KR20240080159A - Personalized food cooking order system for nearby restaurants - Google Patents

Abstract

The present invention relates to an electronic commerce method including personalized food ordering, delivery, consumption, or social dining in which a group of people with similar health conditions eat together using personal medical data of an individual's health checkup record. An interactive e-commerce system is provided, which extracts the user's physical condition, health, excess or deficiency, or anticipated disease, illness or condition based on the user's health checkup and medical data through the user's terminal, and recommends a food group that improves or maintains the corresponding condition in the first stage, and automatically adjusts and combines the user's past, illness, doctor, medical history, and prescription history of medication, specific allergies, etc., or the food ingredients and material elements that have mutual side effects or mutual synergy among the recommended foods, and finally matches the most effective personalized health food recipe for the user to improve his/her health, and allows the user to order cooking from a nearby restaurant or food cook by determining the user's taste preference, one-time meal amount, other allergic reactions, constitution, food ingredients, etc. for the matched food recipe. According to the present invention, individuals can order and consume food in appropriate amounts according to their health conditions, such as customized food or personalized health functional food, through rapid transactions with local restaurants, retailers, and the like. Local small business owners can also secure additional customers through this, and can help increase sales.

Description

Local nearby restaurant matching personalized food cooking order consumption delivery system {Personalized food cooking order system for nearby restaurants}

The present invention relates to a food recipe matching tailored to personal health status based on the individual's health checkup record and an ordering and consumption system based thereon. More specifically, it identifies excess and deficiency compared to the values for each personal health checkup item and the results of the checkup and determines the excess and deficiency values. Search for foods that are effective in improving the food, exclude foods that have side effects on one's physical health based on the user's illness, clinic prescription history, past medication prescriptions, constitution data, or body index. The cooking recipe that creates healthy food with a synergistic effect is finally extracted and sent to nearby restaurants or cooking sellers to automatically match food buyers and food delivery destinations according to personal health status or taste. Afterwards, meal size, food taste, etc. It is about a consumption system for personalized health-tailored food that is ordered and consumed through mutual coordination and consultation.

For most food delivery services, regardless of gender or age, only the menu items selected by the consumer from among the foods provided by the restaurant are ordered and delivered. However, as the awareness that one product cannot provide the same taste and food efficacy to all people has strengthened, and as the personal wellness trend has gradually strengthened, especially in the recent aging wellness era, food has also become customized to suit individual health and taste. The demand for is increasing.

Consumption of these healthy foods is mainly done in nearby residences based on word of mouth and consumers' usage experiences. However, due to the recent development of the Internet and the expansion of the base of social network services, online marketing and the development of the 4th industry, interest in online electronic transactions using personal health big data and artificial intelligence functions is increasing.

In addition, non-face-to-face online transactions, which have recently been accelerated due to the development of the 4th industrial revolution, are based on the logic of economic feasibility of large quantities and speed in the online ordering and delivery market. In the field of food consumption, various foods are provided in disposable consumption forms such as meal kits, but non-face-to-face On the Internet, it is becoming more realistic to order, purchase, and consume specific health foods or food products based on individual characteristics.

In particular, in the age of aging, more than 80% of the elderly population has chronic diseases, and the need for socially vulnerable people such as single-person households to consume healthy foods, foods, or specific foods appropriate for their health status is socially recognized. While it is gradually increasing, due to the popularity of online, mass distribution, and consumption logic, we are gradually becoming alienated from personalized consumption, and are facing difficulties in individual consumption that is suitable for one's health.

On the other hand, most small local restaurants cook food based only on their own knowledge and life experience, and due to a lack of information and promotional means for online marketing and distribution, their sales are limited to local sales rather than public promotion. It is suffering from excessive competition in the region.

Therefore, in order to resolve the increase in personal consumption desires of the socially vulnerable elderly with chronic diseases and other customers with personal tastes due to the aging population and the personal well-being era that pursues a healthy life, as well as the disconnect in consuming food tailored to personal health. , it not only provides simple information about the consumption of healthy food for each individual and food preparation recipes, but also provides information on each individual's height, weight, existing diseases, allergic reactions, personal taste preferences, meal size and preferences, etc. A social system is needed that allows people to produce, order, and consume food customized to their physical and health conditions.

In addition, it preserves the profits and losses of food providers and food restaurants for cooking and selling customized food for one person according to a personalized food recipe, and ensures smooth operation of the system for ordering and consuming personalized healthy food in the aging and well-being society. To this end, the restaurant uses the healthy food recipe order to introduce and promote it to existing regular customers as well as nearby elderly people or people with similar chronic diseases so that they can also consume it, thereby overcoming the sales risk caused by personalized orders. Only when this can be done will the sales and consumption of food tailored to the personal health of food cooks be smooth.

