System for informing about personalized nutritional components and providing food purchasing service

Abstract

A system for dietary adjustment based on individual eating habits, the system comprising at least one processor, according to an embodiment of the disclosed invention: is configured to receive purchased food list data including information on the types and amounts of purchased foods purchased by a user and information on an expected consumption period which is a food purchasing cycle planned and preset by the user; and on the basis of the purchased food list data, the information on the expected consumption period, and eating habit information of the user, may generate at least one of information on the type and amount of a user-customized recommended food for purchase, which needs to be additionally purchased, and information on the type and amount of a consumption-deferred food, which needs to be left uneaten until the next food purchasing time.

Description

A system that provides personalized nutritional information and food purchasing services.

[0001] The present invention relates to a diet control system according to a user's eating habit style, which can provide personalized nutritional information and a food purchasing service by considering the user's personal eating habit style.

[0002] Recently, interest in individual health has increased, and more and more people are pursuing their own diets, either lifelong or for a certain period of time, for reasons such as personal dietary preferences, ethical considerations, health considerations, and environmental considerations.

[0003] Meanwhile, although health-related apps that help people plan their diets are widely used, there is a lack of services that take into account the diverse dietary preferences or eating habits of individuals as mentioned above.

[0004] The present invention provides a diet control system according to eating habit style, which can guide a user on the nutritional components that are insufficient or excessively consumed when purchasing food to be consumed during a set period of time, and recommend foods to be excluded or added to the diet, and a control method of the diet control system according to eating habit style.

[0005] In addition, the present invention provides a diet control system according to eating habit style and a control method of the diet control system according to eating habit style, which can provide information to readjust the food to be consumed by considering not only the physical condition of the individual user but also the individual eating habit style.

[0006] In addition, the present invention provides a diet control system according to eating habit style and a control method of the diet control system according to eating habit style, which can perform immediate purchase of food to be recommended for purchase.

[0007] In addition, the present invention provides a recipe that can be cooked with selected foods, and provides a diet control system according to eating habit style that enables the provision of a food list for individuals who have difficulty cooking at home, and a control method of the diet control system according to eating habit style.

[0008] In addition, the present invention provides a diet control system according to eating habits style and a control method of the diet control system according to eating habits style, which can help the user pursue the diet he or she wants by initially inputting allowed foods, and can clearly confirm whether the user is maintaining his or her health by providing guidance on the ingredients he or she is lacking or consuming in excess.

[0009] In addition, the present invention provides a diet control system according to eating habit style and a control method of the diet control system according to eating habit style, which can provide advance guidance on an acceptable diet suitable for the changed eating habit style through an application when a user changes his or her eating habit style in the middle and inputs the change.

[0010] In addition, the present invention provides a diet control system according to eating habits style and a control method of the diet control system according to eating habits style, which can provide information on the type and quantity of food products recommended for purchase by the user, information on the type and quantity of food products to be withheld from consumption, and recipe information, reflecting even the user's diet-related diseases or diseases requiring dietary treatment.

[0011] In addition, the present invention provides a diet control system according to eating habit style and a control method of the diet control system according to eating habit style that can improve performance, such as increasing data processing speed or reducing required memory capacity, compared to a conventional system.

[0012] According to one aspect of the disclosed invention, a system for controlling a diet according to a dietary habit style includes a data receiving unit configured to receive purchased food list data including information on the types and quantities of food purchased by a user and information on an expected intake period, which is a food purchase cycle planned and preset by the user; and a food adjustment information generating unit configured to generate, based on the purchased food list data, the information on the expected intake period, and the user's dietary habit style information, at least one of information on the types and quantities of user-customized recommended food to be additionally purchased and information on the types and quantities of food to be withheld from consumption and to be left until the next food purchase period, wherein the dietary habit style information may be preset based on at least one of personal dietary preferences, ethical considerations, health considerations, and environmental considerations.

[0013] In addition, the method further includes a nutrient information generation unit configured to generate at least one of insufficient nutrient information and excessive nutrient information based on the purchased food list data and the information on the expected intake period, and the food adjustment information generation unit is configured to generate at least one of information on the type and amount of the user-customized recommended purchase food and information on the type and amount of the food to be withheld from consumption based on at least one of the insufficient nutrient information and the excessive nutrient information and the eating habit style information, wherein the insufficient nutrient information may be information on a nutrient that the user needs to consume during the expected intake period based on the purchased food list data and the information on the expected intake period but cannot consume or is insufficient with the purchased food, and the excessive nutrient information may be information on a nutrient that the user will consume excessively if the user consumes all of the purchased food during the expected intake period based on the purchased food list data and the information on the expected intake period.

