WO2024010397A1 - Serveur, procédé, programme et dispositif de fourniture d'aliment destiné à fournir un aliment personnalisé sur la base d'une analyse d'un index de composition - Google Patents

Serveur, procédé, programme et dispositif de fourniture d'aliment destiné à fournir un aliment personnalisé sur la base d'une analyse d'un index de composition Download PDF

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Publication number
WO2024010397A1
WO2024010397A1 PCT/KR2023/009591 KR2023009591W WO2024010397A1 WO 2024010397 A1 WO2024010397 A1 WO 2024010397A1 KR 2023009591 W KR2023009591 W KR 2023009591W WO 2024010397 A1 WO2024010397 A1 WO 2024010397A1
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food
component
index
weight
calculating
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PCT/KR2023/009591
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English (en)
Korean (ko)
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이기호
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주식회사 메디푸드플랫폼
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Publication of WO2024010397A1 publication Critical patent/WO2024010397A1/fr

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    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23P—SHAPING OR WORKING OF FOODSTUFFS, NOT FULLY COVERED BY A SINGLE OTHER SUBCLASS
    • A23P20/00—Coating of foodstuffs; Coatings therefor; Making laminated, multi-layered, stuffed or hollow foodstuffs
    • A23P20/20—Making of laminated, multi-layered, stuffed or hollow foodstuffs, e.g. by wrapping in preformed edible dough sheets or in edible food containers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y10/00—Processes of additive manufacturing
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00—Data acquisition or data processing for additive manufacturing
    • B33Y50/02—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y80/00—Products made by additive manufacturing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9035—Filtering based on additional data, e.g. user or group profiles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9038—Presentation of query results
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Social work or social welfare, e.g. community support activities or counselling services
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
    • A—HUMAN NECESSITIES
    • A23—FOODS OR FOODSTUFFS; TREATMENT THEREOF, NOT COVERED BY OTHER CLASSES
    • A23P—SHAPING OR WORKING OF FOODSTUFFS, NOT FULLY COVERED BY A SINGLE OTHER SUBCLASS
    • A23P20/00—Coating of foodstuffs; Coatings therefor; Making laminated, multi-layered, stuffed or hollow foodstuffs
    • A23P20/20—Making of laminated, multi-layered, stuffed or hollow foodstuffs, e.g. by wrapping in preformed edible dough sheets or in edible food containers
    • A23P20/25—Filling or stuffing cored food pieces, e.g. combined with coring or making cavities
    • A23P2020/253—Coating food items by printing onto them; Printing layers of food products

Definitions

  • the present disclosure relates to a server, method, program, and food serving device that analyzes the ingredient index of an analysis object and provides customized food based on the analysis target.
  • the purpose of the embodiments disclosed in the present disclosure is to provide customized foods by analyzing the effect of specific ingredients on the analysis subject.
  • the server that provides customized food based on ingredient index analysis receives real-time inspection data for the analysis target from a memory and a food provision device in which existing inspection data for the analysis target is stored. Based on the communication unit and the existing test data and the real-time test data, calculate a final ingredient index that quantifies the influence of at least one ingredient on the analysis object, and based on the calculated final ingredient index, the analysis object and a processor that derives food information for and transmits the derived food information to the food providing device through the communication unit to request food production, and the existing test data is performed on the analysis target at a medical institution. and inspection data for a plurality of inspection items, and the real-time inspection data includes inspection data obtained by inspecting the analysis target with the plurality of inspection items in real time by an inspection module of the food serving device.
  • the method of providing customized food based on ingredient index analysis includes receiving existing test data for an analysis target and storing it in the memory of the server, the communication unit of the server Receiving real-time test data for the analysis object from a food serving device through a processor of the server, based on the existing test data and the real-time test data, determining the influence of at least one ingredient on the analysis object Calculating a quantified final ingredient index, deriving food information for the analysis target based on the calculated final ingredient index through the processor of the server, and deriving the derived food information through the processor of the server Requesting food production by transmitting to the food serving device through the communication unit, wherein the existing test data includes test data for a plurality of test items performed on the analysis subject at a medical institution, Real-time test data includes test data obtained by real-time testing the analysis object with the plurality of test items by an test module of the food serving device.
  • the device for providing customized food based on ingredient index analysis includes a communication unit, at least one inspection module, and real-time inspection of the analysis target with a plurality of inspection items by the inspection module.
  • a processor that transmits the obtained real-time inspection data to a server through the communication unit, receives food information derived for the analysis target from the server through the communication unit, and controls to manufacture food based on the received food information.
