possible to provide guidance to the user in the pharmacy. Some or all of the above-mentioned processing in the pharmacy information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the pharmacy information collection unit can input information on products, services, and facilities in the pharmacy into AI, which can collect the information.

[0041] The drug information providing unit can provide specific health information or health-related quizzes to the user during the waiting time at the pharmacy. The health information includes, for example, the latest research results on health and advice for maintaining health. The health quizzes include, for example, the format of the quiz and the frequency of questions. This makes it possible to effectively utilize the waiting time at the pharmacy and provide the user with health information and quizzes, thereby increasing the user's health awareness. Some or all of the above-mentioned processing in the drug information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information providing unit can input the health information or the content of the quiz into AI, and the AI ​​can provide the information.

[0042] The interaction information providing unit can issue a specific warning to the user when the checking unit determines that an interaction exists. The warning can include, for example, the contents of a warning message, the timing of the warning, and the like. By issuing a warning to the user when an interaction exists, the user can take appropriate action. Some or all of the above-mentioned processing in the interaction information providing unit can be performed, for example, using AI, or can be performed without using AI. For example, the interaction information providing unit can input the risk of an interaction to AI, which can then issue a warning.

[0043] The drug information providing unit can provide customized information based on the user's past medical history. The customized information includes, for example, recommended drugs based on the past medical history, individual drug intake schedules, and the like. This allows more appropriate drug information to be provided by providing customized information based on the user's past medical history. Some or all of the above-mentioned processing in the drug information providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the drug information providing unit can input the user's past medical history into AI, which then provides customized information.

[0044] The interaction information providing unit can suggest an alternative drug when the checking unit determines that an interaction exists. Alternative drugs include, for example, drugs with a low risk of interaction and drugs with equivalent effects. By suggesting an alternative drug when an interaction exists, the user can take the drug safely. Some or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit can input the risk of an interaction into AI, which can then suggest an alternative drug.

[0045] The interaction information providing unit may have an interface that visually displays the risk of an interaction. The visual display may include, for example, a graph, a chart, an icon, and the like. This makes it easier for a user to understand the risk of an interaction by visually displaying the risk. Some or all of the above-described processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit may input the risk of an interaction to an AI, which may visually display it.

[0046] The drug information collection unit can collect information on the manufacturer and production lot of the drug and use it for quality control. The manufacturer information includes, for example, the name of the manufacturer and the production location. The production lot information includes, for example, the lot number and the production date. In this way, collecting the manufacturer and production lot information of the drug can be useful for quality control. Some or all of the above-mentioned processing in the drug information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information collection unit can input the manufacturer and production lot information to AI, and the AI ​​can collect the information.

[0047] The drug information collecting unit can collect information on storage conditions and expiration dates of drugs and propose an appropriate storage method. Storage conditions include, for example, temperature, humidity, and light conditions. Expiration date information includes, for example, expiration date and expiration date after opening. In this way, by collecting storage conditions and expiration date information of drugs, an appropriate storage method can be proposed. Some or all of the above-mentioned processing in the drug information collecting unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information collecting unit can input storage conditions and expiration date information to AI, which can collect information.

[0048] The drug information collection unit can collect drug price information and suggest drugs with high cost performance. The price information includes, for example, the market price of the drug, discount information, etc. The evaluation of cost performance includes, for example, the balance between effect and price, long-term cost, etc. By collecting drug price information, it is possible to suggest drugs with high cost performance. Some or all of the above-mentioned processing in the drug information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information collection unit can input price information into AI, which then collects the information.

[0049] The drug information collection unit can collect user reviews and ratings of drugs and provide them to the user. User reviews include, for example, the reliability of the reviews and rating criteria. Ratings include, for example, star ratings and comments. By collecting user reviews and ratings of drugs, users can refer to them when selecting drugs. Some or all of the above-mentioned processing in the drug information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information collection unit can input user reviews and ratings into AI, which can collect information.

[0050] The drug information providing unit can provide the latest research results regarding the effects and side effects of drugs. The latest research results include, for example, academic papers, clinical trial results, and the like. This allows the user to obtain the latest information by providing the latest research results regarding the effects and side effects of drugs. Some or all of the above-mentioned processing in the drug information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information providing unit can input the latest research results into AI, which then provides the information.

[0051] The medicine information providing unit can provide an individually customized medicine taking schedule. The taking schedule includes, for example, taking time, taking amount, taking interval, etc. By providing an individually customized medicine taking schedule, the user can take medicine according to an optimal schedule. Some or all of the above-mentioned processing in the medicine information providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the medicine information providing unit can input a taking schedule that matches the user's life rhythm to AI, and the AI ​​can provide the customized schedule.

[0052] The medicine information providing unit can provide the medicine taking method by video or audio. The provision of the video or audio includes, for example, the length of the video, the content of the audio, and the like. By providing the medicine taking method by video or audio, the user can easily understand visually and aurally. A part or all of the above-mentioned processing in the medicine information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the medicine information providing unit can input the video or audio of the medicine taking method to AI, and the AI ​​can provide the information.

[0053] The drug information providing unit provides drug information in multiple languages, and can also accommodate foreign users. Multilingual support includes, for example, the types of languages ​​supported and the accuracy of translation. As a result, drug information can be provided in multiple languages, and foreign users can also be accommodated. Some or all of the above-mentioned processing in the drug information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information providing unit can input drug information in multiple languages ​​to AI, and the AI ​​can provide the information.

[0054] The check unit can compare the drug interaction risk with past data to evaluate it. The comparison of past data includes, for example, past interaction cases, risk evaluation criteria, and the like. This makes it possible to identify high-risk interactions by comparing the drug interaction risk with past data to evaluate it. Some or all of the above-mentioned processing in the check unit may be performed, for example, using AI, or may be performed without using AI. For example, the check unit can input past data into AI, which can evaluate the risk.

[0055] The check unit can monitor the drug interaction risk in real time and immediately notify if there is an abnormality. Real-time monitoring includes, for example, the frequency of monitoring and the type of sensor used. In this way, by monitoring the drug interaction risk in real time, it is possible to immediately respond if an abnormality occurs. Some or all of the above-mentioned processing in the check unit may be performed, for example, using AI, or may be performed without using AI. For example, the check unit can input real-time data to AI, which can detect and notify an abnormality.

[0056] The check unit can also check interactions with foods and supplements. Checking interactions includes, for example, interaction risk assessment, check items, and the like. By checking interactions with foods and supplements, a more comprehensive interaction risk can be evaluated. Some or all of the above-mentioned processing in the check unit may be performed, for example, using AI, or may be performed without using AI. For example, the check unit can input information about foods and supplements into AI, which can check interactions.

[0057] The check unit can visually display the drug interaction risk in a graph or chart. The visual display includes, for example, the type of graph to be used, the contents of the data to be displayed, and the like. By visually displaying the drug interaction risk, the user can easily understand the risk. Some or all of the above-mentioned processing in the check unit may be performed, for example, using AI, or may be performed without using AI. For example, the check unit can input data on the interaction risk into AI, which then displays it in a graph or chart.

[0058] The interaction information providing unit can provide a detailed explanation of the interaction risk to deepen understanding. The detailed explanation includes, for example, the cause and effect of the risk, and specific measures to avoid the risk. By providing a detailed explanation of the interaction risk, the user can easily understand the risk. Some or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit can input a detailed explanation of the risk to the AI, and the AI ​​can provide the information.

[0059] The interaction information providing unit can provide specific guidelines for behavior to avoid interaction risks. The guidelines for behavior include, for example, advice on lifestyle habits, diet and exercise, and the like. By providing specific guidelines for behavior to avoid interaction risks, the user can easily avoid the risks. Some or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit can input the guidelines for behavior to AI, and the AI ​​can provide the information.

[0060] The interaction information providing unit can suggest alternative drugs to avoid interaction risks. Alternative drugs include, for example, drugs with a low risk of interaction and drugs with equivalent effects. By suggesting alternative drugs to avoid interaction risks, the user can take the drug safely. Some or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit can input information on alternative drugs to AI, which can then make the suggestion.

[0061] The interaction information providing unit can provide lifestyle advice for avoiding interaction risks. The lifestyle advice includes, for example, improving diet, recommending exercise, and advice on sleep and stress management. By providing lifestyle advice for avoiding interaction risks, the user can easily avoid the risks. Some or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit can input lifestyle advice to AI, which provides the information.

[0062] The measurement unit can detect anomalies by comparing the measurement data with past data. Comparison of past data includes, for example, past measurement values, abnormality criteria, and the like. This allows for early detection of abnormalities by comparing the measurement data with past data. Some or all of the above-mentioned processing in the measurement unit may be performed, for example, using AI, or may be performed without using AI. For example, the measurement unit can input past data into AI, which can detect abnormalities.

[0063] The measurement unit can store the measurement data in the cloud and share it with a doctor. Cloud storage and sharing include, for example, data security, timing of sharing, and the like. By storing the measurement data in the cloud and sharing it with a doctor, the doctor can make an appropriate diagnosis. Some or all of the above-mentioned processing in the measurement unit may be performed, for example, using AI, or may be performed without using AI. For example, the measurement unit can store the measurement data in the cloud and AI can share it with a doctor.

[0064] The measurement unit can visually display the measurement data in a graph or chart. The visual display includes, for example, the type of graph to be used, the contents of the data to be displayed, and the like. By visually displaying the measurement data, the user can easily understand the data. Some or all of the above-mentioned processing in the measurement unit may be performed, for example, using AI, or may be performed without using AI. For example, the measurement unit can input the measurement data to AI, which then displays it in a graph or chart.