[0014] In addition, the method may include a display screen generation unit configured to generate information on a user-customized food adjustment analysis screen displayed on a display of a user terminal based on at least one of information on the type and quantity of the user-customized purchase recommendation food and information on the type and quantity of the food to be withheld from consumption.

[0015] In addition, the method may further include a recipe information generation unit that determines food to be consumed by the user during the expected consumption period based on the changed food list data generated by adding the user-customized purchase recommendation food to the purchased food and removing the food to be withheld, and generates information on a recipe for cooking the determined food using the food included in the food list data.

[0016] In addition, the food adjustment information generation unit may be configured to generate information on the type and amount of user-tailored recommended purchase foods excluding the specific food group, based on the information on the chronic disease, the purchased food list data, the information on the expected consumption period, and the information on the user's eating habit style, when the data reception unit receives information on a user's chronic disease that requires the user to not consume a specific food group.

[0017] In addition, the data receiving unit: receives secondary purchased food list data after the food purchase cycle has passed after receiving the purchased food list data; and generates stored food list data including information on the type and quantity of purchased food included in the secondary purchased food list data and information on the type and quantity of the food to be reserved for consumption, and the food adjustment information generating unit may be configured to generate information on the type and quantity of the user-tailored recommended purchase food based on the stored food list data, information on the expected consumption period, and information on the user's eating habit style.

[0018] In addition, the data receiving unit may be configured to receive the purchased food list data input from a user terminal through an input unit of the user terminal.

[0019] In addition, the data receiving unit may be configured to receive, from at least one of a food sales server and a user terminal providing an online food sales service, purchase food list data including information on the type and quantity of purchased food that the user has purchased through the online food sales service based on food purchase request input information entered into the user terminal indicating a desire to purchase the purchased food.

[0020] In addition, the food adjustment information generation unit may be configured to: generate recommended food purchase request information indicating a desire to purchase the user-customized recommended food through the online food sales service based on information on the type and quantity of the user-customized recommended food; and transmit the recommended food purchase request information to the food sales server.

[0021] In addition, the nutrient information generation unit may be configured to: generate period-specific required nutrient information, which is information on the types and amounts of nutrients that the user should consume during a specific period, based on the user's body information including at least one of the user's age information, gender information, and weight information, and the eating habit style information; and generate at least one of insufficient nutrient information and excessive nutrient information, based on the period-specific required nutrient information, the purchased food list data, and the information on the expected intake period.

[0022] In addition, the nutrient information generation unit may be configured to generate the necessary nutrient information for each period using a first artificial intelligence model based on the user's body information and the eating habit style information.

[0023] In addition, the first artificial intelligence model can be configured to be generated through a machine learning method by setting learning body information and learning eating habit style information for learning users as input variables and setting learning period-specific necessary nutrient information corresponding to learning meal data of each learning user as output variables.

[0024] In addition, the food adjustment information generation unit may be configured to generate information on the type and quantity of the user-tailored purchase recommendation food using a second artificial intelligence model based on the purchased food list data, the expected consumption period information, and the user's eating habit style information.

[0025] In addition, the system may further include a machine learning unit configured to generate the second artificial intelligence model through a machine learning method by setting information on the expected intake period for learning, data on the purchase list for learning users, and information on the eating habit style for learning as input variables, and setting data on the list of learning foods corresponding to each of the learning users and the expected intake period for learning as output variables.

[0026] Additionally, the data receiving unit, the food adjustment information generating unit, the display display screen generating unit, the nutrient information generating unit, the recipe information generating unit, and the machine learning unit may be any one of a plurality of processors included in the diet control system according to eating habit style.