  • the food information is derived based on the final ingredient index derived based on the existing test data and the real-time test data for the analysis object, and the existing test data is obtained from the analysis object at a medical institution. It includes test data for a plurality of test items performed, and the final ingredient index is characterized in that it quantifies the influence of at least one ingredient on the analysis subject.
  • the direction of influence of a specific ingredient on the subject of analysis (whether the influence of the ingredient on the subject is positive or negative) and the magnitude of the influence (level of positive influence, level of negative influence) It is possible to prescribe ingredients to consume or avoid by taking the level into consideration.
  • Figure 1 is a schematic diagram of a customized food provision system based on ingredient index analysis according to an embodiment of the present disclosure.
  • Figure 2 is a block diagram of a customized food provision system based on ingredient index analysis according to an embodiment of the present disclosure.
  • Figure 3 is a diagram illustrating items that can be obtained using real-time inspection data.
  • 4 to 10 are flowcharts of a method for providing customized food based on ingredient index analysis according to an embodiment of the present disclosure.
  • Figures 11 and 12 are diagrams illustrating types of inspection items.
  • Figure 13 is a diagram illustrating section matching of the second weight and the third weight.
  • Figure 14 is a schematic flow chart including various embodiments of a method for providing customized food based on ingredient index analysis.
  • Figure 15 is a diagram illustrating a first manufacturing method of a 3D food printer.
  • Figure 16 is a diagram illustrating a second manufacturing method of a 3D food printer.
  • Figure 17 is a diagram illustrating a third manufacturing method of a 3D food printer.
  • first and second are used to distinguish one component from another component, and the components are not limited by the above-mentioned terms.
  • the identification code for each step is used for convenience of explanation.
  • the identification code does not explain the order of each step, and each step may be performed differently from the specified order unless a specific order is clearly stated in the context. there is.
  • 'a server that provides customized food based on ingredient index analysis according to the present disclosure' includes various devices that can perform computational processing and provide results to the user.
  • the service server according to the present disclosure may include all of a computer, a server device, and a portable terminal, or may be in any one form.
  • the computer may include, for example, a laptop, desktop, laptop, tablet PC, slate PC, etc. equipped with a web browser.
  • the server device is a server that processes information by communicating with external devices, and may include an application server, computing server, database server, file server, game server, mail server, proxy server, and web server.
  • the portable terminal is, for example, a wireless communication device that guarantees portability and mobility, such as PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), and PDA. (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), WiBro (Wireless Broadband Internet) terminal, smart phone ), all types of handheld wireless communication devices, and wearable devices such as watches, rings, bracelets, anklets, necklaces, glasses, contact lenses, or head-mounted-device (HMD). may include.
  • PCS Personal Communication System
  • GSM Global System for Mobile communications
  • PDC Personal Digital Cellular
  • PHS Personal Handyphone System
  • PDA Personal Digital Assistant
  • IMT International Mobile Telecommunication
  • CDMA Code Division Multiple Access
  • W-CDMA Wideband Code Division Multiple Access
  • WiBro Wireless Broadband Internet
  • smart phone smart phone
  • the “ingredient index” refers to the direction of influence of a specific ingredient on the user (target of analysis) (whether the influence of the ingredient on the subject is positive or negative) and the magnitude of the influence (level of positive influence, level of negative influence). It means a value quantified by analyzing the level).
  • the term “ingredient power” refers to a value calculated based on each test item that can determine the impact of a specific ingredient on the user (target of analysis).
  • the component power can be used to calculate the component index.
  • Figure 1 is a schematic diagram of a customized food provision system 10 based on ingredient index analysis according to an embodiment of the present disclosure.
  • the service server 100 may utilize data received from at least one of the medical institution server and the user terminal 50 where the user performed various tests as existing test data.
  • the service server 100 may receive real-time inspection data from at least one of the food serving device 200 and the user terminal 50.
  • the service server 100 can provide customized food to the user by analyzing existing inspection data and real-time inspection data.
  • the service server 100 can analyze existing test data and real-time test data to analyze ingredients that the user (analysis target) should consume or avoid, and reflect this to derive user-customized food information. Additionally, the service server 100 may provide the derived food information to the food serving device 200 so that the food serving device 200 can manufacture or provide food based on the food information.
  • the present disclosure utilizes both existing test data and real-time test data tested by existing medical institutions to more accurately analyze the user's condition at the time of food provision, thereby providing customized food to the user. .
  • Figure 2 is a block diagram of a customized food provision system 10 based on ingredient index analysis according to an embodiment of the present disclosure.