[0065] The measurement unit can display the measurement data in multiple languages ​​to accommodate foreign users. Multilingual support includes, for example, the types of languages ​​supported and the accuracy of translation. This allows the measurement data to be displayed in multiple languages ​​to accommodate foreign users. Some or all of the above-mentioned processing in the measurement unit may be performed using, for example, AI, or may be performed without using AI. For example, the measurement unit can input the measurement data in multiple languages ​​to AI, and the AI ​​can provide information.

[0066] The management unit can provide health information by individually customizing it. The customized health information includes, for example, information based on the user's health condition, lifestyle habits, and past health data. By providing the health information by individually customizing it, optimal information can be provided to the user. Some or all of the above-mentioned processing in the management unit may be performed, for example, using AI, or may be performed without using AI. For example, the management unit can input the user's health data into AI, which can provide customized information.

[0067] The management unit can periodically update the health information to provide the latest information. Periodic updates include, for example, the latest research results, information based on the user's health condition, and the like. By periodically updating the health information, the latest information can be provided to the user. Some or all of the above-mentioned processing in the management unit can be performed, for example, using AI, or can be performed without using AI. For example, the management unit can input the health information into AI, which can periodically update the health information.

[0068] The management unit can provide the health information in the form of video or audio. Providing the video or audio includes, for example, the length of the video and the content of the audio. By providing the health information in the form of video or audio, the user can easily understand the information visually and audibly. Some or all of the above-mentioned processing in the management unit may be performed, for example, using AI, or may be performed without using AI. For example, the management unit can input the video or audio of the health information into AI, and the AI ​​can provide the information.

[0069] The management unit can provide health information in multiple languages ​​and can also accommodate foreign users. Multilingual support includes, for example, the types of languages ​​supported and the accuracy of translation. As a result, health information can be provided in multiple languages, making it possible to accommodate foreign users. Some or all of the above-mentioned processing in the management unit may be performed, for example, using AI, or may be performed without using AI. For example, the management unit can input health information in multiple languages ​​to AI, and the AI ​​can provide the information.

[0070] The pharmacy information collecting unit can collect pharmacy inventory information in real time. Real-time collection includes, for example, the update frequency of inventory information and the type of sensor used. This allows the pharmacy inventory information to be collected in real time, thereby providing the user with the latest inventory information. Some or all of the above-mentioned processing in the pharmacy information collecting unit may be performed, for example, using AI, or may be performed without using AI. For example, the pharmacy information collecting unit can input inventory information into AI, which can collect information in real time.

[0071] The pharmacy information collection unit can collect pharmacy business hours and holiday information and provide it to the user. Business hours and holiday information includes, for example, the start and end times of business hours and holiday dates. In this way, by collecting pharmacy business hours and holiday information, the most suitable pharmacy can be suggested to the user. Some or all of the above-mentioned processing in the pharmacy information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the pharmacy information collection unit can input business hours and holiday information into AI, which can collect the information.

[0072] The pharmacy information collecting unit can collect pharmacy promotion information and provide it to the user. Promotion information includes, for example, discount information, benefit information, and the like. In this way, by collecting pharmacy promotion information, advantageous information can be provided to the user. Some or all of the above-mentioned processing in the pharmacy information collecting unit may be performed, for example, using AI, or may be performed without using AI. For example, the pharmacy information collecting unit can input promotion information to AI, which can collect the information.

[0073] The pharmacy information collection unit can collect reviews and ratings of pharmacies and provide them to the user. The review information includes, for example, the reliability of the review and the rating criteria. The rating includes, for example, star ratings and comments. By collecting pharmacy reviews and ratings, the user can select a highly reliable pharmacy. Some or all of the above-mentioned processing in the pharmacy information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the pharmacy information collection unit can input the reviews and ratings into AI, which can collect the information.

[0074] The guidance unit can provide real-time guidance on the congestion status in the pharmacy. The real-time guidance includes, for example, the frequency of collecting congestion status and the type of sensor used. This allows the user to select the optimal time to visit by providing real-time guidance on the congestion status in the pharmacy. Some or all of the above-mentioned processing in the guidance unit may be performed using, for example, AI, or may be performed without using AI. For example, the guidance unit can input the congestion status into AI, which can provide guidance in real time.

[0075] The guidance unit can provide guidance on the location of a specific product in the pharmacy. Guidance includes, for example, displaying the location of the product on a map and providing guidance by voice. This makes it easier for the user to find the product by providing guidance on the location of the specific product in the pharmacy. Some or all of the above-mentioned processing in the guidance unit may be performed, for example, using AI, or may be performed without using AI. For example, the guidance unit can input product location information into AI, which can provide guidance.

[0076] The guidance unit can provide information about services and events in the pharmacy. The guidance includes, for example, real-time updates of service information and event information. This makes it easier for the user to understand information in the pharmacy by providing information about services and events in the pharmacy. Some or all of the above-mentioned processing in the guidance unit may be performed using, for example, AI, or may be performed without using AI. For example, the guidance unit can input service and event information into AI, which can provide guidance.

[0077] The guidance unit provides guidance within the pharmacy in multiple languages, and can also accommodate foreign users. Multilingual support includes, for example, the types of languages ​​supported and the accuracy of translation. This allows guidance within the pharmacy to be provided in multiple languages, making it possible to accommodate foreign users. Some or all of the above-mentioned processing in the guidance unit may be performed, for example, using AI, or may be performed without using AI. For example, the guidance unit can input guidance information in multiple languages ​​to AI, and the AI ​​can provide the information.

[0078] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0079] The drug information collection unit can collect information on the manufacturer and manufacturing lot of the drug and use it for quality control. For example, by collecting information such as the name of the manufacturer, the manufacturing location, the lot number, and the manufacturing date, the quality control of the drug can be strengthened. In addition, the drug information providing unit can provide customized information based on the user's past medical history. For example, by providing recommended drugs based on the past medical history and individual drug taking schedules, more appropriate drug information can be provided to the user. Furthermore, the drug interaction information providing unit can suggest an alternative drug if the checking unit determines that there is an interaction. For example, by suggesting drugs with a low risk of interaction and drugs with equivalent effects, the user can take the drug safely.

[0080] The pharmacy information collection unit can collect pharmacy inventory information in real time. For example, by increasing the frequency of updating the inventory information, the latest inventory information can be provided to the user. The pharmacy information collection unit can also collect pharmacy business hours and holiday information and provide it to the user. For example, by collecting information such as the start and end times of business hours and the dates of holidays, the most suitable pharmacy can be suggested to the user. Furthermore, the pharmacy information collection unit can collect pharmacy promotion information and provide it to the user. For example, by collecting discount information, special offer information, and the like, advantageous information can be provided to the user.

[0081] The guidance unit can provide information on the congestion status in the pharmacy in real time. For example, by increasing the frequency of collection of the congestion status, the user can be allowed to select the optimal time to visit the pharmacy. Furthermore, the guidance unit can provide information on the location of a specific product in the pharmacy. For example, the location of the product can be displayed on a map or provided through audio guidance, making it easier for the user to find the product. Furthermore, the guidance unit can provide information on services and events in the pharmacy. For example, by updating service information and event information in real time, the user can easily grasp information in the pharmacy.

[0082] The management unit can provide health information by customizing it individually. For example, by providing information based on the user's health condition, lifestyle habits, and past health data, it is possible to provide optimal information to the user. Furthermore, the management unit can periodically update the health information to provide the latest information. For example, by periodically updating the latest research results, information based on the user's health condition, and the like, it is possible to provide the user with the latest information. Furthermore, the management unit can provide the health information in the form of video and audio. For example, by adjusting the length of the video, the content of the audio, and the like, it is possible to make it easier for the user to understand visually and audibly.

[0083] The checking unit can compare the drug interaction risk with past data to evaluate it. For example, by evaluating it using past interaction cases, risk evaluation criteria, etc., it is possible to identify interactions with high risk. In addition, the checking unit can monitor the drug interaction risk in real time and immediately notify if there is an abnormality. For example, by increasing the frequency of monitoring, it is possible to immediately respond if an abnormality occurs. Furthermore, the checking unit can also check interactions with foods and supplements. For example, by collecting information on foods and supplements and evaluating the risk of interactions, it is possible to evaluate the interaction risk more comprehensively.

[0084] The process flow of the first embodiment will be briefly described below.

[0085] Step 1: The drug information collecting unit collects drug information. The drug information collecting unit collects information such as the type of drug, its effects, how to take it, and side effects. The drug information collecting unit can obtain information from a database. The drug information collecting unit can also measure information using a sensor. Step 2: The medicine information providing unit provides information on medicines to be taken by the user based on the information collected by the medicine information collecting unit. The medicine information providing unit provides information by, for example, a screen display, a voice guide, an email transmission, or the like. Step 3: When the user is taking multiple medicines, the checking unit checks for interactions between the multiple medicines based on the information collected by the medicine information collecting unit. The checking unit checks for interactions using, for example, an algorithm. Step 4: The interaction information providing unit provides the user with the results of the check made by the checking unit. The interaction information providing unit provides information by, for example, a screen display, a voice guide, or an email transmission. Step 5: The measurement unit measures information about the user's body. For example, the measurement unit measures information such as height, weight, blood pressure, and blood sugar level. The measurement unit can measure the information using a sensor. Step 6: The management unit provides health-related information or advice based on the information measured by the measurement unit. The management unit provides the information by, for example, displaying the information on a screen, providing audio guidance, sending an email, or the like. Step 7: The pharmacy information collecting unit collects information within the pharmacy. The pharmacy information collecting unit collects, for example, information on products, services, and facilities within the pharmacy. The pharmacy information collecting unit can obtain information from a database. Step 8: The guidance unit provides guidance within the pharmacy based on the information collected by the pharmacy information collection unit. The guidance unit provides guidance by, for example, a screen display, audio guidance, email transmission, or the like.