[0027] A control method of a diet control system according to an eating habit style according to one aspect of the disclosed invention comprises the steps of: receiving, by a data receiving unit, purchased food list data including information on the type and quantity of food purchased by a user and information on an expected intake period, which is a food purchase cycle planned and set in advance by the user; generating, by a nutrient information generating unit, at least one of insufficient nutrient information and excessive nutrient information based on the purchased food list data and the information on the expected intake period; And a step of generating at least one of information on the type and quantity of user-customized purchase recommendation foods that are foods that need to be additionally purchased and information on the type and quantity of foods that need to be left over until the next food purchase time, based on at least one of the insufficient nutrient information and the excessive nutrient information and the eating habit style information by a food adjustment information generating unit, wherein the eating habit style information is preset according to at least one of personal eating habits preferences, ethical considerations, health considerations, and environmental considerations, and the insufficient nutrient information may be information on nutrients that cannot be consumed or are insufficient with the purchased foods even though the user needs to consume them during the expected consumption period based on the purchased food list data and the information on the expected consumption period, and the excessive nutrient information may be information on nutrients that will be excessively consumed if the user consumes all of the purchased foods during the expected consumption period based on the purchased food list data and the information on the expected consumption period.

[0028] In addition, the method may further include a step of determining food to be consumed by the user during the expected consumption period based on the changed food list data generated by adding the user-customized purchase recommendation food to the purchased food and removing the food to be withheld, and generating information on a recipe for cooking the determined food using the food included in the food list data.

[0029] In addition, the method further includes a step of receiving secondary purchased food list data after the food purchase cycle has passed after receiving the purchased food list data by the data receiving unit; a step of generating, by the data receiving unit, stored food list data including information on the types and quantities of purchased food included in the secondary purchased food list data and information on the types and quantities of the food withheld from consumption; and a step of generating, by the food adjustment information generating unit, information on the types and quantities of the user-customized recommended purchase food based on the stored food list data, information on the expected intake period, and information on the user's eating habit style, wherein the step of generating information on the types and quantities of the user-customized recommended purchase food may include a step of generating, by the food adjustment information generating unit, information on the types and quantities of user-customized recommended purchase food excluding the specific food group based on the information on the chronic disease, the purchased food list data, information on the expected intake period, and information on the user's eating habit style, when the data receiving unit receives information on the user's chronic disease that requires the user to not consume a specific food group.

[0030] In addition, the method may further include a step of receiving, by the data receiving unit, from at least one of a food sales server that provides an online food sales service and a user terminal, purchase food list data including information on the type and quantity of purchased food purchased by the user through the online food sales service based on food purchase request input information indicating a desire to purchase the purchased food inputted into the user terminal; a step of generating, by the food adjustment information generating unit, recommended food purchase request information indicating a desire to purchase the user-customized recommended food through the online food sales service based on the information on the type and quantity of the user-customized recommended food; and a step of transmitting, by the food adjustment information generating unit, the recommended food purchase request information to the food sales server.

[0031] In addition, the method further includes a step of generating period-specific required nutrient information, which is information on the types and amounts of nutrients that the user should consume during a specific period, based on the user's body information including at least one of the user's age information, gender information, and weight information, and the eating habit style information, by the nutrient information generating unit, and the step of generating at least one of the insufficient nutrient information and the excessive nutrient information may include a step of generating at least one of the insufficient nutrient information and the excessive nutrient information, by the nutrient information generating unit, based on the period-specific required nutrient information, the purchased food list data, and the information on the expected intake period.

[0032] A non-transitory recording medium according to one aspect of the disclosed invention may be computer-readable to execute a control method of a diet control system according to a eating habit style.

[0033] According to one aspect of the disclosed invention, when a user purchases food to be consumed during a set period of time, the user can be informed of the nutritional components that are insufficient or excessively consumed and can recommend foods to be excluded or added to the diet.

[0034] Additionally, according to an embodiment of the present invention, information can be provided to adjust the food to be consumed by considering not only the physical condition of the individual user but also the individual eating habit style.

[0035] In addition, according to an embodiment of the present invention, a diet control system according to a eating habit style and a control method of the diet control system according to a eating habit style can be provided, which can perform immediate purchase of food to be recommended for purchase.

[0036] Additionally, according to an embodiment of the present invention, it is possible to provide recipes that can be cooked with selected foods, and to provide a food list for individuals who have difficulty cooking at home.

[0037] In addition, according to an embodiment of the present invention, it is possible to help a user pursue a desired diet by initially inputting permitted foods, and to clearly confirm whether the user is maintaining health by providing guidance on ingredients that the user is lacking or consuming in excess.

[0038] In addition, according to an embodiment of the present invention, if a user changes his / her eating habit style in the middle and inputs the change, an acceptable diet suitable for the changed eating habit style can be provided in advance through the application.

[0039] In addition, according to an embodiment of the present invention, information on the type and quantity of food products recommended for purchase by the user, information on the type and quantity of food products to be withheld from consumption, and recipe information can be provided, reflecting even the user's dietary-related diseases or diseases requiring dietary treatment.