  • the customized food provision system 10 based on ingredient index analysis includes a service server 100, a food provision device 200, a user terminal 50, and an external inspection device 30. ) may include.
  • the service server 100 is an entity that analyzes existing inspection data and real-time inspection data to create customized food information for users (analysis targets).
  • the food serving device 200 may obtain various inspection data from the user in real time and may also receive real-time inspection data from the external inspection device 30.
  • the food serving device 200 transmits real-time inspection data obtained from the user to the service server 100.
  • the food providing device 200 may receive food information derived from the service server 100 and manufacture food by controlling the output module 260 based on the food information.
  • the food providing device 200 includes any device that manufactures or provides customized food based on analysis results received from the service server 100.
  • the food serving device 200 may include a 3D food printer and a device equipped with a plurality of cartridges (eg, refrigerator, blender, automatic feed dispenser, etc.).
  • the service server 100 includes a first processor 110, a first memory 130, and a first communication unit 120.
  • the service server 100 may include fewer or more components than the components shown in FIG. 2.
  • the food serving device 200 includes a second processor 210, a second communication unit 220, a second memory 230, an input/output unit 240, an inspection module 250, and an output module 260.
  • the food serving device 200 may include fewer or more components than those shown in FIG. 2 .
  • the first processor 110 has a memory that stores data for an algorithm for controlling the operation of components within the food serving device 200 or a program that reproduces the algorithm, and performs the above-described operations using the data stored in the memory. It may be implemented with at least one processor. At this time, the memory and processor may each be implemented as separate chips. Alternatively, the memory and processor may be implemented as a single chip.
  • the processor may control any one or a combination of the above-described components in order to implement various embodiments according to the present disclosure described in the drawings below on the service server 100 and the food serving device 200. You can.
  • the first communication unit 120 receives real-time test data on the analysis target from at least one of the test module 250 or the external test device 30.
  • the first communication unit 120 can communicate with the user terminal 50 and the food serving device 200 to transmit and receive data.
  • the second communication unit 220 can communicate with the user terminal 50, the food serving device 200, and the external testing device 30 to transmit and receive data.
  • the communication unit may include one or more components that enable communication with an external device, and may include, for example, at least one of a broadcast reception module, a wired communication module, a wireless communication module, a short-range communication module, and a location information module. there is.
  • Wired communication modules include various wired communication modules such as Local Area Network (LAN) modules, Wide Area Network (WAN) modules, or Value Added Network (VAN) modules, as well as USB (Universal Serial Bus) modules. ), HDMI (High Definition Multimedia Interface), DVI (Digital Visual Interface), RS-232 (recommended standard 232), power line communication, or POTS (plain old telephone service).
  • LAN Local Area Network
  • WAN Wide Area Network
  • VAN Value Added Network
  • USB Universal Serial Bus
  • HDMI High Definition Multimedia Interface
  • DVI Digital Visual Interface
  • RS-232 Recommended standard 232
  • power line communication or POTS (plain old telephone service).
  • wireless communication modules include GSM (global System for Mobile Communication), CDMA (Code Division Multiple Access), WCDMA (Wideband Code Division Multiple Access), and UMTS (universal mobile telecommunications system). ), TDMA (Time Division Multiple Access), LTE (Long Term Evolution), 4G, 5G, 6G, etc. may include a wireless communication module that supports various wireless communication methods.
  • GSM Global System for Mobile Communication
  • CDMA Code Division Multiple Access
  • WCDMA Wideband Code Division Multiple Access
  • UMTS universal mobile telecommunications system
  • TDMA Time Division Multiple Access
  • LTE Long Term Evolution
  • 4G, 5G, 6G, etc. may include a wireless communication module that supports various wireless communication methods.
  • the food serving device 200 provides a user interface (UI: User Interface) through the input/output unit 240 of the touch screen, and can receive various control signals from the user and provide information by outputting various information to the touch screen. there is.
  • UI User Interface
  • the food providing device 200 does not necessarily include the input/output unit 240, and receives a control signal from the user terminal 50 through the second communication unit 220, and sends various generated result data to the user terminal. It can be provided through (50).
  • the input unit is for inputting image information (or signal), audio information (or signal), data, or information input from a user, and may include at least one of at least one camera, at least one microphone, and an input unit. Voice data or image data collected from the input unit can be analyzed and processed as a user's control command.
  • the input unit is for receiving information from the user.
  • the processor can control the operation of the device to correspond to the input information.
  • These input units include hardware-type physical keys (e.g., buttons, dome switches, jog wheels, jog switches, etc. located on at least one of the front, back, and sides of the device) and software-type touch keys. can do.