The purpose of the present invention to solve the above-mentioned problems is to convert the doctor's diagnosis and discrimination information contained in the health examination statement into data for each health examination item based on the individual's past health examination record history, and also to record the individual's previous medicine prescriptions and By searching the medication history, etc., we comprehensively determine the food groups that are beneficial or unfavorable to taking the medicine, and ultimately extract customized food recipes that are helpful or effective in improving health functions according to the individual's health diagnosis and physical condition. By matching and designating a nearby restaurant that cooks food, you can order and consume a certain amount of healthy food that you can consume according to your body type or taste, such as your height and weight, from the matched restaurant, or In order to reduce production costs due to a single order, restaurants use the healthy food recipe order to additionally recruit existing customer groups or nearby people with similar chronic diseases and provide customized food for improvement of each disease to people with similar diseases or groups wishing to improve their health. By providing a social system that can provide social dining functions that can be consumed together,

Specifically, the present invention recognizes the delivery location, such as the address of the purchaser who wants to purchase food useful for the individual's health condition, matches the purchaser to a nearby food supplier, and provides information about the purchaser's preferences, height, etc. along with recommended food recipes. On the one hand, it involves personal consumption of ordering food by transmitting food consumption preferences such as weight and amount of food according to health status, and on the other hand, restaurant owners promote the food to existing business partners based on the recipe provided to the restaurant. and promoting joint consumption of similar functional improvement food groups,

Ultimately, individuals are provided with customized food according to their individual health status, and the restaurant, food cook, or chain store that receives and supplies the ordered food additionally recruits more than a certain number of consumers based on this, and the first The goal is to provide an Internet e-commerce platform that also seeks to increase profits by providing a certain amount of discount to the first orderer who provided the recipe.

In order to achieve the above-mentioned purpose, the personal health checkup record customized food matching, ordering, and consumption system according to an embodiment of the present invention is provided from the user terminal through the operator server or an external medical information provider through the user's public authentication process. A user information receiving module that receives the user's past health checkup details and information about the user by accessing the server or transmitting medical data such as personal health checkup and disease history, pharmacy prescription, etc., wherein the personal The information includes, in detail, information on previous drug prescriptions and medication history, and the step of distinguishing the diagnostic values for each health checkup item and physical condition according to existing medication from the received health checkup statement, and for this purpose, photos from the user terminal. An extraction module that receives one or more files among files, document files, audio files, and video files, recognizes each checkup item and value of each health checkup statement and existing medication history, and converts them into digital data;

Receiving module that receives one's latest health checkup record data from the National Health Insurance Service server or receives a checkup certificate that specifies the doctor's final decision:

A module that classifies diseases and diseases expected to occur by the user's health checkup items according to the doctor's diagnosis or health checkup report received above;

In addition, a module that forms data related to the user's recent drug prescription history and side effects of prohibited drugs from a professional medical institution server;

Detects phenomenon information about phenomena that may appear and disease information about diseases that may occur according to the final judgment results of the health checkup certificate and medication prescription, and is effective in alleviating the phenomenon or preventing the disease. A module that converts food information about food groups into data and matches it to the above diseases and diseases;

In addition, food information is received from servers of food research and related organizations about foods that alleviate the symptoms that appear when the values of each health checkup item are higher or lower than the appropriate values and foods that are effective in preventing diseases that occur in the above cases. Information receiving module;

In addition, a module that compares the foods that are effective in improving health according to the health examination report and drug use information such as the individual's past medication history to determine the side effects and synergy effects between the food and the drug;

At this time, in the above process, foods that alleviate the above phenomenon through websites including internet portal sites, social network sites, and blog sites, and applications such as big data and artificial intelligence, and foods that are effective in preventing diseases that occur in the above cases. Information processing module that converts food recipe information into data and compares it with individual health checkup diagnosis and body-specific medication history to match it with the most appropriate food recipe:

Food information detected in connection with disease information according to the judgment result of the processing module and food cooking recipe information corresponding to the detected food information are displayed on the user terminal, and the detected food cooking recipe information is sent to a nearby cook. A user interface configuration module including a user interface for ordering and paying for food by delivering it;

On the other hand, the food cook who received the request to produce the food recipe distributes the recipe to his or her existing regular customers, elderly people, or nearby public health centers, nursing homes, hospitals, clinics, etc., where there are groups of chronic patients with the same type of disease or symptoms. An interface module that transmits and processes the information to the restaurant owner as needed, including a module that transmits it to the customer stored in his or her address book; In addition, a module including a step of requesting preferences such as height, weight, allergic reaction, meal amount, and seasoning level of the purchaser according to the cooking and provision of the food to the purchaser who has sent the food recipe;

The personal health checkup record customized food matching system includes an electronic transaction server for transactions such as ordering, delivery, and payment of the food; and a big data and artificial intelligence module that verifies the actual efficacy of the matched food to improve the values of each health checkup item, and the cook information includes the cook's name information, the cook's contact information, and the price of the food. Information, address information of the electronic transaction server selling the food, and cooking location information indicating a location where the cook cooks the food, and the processing module includes location information of the user and the cooking location information. Based on this, it is characterized in that it detects cook information about the cook who is closest to the user or is a member among the cooks who can cook and sell the food, and detects a set of similar health conditions or health conditions at the cook's restaurant. It includes a group composition module that recruits buyers with the same taste for the food and allows the recruited group of buyers to gather at a specific cooking location and directly consume the healthy food as a group,

The user information receiving module receives information about the food and food recipe that the user has been matched with since the user's last health checkup from the user terminal, information transmitted to a nearby cook, information about the matching food, information about the matching food recipe, Cooker information about the matching food, information about transmitting the matching food recipe, information about the order of the matching food, information about delivery of the matching food, information about additional purchasers of the matching food, the food Further receive information on the delivery form and group consumption for personal consumption, as well as overall diet information and food recipe transmission information matched by the user after the last health checkup,