[0040] Additionally, it can improve performance, such as increasing data processing speed or reducing required memory capacity, compared to conventional systems.

[0041] Figure 1 is a control block diagram of a diet control system according to eating habit style according to one embodiment.

[0042] FIG. 2 is a diagram illustrating an embodiment in which a diet control system according to eating habit style is provided on a central server according to one embodiment.

[0043] FIG. 3 is a diagram for explaining eating habit style information according to one embodiment.

[0044] FIG. 4 is a diagram illustrating a user terminal displaying a user-customized food adjustment analysis screen according to one embodiment.

[0045] Figure 5 is a flowchart of a control method of a diet control system according to an eating habit style according to one embodiment.

[0046] FIG. 6 is a flowchart of a control method of a diet control system for automatically purchasing recommended foods according to an eating habit style according to one embodiment.

[0047] Figure 7 is a main screen of an application provided by a diet control system according to a eating habit style according to one embodiment.

[0048] FIG. 8 is an input screen of an application that allows a user to input eating habit style information according to one embodiment.

[0049] FIG. 9 is an input screen of an application that allows a user to input his or her body information according to one embodiment.

[0050] FIG. 10 is an input screen of an application that allows a user to directly input his / her period-specific nutrient requirements information according to one embodiment.

[0051] FIG. 11 is an input screen of an application that allows a user to input a list of food items to be purchased, according to one embodiment.

[0052] FIG. 12 is an input screen of an application that displays a list of purchased foods entered by a user according to one embodiment.

[0053] FIG. 13 is a screen of an application that displays the amount of nutrients that a user can consume during an expected consumption period based on a list of purchased foods according to one embodiment.

[0054] FIG. 14 is a screen of an application displaying shopping items that can be purchased according to one embodiment.

[0055] FIG. 15 is a screen of an application displaying user-customized purchase recommendation foods according to one embodiment.

[0056] FIG. 16 is a screen of an application displaying food items purchased by a user according to one embodiment.

[0057] Fig. 17 is a screen of an application displaying information on recommended food determined according to one embodiment.

[0058] Fig. 18 is a screen of an application displaying information of a recipe generated according to one embodiment.

[0059] Like reference numerals refer to like elements throughout the specification. This specification does not describe all elements of the embodiments, and general information within the technical field to which the disclosed invention pertains or information that overlaps between the embodiments is omitted.

[0060] Additionally, when a part is said to "include" a component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise specifically stated.

[0061] As used herein, the term "~unit" refers to a unit that processes at least one function or operation, and may refer to, for example, software, an FPGA, or a hardware component. The function provided by the "~unit" may be performed separately by multiple components, or may be integrated with other additional components. The "~unit" of this specification is not necessarily limited to software or hardware, and may be configured to be located in an addressable storage medium, or may be configured to play one or more processors. According to embodiments, multiple "~units" may be implemented as a single component, or a single "~unit" may include multiple components.

[0062] The terms first, second, etc. are used to distinguish one component from another, and the components are not limited by the aforementioned terms.

[0063] Singular expressions include plural expressions unless the context clearly indicates otherwise.

[0064] The identification codes for each step are used for convenience of explanation and do not describe the order of each step. Each step may be performed in a different order than specified unless the context clearly indicates a specific order.

[0065] The operating principle and embodiments of the disclosed invention are described below with reference to the attached drawings.

[0066] FIG. 1 is a control block diagram of a diet control system according to an eating habit style according to one embodiment, and FIG. 2 is a drawing for explaining an embodiment in which a diet control system according to an eating habit style according to one embodiment is provided on a central server.

[0067] Referring to FIGS. 1 and 2, the diet control system (100) by eating habit style may be a system that adjusts the composition of food to be consumed during a specific period based on information on food purchased by the user and the eating habit style or diet style of the user, and generates information on food to be purchased more and food to be consumed less during the period, and informs the user of this information.

[0068] Referring to FIG. 2, a diet control system (100) according to eating habit style is provided in a central server, and can communicate with at least one user terminal (200) and a food sales server (300) via wired or wireless means.

[0069] The user terminal (200) may be a terminal used by a user who has already purchased several days' worth of food offline or online to obtain information on the purchased food, information on a diet tailored to the user's eating habits, and information on which foods to purchase more of and which to consume less of. The user can view a customized food adjustment analysis screen (201) generated by the diet adjustment system (100) based on the user's eating habits style on the display of the user terminal (200).