[0086] (Example 2) The agent system according to the embodiment of the present invention is a system that provides and explains medicines, checks drug interactions, supports health management, and provides pharmacy guidance. This agent system collects information about medicines and provides it to the user. Next, when a user is taking multiple medicines, it checks drug interactions and provides the results to the user. In addition, it measures the user's physical information and provides health information and advice. In addition, it collects information about the pharmacy and provides guidance about the pharmacy. For example, it collects information such as the type of medicine, its effect, how to take it, and side effects. This makes it possible to provide the user with appropriate drug information. Next, when a user is taking multiple medicines, it checks drug interactions. For example, when multiple medicines are taken at the same time, if there is a risk of side effects or interactions, the agent can warn the user and encourage the user to consult a doctor or pharmacist. In addition, it measures the user's physical information. For example, it measures information such as height, weight, blood pressure, and blood sugar level. This makes it possible to grasp the user's health condition and provide appropriate advice. In addition, it collects information about the pharmacy and provides guidance about the pharmacy. For example, it can provide guidance about products and services in the pharmacy, guidance about facilities, and guidance about waiting times. This allows the agent system to efficiently provide and explain medicines, check for drug interactions, support health management, and guide users to pharmacies, improving user convenience. For example, the agent can provide health information and health quizzes to make effective use of waiting time at the pharmacy. It is also possible to provide customized information based on the user's past medical history. Furthermore, by having an interface that visually displays the risk of interactions, it is possible to provide information to the user in an easy-to-understand manner. This allows the agent system to efficiently provide and explain medicines, check for drug interactions, support health management, and guide users to pharmacies.

[0087] The agent system according to the embodiment includes a drug information collecting unit, a drug information providing unit, a check unit, an interaction information providing unit, a measurement unit, a management unit, a pharmacy information collecting unit, and a guidance unit. The drug information collecting unit collects drug information. The drug information collecting unit collects information such as the type of drug, effects, how to take the drug, and side effects. The drug information collecting unit can acquire information from a database. The drug information collecting unit can also measure information using a sensor. The drug information providing unit provides information on drugs to be taken by the user based on the information collected by the drug information collecting unit. The drug information providing unit provides information by, for example, a screen display, voice guidance, or email transmission. When there are multiple drugs to be taken by the user, the check unit checks interactions between multiple drugs based on the information collected by the drug information collecting unit. The check unit checks interactions using, for example, an algorithm. The interaction information providing unit provides the check result by the check unit to the user. The interaction information providing unit provides information by, for example, a screen display, voice guidance, or email transmission. The measurement unit measures information about the user's body. The measurement unit measures information such as height, weight, blood pressure, and blood sugar level. The measurement unit can measure information using a sensor. The management unit provides health information or advice based on the information measured by the measurement unit. The management unit provides information by, for example, a screen display, voice guidance, or email transmission. The pharmacy information collection unit collects information within the pharmacy. The pharmacy information collection unit collects information on products, services, and facilities within the pharmacy. The pharmacy information collection unit can acquire information from a database. The guidance unit provides guidance within the pharmacy based on the information collected by the pharmacy information collection unit. The guidance unit provides guidance by, for example, a screen display, voice guidance, or email transmission. As a result, the agent system according to the embodiment can efficiently provide and explain medicines, check for drug interactions, support health management, and guide the pharmacy.

[0088] The drug information collecting unit collects drug information. The drug information collecting unit collects information such as the type of drug, its effects, how to take it, and side effects. Specifically, the drug information collecting unit can acquire information from a pharmaceutical database or an electronic medical record system of a medical institution. This makes it possible to always hold the latest drug information and provide it to the user. The drug information collecting unit can also measure information using a sensor. For example, a drug ingredient analysis sensor can be used to measure the ingredients and concentration of a drug in real time and add the information to the database. Furthermore, the drug information collecting unit can also collect information from reliable medical information sites and academic papers on the Internet and update the database. This allows the drug information collecting unit to build a foundation for collecting comprehensive drug information from a wide range of information sources and providing it to users.

[0089] The drug information providing unit provides information on the drug to be taken by the user based on the information collected by the drug information collecting unit. The drug information providing unit provides information by, for example, a screen display, voice guidance, or email transmission. Specifically, when a user accesses the drug information providing unit using a smartphone or tablet, detailed information on the drug is displayed on the screen. This includes the name of the drug, its effects, how to take it, side effects, and precautions. In addition, by using the voice guidance function, the information can be provided in an easy-to-understand manner even for visually impaired people and the elderly. Furthermore, if the user wishes, it is also possible to send drug information by email or SMS so that the information can be checked at any time. In this way, the drug information providing unit can quickly and accurately provide the drug information required by the user and support appropriate drug use.

[0090] The checking unit checks interactions between multiple drugs based on the information collected by the drug information collecting unit when the user is taking multiple drugs. The checking unit checks interactions using, for example, an algorithm. Specifically, the checking unit implements an algorithm that evaluates the risk of interactions based on the ingredients and mechanism of action of drugs. This algorithm is built based on interaction information obtained from existing pharmaceutical databases and academic papers, and detects potential interactions for combinations of drugs taken by the user. For example, it can detect cases where the effectiveness of a specific drug decreases or side effects increase when used in combination with other drugs, and issue a warning to the user. In this way, the checking unit can support the user in taking drugs safely and minimize the risks of drug interactions.

[0091] The interaction information providing unit provides the user with the check result by the checking unit. The interaction information providing unit provides information by, for example, a screen display, voice guidance, email transmission, or the like. Specifically, the risk of an interaction detected by the checking unit is notified to the user's device in real time. Detailed information on the interaction and recommended measures are displayed on the screen, and are provided in a format that is easy for the user to understand. By using the voice guidance function, information can be provided that is easy to understand for visually impaired people and the elderly. It is also possible to send interaction information by email or SMS so that the user can check it at any time. Furthermore, the interaction information providing unit provides information that is useful when the user consults a doctor or pharmacist, and supports the user in receiving appropriate advice. In this way, the interaction information providing unit can quickly and accurately grasp information on drug interactions and support the user in taking medicines safely.

[0092] The measurement unit measures information about the user's body. The measurement unit measures information such as height, weight, blood pressure, and blood glucose level. Specifically, the measurement unit measures this information in real time using a wearable device worn by the user or a home health management device. For example, a smart watch or fitness tracker can be used to continuously monitor heart rate and blood pressure and collect data. In addition, home devices such as a blood glucose meter and a weight scale can be used to periodically obtain data and transmit it to the measurement unit. This allows the measurement unit to build a foundation for constantly understanding the user's health condition and providing appropriate advice and warnings as necessary. Furthermore, the measurement unit can store the collected data in a cloud server and cooperate with other systems and medical institutions to realize more advanced health management.

[0093] The management unit provides information or advice on health based on the information measured by the measurement unit. The management unit provides information by, for example, a screen display, voice guidance, or email transmission. Specifically, the management unit analyzes the data transmitted from the measurement unit and evaluates the user's health condition. For example, the management unit monitors fluctuations in blood pressure and blood sugar levels, and issues a warning to the user when an abnormality is detected. The management unit also provides advice on diet and exercise according to the health condition, and supports the user in maintaining his or her health. Furthermore, the management unit can grasp trends in the health condition and predict future risks by storing the user's health data for the long term and comparing it with past data. This allows the management unit to play an important role in helping the user maintain their health and prevent and detect diseases early.

[0094] The pharmacy information collecting unit collects information within the pharmacy. The pharmacy information collecting unit collects, for example, information on products, services, and facilities within the pharmacy. Specifically, the pharmacy information collecting unit can obtain information from the inventory management system and POS system of the pharmacy and update it in real time. This makes it possible to always grasp the latest inventory status, prices, and sale information of products within the pharmacy. In addition, information on services and facilities provided within the pharmacy can be collected and provided to the user. For example, information such as health consultations and vaccination schedules performed within the pharmacy, and the presence or absence of barrier-free facilities is collected and provided in a form that is easy for the user to use. This allows the pharmacy information collecting unit to support users in efficiently using the pharmacy and contribute to improving the pharmacy's services.

[0095] The guidance unit provides guidance within the pharmacy based on the information collected by the pharmacy information collection unit. The guidance unit provides guidance, for example, by a method such as a screen display, voice guidance, or email transmission. Specifically, when a user visits a pharmacy and accesses the guidance unit using a smartphone or tablet, a map of the pharmacy, product locations, and service locations are displayed. This allows the user to quickly find the desired product or service. In addition, the voice guidance function can be used to provide guidance that is easy to understand for visually impaired people and elderly people. Furthermore, it is also possible to transmit sale information and campaign information within the pharmacy by email or SMS, allowing the user to efficiently obtain information. In this way, the guidance unit can support the user to use the pharmacy comfortably and contribute to promoting the use of the pharmacy.

[0096] The drug information collecting unit can collect information on the type, effect, method of taking, and side effects of the drug. The types of drugs include, for example, prescription drugs, over-the-counter drugs, generic drugs, etc. The effects include, for example, therapeutic effects, the presence or absence of side effects, etc. The method of taking the drug includes, for example, the number of times to take the drug, the time to take the drug, and the dosage. The side effects include, for example, the frequency of occurrence, the severity, etc. In this way, by collecting information on the type, effect, method of taking the drug, and side effects, it is possible to provide appropriate drug information to the user. A part or all of the above-mentioned processing in the drug information collecting unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information collecting unit can input information on the type, effect, method of taking the drug, and side effects into AI, and the AI ​​can collect the information.