The storage module includes information about the received food details, information about the matching period of the matching food, information about the consumption amount of the matching food, information about the eating time of the matching food, and total consumers of the corresponding ordered food. Stores person information, information on the cooking type of the food being matched, and information on the entire diet matched by the user since the last health checkup,

The artificial intelligence verification module receives the values for each health checkup item of the user from the extraction module, and converts the values for each health checkup item received into each health checkup item for the user according to the past health checkup details previously stored in the storage module. Numerical improvement confirmation module that checks whether the numerical value of each health checkup item has improved by comparing it with the numerical value; Health checkup items related to food matched by the user are selected based on information about food details matched by the user since the user's last health checkup previously stored in the storage module, and health checkup items confirmed by the numerical improvement confirmation module. a verification module that verifies the effectiveness of the matched food in improving numerical values for the health examination items by checking whether the numerical values of the selected health examination items have been improved based on the results of whether the star numerical values have improved; and

Information about the food details stored in the storage module through an artificial neural network, information about the matching period of the food being matched, information about the matching amount of the food being matched, information about the number of additional people matching the food being matched, Iteratively learning the causal relationship between the information on the matching type of the food being matched, the overall diet information matched by the user since the last health checkup, and the result of improvement in the numerical value of each health checkup item of the user confirmed by the verification module. It is characterized by including a learning module that infers right and wrong about the verification result of the verification module.

Preferably, the artificial intelligence verification module uses the verification results by the learning module to delete information about foods that do not have the effect of improving the numerical value or that do not extend the additional purchase history in the storage module and determine the effectiveness of the numerical improvement. It is characterized by further comprising an update module that updates the information about the food in the storage module in real time by continuously storing information about the food that has been verified or expanded by additional buyers, and the learning module is configured to determine the number of nodes, the hierarchy, Characterized by managing an artificial neural network pool that stores a plurality of artificial neural networks with different numbers, selecting one or more artificial neural networks from the plurality of artificial neural networks stored in the artificial neural network pool, and learning the selected one or more artificial neural networks simultaneously, , the learning module calculates the performance of the artificial neural network based on the learning rate and accuracy of the selected one or more artificial neural networks at specific times during learning, records the evaluation score of each artificial neural network, and based on the recorded evaluation score An artificial neural network to stop learning is selected, and a new artificial neural network to replace the selected artificial neural network is selected from the artificial neural network pool and trained, and the learning module is selected at each stage of the learning process. It is characterized in that the evaluation score is recorded by calculating the learning rate and error of the artificial neural network, and the learning module determines whether the recorded evaluation score multiplied by an arbitrary constant a reaches the standard value and determines whether the artificial neural network does not meet the standard. is selected, the selected artificial neural network is discarded and a new artificial neural network is selected from the artificial neural network pool, and the constant a is greater than 1.

The present invention converts the information contained in the health checkup statement into data for each health checkup item, and allows an individual to receive information such as the individual's constitution, body rhythm, health status, etc. from personal medical data such as health checkup diagnosis results and existing hospital prescription history received from medical institutions, etc. By understanding this, it is possible to provide a system for matching, ordering, and consuming customized food that is useful for improving and maintaining an individual's health.

In addition, the present invention provides information about nearby cooks who can cook and sell food that is effective in improving one's health condition, and directly matches buyers and cooks so that the buyer can send the cook a personal message with a specific food cooking recipe. It also provides an e-commerce platform for the actual transaction of custom-made food that does not generate food waste from existing restaurants through personalized orders based on individual preferences such as height, weight, meal size, and taste preferences. It can provide a food matching, ordering, and consumption system tailored to health checkup records.

In addition, a restaurant that has received an order to produce a food recipe through the present invention may send the recipe to its existing regular customer address book, nearby public health centers, nursing homes, hospitals, clinics, etc. for the elderly and chronically ill groups with the same type of disease or symptoms. By recruiting additional consumers of the healthy food as a target, small business owners such as local restaurants can improve the unprofitability of cooking and selling food based on individual orders, or, if necessary, initially in proportion to the gathering of a certain number of consumers. For the first orderer who provided the recipe, a system can be provided to increase sales by selling it at a certain amount of discount.

In addition, the present invention uses data on whether the numerical value is improved after consuming the food matched through the system, and automatically learns and verifies the causal relationship between the food and the numerical value of each health examination item. Customized food matching of the individual's health examination record , ordering, and consumption systems can be provided.

Figure 1 is a schematic diagram of the entire network system for the operation of the personal health customized food matching, ordering, and consumption system according to an embodiment of the present invention.

Figure 2 is a diagram illustrating the configuration of a system for matching, ordering, and consuming food tailored to one's personal health according to an embodiment of the present invention.

Figure 3 is a diagram illustrating the configuration of a system for matching, ordering, and consuming food tailored to one's personal health, which further includes an electronic transaction server according to an embodiment of the present invention.

Figure 4 is a diagram illustrating the configuration of a system for matching, ordering, and consuming food tailored to one's personal health, which further includes an artificial intelligence module according to an embodiment of the present invention.