  • the touch key consists of a virtual key, soft key, or visual key displayed on a touch screen-type display unit through software processing, or is displayed on the touch screen. It may be composed of touch keys placed in other parts.
  • the virtual key or visual key can be displayed on the touch screen in various forms, for example, graphic, text, icon, video or these. It can be made up of a combination of .
  • card-type memory e.g., SD or It may include at least one type of storage medium among (only memory), PROM (programmable read-only memory), magnetic memory, magnetic disk, and optical disk. Additionally, the memory may be a database that is separate from the device, but is connected wired or wirelessly.
  • the first memory 130 stores various commands, algorithms, etc. for the service server 100 to execute a customized food provision method based on ingredient index analysis.
  • the final ingredient is based on existing test data and real-time test data.
  • the algorithm for calculating the index and the algorithm for deriving food information for the analysis target based on the final ingredient index are stored.
  • the second memory 230 stores various commands, algorithms, etc. for operating the food serving device 200, and converts the test results through the test module 250 or the external test device 30 into real-time test data. An algorithm for doing so may be stored.
  • the second memory 230 may store an algorithm that can output food information received from the service server 100 through the output module 260.
  • the inspection module 250 and the external inspection device 30 refer to devices that can inspect preset inspection items.
  • the test module 250 may refer to a test device provided in the food serving device 200, and for example, a blood test device, a blood pressure measurement device, a biological tissue analysis device, an image analysis device, etc. can be applied.
  • the external inspection device 30 refers to an external inspection device that transmits real-time inspection data to the service server 100, and can be applied to smartphones, smart watches, etc.
  • test module 250 and the external test device 30 examples include blood tests, blood pressure tests, ECS (Electro Chemical Screening) tests, electrocardiogram tests, and skin tests (moisture, pores, etc.) , scalp tests (hair amount, hair thickness, etc.), image-based tests (iris, fingerprints, facial images, etc.) are applicable.
  • 4 to 10 are flowcharts of a method for providing customized food based on ingredient index analysis according to an embodiment of the present disclosure.
  • Figures 11 and 12 are diagrams illustrating types of inspection items.
  • the service server 100 receives real-time inspection data on the analysis target through the first communication unit 120. (S1000)
  • the food serving device 200 obtains real-time test data on the analysis target from at least one of the test module 250 and the external test device 30.
  • the service server 100 receives real-time inspection data on the analysis target from the second communication unit 220 of the food serving device 200 through the first communication unit 120.
  • the service server 100 may receive existing test data on the analysis target (user) through the first communication unit 120.
  • the service server 100 may receive existing test data from at least one of the user terminal 50 or the medical institution server, and store the received existing test data in the first memory 130 along with the test time. You can.
  • the service server 100 may proceed with the process from S1000 to produce customized food for the user.
  • the food providing device 200 when a food production request signal is received from the user, the food providing device 200 performs a real-time inspection of the user through the inspection module 250 and uses the external inspection device 30 and the second communication unit 220. You can receive real-time test results for users by connecting through
  • the food serving device 200 when the food serving device 200 completes the collection of real-time inspection data, it can transmit the real-time inspection data to the service server 100 and request derivation of food information for the user.
  • the service server 100 may receive a food production request signal by receiving real-time inspection data and a request signal for deriving food information from the food serving device 200.
  • the first processor 110 calculates the final component index based on existing inspection data and real-time inspection data. (S2000)
  • two methods can be broadly applied for the customized food manufacturing device to calculate the final ingredient index.
  • the ingredient index quantifies the influence of at least one ingredient on the subject of analysis (user).
  • the first processor 110 calculates the first component index based on existing inspection data, calculates the second component index based on real-time inspection data, and calculates the first component index. and the final component index can be calculated based on the second component index.
  • the first processor 110 may calculate the final component index by multiplying or adding the first component index and the second component index, but the calculation is not limited thereto and various calculation algorithms may be applied.
  • S2000 may include the following steps.
  • the first processor 110 calculates the second component index based on real-time inspection data. (S2100)
  • the first processor 110 calculates the final component index based on the first component index calculated based on existing inspection data and the second component index calculated in S2100. (S2200)
  • the first processor 110 may calculate the final component index by adding or multiplying the first component index and the second component index, and may apply a correction coefficient in this process. Meanwhile, there is no limit to the order of calculating the first component index and the second component index.
  • the first memory 130 may store the importance of the first component index and the importance of the second component index for each component, and the importance is determined by checking in real time whether the test result at a medical institution is more important. It can mean whether the outcome is more important.