[0097] The measurement unit can measure the height, weight, blood pressure, and blood glucose level of the user. For example, a measuring device is used to measure the height. For example, a weight scale is used to measure the weight. For example, a blood pressure monitor is used to measure the blood glucose level. For example, a blood glucose meter is used to measure the blood glucose level. In this way, by measuring the height, weight, blood pressure, and blood glucose level of the user, the user's health condition can be understood and appropriate advice can be provided. A part or all of the above-mentioned processing in the measurement unit may be performed, for example, using AI, or may be performed without using AI. For example, the measurement unit can input data on the user's height, weight, blood pressure, and blood glucose level to AI, which can analyze the data.

[0098] The pharmacy information collection unit can collect information on products, services, and facilities in the pharmacy. Product information includes, for example, product names, prices, and inventory status. Service information includes, for example, the types of services provided, terms of use, and the like. Facility information includes, for example, the location of the facility, available hours, and the like. In this way, by collecting information on products, services, and facilities in the pharmacy, it is possible to provide guidance to the user in the pharmacy. Some or all of the above-mentioned processing in the pharmacy information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the pharmacy information collection unit can input information on products, services, and facilities in the pharmacy into AI, which can collect the information.

[0099] The drug information providing unit can provide specific health information or health-related quizzes to the user during the waiting time at the pharmacy. The health information includes, for example, the latest research results on health and advice for maintaining health. The health quizzes include, for example, the format of the quiz and the frequency of questions. This makes it possible to effectively utilize the waiting time at the pharmacy and provide the user with health information and quizzes, thereby increasing the user's health awareness. Some or all of the above-mentioned processing in the drug information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information providing unit can input the health information or the content of the quiz into AI, and the AI ​​can provide the information.

[0100] The interaction information providing unit can issue a specific warning to the user when the checking unit determines that an interaction exists. The warning can include, for example, the contents of a warning message, the timing of the warning, and the like. By issuing a warning to the user when an interaction exists, the user can take appropriate action. Some or all of the above-mentioned processing in the interaction information providing unit can be performed, for example, using AI, or can be performed without using AI. For example, the interaction information providing unit can input the risk of an interaction to AI, which can then issue a warning.

[0101] The drug information providing unit can provide customized information based on the user's past medical history. The customized information includes, for example, recommended drugs based on the past medical history, individual drug intake schedules, and the like. This allows more appropriate drug information to be provided by providing customized information based on the user's past medical history. Some or all of the above-mentioned processing in the drug information providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the drug information providing unit can input the user's past medical history into AI, which then provides customized information.

[0102] The interaction information providing unit can suggest an alternative drug when the checking unit determines that an interaction exists. Alternative drugs include, for example, drugs with a low risk of interaction and drugs with equivalent effects. By suggesting an alternative drug when an interaction exists, the user can take the drug safely. Some or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit can input the risk of an interaction into AI, which can then suggest an alternative drug.

[0103] The interaction information providing unit may have an interface that visually displays the risk of an interaction. The visual display may include, for example, a graph, a chart, an icon, and the like. This makes it easier for a user to understand the risk of an interaction by visually displaying the risk. Some or all of the above-described processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit may input the risk of an interaction to an AI, which may visually display it.

[0104] The drug information collecting unit can estimate the user's emotion and adjust the timing of collecting drug information based on the estimated user's emotion. Emotion estimation includes, for example, facial expression recognition, voice analysis, behavior analysis, etc. Adjustment of the collection timing includes, for example, timing adjustment according to the user's stress level, etc. As a result, by adjusting the timing of collecting drug information according to the user's emotion, information can be collected at a more appropriate timing. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the drug information collecting unit may be performed, for example, using an AI, or may be performed without using an AI. For example, the drug information collecting unit can input the user's emotion data to an AI, and the AI ​​can adjust the collection timing.

[0105] The drug information collection unit can collect information on the manufacturer and production lot of the drug and use it for quality control. The manufacturer information includes, for example, the name of the manufacturer and the production location. The production lot information includes, for example, the lot number and the production date. In this way, collecting the manufacturer and production lot information of the drug can be useful for quality control. Some or all of the above-mentioned processing in the drug information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information collection unit can input the manufacturer and production lot information to AI, and the AI ​​can collect the information.

[0106] The drug information collecting unit can collect information on storage conditions and expiration dates of drugs and propose an appropriate storage method. Storage conditions include, for example, temperature, humidity, and light conditions. Expiration date information includes, for example, expiration date and expiration date after opening. In this way, by collecting storage conditions and expiration date information of drugs, an appropriate storage method can be proposed. Some or all of the above-mentioned processing in the drug information collecting unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information collecting unit can input storage conditions and expiration date information to AI, which can collect information.

[0107] The drug information collection unit can estimate the user's emotion and determine the priority of the drug information to be collected based on the estimated user's emotion. The emotion estimation includes, for example, facial expression recognition, voice analysis, behavior analysis, etc. The priority determination includes, for example, the intensity of emotion, urgency, etc. This allows more appropriate information to be provided by determining the priority of the drug information to be collected according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the drug information collection unit may be performed, for example, using an AI, or may be performed without using an AI. For example, the drug information collection unit can input the user's emotion data into an AI, and the AI ​​can determine the priority.

[0108] The drug information collection unit can collect drug price information and suggest drugs with high cost performance. The price information includes, for example, the market price of the drug, discount information, etc. The evaluation of cost performance includes, for example, the balance between effect and price, long-term cost, etc. By collecting drug price information, it is possible to suggest drugs with high cost performance. Some or all of the above-mentioned processing in the drug information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information collection unit can input price information into AI, which then collects the information.

[0109] The drug information collection unit can collect user reviews and ratings of drugs and provide them to the user. User reviews include, for example, the reliability of the reviews and rating criteria. Ratings include, for example, star ratings and comments. By collecting user reviews and ratings of drugs, users can refer to them when selecting drugs. Some or all of the above-mentioned processing in the drug information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information collection unit can input user reviews and ratings into AI, which can collect information.

[0110] The medicine information providing unit can estimate the user's emotion and adjust the method of providing medicine information based on the estimated user's emotion. The emotion estimation includes, for example, facial expression recognition, voice analysis, behavior analysis, etc. The adjustment of the providing method includes, for example, the format of information and the timing of providing. In this way, more appropriate information can be provided by adjusting the method of providing medicine information according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the medicine information providing unit may be performed, for example, using an AI, or may be performed without using an AI. For example, the medicine information providing unit can input the user's emotion data to an AI, and the AI ​​can adjust the providing method.

[0111] The drug information providing unit can provide the latest research results regarding the effects and side effects of drugs. The latest research results include, for example, academic papers, clinical trial results, and the like. This allows the user to obtain the latest information by providing the latest research results regarding the effects and side effects of drugs. Some or all of the above-mentioned processing in the drug information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information providing unit can input the latest research results into AI, which then provides the information.

[0112] The medicine information providing unit can provide an individually customized medicine taking schedule. The taking schedule includes, for example, taking time, taking amount, taking interval, etc. By providing an individually customized medicine taking schedule, the user can take medicine according to an optimal schedule. Some or all of the above-mentioned processing in the medicine information providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the medicine information providing unit can input a taking schedule that matches the user's life rhythm to AI, and the AI ​​can provide the customized schedule.

[0113] The medicine information providing unit can estimate the user's emotion and adjust the frequency of providing medicine information based on the estimated user's emotion. The emotion estimation includes, for example, facial expression recognition, voice analysis, and behavior analysis. The adjustment of the frequency of providing includes, for example, frequency adjustment according to changes in emotion. By adjusting the frequency of providing medicine information according to the user's emotion, information can be provided at a more appropriate timing. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the medicine information providing unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the medicine information providing unit can input the user's emotion data to an AI, and the AI ​​can adjust the frequency of providing.

[0114] The drug information providing unit can provide the method of taking the drug by video or audio. The drug information providing unit, for example, provides the method of taking the drug by video or audio. The provision of video or audio includes, for example, the length of the video and the content of the audio. As a result, by providing the method of taking the drug by video or audio, the user can easily understand visually and aurally. A part or all of the above-mentioned processing in the drug information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information providing unit can input the video or audio of the drug taking method to AI, and the AI ​​can provide the information.

[0115] The drug information providing unit provides drug information in multiple languages, and can also accommodate foreign users. Multilingual support includes, for example, the types of languages ​​supported and the accuracy of translation. As a result, drug information can be provided in multiple languages, and foreign users can also be accommodated. Some or all of the above-mentioned processing in the drug information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the drug information providing unit can input drug information in multiple languages ​​to AI, and the AI ​​can provide the information.

[0116] The check unit can estimate the user's emotion and adjust the criteria for the interaction check based on the estimated user's emotion. Emotion estimation includes, for example, facial expression recognition, voice analysis, and behavior analysis. Adjustment of the check criteria includes, for example, adjustment of criteria according to the intensity of the emotion. This allows the check to be performed with more appropriate criteria by adjusting the criteria for the interaction check according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the check unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the check unit can input the user's emotion data into the AI, and the AI ​​can adjust the criteria.

[0117] The check unit can compare the drug interaction risk with past data to evaluate it. The comparison of past data includes, for example, past interaction cases, risk evaluation criteria, and the like. This makes it possible to identify high-risk interactions by comparing the drug interaction risk with past data to evaluate it. Some or all of the above-mentioned processing in the check unit may be performed, for example, using AI, or may be performed without using AI. For example, the check unit can input past data into AI, which can evaluate the risk.