Figure 5 is a diagram illustrating the configuration of a system for matching, ordering, and consuming food tailored to one's personal health, which further includes an update module according to an embodiment of the present invention.

Figure 6 is a network configuration diagram for a food cook to additionally recruit orderers of food customized for personal health according to an embodiment of the present invention.

Figure 7 shows the personal health customized food matching, ordering, and consumption system (1090) by adding a method (6010) for recruiting nearby regular customers based on food recipes through a food cook.

Figure 8 is a flowchart of a method for matching, ordering, and consuming food tailored to one's personal health according to an embodiment of the present invention.

Figure 9 is a flow chart of a method of automatically verifying the efficacy of food tailored to personal health based on artificial intelligence according to an embodiment of the present invention.

Hereinafter, some embodiments of the present invention will be described in detail through illustrative drawings. When adding reference numerals to components in each drawing, it should be noted that identical components are given the same reference numerals as much as possible even if they are shown in different drawings.

Also, when describing embodiments of the present invention, if it is determined that detailed descriptions of related known configurations or functions interfere with understanding of the embodiments of the present invention, the detailed descriptions will be omitted.

Additionally, when describing the components of an embodiment of the present invention, terms such as first, second, A, B, (a), and (b) may be used. These terms are only used to distinguish the component from other components, and the essence, order, or order of the component is not limited by the term.

With reference to FIGS. 1 to 7, the configuration and operation of a system for matching, ordering, and consuming food tailored to one's personal health according to an embodiment of the present invention will be described below.

Figure 1 is a schematic diagram of the entire network system for the operation of the personal health customized food matching, ordering, and consumption system according to an embodiment of the present invention.

Referring to Figure 1, a user terminal 1010, a National Health Insurance Service server 1020, a professional medical institution server 1030, a food institution server and website 1040, a food recipe data server 1050,

Application program (1060), food cook terminal (1070), food cook's regular customer terminal (1080)

And/or the individual's personal health customized food matching, ordering, and consumption system 1090 may transmit and receive necessary information with each other through a network 1100.

A detailed description of each of the above-described components will be provided later.

Figure 2 is a configuration diagram of a system for matching, ordering, and consuming food tailored to one's personal health according to an embodiment of the present invention.

The personal health customized food matching, ordering, and consumption system (1090) according to an embodiment of the present invention includes a user information receiving module (2010), a health checkup history and numerical value receiving module (2020), and a disease and disease information receiving module ( 2030), hospital prescription and drug history information reception module (2040),

Food recipe information reception module (2050), food cook information reception module (2060), user preference and meal amount information provision module (2070), extraction module (2080), storage module (2090), processing module (2100) and/or It may include a user interface configuration module 2011.

The user information receiving module 2010 may receive the user's health checkup report and/or personal information from the user terminal 1010. At this time, the user terminal 1010 may include a smartphone, tablet computer, laptop, desktop, etc. A health examination statement is a document that describes the results of a health examination conducted by the National Health Insurance Corporation, and may include figures for each item of the health examination conducted. Health checkup items include height, weight, waist circumference, body mass index, vision, hearing, blood pressure, total cholesterol, HDL cholesterol, LDL cholesterol, triglyceride, AST (SGOT), ALT (SGPT), gamma TP, fasting blood sugar, and urine. Protein, serum creatinine, hemoglobin, glomerular filtration rate (e-GFR), chest radiography, oral examination, KDSQ-P screening test (dementia test), KDSQ-C screening test (dementia test), chest radiography, bone density, hepatitis test It may include etc. In addition, the values for each health checkup item may include the values detected through each of the above-mentioned tests, the doctor's opinion and the results of the examination, and depending on the high or low level of the corresponding value, the number of people who may develop the disease due to the item may be included. It includes the diagnosis results of the examination agency regarding the presence or absence of the disease. Personal information may include the user's age information, gender information, and/or location information where the user is located. The user information receiving module 2010 may receive health checkup details from the user terminal 1010 in the form of photo files, document files, audio files, video files, etc.

The health checkup details and value receiving module (2020) can receive the average value of each health checkup item of the user and similar data compared thereto from the National Health Insurance Service server (1020). The health checkup details and values receiving module (2020) provides the average value of each health checkup item by age, gender, income, and/or region of the user and/or other medical examiners even if it is not from the National Health Insurance Corporation server (1020). If there is a server, you can receive the information from that server.

Even if the disease and disease information receiving module (2030) is not from the professional medical institution server (1030), Naver Intellectual's medical expert response posts, medical blogs, medical YouTube channels, medical internet broadcasting channels, public health centers, and National Health Insurance Service servers You can receive phenomenon information and/or disease and disease information corresponding to the item from the etc.

The food recipe reception information module 2050 receives information from the food research institute server and website 1040, such as food that alleviates the symptoms that appear when the value of each health checkup item is higher or lower than the appropriate value, and/or the disease that occurs in this case, You can receive food information about foods that are effective in preventing disease. For example, the above-mentioned food information may mean information about foods such as corn, eggplant mushrooms, and other agricultural crops that relieve dizziness caused by excessive or insufficient levels of a specific item or prevent anemia caused by this.