  • the first processor 110 may calculate the final component index by reflecting the correction coefficient so that as the importance of the first component index for a specific component increases, the first component index is reflected more than the second component index.
  • the first processor 110 may calculate the final component index by reflecting the correction coefficient so that the second component index is reflected more than the first component index as the importance of the second component index for a specific component increases.
  • the first processor 110 may change the correction coefficient by considering the inspection timing of existing inspection data. For example, the first processor 110 may change the correction coefficient so that the importance of the first component index is reduced according to the length of time that has elapsed from the current point in the existing test data for the user. However, the first processor 110 may not change the correction coefficient if the inspection item is not relevant until the preset period even if the inspection period is in the past.
  • S2100 may include the following steps.
  • the service server 100 calculates ingredient power for each test item for various ingredients, where the various ingredients include calcium, magnesium, copper, vitamins, omega-3 fatty acids, methionine, cryptophane, selenium, It refers to one of various ingredients such as zinc and gluten, and ultimately, the service server 100 analyzes the target of analysis (user) and analyzes all ingredients to provide/manufacture optimized food.
  • the first processor 110 calculates the component power for each test item for a specific component, and calculates the component index by adding up the component powers calculated for all test items for the corresponding component.
  • One component does not only apply to one test item. , because it may apply to multiple inspection items.
  • test items include at least one level of higher classification items, and the lowest classification item list in the classification items of FIG. 12 represents each test item.
  • inspection items classified as the highest level include inspection data and non-inspection data items.
  • non-test data items are data items that can be directly entered by the client without going through a doctor (third test item), and data items that must be entered through a doctor (fourth test item). It is classified as
  • the medical history items include at least one of amenorrhea, alcoholism, tonsillitis, angina, venous insufficiency, glaucoma, influenza, measles, Parkinson's disease, sinusitis, tumor, and cancer, in addition to those shown in Figure 12. Any test item that corresponds to the medical history can be included.
  • examination data items refer to examination items requiring physical examination, including vital signs, general appearance and behavior of the analysis subject, body temperature, pulse rate, respiratory rate, blood pressure, overall inspection, overall palpation, complexion, rash, It includes at least one of intraocular pressure and strabismus, and can include any test item that corresponds to the examination data item in addition to those shown in FIG. 12.
  • Data items that have not gone through a doctor may include simple personal information items of the analysis target and query data items about the analysis target.
  • the query data items may include symptom items, family history items, and social history items.
  • the family history items include one of high blood pressure, diabetes, hyperlipidemia, and cancer, even if it is fatal, and can include any test item that corresponds to the family history items in addition to those shown in FIG. 12.
  • S2110 may include the following steps.
  • the first weight is a category weight, meaning a weight assigned to reflect the diagnostic reliability of each test method.
  • a test data item may have a higher weight than a non-test data item, doctored data (fourth test item), and a non-test data item, doctored data (fourth test item) may have a higher weight than a non-test data item, doctored data (fourth test item). It may have a higher weight than unused data (third test item).
  • the test item includes at least one higher classification item.
  • the first classification weight is set for the first inspection item (first classification weight) and the second inspection item (second classification weight).
  • the third test item (2-1 classification weight), the fourth test item (2-2 classification weight), the general test item (2-3 classification weight), the molecular biology test item (2-2 -4 classification weight) is set as the second classification weight.
  • a simple personal information item (3-1 classification weight), a query data item (3-2 classification weight), a medical history item (3-3 classification weight), a medical examination data item (3-4 classification weight) Classification weight) is set as the third classification weight.
  • the fourth classification weight is set for the symptom item (4-1 classification weight), family history item (4-2 classification weight), and social history item (4-3 classification weight).
  • the test item may include at least one higher level classification item.
  • the first processor 110 may calculate the first weight by multiplying the classification weight set for all higher classification items to which each test item belongs.
  • the first weight for social history is the result value of the analysis object for social history (fourth classification weight for social history) ⁇ third classification weight for query data ⁇ third test item It can be calculated based on the second classification weight for x the first classification weight for the first inspection item.
  • the fourth classification weight for social history refers to the result value calculated based on the input value of the analysis target for the corresponding test item.
  • the first processor 110 calculates a second weight corresponding to the result value of the test item. (S2112)
  • the second weight is a weight given according to the severity of the test result, and is given for each numerical range of the data value, and the numerical range may differ depending on the type of data.
  • test item A may include 4 numerical ranges
  • test B may include 5 numerical ranges
  • test C may include 7 numerical ranges.
  • the second weight does not necessarily have to be weighted, and minus, 0, and plus can all be applied, and decimal values can also be applied.