[0118] The check unit can monitor the drug interaction risk in real time and immediately notify if there is an abnormality. Real-time monitoring includes, for example, the frequency of monitoring and the type of sensor used. In this way, by monitoring the drug interaction risk in real time, it is possible to immediately respond if an abnormality occurs. Some or all of the above-mentioned processing in the check unit may be performed, for example, using AI, or may be performed without using AI. For example, the check unit can input real-time data to AI, which can detect and notify an abnormality.

[0119] The check unit can estimate the user's emotion and adjust the result display method of the interaction check based on the estimated user's emotion. Emotion estimation includes, for example, facial expression recognition, voice analysis, behavior analysis, etc. Adjustment of the result display includes, for example, the display format, the display timing, etc. Thereby, by adjusting the result display method of the interaction check according to the user's emotion, the result can be displayed in a more appropriate manner. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the check unit may be performed, for example, using an AI, or may be performed without using an AI. For example, the check unit can input the user's emotion data to an AI, and the AI ​​can adjust the result display method.

[0120] The check unit can also check interactions with foods and supplements. Checking interactions includes, for example, interaction risk assessment, check items, and the like. By checking interactions with foods and supplements, a more comprehensive interaction risk can be evaluated. Some or all of the above-mentioned processing in the check unit may be performed, for example, using AI, or may be performed without using AI. For example, the check unit can input information about foods and supplements into AI, which can check interactions.

[0121] The check unit can visually display the drug interaction risk in a graph or chart. The visual display includes, for example, the type of graph to be used, the contents of the data to be displayed, and the like. By visually displaying the drug interaction risk, the user can easily understand the risk. Some or all of the above-mentioned processing in the check unit may be performed, for example, using AI, or may be performed without using AI. For example, the check unit can input data on the interaction risk into AI, which then displays it in a graph or chart.

[0122] The interaction information providing unit can estimate the user's emotion and adjust the method of providing the interaction information based on the estimated user's emotion. The emotion estimation includes, for example, facial expression recognition, voice analysis, behavior analysis, and the like. The adjustment of the providing method includes, for example, the format of information and the timing of providing. In this way, by adjusting the method of providing the interaction information according to the user's emotion, it is possible to provide information in a more appropriate manner. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using an AI, or may be performed without using an AI. For example, the interaction information providing unit can input the user's emotion data to an AI, and the AI ​​can adjust the providing method.

[0123] The interaction information providing unit can provide a detailed explanation of the interaction risk to deepen understanding. The detailed explanation includes, for example, the cause and effect of the risk, and specific measures to avoid the risk. By providing a detailed explanation of the interaction risk, the user can easily understand the risk. Some or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit can input a detailed explanation of the risk to the AI, and the AI ​​can provide the information.

[0124] The interaction information providing unit can provide specific guidelines for behavior to avoid interaction risks. The guidelines for behavior include, for example, advice on lifestyle habits, diet and exercise, and the like. By providing specific guidelines for behavior to avoid interaction risks, the user can easily avoid the risks. Some or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit can input the guidelines for behavior to AI, and the AI ​​can provide the information.

[0125] The interaction information providing unit can estimate the user's emotion and adjust the frequency of providing the interaction information based on the estimated user's emotion. The emotion estimation includes, for example, facial expression recognition, voice analysis, and behavior analysis. The adjustment of the frequency of providing includes, for example, frequency adjustment according to changes in emotion. In this way, by adjusting the frequency of providing the interaction information according to the user's emotion, it is possible to provide information at a more appropriate timing. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using an AI, or may be performed without using an AI. For example, the interaction information providing unit can input the user's emotion data to an AI, and the AI ​​can adjust the frequency of providing.

[0126] The interaction information providing unit can suggest alternative drugs to avoid interaction risks. Alternative drugs include, for example, drugs with a low risk of interaction and drugs with equivalent effects. By suggesting alternative drugs to avoid interaction risks, the user can take the drug safely. Some or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit can input information on alternative drugs to AI, which can then make the suggestion.

[0127] The interaction information providing unit can provide lifestyle advice for avoiding interaction risks. The lifestyle advice includes, for example, improving diet, recommending exercise, and advice on sleep and stress management. By providing lifestyle advice for avoiding interaction risks, the user can easily avoid the risks. Some or all of the above-mentioned processing in the interaction information providing unit may be performed, for example, using AI, or may be performed without using AI. For example, the interaction information providing unit can input lifestyle advice to AI, which provides the information.

[0128] The measurement unit can estimate the user's emotion and adjust the measurement timing based on the estimated user's emotion. Emotion estimation includes, for example, facial expression recognition, voice analysis, behavior analysis, etc. Adjustment of the measurement timing includes, for example, timing adjustment according to changes in emotion. This allows measurement to be performed at a more appropriate timing by adjusting the measurement timing according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the measurement unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the measurement unit can input the user's emotion data to an AI, and the AI ​​can adjust the measurement timing.

[0129] The measurement unit can detect anomalies by comparing the measurement data with past data. Comparison of past data includes, for example, past measurement values, abnormality criteria, and the like. This allows for early detection of abnormalities by comparing the measurement data with past data. Some or all of the above-mentioned processing in the measurement unit may be performed, for example, using AI, or may be performed without using AI. For example, the measurement unit can input past data into AI, which can detect abnormalities.

[0130] The measurement unit can store the measurement data in the cloud and share it with a doctor. Cloud storage and sharing include, for example, data security, timing of sharing, and the like. By storing the measurement data in the cloud and sharing it with a doctor, the doctor can make an appropriate diagnosis. Some or all of the above-mentioned processing in the measurement unit may be performed, for example, using AI, or may be performed without using AI. For example, the measurement unit can store the measurement data in the cloud and AI can share it with a doctor.

[0131] The measurement unit can estimate the user's emotion and adjust the display method of the measurement data based on the estimated user's emotion. Emotion estimation includes, for example, facial expression recognition, voice analysis, behavior analysis, etc. Adjustment of the display method includes, for example, display format, display timing, etc. Thereby, by adjusting the display method of the measurement data according to the user's emotion, the data can be displayed in a more appropriate manner. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the measurement unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the measurement unit can input the user's emotion data to an AI, and the AI ​​can adjust the display method.

[0132] The measurement unit can visually display the measurement data in a graph or chart. The visual display includes, for example, the type of graph to be used, the contents of the data to be displayed, and the like. By visually displaying the measurement data, the user can easily understand the data. Some or all of the above-mentioned processing in the measurement unit may be performed, for example, using AI, or may be performed without using AI. For example, the measurement unit can input the measurement data to AI, which then displays it in a graph or chart.

[0133] The measurement unit can display the measurement data in multiple languages ​​to accommodate foreign users. Multilingual support includes, for example, the types of languages ​​supported and the accuracy of translation. This allows the measurement data to be displayed in multiple languages ​​to accommodate foreign users. Some or all of the above-mentioned processing in the measurement unit may be performed using, for example, AI, or may be performed without using AI. For example, the measurement unit can input the measurement data in multiple languages ​​to AI, and the AI ​​can provide information.

[0134] The management unit can estimate the user's emotion and adjust the method of providing health information based on the estimated user's emotion. Emotion estimation includes, for example, facial expression recognition, voice analysis, behavior analysis, etc. Adjustment of the method of providing includes, for example, the format of information and the timing of providing. This allows the information to be provided in a more appropriate manner by adjusting the method of providing health information according to the user's emotion. The estimation of emotion is realized using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the management unit may be performed, for example, using an AI, or may be performed without using an AI. For example, the management unit can input the user's emotion data into an AI, and the AI ​​can adjust the method of providing.

[0135] The management unit can provide health information by individually customizing it. The customized health information includes, for example, information based on the user's health condition, lifestyle habits, and past health data. By providing the health information by individually customizing it, optimal information can be provided to the user. Some or all of the above-mentioned processing in the management unit may be performed, for example, using AI, or may be performed without using AI. For example, the management unit can input the user's health data into AI, which can provide customized information.

[0136] The management unit can periodically update the health information to provide the latest information. Periodic updates include, for example, the latest research results, information based on the user's health condition, and the like. By periodically updating the health information, the latest information can be provided to the user. Some or all of the above-mentioned processing in the management unit can be performed, for example, using AI, or can be performed without using AI. For example, the management unit can input the health information into AI, which can periodically update the health information.

[0137] The management unit can estimate the user's emotion and adjust the frequency of providing health information based on the estimated user's emotion. Emotion estimation includes, for example, facial expression recognition, voice analysis, behavior analysis, etc. Adjustment of the frequency of providing includes, for example, frequency adjustment according to changes in emotion. By adjusting the frequency of providing health information according to the user's emotion, information can be provided at a more appropriate timing. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the management unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the management unit can input the user's emotion data to an AI, and the AI ​​can adjust the frequency of providing.

[0138] The management unit can provide the health information in the form of video or audio. The management unit, for example, provides the health information in the form of video or audio. By providing the health information in the form of video or audio, the user can easily understand it visually and audibly. Some or all of the above-mentioned processing in the management unit may be performed, for example, using AI, or may be performed without using AI. For example, the management unit can input the video or audio of the health information to AI, and the AI ​​can provide the information.

[0139] The management unit can provide health information in multiple languages ​​and can also accommodate foreign users. Multilingual support includes, for example, the types of languages ​​supported and the accuracy of translation. As a result, health information can be provided in multiple languages, making it possible to accommodate foreign users. Some or all of the above-mentioned processing in the management unit may be performed, for example, using AI, or may be performed without using AI. For example, the management unit can input health information in multiple languages ​​to AI, and the AI ​​can provide the information.