Even if the food recipe reception information module (2050) is not from the food research institute server and website (1040), it can receive posts about the efficacy of food provided by portal sites, websites of food associations, websites of medical institutions, YouTube channels, and Internet broadcasts. You can receive information about food from channels and other health broadcasting channels.

The food cook information collection module 2060 collects food and/or possible diseases that alleviate the phenomenon caused by excessive or insufficient values of each health checkup item through Internet portal sites, social network sites, blog sites, and applications 1060. Food cook information can be collected about food cooks who cook and sell food with preventive or curative effects. At this time, the food recipe data server 1050 may use data accumulated through the operating program 1060 and/or a website operated by a food recipe research institute, a website of a food association, or a personal website operated directly by a food cook. It may include blogs, YouTube channels, Internet and cable broadcasting channels, etc., and the application program (1060) can process, accumulate and manage the data from the above process. Additionally, the food cook information may include the name information of the cook who cooks the food-related cooking recipe, contact information, and regional information where the food cook's sales place is located.

The extraction module 2080 may extract values for each health checkup item and/or liver checkup records from the health checkup statement received by the user information receiving module 2010. The extraction module 2080 recognizes each health checkup item and value in the health checkup statement in the form of a photo file, document file, audio file, or video file received from the user terminal 1010 and the food cook terminal 1070 and converts them into digital data. It can be extracted.

The storage module 2090 stores personal information received or extracted by each module described above, values for each health checkup item, average value for each health checkup item, phenomenon information and disease information, food information, and/or food preparation information. You can. At this time, the storage module 2090 can store the above-described information without any rules, or can classify and store the information corresponding to each health checkup item.

Then, the processing module 2100 compares the detected average value for each health checkup item with the value for each health checkup item of the user, and determines whether the user's value is high or low based on the average value for each health checkup item. The difference value of how high it is and how low it is low can be used as a result of the health checkup diagnosis. The processing module 2100 provides health checkup items for which the user's values are determined to be higher or lower than the average value among the phenomenon information, diseases, and disease information for all health checkup items stored in the storage module 2090. It is possible to detect information about phenomena that may occur due to excessive or insufficient values for the relevant item and information about diseases that may occur accordingly. At this time, information about the detected phenomenon and/or information about the disease may be plural. And, the processing module 2110, among the food information for all health checkup items stored in the storage module 2090, for health checkup items and/or health checkup results for which the user's value is determined to be higher or lower than the average value. It is possible to detect information about foods that are effective in alleviating symptoms that may occur due to excess or deficiency of values for the relevant item, or preventing or treating diseases that may develop accordingly.

In addition, the processing module 2100 compares and analyzes the mutual non-toxic effects between foods or the mutual synergy effects between foods based on the user's past illness history, body index, hospital and clinic medication history, etc., among foods effective for diseases or diseases. This allows you to extract appropriate and efficient food cooking recipes based on the user's health condition.

Furthermore, the processing module 2100, among all the food cook information stored in the storage module 2090, determines that the user's value is higher or lower than the average value for the health checkup item due to excessive or insufficient value for the item. It is possible to detect information about food cooks who cook and sell food that is effective in alleviating symptoms that may occur or preventing or treating diseases that may develop accordingly. Accordingly, the processing module 2100 detects health checkup items that have values higher or lower than the average value for each health checkup item of the examinee corresponding to the user's age, gender, and region (location) due to excessive or insufficient values for the corresponding item. By detecting phenomena and diseases that may occur, foods that can improve the levels of the items, and/or information about the food cook who prepares and sells the food, items that are excessive or insufficient for the user, diseases expected accordingly, and such diseases. It is possible to automatically match users and food cooks by automatically providing information about foods that prevent and the food cooks who sell the foods. In other words, the processing module 2100 can extract information about a phenomenon that may occur in an individual and/or a disease resulting therefrom, considering the individual's constitution, body rhythm, health condition, etc., and can extract information about the phenomenon and/or the disease caused by the phenomenon. (Agricultural) food and/or food cooking recipes related to the food that can be used to alleviate or prevent/treat disease can be extracted, and the food cook and/or who cooks or sells the food and/or the recipe Information about the seller can be extracted. In addition, the user interface configuration module 2110 configures the above-described information, such as food order quantity, food taste preference, etc., customized and extracted for each individual, into a user interface and provides it to the individual and/or the food cook. .

The user interface configuration module 2110 determines the user matched by the processing module 2100, the value of each health checkup item of the user, the average value of the corresponding item, the excess or deficiency value of the user's value and the average value, and the excess or deficiency of the corresponding item. Users can display electronic transactions, such as orders to food cooks who cook and sell the food, diseases and conditions caused by excess or lack of the relevant items, food to prevent the relevant disease or disease, etc., as one set. The interface can be configured.

According to another embodiment of the present invention, food cook information may include cooking location information indicating the location where the food is cooked. In addition, the processing module 2100 uses the user's location information and cooking location information stored in the storage module 2090 to cook and sell food that is effective in improving the user's health checkup scores. Among the users, only information about the food cook closest to the user can be detected. Additionally, the user interface configuration module 2110 can configure the user interface to display only information about the food cook closest to the corresponding food.

Figure 3 is a configuration diagram of a customized food ordering and consumption system according to an individual's health status, which further includes an electronic transaction server according to another embodiment of the present invention.