  • the first processor 110 may calculate the second weight so that the test value (result value output through the input value for the analysis target) is given according to the degree to which it deviates from the preset standard value.
  • the first processor 110 may calculate the second weight so that it is assigned to each grade to which the inspection value (result value output through the input value for the analysis target) belongs. (Example: very severe/severe/mild or very lacking/slightly lacking ingredients, etc.)
  • the first processor 110 calculates a third weight based on the second weight. (S2113)
  • the third weight may have the following purposes.
  • the third weight may be intended to increase, decrease, or nullify the influence of the second weight by a certain coefficient.
  • the third weight may be a weight for the efficacy of the first component for the analysis target according to the output data of the test item.
  • the first processor 110 may calculate the third weight based on the type of the test item and the second weight calculated for the test item.
  • Figure 13 is a diagram illustrating section matching of the second weight and the third weight.
  • the first processor 110 may calculate the third weight by matching the interval with the second weight.
  • the third weight may include the same number of numerical ranges as the second weight.
  • the first test item may have a second weight set to have four numerical ranges, 0/0/1/5, depending on the range of the result value.
  • the third weight of the first inspection item may be set to have the same four numerical ranges as the second weight.
  • the second weight and the third weight only have the same number of numerical ranges, and the weights may be different.
  • the first processor 110 calculates the component power by multiplying the first weight, the second weight, and the third weight. (S2114)
  • the first processor 110 generates comprehensive inspection data using existing inspection data and real-time inspection data, and uses this to generate the final component index. can be calculated.
  • S2000 may include the following steps.
  • the first processor 110 generates comprehensive inspection data based on real-time inspection data and existing inspection data. (S2300)
  • the first processor 110 calculates the final component index based on comprehensive inspection data. (S2400)
  • the first processor 110 may update the value of an item overlapping with existing inspection data (first inspection data) with the value of real-time inspection data (second inspection data). Additionally, the first processor ( 110) can generate comprehensive inspection data (third inspection data) by adding the values of items that are not in the existing inspection data but only in the real-time inspection data.
  • the first processor 110 may generate third inspection data based on first inspection data including existing inspection data and second inspection data including real-time inspection data.
  • the first processor 110 performs the latest inspection of the first value. This means updating with the second value that is the result.
  • the service server 100 uses this configuration to generate comprehensive inspection data by utilizing both existing inspection data and real-time inspection data, which has the effect of providing customized food optimized for users. .
  • S2400 may further include the following steps.
  • the first processor 110 calculates component power for each of a plurality of inspection items for at least one component based on comprehensive inspection data. (S2410)
  • the first processor 110 calculates a final component index for the at least one component by adding the component powers calculated for each of the plurality of test items. (S2420)
  • the final ingredient index quantifies the influence of at least one ingredient on the subject of analysis (user).
  • S2410 is the same as S2110 and S2420 is the same as S2120 except that it is based on comprehensive inspection data, so please refer to the description of the corresponding part for detailed description.
  • S2410 may further include the following steps.
  • the first processor 110 calculates a first weight corresponding to the importance of each inspection item. (S2411)
  • the first processor 110 calculates a second weight corresponding to the result value of the test item. (S2412)
  • the first processor 110 calculates a third weight based on the second weight. (S2413)
  • the first processor 110 calculates the component power by multiplying the first weight, the second weight, and the third weight. (S2414)
  • S2411 is the same as S2111
  • S2422 is the same as S2122
  • S2413 is the same as S2113
  • S2414 is the same as S2124.
  • S2411 is the same as S2111
  • S2422 is the same as S2122
  • S2413 is the same as S2113
  • S2414 is the same as S2124.
  • the first processor 110 derives food information for the analysis target based on the final ingredient index. (S3000)
  • the first processor 110 transmits the food information derived in S3000 to the food provision device 200 through the first communication unit 120 to request food production. (S4000)
  • the food serving device 200 may manufacture food based on food information or provide food information to the user.
  • the second processor 210 of the food serving device 200 can control the output module 260 to manufacture food according to food information.
  • the 3D food printer may manufacture food through a 3D food printing process based on food information received from the service server 100. A detailed description of how a 3D food printer produces food will be described later with reference to FIGS. 15 to 17.
  • the service server 100 can derive food information for the analysis target (user) based on the final ingredient index. Additionally, the service server 100 may request that the food serving device 200 manufacture user-customized food based on the derived food information. That is, the food serving device 200 can manufacture user-customized food based on food information received from the service server 100. Meanwhile, the food information may include the type of one or more food ingredients consisting of user-customized ingredients and the amount of each ingredient.