[0140] The pharmacy information collecting unit can estimate the user's emotion and adjust the collection timing of the pharmacy information based on the estimated user's emotion. The emotion estimation includes, for example, facial expression recognition, voice analysis, and behavior analysis. The adjustment of the collection timing includes, for example, timing adjustment according to changes in emotion. This allows the pharmacy information collection timing to be adjusted according to the user's emotion, so that information can be collected at a more appropriate timing. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the pharmacy information collecting unit may be performed, for example, using an AI, or may be performed without using an AI. For example, the pharmacy information collecting unit can input the user's emotion data to an AI, and the AI ​​can adjust the collection timing.

[0141] The pharmacy information collecting unit can collect pharmacy inventory information in real time. Real-time collection includes, for example, the update frequency of inventory information and the type of sensor used. This allows the pharmacy inventory information to be collected in real time, thereby providing the user with the latest inventory information. Some or all of the above-mentioned processing in the pharmacy information collecting unit may be performed, for example, using AI, or may be performed without using AI. For example, the pharmacy information collecting unit can input inventory information into AI, which can collect information in real time.

[0142] The pharmacy information collection unit can collect pharmacy business hours and holiday information and provide it to the user. Business hours and holiday information includes, for example, the start and end times of business hours and holiday dates. In this way, by collecting pharmacy business hours and holiday information, the most suitable pharmacy can be suggested to the user. Some or all of the above-mentioned processing in the pharmacy information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the pharmacy information collection unit can input business hours and holiday information into AI, which can collect the information.

[0143] The pharmacy information collecting unit can estimate the user's emotion and determine the priority of the pharmacy information to be collected based on the estimated user's emotion. The emotion estimation includes, for example, facial expression recognition, voice analysis, and behavior analysis. The priority determination includes, for example, the intensity of emotion and urgency. This allows more appropriate information to be provided by determining the priority of the pharmacy information to be collected according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the pharmacy information collecting unit may be performed, for example, using an AI, or may be performed without using an AI. For example, the pharmacy information collecting unit can input the user's emotion data into an AI, and the AI ​​can determine the priority.

[0144] The pharmacy information collecting unit can collect pharmacy promotion information and provide it to the user. Promotion information includes, for example, discount information, benefit information, and the like. In this way, by collecting pharmacy promotion information, advantageous information can be provided to the user. Some or all of the above-mentioned processing in the pharmacy information collecting unit may be performed, for example, using AI, or may be performed without using AI. For example, the pharmacy information collecting unit can input promotion information to AI, which can collect the information.

[0145] The pharmacy information collection unit can collect reviews and ratings of pharmacies and provide them to the user. The review information includes, for example, the reliability of the review and the rating criteria. The rating includes, for example, star ratings and comments. By collecting pharmacy reviews and ratings, the user can select a highly reliable pharmacy. Some or all of the above-mentioned processing in the pharmacy information collection unit may be performed, for example, using AI, or may be performed without using AI. For example, the pharmacy information collection unit can input the reviews and ratings into AI, which can collect the information.

[0146] The guidance unit can estimate the user's emotion and adjust the guidance method based on the estimated user's emotion. The emotion estimation includes, for example, facial expression recognition, voice analysis, behavior analysis, and the like. The adjustment of the guidance method includes, for example, the format of guidance, the timing of guidance, and the like. This allows the guidance to be performed in a more appropriate manner by adjusting the guidance method according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the guidance unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the guidance unit can input the user's emotion data into the AI, and the AI ​​can adjust the guidance method.

[0147] The guidance unit can provide real-time guidance on the congestion status in the pharmacy. The real-time guidance includes, for example, the frequency of collecting congestion status and the type of sensor used. This allows the user to select the optimal time to visit by providing real-time guidance on the congestion status in the pharmacy. Some or all of the above-mentioned processing in the guidance unit may be performed using, for example, AI, or may be performed without using AI. For example, the guidance unit can input the congestion status into AI, which can provide guidance in real time.

[0148] The guidance unit can provide guidance on the location of a specific product in the pharmacy. Guidance includes, for example, displaying the location of the product on a map and providing guidance by voice. This makes it easier for the user to find the product by providing guidance on the location of the specific product in the pharmacy. Some or all of the above-mentioned processing in the guidance unit may be performed, for example, using AI, or may be performed without using AI. For example, the guidance unit can input product location information into AI, which can provide guidance.

[0149] The guidance unit can estimate the user's emotion and determine the priority of guidance based on the estimated user's emotion. The emotion estimation includes, for example, facial expression recognition, voice analysis, behavior analysis, etc. The priority determination includes, for example, the intensity of emotion, urgency, etc. This allows more appropriate information to be provided by determining the priority of guidance according to the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the guidance unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the guidance unit can input the user's emotion data into an AI, and the AI ​​can determine the priority.

[0150] The guidance unit can provide information about services and events in the pharmacy. The guidance includes, for example, real-time updates of service information and event information. This makes it easier for the user to understand information in the pharmacy by providing information about services and events in the pharmacy. Some or all of the above-mentioned processing in the guidance unit may be performed using, for example, AI, or may be performed without using AI. For example, the guidance unit can input service and event information into AI, which can provide guidance.

[0151] The guidance unit provides guidance within the pharmacy in multiple languages, and can also accommodate foreign users. Multilingual support includes, for example, the types of languages ​​supported and the accuracy of translation. This allows guidance within the pharmacy to be provided in multiple languages, making it possible to accommodate foreign users. Some or all of the above-mentioned processing in the guidance unit may be performed, for example, using AI, or may be performed without using AI. For example, the guidance unit can input guidance information in multiple languages ​​to AI, and the AI ​​can provide the information.

[0152] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0153] The drug information collection unit can collect information on the manufacturer and manufacturing lot of the drug and use it for quality control. For example, by collecting information such as the name of the manufacturer, the manufacturing location, the lot number, and the manufacturing date, the quality control of the drug can be strengthened. In addition, the drug information providing unit can provide customized information based on the user's past medical history. For example, by providing recommended drugs based on the past medical history and individual drug taking schedules, more appropriate drug information can be provided to the user. Furthermore, the drug interaction information providing unit can suggest an alternative drug if the checking unit determines that there is an interaction. For example, by suggesting drugs with a low risk of interaction and drugs with equivalent effects, the user can take the drug safely.

[0154] The measurement unit can estimate the user's emotions and adjust the timing of measurement based on the estimated user's emotions. For example, if the user is feeling stressed, adjustments can be made such as postponing the measurement. The measurement unit can also compare the measurement data with past data to detect abnormalities. For example, if an abnormal value is detected in comparison with past measurement values, a warning can be issued. Furthermore, the measurement unit can store the measurement data in the cloud and share it with a doctor. This allows the doctor to make an appropriate diagnosis.

[0155] The pharmacy information collection unit can collect pharmacy inventory information in real time. For example, by increasing the frequency of updating the inventory information, the latest inventory information can be provided to the user. The pharmacy information collection unit can also collect pharmacy business hours and holiday information and provide it to the user. For example, by collecting information such as the start and end times of business hours and the dates of holidays, the most suitable pharmacy can be suggested to the user. Furthermore, the pharmacy information collection unit can collect pharmacy promotion information and provide it to the user. For example, by collecting discount information, special offer information, and the like, advantageous information can be provided to the user.

[0156] The guidance unit can provide information on the congestion status in the pharmacy in real time. For example, by increasing the frequency of collection of the congestion status, the user can be allowed to select the optimal time to visit the pharmacy. Furthermore, the guidance unit can provide information on the location of a specific product in the pharmacy. For example, the location of the product can be displayed on a map or provided through audio guidance, making it easier for the user to find the product. Furthermore, the guidance unit can provide information on services and events in the pharmacy. For example, by updating service information and event information in real time, the user can easily grasp information in the pharmacy.

[0157] The management unit can provide health information by customizing it individually. For example, by providing information based on the user's health condition, lifestyle habits, and past health data, it is possible to provide optimal information to the user. Furthermore, the management unit can periodically update the health information to provide the latest information. For example, by periodically updating the latest research results, information based on the user's health condition, and the like, it is possible to provide the user with the latest information. Furthermore, the management unit can provide the health information in the form of video and audio. For example, by adjusting the length of the video, the content of the audio, and the like, it is possible to make it easier for the user to understand visually and audibly.

[0158] The drug information providing unit can estimate the user's emotions and adjust the method of providing drug information based on the estimated user's emotions. For example, if the user feels anxious, adjustments can be made such as providing a more detailed explanation. In addition, the drug information providing unit can provide the latest research results regarding the effects and side effects of drugs. For example, by providing academic papers, clinical trial results, etc., the user can obtain the latest information. Furthermore, the drug information providing unit can provide an individual customized drug taking schedule. For example, by adjusting the taking time, dosage, taking interval, etc., the user can take the drug according to an optimal schedule.

[0159] The checking unit can compare the drug interaction risk with past data to evaluate it. For example, by evaluating it using past interaction cases, risk evaluation criteria, etc., it is possible to identify interactions with high risk. In addition, the checking unit can monitor the drug interaction risk in real time and immediately notify if there is an abnormality. For example, by increasing the frequency of monitoring, it is possible to immediately respond if an abnormality occurs. Furthermore, the checking unit can also check interactions with foods and supplements. For example, by collecting information on foods and supplements and evaluating the risk of interactions, it is possible to evaluate the interaction risk more comprehensively.

[0160] The interaction information providing unit can estimate the user's emotions and adjust the method of providing the interaction information based on the estimated user's emotions. For example, if the user feels anxious, adjustments can be made, such as providing a more detailed explanation. Furthermore, the interaction information providing unit can provide a detailed explanation of the interaction risk to deepen understanding. For example, by providing the causes and effects of the risk, and specific measures to avoid the risk, the user can easily understand the risk. Furthermore, the interaction information providing unit can provide specific guidelines for action to avoid the interaction risk. For example, by providing advice on lifestyle habits, diet and exercise advice, the user can easily avoid the risk.