The personal health customized food matching, ordering, and consumption system 1090 according to another embodiment of the present invention may further include an electronic transaction server 3010.

The electronic transaction server 3010 can mediate food transactions between the user and the food cook who sells the food needed to improve the excessive or insufficient values of the user's health checkup items.

According to this embodiment, the food cook information detected by the processing module 2100 and configured as a user interface by the user interface configuration module 2110 includes the food cook's name information, the food cook's contact information, and the user's numerical value improvement. It may include price information on foods that are effective and/or address information on electronic transaction servers for transactions of the foods.

The user can check the price information of the food displayed on the user terminal 1010 and access the electronic transaction server 3010 using the address information of the electronic transaction server. The electronic transaction server provides the user with detailed information about the food in question and the address information of the escrow server (included in the personal health customized food matching, ordering, and consumption system, not shown) to the user through the user terminal 1010. You can. Users can enter address information where the food will be delivered to the e-commerce server. The user entrusts the payment for the food to the escrow server, and after confirming that the user entrusted the payment to the escrow server, the food cook can deliver the food to the user's address entered in the electronic transaction server. The user can confirm the arrival of the food and notify the escrow server that the food has arrived safely. Afterwards, the escrow server can transfer the payment received from the user to the cook.

Figure 4 is a configuration diagram of a customized food ordering and consumption system according to an individual's health status, which further includes an artificial intelligence verification module according to another embodiment of the present invention.

The personal health customized food matching, ordering, and consumption system 1090 according to another embodiment of the present invention may further include an artificial intelligence verification module 4010.

According to this embodiment, the user information receiving module 2010 receives information from the user terminal 1010 about the food the user is taking to improve excess or insufficient levels after the last health checkup, and the total amount the user has taken since the last health checkup. You may further receive dietary information, information about the duration of the food being taken, information about the dosage of the food, information about the timing of the food being taken, and/or information about the dosage form of the food. And, the storage module 2090 can store the above-described information.

The artificial intelligence verification module 4010 can verify the actual efficacy of prescribed foods to improve the values of each health checkup item according to the last health checkup. This artificial intelligence verification module 4010 may include a numerical improvement verification module 4020, a verification module 4030, and/or a learning module 4040.

First, the numerical improvement confirmation module 4020 may receive numerical values for each user's health checkup item from the extraction module 2080. In addition, the value improvement confirmation module 4020 stores the values for each health checkup item of the user received from the extraction module 2080, and the user's past health checkup items according to the user's past health checkup history previously stored in the module 2090. You can check whether the values of each health checkup item have improved by comparing them with the star values.

The verification module 4030 stores health checkup items related to the food taken by the user (where the food functions) based on the information about the food history that the user has taken since the last health checkup stored in the storage module 2090. and improving the value of the corresponding item of the food by checking whether the value of the selected health checkup item has improved based on the result of improvement in the value of each health checkup item confirmed by the numerical improvement confirmation module 4020. Efficacy can be verified.

The learning module 4040 stores information about the food the user is taking to improve excess or insufficient levels after the last health checkup, stored in the storage module 2090 through an artificial neural network (not shown), and the user's last health checkup. Information on the overall diet taken since then, information on the period of taking the food the user is taking, information on the dosage of the food being taken, information on the time of taking the food being taken, and information on the dosage form of the food being taken. It is possible to infer whether the verification result of the verification module is right or wrong by repeatedly learning the causal relationship between the information and the result of improvement in the numerical value of each health checkup item of the user confirmed by the verification module. In other words, the learning module 4040 can infer through artificial intelligence whether the improvement in the health checkup items is due to the consumption of the food or another cause.

Figure 5 is a configuration diagram of a system for matching, ordering, and consuming food tailored to one's personal health, which further includes an update module according to another embodiment of the present invention.

The personal health customized food matching, ordering, and consumption system 1090 according to another embodiment of the present invention may include an artificial intelligence verification module 4010, and the artificial intelligence verification module 4010 may include an update module 5010. ) may further be included.

The update module 5010 uses the verification results from the verification module 4030 to delete information about foods that do not have the effect of improving values in the storage module 2090 and continues to retain information about foods that have been verified to have the effect of improving values. By allowing it to be stored, information about the food in the storage module 2090 can be updated in real time.

According to another embodiment of the present invention, the learning module manages an artificial neural network pool that stores a plurality of artificial neural networks with different numbers of nodes and layers, and one or more artificial neural networks among the plurality of artificial neural networks stored in the artificial neural network pool. A neural network can be selected, and one or more selected artificial neural networks can be trained simultaneously. Furthermore, the learning module calculates the performance of the artificial neural network based on the learning rate and accuracy of the selected one or more artificial neural networks at specific times during learning, records the evaluation score of each artificial neural network, and uses the recorded evaluation score as As a basis, an artificial neural network to stop learning can be selected, and a new neural network to replace the selected artificial neural network can be selected from the artificial neural network pool and trained. A pool of artificial neural networks (not shown) and multiple artificial neural networks (not shown) may be included in the artificial intelligence verification module.