  • the food serving device 200 is a 3D food printer
  • the food information derived by the first processor 110 for the analysis target based on the final ingredient index may include at least one edible filament and the amount of each edible filament.
  • Figure 15 is a diagram illustrating a first manufacturing method of a 3D food printer.
  • Figure 16 is a diagram illustrating a second manufacturing method of a 3D food printer.
  • Figure 17 is a diagram illustrating a third manufacturing method of a 3D food printer.
  • the second processor 210 of the food providing device 200 controls the output module 260 or the 3D food printer to perform at least one of the first manufacturing method, the second manufacturing method, and the third manufacturing method.
  • Food can be manufactured/printed using the manufacturing method.
  • the first manufacturing method is a method of manufacturing food using edible filament mixed with a plurality of ingredients.
  • the edible filament may have a plurality of components arranged by region within the edible filament.
  • the edible filament may be a mixture of a plurality of ingredients.
  • the second manufacturing method is a method of manufacturing food using a plurality of edible filaments having a single ingredient.
  • the ingredients contained in each of the plurality of edible filaments may be different.
  • the 3D food printer can set the input amount for each edible filament by reflecting the required intake of each ingredient when manufacturing food.
  • a plurality of input edible filaments can be combined at one point.
  • the plurality of combined edible filaments may be joined to each other and arranged in each region, or the plurality of edible filaments may be mixed together.
  • a process of providing heat energy to the point where a plurality of edible filaments are gathered may be performed, but is not limited to this.
  • the third manufacturing method is a method of manufacturing food using edible filaments made of different ingredients for each section.
  • the edible filament manufactured by the third manufacturing method may be manufactured in advance by customizing the length or thickness of the section where each ingredient is placed based on the one-time consumption (or serving size).
  • first, second, and third manufacturing methods of the edible filament described above may be selectively applied, or at least two of them may be applied simultaneously.
  • the first processor 110 can derive food information for the analysis target (user) based on the final ingredient index, and the derived food information includes a plurality of food ingredients and a plurality of food ingredients so that the service server 100 can manufacture it.
  • the amount of each food ingredient may be included.
  • the first processor 110 may correct the final component indices by adjusting the final component indices of all calculated components to percentiles.
  • the first processor 110 can set the number of food ingredient data to be extracted and extract as many ingredients as the set number of food ingredient data to be extracted.
  • the first processor 110 sets the number of food ingredient data extracted based on the corrected final ingredient index, and the following embodiments can be applied.
  • the first processor 110 may extract food ingredient data as many as the number corresponding to the percentile number of the corrected ingredient index.
  • the first processor 110 can extract the food ingredients ranked 1st to 17th among the food ingredients containing calcium from the food ingredient DB.
  • the first processor 110 may extract food ingredient data at a rate corresponding to the percentile number of the corrected ingredient index.
  • the first processor 110 can extract the food ingredients that rank in the top 17% among the food ingredients containing calcium from the food ingredient DB.
  • the first processor 110 may calculate a score for each food ingredient by summing the best ingredient indices corresponding to each extracted food ingredient.
  • the first processor 110 may assign content weights to each food ingredient.
  • the first processor 110 may calculate a score for each food ingredient by multiplying the content ratio compared to the food ingredient corresponding to the first ranking of the final ingredient index.
  • the first processor 110 extracts the first food ingredient.
  • the first processor 110 may calculate the required intake of each food ingredient based on the calculated score for each ingredient.
  • the first processor 110 calculates the required intake of each food ingredient based on the calculated score for each ingredient, and can derive ingredient information for one serving of the analysis target. Alternatively, the first processor 110 may calculate the required intake of each food ingredient based on the calculated score for each ingredient, and may provide food ingredient information by calculating the required intake in specific weight units. (e.g. per 100g)
  • the first processor 110 can calculate the required intake amount of each food ingredient and derive food information based on this.
  • the customized food provision system 10 may be used by a plurality of different users, so it may further include components that can distinguish each user as shown below.
  • the customized food provision system 10 may further include a biometric information recognition module.
  • the first processor 110 may use the user's biometric information (e.g., fingerprint, iris, face information, etc.) to store the user's information in a memory and identify the user using the biometric information.
  • biometric information e.g., fingerprint, iris, face information, etc.
  • the customized food serving device 200 may further include a biometric information recognition module.
  • the customized food provision device 200 and the user terminal 50 are paired, and the service server 100 or the customized food provision device 200 collects biometric information from the user terminal 50. Users can also be identified based on
  • the customized food provision system 10 may further include an identification code generation module and an identification code recognition module.