[0070] Meanwhile, the system (100) for controlling the diet by eating habit style according to one embodiment is not necessarily limited to being provided on a central server and transmitting analysis result data or information of a user-tailored food adjustment analysis screen (201) to the user terminal (200) through communication with the user terminal (200). For example, if the user terminal (200) downloads the system (100) for controlling the diet by eating habit style by downloading an application from the central server, the system (100) for controlling the diet by eating habit style can be provided on the user terminal (200). That is, as long as the user can check information on the adjusted diet, information on foods to be purchased more and foods to be consumed less through the user terminal (200), and purchase recommended foods, the system (100) for controlling the diet by eating habit style does not matter on which terminal or server the system is provided and in which method it is operated.

[0071] Referring to FIG. 1, a diet control system (100) according to eating habit style may include a data receiving unit (110), a food control information generating unit (120), a display screen generating unit (130), a nutrient information generating unit (140), a recipe information generating unit (150), a memory (160), and a machine learning unit (170).

[0072] When a diet control system (100) according to eating habit style is provided on a server, the data receiving unit (110) can receive information entered into an input unit such as a touch pad of the user terminal (200) or data stored in the user terminal (200) from the user terminal (200).

[0073] When a diet control system (100) according to eating habit style is provided in a user terminal (200), the data receiving unit (110) can receive information input into the input unit of the user terminal (200) from the input unit. In other words, it does not matter how the data receiving unit (110) receives the data. The data receiving unit (110) can transmit the received data to the food control information generating unit (120) or the nutrient information generating unit (140).

[0074] The data receiving unit (110) can receive purchased food list data and information on expected consumption period.

[0075] The purchased food list data may include information on the type and quantity of food purchased by the user. After visiting a food store, the user can input information regarding the type and quantity of food purchased directly through the user terminal (200). Additionally, the food sales server (300) may generate information regarding the type and quantity of food purchased by the user and store it in server memory.

[0076] The data receiving unit (110) may receive the purchased food list data input into the user terminal (200) from the user terminal (200), or may automatically receive the purchased food list data of the foods purchased by the user from the food sales server (300) without the user inputting information.

[0077] The expected consumption period information may be information regarding a food purchase cycle planned and preset by the user. For example, if a user has a routine of purchasing food once every three days, the expected consumption period information may include "three days." This expected consumption period information can be directly entered by the user into the user terminal (200) and may be later modified to a different length. Furthermore, rather than being directly set by the user, the expected consumption period information may be automatically determined by the food sales server (300) by averaging the user's food purchase cycles.

[0078] The food adjustment information generation unit (120) can generate information on the type and quantity of food items recommended for purchase based on the purchased food list data, information on the expected consumption period, and the user's eating habits. The recommended food items may be items that the user needs to purchase additionally because they are determined to be insufficient to meet the appropriate nutrient intake standards for the user until the next purchase.

[0079] The food adjustment information generation unit (120) can generate information on the types and quantities of foods to be withheld based on purchased food list data, information on the expected intake period, and the user's eating habits. Foods to be withheld may be foods that are deemed excessive compared to the user's appropriate nutrient intake standards until the next food purchase, and thus should be left uneaten until the next food purchase.

[0080] In this way, the diet control system (100) based on the user's shopping habits can generate and notify the user of any food shortages or excesses until the user next shop based on the list of food items purchased after shopping. The user's eating habits can also be reflected to generate information on any food shortages or excesses until the user next shop.

[0081] FIG. 3 is a diagram for explaining eating habit style information according to one embodiment.

[0082] Referring to Figure 3, one can see various categorized eating habits styles and the types of foods that can or cannot be consumed for each eating habit style.

[0083] Dietary style information can be preset based on at least one of personal dietary preferences, ethical considerations, health concerns, and environmental considerations. However, dietary styles are not limited to vegetarianism; vegetarianism can exist in a variety of styles.