According to another embodiment of the present invention, the learning module may calculate the learning rate and/or error of each selected artificial neural network at each certain stage of the learning process and record the evaluation score. Furthermore, the learning module can determine whether the recorded evaluation score multiplied by an arbitrary constant a matches the standard value and select an artificial neural network that does not meet the standard. At this time, any constant a may correspond to a value greater than 1. Furthermore, the learning module can discard the selected artificial neural network and select and learn a new artificial neural network from the artificial neural network pool.

According to another embodiment of the present invention, since the learning process of an artificial neural network does not linearly improve the learning rate with repetition, even an artificial neural network with a poor initial learning rate can rapidly improve in the future, so an arbitrary bonus point system is introduced. This can give artificial neural networks an opportunity to learn. For example, when considering an additional point of around 10 percent, the learning module can generate a random number a between 1 and 1.1 and consider the value of multiplying the generated random number a by the current learning rate as the evaluation score. The learning module can choose a number greater than 1 as a to avoid receiving a worse evaluation than the current learning rate. Here, the random number a means the arbitrary constant a described above.

According to another embodiment of the present invention, the performance of an artificial neural network generally improves with repetition of learning, but the results may not be linearly proportional to the number of repetitions of learning. In other words, since some artificial neural networks may rapidly become superior after a certain repeated learning, the present invention can take such cases into consideration by using an arbitrary constant a and give the artificial neural networks an even opportunity.

For example, in a situation where the performance (learning rate, accuracy, etc.) of an artificial neural network is measured at a specific time, and only the artificial neural network with a performance score of 80 or higher is assumed to continue learning and the rest are discarded, and the random number a is between 1 and 1.5. , learning opportunities can arise as long as the score of artificial neural network A is 54 points (54 * a > 80) or higher. The above standard score (54 points) may vary depending on the random number. Therefore, artificial neural network A, which initially scores poorly, can continue to have opportunities for learning without being discarded at a specific time. Furthermore, since the random number is greater than 1, artificial neural networks that exceed the threshold score are not discarded and can pass the test.

Figure 6 is a detailed diagram of recruiting nearby regular customers based on food recipes through food cooks in the personal health customized food matching, ordering, and consumption system according to an embodiment of the present invention.

The method (6010) of recruiting nearby regular customers based on food recipes through a food cook in an individual's personal health customized food matching, ordering, and consumption system according to an embodiment of the present invention is an application program (1060) of the above-described system. ), the food cook 1070, who has received the customized food recipe extracted through the user terminal 1010, uses the existing It is possible to recruit additional consumers for the healthy food through the customer terminal (1080) of a number of cooks who need the healthy food, such as regular customers or food cooks in nearby nursing homes, hospitals, clinics, public health centers, and welfare centers. there is. Through this, the food cook (1070) generates additional sales revenue by selling individually customized healthy food from the first single user to multiple people who need similar healthy food, thereby avoiding the risk of selling personalized health food to a single user. can do.

In addition, at this time, additional recruited customers through the method (6010) of recruiting regular customers around the food recipe based on the food cook are linked to the data server (1050) and convert the additionally recruited customers into data, so that the food cook (1070) is a regular customer. It can be secured by additional means.

In addition, the method (6010) of recruiting nearby regular customers based on food recipes through a food cook is linked to the network (1100) of Figure 1 described above, and the food cook (1070) first performs the process of Figures 1 to 5 above. After confirming the final sales volume and expected sales revenue for the personal health customized food recipe extracted through Reflecting the requirements such as taste preferences, the price of the food tailored to the individual's personal health is finally set, cooked, and delivered. As a result, the individual cooks, orders, and consumes the food tailored to the individual's health according to the individual's health status. can be accomplished.

Figure 7 shows the personal health customized food matching, ordering, and consumption system (1090) by adding a method (6010) for recruiting nearby regular customers based on food recipes through a food cook.

In the method (6010) of recruiting nearby regular customers based on food recipes through food cooks, the food cooks directly recruit consumers additionally through their food cook recruitment reception information module (6011) through electronic transactions (3010). In order to allow consumers with similar diseases or diseases who need delivery, sales, or relevant healthy food to come together for the purpose of exchanging information, they can be contacted by the food cook's sales agency, etc. through the receiving information module (6012) of consumers in groups with similar diseases. , you can gather together in a certain place and consume it as a group.

Figure 8 is a flowchart of a method for matching, ordering, and consuming food tailored to one's personal health according to an embodiment of the present invention.

The method of matching, ordering, and consuming personal health customized food according to an embodiment of the present invention includes the steps of receiving the health checkup statement and personal information of the user, the examiner (S8010), and extracting personal health checkup data and history therefrom. Step (S8080), receiving diagnostic diseases and disease information for each health item of the examinee (S8020), receiving the disease, clinic, and drug prescription history of the examinee (S8030), improving diseases and diseases for each examination item A step of receiving food information (S8040), a step of extracting a cooking recipe for the food therefrom (S8090), a step of receiving information on the cook of each food recipe (S8050), body index, weight, body weight of the buyer who is the user and examiner. , a step of receiving information such as food preference, meal amount, etc. (S8060), a step of sending additional recruitment to the food cook's existing customers (S8070) and a step of receiving additional food consumer information therefrom (S8100), health checkup diagnosis Step of storing numerical values and phenomenon information for each result examination item, disease, disease information, food and recipe information, purchaser purchase request information, food cook information, and cook's additional consumer recruitment information (S8110), phenomenon for each user's health examination item, Step of extracting diseases and illnesses (S8120), diagnosing the user's symptoms and extracting improvement food groups for expected diseases and diseases (S8130), side effects and synergies between food groups such as the user's illness, clinic drug prescription history and physical allergies An effect analysis and extraction step (S8140), a step of detecting cook information of the detected food recipe (S8150), a step of matching requests such as the user's weight, height, body specifics, meal amount, etc. (S8160), the user's body and It may include a step (S8170) of extracting the optimal food recipe according to health status, cooking information, delivery information of ordered food, additional consumer group eating information, etc., by configuring and displaying them in a user interface.