  • the service server 100 or the customized food provision device 200 provides a user identification code (e.g., QR code, barcode, etc.) to the user's terminal, and the customized food provision device 200 displays/ Users can be identified by recognizing the output identification code.
  • a user identification code e.g., QR code, barcode, etc.
  • the second communication unit 220 of the customized food provision device 200 includes a short-range communication function such as NFC, and the second processor 210 communicates wirelessly with a user terminal adjacent to the customized food provision device 200 and within a preset distance. Communication can be performed and the user can be identified through this.
  • a short-range communication function such as NFC
  • the customized food provision system 10 may further include a configuration to prevent misuse by allowing the user to consume an appropriate amount.
  • the customized food provision system 10 provides customized food information optimized for the user by using the user's existing test data and real-time test data, there may be cases where the user consumes it by using it more than a set number of times. Therefore, the customized food provision system 10 provides this function.
  • the first processor 110 can calculate the consumption amount of edible filament used through the 3D food printer, and based on this, calculate the user's first intake per time or per day.
  • the first processor 110 determines that if the user has consumed the limited intake once or per day, or if a preset time has not been exceeded after consuming the first intake, the user has already consumed the food and is prompted to consume again after a certain period of time. Notifications can be provided.
  • the user may consume food only through the customized food provision system 10, but may also consume food through other methods. Therefore, the first processor 110 provides a second processing information for the user based on the user's food intake information (food intake other than food provided by the service server 100) input from the user or received from the user terminal 50. Intake can be calculated.
  • food intake information food intake other than food provided by the service server 100
  • the service server 100 may provide a notification of the use of a customized food provision service to the user based on at least one of the first intake and the second intake, and the food provision device 200 or the user terminal ( 50), notifications can be provided.
  • the food serving device 200 which provides customized food based on ingredient index analysis according to an embodiment of the present disclosure, transmits real-time test data on the analysis target obtained from at least one of the test module or external test device to the server, , It may include a communication unit 220 that receives food information derived about the analysis object from the server, and a processor 210 that controls to produce food based on the received food information.
  • the first processor 110 of the service server 100 calculates the final ingredient index based on real-time inspection data and existing inspection data and derives food information based on this, but it is necessarily limited to this.
  • the method according to an embodiment of the present disclosure described above may be implemented as a program (or application) and stored in a medium in order to be executed in combination with a server, which is hardware.
  • the above-mentioned program is C, C++, JAVA, machine language, etc. that can be read by the processor (CPU) of the computer through the device interface of the computer in order for the computer to read the program and execute the methods implemented in the program.
  • It may include code coded in a computer language. These codes may include functional codes related to functions that define the necessary functions for executing the methods, and include control codes related to execution procedures necessary for the computer's processor to execute the functions according to predetermined procedures. can do.
  • these codes may further include memory reference-related codes that indicate at which location (address address) in the computer's internal or external memory additional information or media required for the computer's processor to execute the above functions should be referenced. there is.
  • the code uses the computer's communication module to determine how to communicate with any other remote computer or server. It may further include communication-related codes regarding whether communication should be performed and what information or media should be transmitted and received during communication.
  • the steps of the method or algorithm described in connection with the embodiments of the present disclosure may be implemented directly in hardware, implemented as a software module executed by hardware, or a combination thereof.
  • the software module may be RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), Flash Memory, hard disk, removable disk, CD-ROM, or It may reside on any type of computer-readable recording medium well known in the art to which this disclosure pertains.

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Abstract

La présente divulgation concerne un serveur, un procédé, un programme et un dispositif de fourniture d'aliment destiné à fournir un aliment personnalisé sur la base d'une analyse d'un index de composition. Le serveur comprend : une mémoire dans laquelle sont stockées des données de test existantes relatives à un sujet devant être analysé ; une unité de communication qui reçoit du dispositif de fourniture d'aliment des données de test en temps réel relatives au sujet devant être analysé ; et un processeur qui, sur la base des données de test existantes et des données de test en temps réel, calcule un index de composition final qui quantifie l'influence d'au moins une composition sur le sujet devant être analysé et, sur la base de l'index de composition final calculé, déduit des informations sur un aliment relatives au sujet devant être analysé et transmet les informations sur un aliment déduites au dispositif de fourniture d'aliment par l'intermédiaire de l'unité de communication de façon à demander une préparation de l'aliment.
PCT/KR2023/009591 2022-07-08 2023-07-06 Serveur, procédé, programme et dispositif de fourniture d'aliment destiné à fournir un aliment personnalisé sur la base d'une analyse d'un index de composition WO2024010397A1 (fr)

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