[0084] For example, a flexitarian diet falls somewhere between a meat-eating and a vegetarian diet, primarily consuming plant-based foods but occasionally consuming meat or other animal products. A pollo-pescetarian diet may consist of plant-based foods, including chicken (pollo) and seafood (pesco), while limiting other meats or animal products. A pescatarian diet may consist primarily of plant-based foods and seafood (fish and seafood), while limiting meat or other animal products. A pollo-vegetarian diet may consist primarily of plant-based foods and chicken (pollo), while limiting other meats or animal products. Lacto-ovo diet is a diet that focuses on plant-based foods, dairy (lacto), and eggs (ovo), while limiting other meats and animal products. It can also allow dairy and eggs while avoiding meat. Lacto-vegetarian diet is a diet that focuses primarily on plant-based foods and dairy products, while limiting meats and other animal products. Ovo-vegetarian diet is a diet that focuses primarily on plant-based foods and eggs, while limiting meats and other animal products. Vegan diet is a diet that excludes all animal products and consumes only plant-based foods. Frugitarian diet is a diet that focuses primarily on a vegetarian diet centered on fruits and nuts.

[0085] The aforementioned eating habit style information may be pre-stored in memory (160), and regardless of the illustrated table, an individual user may input his or her own criteria through the user terminal (200). Alternatively, the user terminal (200) may display a screen asking the user which of the aforementioned classifications he or she falls into. At this time, if the user performs an input corresponding to his or her classification criteria, the eating habit style-specific diet control system (100) may set the corresponding classification criteria as the user's eating habit style information.

[0086] When a user inputs his or her eating pattern by directly inputting eating habit style information through a user terminal (200), the data receiving unit (110) can receive the eating habit style information input into the user terminal (200) from the user terminal (200).

[0087] At this time, even if the user initially inputs the eating habit style information into the user terminal (200) and is provided with information on the type and amount of user-customized purchase recommendation food and information on the type and amount of food to be reserved for consumption that should not be consumed until the next food purchase time, the user can modify his / her eating habit style information. When the user modifies his / her eating habit style information, the modified eating habit style information can be transmitted from the user terminal (200) to the data receiving unit (110). At this time, the food adjustment information generation unit can change at least one of the type and amount of user-customized purchase recommendation food that is food to be additionally purchased and the type and amount of food to be reserved for consumption that should not be consumed until the next food purchase time, based on the user's changed eating habit style information. Referring to FIG. 1, the nutrient information generation unit (140) can generate at least one of insufficient nutrient information and excessive nutrient information based on the purchased food list data and the expected consumption period information. At this time, the nutrient information generation unit (140) may generate only one of the insufficient nutrient information and the excessive nutrient information, or may generate the insufficient nutrient information and the excessive nutrient information simultaneously.

[0088] Information on insufficient nutrients may be information on nutrients that cannot be consumed or are insufficient through purchased foods, even though the user should consume them during the expected consumption period, based on the purchased food list data and information on the expected consumption period.

[0089] Excessive nutrient information may be information on nutrients that would be excessively consumed if the user consumes all of the purchased food within the expected consumption period, based on the purchased food list data and the expected consumption period information.

[0090] Specifically, the memory (160) may have the average nutritional information of foods or foods cooked with foods included in the purchased food list data stored or set in advance, and the nutritional information generation unit (140) may calculate the total amount of nutrients that the user will consume when the user consumes all foods included in the purchased food list based on the nutritional information of each food or food. At this time, the nutritional information generation unit (140) may generate insufficient nutrient information and excessive nutrient information based on the total amount of nutrients that the user will consume and the user's personal body information.

[0091] The food adjustment information generation unit (120) can generate at least one of information on the type and quantity of user-customized recommended food to purchase and information on the type and quantity of food to be withheld from consumption based on at least one of information on insufficient nutrients and information on excessive nutrients and eating habit style information.

[0092] The food adjustment information generation unit (120) can generate modified food list data based on information on the types and quantities of user-customized recommended food for purchase and information on the types and quantities of foods to be withheld from consumption. The modified food list data may be food list data generated by adding user-customized recommended food for purchase and removing foods to be withheld from consumption.

[0093] The food adjustment information generation unit (120) can transmit information on the type and quantity of user-customized purchase recommendation foods and information on the type and quantity of food to be withheld from consumption to the display screen generation unit (130) or the recipe information generation unit (150).

[0094] The recipe information generation unit (150) can determine the food to be consumed by the user during the expected consumption period based on the changed food list data, and generate information on a recipe for cooking the food determined as the food included in the food list data.

[0095] Specifically, the memory (160) may have recipe information for cooking foods that can be cooked with a certain amount of food stored or set in advance, and the recipe information generation unit (150) may receive recipe information for dishes that can be consumed with the corresponding foods during the expected consumption period from the memory (160) or a central server based on information on the types and amounts of foods included in the changed food list data.