The detailed description of each step described above is replaced with the description of FIGS. 1 to 7 described above.

Figure 9 is a flowchart of a method for automatically verifying the efficacy of food based on artificial intelligence according to an embodiment of the present invention.

The method of automatically verifying the efficacy of food based on artificial intelligence according to an embodiment of the present invention can be performed following the method of matching, ordering, and consuming personalized food tailored to one's personal health described above in FIG. 8.

A method of automatically verifying the efficacy of food based on artificial intelligence according to an embodiment of the present invention includes receiving numerical values and diagnosis results for each health checkup item of the user (S9010), and the user's health checkup items according to the past health checkup history. A step (S9020) of checking whether the values for each item are improved by comparing the values and diagnosis results for each health item with the received current health item values and diagnosis results (S9020), selecting health checkup items related to the food taken by the user, and selecting the selected health checkup items. A step (S9030) of verifying the effectiveness of improving the health check-up items of the food recipe taken or consumed by checking whether the values of the health check-up items have improved. If the verification result shows efficacy, the storage module contains information about the check-up items. It may include a step of maintaining information about the food recipe (S9040) and/or, if the verification result shows no efficacy, a step of deleting information about the food recipe for the health checkup item from the storage module (S9050).

The detailed description of each step described above is replaced with the description of FIGS. 1 to 7 described above.

In this specification, a user information receiving module, an average value receiving module, a disease information receiving module, a food information receiving module, a cook information collection module, an extraction module, a storage module, a processing module, a user interface configuration module, an artificial intelligence verification module, and a numerical value receiving module. The improvement confirmation module, verification module, learning module, and/or update module may be processors that execute sequential execution processes stored in memory. Alternatively, they may operate as software modules driven and controlled by a processor. Furthermore, a processor may be a hardware device.

For reference, the method of automatically verifying the efficacy of food based on artificial intelligence and/or matching, ordering, and consuming food tailored to an individual's personal health according to an embodiment of the present invention is a program that can be performed through various computer means. It may be implemented in the form of instructions and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., singly or in combination. Program instructions recorded on the medium may be those specifically designed and constructed for the present invention, or may be known and usable by those skilled in the art of computer software. Examples of computer readable media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and ROM, RAM, Hardware devices specifically configured to store and perform program instructions, such as flash memory, may be included. Examples of program instructions include not only machine code such as that created by a compiler, but also high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

The scope of protection of the present invention is not limited to the description and expression of the embodiments explicitly described above. In addition, it is once again added that the scope of protection of the present invention may not be limited due to changes or substitutions that are obvious in the technical field to which the present invention pertains.

1010: User terminal
1020: National Health Insurance Corporation server
1030: Professional medical institution server
1040: Food agency servers and websites
1050: Food recipe data server
1060: Application
1070: Food cook terminal
1080: Food cook regular customer terminal
1090 ; Personal health customized food recipe matching system
1100 ; network
2010: User information reception module
2020: Health checkup details and numerical data reception module
2030: Disease and disease information reception module
2040: Hospital, clinic and drug prescription information reception module
2050: Food recipe information collection module
2060: Food cook reception information
2070: User preference and meal requirement information
2080: Extraction module
2090: storage module
2100: Processing module
2110: User interface configuration module
3010: E-commerce server
4010: Artificial intelligence verification module
4020: Numerical improvement confirmation module
4030: Verification module
4040: Learning module
5010: Update module

Claims (2)

Through the user terminal, based on the user's health checkup and medical data, the user extracts his or her physical condition, excess or lack of health, or expected disease, illness or disease, and recommends a food group that improves or maintains the condition as the first step. ,
Among these recommended food groups, the user's past, illness, clinic, history and drug prescription history, specific allergies, etc., or among the recommended foods, food materials and ingredient elements that have mutual side effects or mutual synergy are automatically adjusted and mixed to obtain a final result. We match personalized health food recipes that are most effective in improving the user's health, and for the matched food recipes, the orderer determines the orderer's taste preferences, portion size, other allergic reactions, constitution, food ingredients, etc. to find nearby restaurants, food, etc. An interactive e-commerce system featuring ordering dishes from a cook.
A food cook or food seller receives recommendations from individuals for healthy food recipes that are most effective in improving the orderer's individual health, and based on this, the food cook or food seller recommends recipes to existing customers and/or nearby elderly people, people with chronic diseases, etc. An online and offline commerce system that introduces and promotes foods according to the recipe to a large number of ordinary people, and cooks and sells recommended specific health-improving foods to a large number of people.

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