[0161] The pharmacy information collecting unit can estimate the user's emotions and determine the priority of the pharmacy information to be collected based on the estimated user's emotions. For example, when the user is in a hurry, adjustments can be made such as prioritizing the collection of important information. In addition, the pharmacy information collecting unit can collect reviews and ratings of pharmacies and provide them to the user. For example, by collecting the reliability of reviews, evaluation criteria, etc., it is possible to enable the user to select a reliable pharmacy. Furthermore, the pharmacy information collecting unit can collect promotional information of pharmacies and provide it to the user. For example, by collecting discount information, special offer information, etc., it is possible to provide the user with advantageous information.

[0162] The guidance unit can estimate the user's emotions and determine the priority of guidance based on the estimated user's emotions. For example, when the user is in a hurry, adjustments can be made such as giving priority to important information. In addition, the guidance unit can provide guidance in multiple languages ​​within the pharmacy to accommodate foreign users. For example, by adjusting the types of languages ​​supported and the accuracy of translation, it is possible to accommodate foreign users as well. Furthermore, the guidance unit can provide guidance on services and event information within the pharmacy. For example, by updating service information and event information in real time, it is possible to make it easier for the user to grasp information within the pharmacy.

[0163] The process flow of the second embodiment will be briefly described below.

[0164] Step 1: The drug information collecting unit collects drug information. The drug information collecting unit collects information such as the type of drug, its effects, how to take it, and side effects. The drug information collecting unit can obtain information from a database. The drug information collecting unit can also measure information using a sensor. Step 2: The medicine information providing unit provides information on medicines to be taken by the user based on the information collected by the medicine information collecting unit. The medicine information providing unit provides information by, for example, a screen display, a voice guide, an email transmission, or the like. Step 3: When the user is taking multiple medicines, the checking unit checks for interactions between the multiple medicines based on the information collected by the medicine information collecting unit. The checking unit checks for interactions using, for example, an algorithm. Step 4: The interaction information providing unit provides the user with the results of the check made by the checking unit. The interaction information providing unit provides information by, for example, a screen display, a voice guide, or an email transmission. Step 5: The measurement unit measures information about the user's body. For example, the measurement unit measures information such as height, weight, blood pressure, and blood sugar level. The measurement unit can measure the information using a sensor. Step 6: The management unit provides health-related information or advice based on the information measured by the measurement unit. The management unit provides the information by, for example, displaying the information on a screen, providing audio guidance, sending an email, or the like. Step 7: The pharmacy information collecting unit collects information within the pharmacy. The pharmacy information collecting unit collects, for example, information on products, services, and facilities within the pharmacy. The pharmacy information collecting unit can obtain information from a database. Step 8: The guidance unit provides guidance within the pharmacy based on the information collected by the pharmacy information collection unit. The guidance unit provides guidance by, for example, a screen display, audio guidance, email transmission, or the like.

[0165] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0166] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) are input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may also be an AI agent. In addition, when the processes of each of the above-mentioned parts are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples.In addition, processing performed by AI including the generation AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI including the generation AI.

[0167] Furthermore, the above-described processing by the data processing system 10 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information required for processing from the data processing device 12 or an external device.

[0168] For example, the drug information collecting unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14. For example, the drug information providing unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14. For example, the check unit is realized by the specific processing unit 290 of the data processing device 12. For example, the interaction information providing unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14. For example, the measurement unit is realized by the sensor and control unit 46A of the smart device 14. For example, the management unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14. For example, the pharmacy information collecting unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14. For example, the guidance unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14. The correspondence between each part and the device or control part is not limited to the above-mentioned example, and various modifications are possible.

[0169] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0170] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0171] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0172] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0173] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0174] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0175] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0176] Fig. 4 shows an example of main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0177] The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0178] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0179] In the smart glasses 214, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0180] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0181] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0182] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0183] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device.

[0184] For example, the drug information collection unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214. For example, the drug information provision unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214. For example, the check unit is realized by the specific processing unit 290 of the data processing device 12. For example, the interaction information provision unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214. For example, the measurement unit is realized by the sensor and control unit 46A of the smart glasses 214. For example, the management unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214. For example, the pharmacy information collection unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214. For example, the guidance unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214. The correspondence between each part and the device or control part is not limited to the above-mentioned example, and various modifications are possible.

[0185] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0186] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0187] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0188] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0189] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0190] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0191] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0192] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0193] The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0194] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0195] In the headset type terminal 314, the specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50, and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0196] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0197] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0198] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0199] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device.

[0200] For example, the drug information collecting unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314. For example, the drug information providing unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314. For example, the check unit is realized by the specific processing unit 290 of the data processing device 12. For example, the interaction information providing unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314. For example, the measurement unit is realized by the sensor and control unit 46A of the headset type terminal 314. For example, the management unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314. For example, the pharmacy information collecting unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314. For example, the guidance unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314. The correspondence between each part and the device or control part is not limited to the above-mentioned example, and various modifications are possible.

[0201] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0202] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0203] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0204] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0205] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0206] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of a typical healthy person).

[0207] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0208] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and legs. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, and legs. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0209] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0210] The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0211] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0212] In the robot 414, the specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads out the specific program 60 from the storage 50, and executes the specific program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0213] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0214] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0215] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0216] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0217] For example, the drug information collecting unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414. For example, the drug information providing unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414. For example, the check unit is realized by the specific processing unit 290 of the data processing device 12. For example, the interaction information providing unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414. For example, the measurement unit is realized by the sensor and control unit 46A of the robot 414. For example, the management unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414. For example, the pharmacy information collecting unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414. For example, the guidance unit is realized by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414. The correspondence between each part and the device or control part is not limited to the above-mentioned example, and various modifications are possible.

[0218] The emotion identification model 59 as an emotion engine may determine the emotion of the user according to a specific mapping. Specifically, the emotion identification model 59 may determine the emotion of the user according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the emotion of the robot, and the identification processing unit 290 may perform identification processing using the emotion of the robot.

[0219] FIG. 9 is a diagram showing an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive emotions are arranged. The more outside the concentric circles, the more emotions that represent states and actions that arise from a state of mind are arranged. Emotions are a concept that includes emotions and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions that occur in the brain are arranged. On the right side of the concentric circles, emotions that are generally induced by situational judgment are arranged. On the upper and lower sides of the concentric circles, emotions that are generally generated from reactions that occur in the brain and are induced by situational judgment are arranged. In addition, on the upper side of the concentric circles, emotions of "pleasure" are arranged, and on the lower side, emotions of "discomfort" are arranged. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0220] These emotions are distributed in the 3 o'clock direction of emotion map 400 and usually fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0221] The inside of emotion map 400 represents what is going on inside one's mind, and the outside of emotion map 400 represents behavior, so the further out you go on emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0222] Here, human emotions are based on various balances such as posture and blood sugar level, and when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. Emotions can also be created for robots, cars, motorcycles, etc., based on various balances such as posture and battery level, so that when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. The emotion map may be generated, for example, based on the emotion map of Dr. Mitsuyoshi (Research on speech emotion recognition and emotion brain physiological signal analysis system, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). On the left half of the emotion map, emotions belonging to an area called "reaction" where sensation is dominant are lined up. On the right half of the emotion map, emotions belonging to an area called "situation" where situation recognition is dominant are lined up.

[0223] The emotion map defines two emotions that promote learning. The first is the negative emotion around the middle of "repentance" or "remorse" on the situation side. In other words, this is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the positive emotion around "desire" on the response side. In other words, this is when the robot has positive feelings such as "I want more" or "I want to know more."

[0224] The emotion identification model 59 inputs the user input to a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the emotion of the user. This neural network is pre-trained based on multiple learning data that are combinations of the user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in Fig. 10. Fig. 10 shows an example in which multiple emotions, "relief," "calm," and "encouraging," have similar emotion values.

[0225] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers, including computer 22.

[0226] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable computer-readable non-transitory storage medium such as a Universal Serial Bus (USB) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0227] In addition, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 upon request from the data processing device 12.

[0228] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0229] As the hardware resource for executing the specific process, various processors as shown below can be used. An example of the processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing the specific process by executing software, i.e., a program. Another example of the processor is a dedicated electric circuit, which is a processor having a circuit configuration designed exclusively for executing a specific process, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), or an Application Specific Integrated Circuit (ASIC). Each processor has a built-in or connected memory, and each processor executes the specific process by using the memory.

[0230] The hardware resource that executes the specific process may be one of these various processors, or may be a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0231] As an example of a configuration using one processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a configuration using a processor that realizes the functions of the entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0232] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements. The specific processes described above are merely examples. It goes without saying that unnecessary steps may be deleted, new steps may be added, or the order of processes may be changed without departing from the spirit of the invention.

[0233] In the above example, the first to fourth embodiments are described separately, but some or all of these embodiments may be combined. The smart device 14, the smart glasses 214, the headset terminal 314, and the robot 414 are only examples, and they may be combined with each other, or may be other devices. In the above example, the first and second embodiments are described separately, but they may be combined.

[0234] The above description and illustrations are detailed descriptions of the parts related to the technology of the present disclosure, and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, function, action, and effect is an example of the configuration, function, action, and effect of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replaced with respect to the description and illustrations shown above, within the scope of the gist of the technology of the present disclosure. In addition, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the description and illustrations shown above omit explanations of technical common sense that do not require particular explanation in enabling the implementation of the technology of the present disclosure.

[0235] All publications, patent applications, and standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, and standard was specifically and individually indicated to be incorporated by reference.

[0236] (Appendix 1) a drug information collection unit that collects drug information; a medicine information providing unit that provides information on medicines to be taken by the user based on the information collected by the medicine information collecting unit; A check unit that checks interactions between the plurality of drugs based on information collected by the drug information collection unit when the plurality of drugs are taken by the user; an interaction information providing unit for providing a result of the check by the checking unit to the user; A measurement unit that measures information about the user's body; a management unit that provides the user with specific health-related information or advice based on the information measured by the measurement unit; A pharmacy information collection department that collects information about pharmacies; A guidance unit that provides specific guidance within the pharmacy based on the information collected by the pharmacy information collection unit. A system characterized by: (Appendix 2) The drug information collection unit includes: Collect information about medications, their effects, how to take them, and side effects 2. The system of claim 1, (Appendix 3) The measurement unit is Measure the user's height, weight, blood pressure, and blood glucose level 2. The system of claim 1, (Appendix 4) The pharmacy information collection unit includes: Collect information about products, services, and facilities within the pharmacy 2. The system of claim 1, (Appendix 5) The drug information providing unit includes: Providing users with specific health information or health quizzes while they wait at the pharmacy 2. The system of claim 1, (Appendix 6) The interaction information providing unit includes: If the checking unit determines that the interaction exists, a specific warning is issued to the user. 2. The system of claim 1, (Appendix 7) The drug information providing unit includes: Providing customized information based on a user's past medication history 2. The system of claim 1, (Appendix 8) The interaction information providing unit includes: If the checking unit determines that an interaction exists, an alternative drug is suggested. 2. The system of claim 1, (Appendix 9) The interaction information providing unit includes: and an interface for visually displaying the risk of said interaction. 2. The system of claim 1, (Appendix 10) The drug information collection unit includes: To estimate a user's emotions and adjust the timing of collecting drug information based on the estimated user's emotions. 2. The system of claim 1, (Appendix 11) The drug information collection unit includes: Collect information on drug manufacturers and production lots to help with quality control 2. The system of claim 1, (Appendix 12) The drug information collection unit includes: Collect information on drug storage conditions and expiration dates, and propose appropriate storage methods 2. The system of claim 1, (Appendix 13) The drug information collection unit includes: Estimate the user's emotions and determine the priority of the drug information to be collected based on the estimated user's emotions. 2. The system of claim 1, (Appendix 14) The drug information collection unit includes: Collecting drug price information and proposing cost-effective drugs 2. The system of claim 1, (Appendix 15) The drug information collection unit includes: Collect drug user reviews and ratings and provide them to users 2. The system of claim 1, (Appendix 16) The drug information providing unit includes: To estimate a user's emotions and adjust the method of providing drug information based on the estimated user's emotions 2. The system of claim 1, (Appendix 17) The drug information providing unit includes: Providing the latest research results on drug effects and side effects 2. The system of claim 1, (Appendix 18) The drug information providing unit includes: Providing personalized medication schedules 2. The system of claim 1, (Appendix 19) The drug information providing unit includes: The user's emotions are estimated, and the frequency of providing drug information is adjusted based on the estimated user's emotions. 2. The system of claim 1, (Appendix 20) The drug information providing unit includes: Providing video and audio on how to take medicine 2. The system of claim 1, (Appendix 21) The drug information providing unit includes: Providing drug information in multiple languages ​​to accommodate foreign users 2. The system of claim 1, (Appendix 22) The checking unit is Inferring a user's emotion and adjusting the criteria for interaction checking based on the estimated user's emotion 2. The system of claim 1, (Appendix 23) The checking unit is Evaluate the risk of drug interactions by comparing with historical data 2. The system of claim 1, (Appendix 24) The checking unit is Monitor drug interaction risks in real time and immediately notify if there are any abnormalities 2. The system of claim 1, (Appendix 25) The checking unit is To estimate a user's emotion and adjust a method of displaying the result of an interaction check based on the estimated user's emotion. 2. The system of claim 1, (Appendix 26) The checking unit is Check for interactions with foods and supplements 2. The system of claim 1, (Appendix 27) The checking unit is Visually display drug interaction risks with graphs and charts 2. The system of claim 1, (Appendix 28) The interaction information providing unit includes: To estimate a user's emotion and adjust a method of providing interaction information based on the estimated user's emotion. 2. The system of claim 1, (Appendix 29) The interaction information providing unit includes: Provide detailed descriptions of interaction risks to improve understanding 2. The system of claim 1, (Appendix 30) The interaction information providing unit includes: Provide specific guidelines for avoiding interaction risks 2. The system of claim 1, (Appendix 31) The interaction information providing unit includes: A user's emotion is estimated, and a frequency of providing interaction information is adjusted based on the estimated user's emotion. 2. The system of claim 1, (Appendix 32) The interaction information providing unit includes: Suggest alternative medications to avoid drug interactions 2. The system of claim 1, (Appendix 33) The interaction information providing unit includes: Providing lifestyle advice to avoid risk of interactions 2. The system of claim 1, (Appendix 34) The measurement unit is Estimate the user's emotions and adjust the measurement timing based on the estimated user emotions. 2. The system of claim 1, (Appendix 35) The measurement unit is Detect anomalies by comparing measurement data with past data 2. The system of claim 1, (Appendix 36) The measurement unit is Measurement data is stored in the cloud and shared with doctors 2. The system of claim 1, (Appendix 37) The measurement unit is Inferring user emotion and adjusting the display method of measurement data based on the estimated user emotion 2. The system of claim 1, (Appendix 38) The measurement unit is Visually display measurement data in graphs and charts 2. The system of claim 1, (Appendix 39) The measurement unit is Displaying measurement data in multiple languages ​​to accommodate foreign users 2. The system of claim 1, (Appendix 40) The management unit To estimate a user's emotion and adjust a method of providing health information based on the estimated user's emotion 2. The system of claim 1, (Appendix 41) The management unit Providing personalized health information 2. The system of claim 1, (Appendix 42) The management unit Regularly update your health information to provide the latest information 2. The system of claim 1, (Appendix 43) The management unit To estimate a user's emotion and adjust the frequency of providing health information based on the estimated user's emotion. 2. The system of claim 1, (Appendix 44) The management unit Providing health information through video and audio 2. The system of claim 1, (Appendix 45) The management unit Providing health information in multiple languages ​​to accommodate foreign users 2. The system of claim 1, (Appendix 46) The pharmacy information collection unit includes: To estimate a user's emotion and adjust a timing of collecting pharmacy information based on the estimated user's emotion. 2. The system of claim 1, (Appendix 47) The pharmacy information collection unit includes: Collect pharmacy inventory information in real time 2. The system of claim 1, (Appendix 48) The pharmacy information collection unit includes: Collect pharmacy business hours and holiday information and provide it to users 2. The system of claim 1, (Appendix 49) The pharmacy information collection unit includes: A user's emotion is estimated, and a priority order of pharmacy information to be collected is determined based on the estimated user's emotion. 2. The system of claim 1, (Appendix 50) The pharmacy information collection unit includes: Collect pharmacy promotion information and provide it to users 2. The system of claim 1, (Appendix 51) The pharmacy information collection unit includes: Collect pharmacy reviews and ratings and provide them to users 2. The system of claim 1, (Appendix 52) The guide portion is To estimate a user's emotion and adjust a guidance method based on the estimated user's emotion. 2. The system of claim 1, (Appendix 53) The guide portion is Provides real-time information on congestion status within the pharmacy 2. The system of claim 1, (Appendix 54) The guide portion is Provide location of specific products within the pharmacy 2. The system of claim 1, (Appendix 55) The guide portion is To estimate a user's emotion and determine a priority of guidance based on the estimated user's emotion. 2. The system of claim 1, (Appendix 56) The guide portion is Providing information about pharmacy services and events 2. The system of claim 1, (Appendix 57) The guide portion is Providing pharmacy guidance in multiple languages ​​to accommodate foreign users 2. The system of claim 1, [Explanation of symbols]

[0237] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a drug information collection unit that collects drug information; a medicine information providing unit that provides information on medicines to be taken by the user based on the information collected by the medicine information collecting unit; A check unit that checks interactions between the plurality of drugs based on information collected by the drug information collection unit when the plurality of drugs are taken by the user; an interaction information providing unit for providing a result of the check by the checking unit to the user; A measurement unit that measures information about the user's body; a management unit that provides the user with specific health-related information or advice based on the information measured by the measurement unit; A pharmacy information collection department that collects information about pharmacies; A guidance unit that provides specific guidance within the pharmacy based on the information collected by the pharmacy information collection unit. A system characterized by:

2. The drug information collection unit includes: Collect information about medications, their effects, how to take them, and side effects 2. The system of claim 1 .

3. The measurement unit is Measuring the user's height, weight, blood pressure, and blood sugar level 2. The system of claim 1 .

4. The pharmacy information collection unit includes: Collect information about the products, services, and facilities within said pharmacy 2. The system of claim 1 .

5. The drug information providing unit includes: Providing the user with specific health information or a health quiz while they wait at the pharmacy 2. The system of claim 1 .

6. The interaction information providing unit includes: If the checking unit determines that the interaction exists, a specific warning is issued to the user.

2. The system of claim 1 .

7. The drug information providing unit includes: Providing customized information based on the user's past medical history 2. The system of claim 1 .

8. The interaction information providing unit includes: If the checking unit determines that an interaction exists, an alternative drug is suggested.

2. The system of claim 1 .

9. The interaction information providing unit includes: and an interface for visually displaying the risk of said interaction.

2. The system of claim 1 .

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