[0096] As described above, a user has a dietary style based on his or her own beliefs or tastes, and a diet control system (100) for each dietary style can provide information on the type and quantity of recommended food products for purchase, information on the type and quantity of food products to be withheld from consumption, and recipe information that reflect the user's dietary style.

[0097] Meanwhile, it is possible to provide information on the type and quantity of recommended foods for purchase, information on the type and quantity of foods to be avoided, and recipe information that reflect not only the user's beliefs and preferences but also the user's dietary diseases or diseases requiring dietary treatment.

[0098] Chronic conditions that require specific food groups are referred to as "diet-related diseases" or "diseases requiring dietary treatment." Individual dietary habits can significantly impact the management and improvement of symptoms. Avoiding or controlling certain foods or ingredients can help manage symptoms. Examples include atopic dermatitis, nasopharyngeal infections, lymphomatous esophagitis, autoimmune diseases, colitis, and Crohn's disease. Management of these conditions is individualized and can vary depending on the patient's eating habits and food allergies. Therefore, tailoring the patient's diet and developing a dietary management plan can help manage symptoms and control disease progression.

[0099] For example, rheumatoid arthritis is an autoimmune disease that causes inflammation in the joints. It may be necessary to avoid foods and ingredients that can contribute to joint pain and inflammation, such as salt, processed foods, saturated and trans fats, and sugars. It may also be important to maintain a healthy diet low in saturated fat and excessive sugar, and increase healthy nutrients like fruits, vegetables, nuts, and fish. People with atopic dermatitis may need to avoid certain foods and ingredients that can manage and worsen skin inflammation, such as milk, eggs, peanuts, tree nuts, shellfish, wheat, and soy.

[0100] The data receiving unit (110) may receive information on a chronic disease from a user terminal (200) in which the user has input information on his or her chronic disease, or from a memory (160) in which information on the user's chronic disease is pre-stored. The information on the chronic disease may include information on the characteristics of the user's disease that may prevent the user from consuming certain food groups, certain food groups whose consumption is restricted, or recommended food groups.

[0101] When the data receiving unit (110) receives information on the user's chronic disease, the food adjustment information generation unit (120) can generate information on the type and amount of food products recommended for purchase by the user, excluding specific food groups, based on the information on the chronic disease, the purchase food list data, the expected intake period information, and the user's eating habit style information.

[0102] Meanwhile, if a user plans and consumes food based on the modified food list data, the reserved foods may remain in the user's shopping cart even when the user next checks out. In this case, it may be desirable to consider not only the foods purchased during a second shopping trip but also the reserved foods left over from previous shopping trips, providing customized purchase recommendations that reflect the user's eating habits, including the types and quantities of recommended foods, the types and quantities of reserved foods, and recipe information.

[0103] After receiving the purchased food list data and the food purchase cycle has passed, the data receiving unit (110) can receive secondary purchased food list data from the user terminal (200) or the food sales server (300).

[0104] The data receiving unit (110) can generate stored food list data that includes information on the types and quantities of purchased food included in the secondary purchase food list data and information on the types and quantities of foods to be reserved for consumption. The stored food list data can include information on the types and quantities of foods that the user will store when secondary purchases are added.

[0105] The food adjustment information generation unit (120) can generate information on the type and quantity of food products recommended for purchase by the user based on the stored food list data, information on the expected consumption period, and information on the user's eating habit style.

[0106] Referring to FIGS. 1 and 2, the data receiving unit (110) can receive purchased food list data input from the user terminal (200) through the input unit of the user terminal (200).

[0107] The user can purchase more food through the food sales server (300) by entering information into the user terminal (200) based on the information on the food to be purchased.

[0108] A user can input food purchase request input information indicating that he or she wishes to purchase food into the input section of the user terminal (200).

[0109] The purchased food may be food purchased by the user through the online food sales service based on food purchase request input information entered into the user terminal (200) from at least one of the food sales server (300) and the user terminal (200) that provides the online food sales service.

[0110] The data receiving unit (110) can receive purchased food list data including information on the type and quantity of purchased food.

[0111] Meanwhile, food purchases may be made through a food sales server (300) in a manner in which a user terminal (200) or a diet control system (100) according to eating habit style transmits food purchase request information to the food sales server (300) without the user having to input information.

[0112] The food adjustment information generation unit (120) can generate recommended food purchase request information based on information about the type and quantity of user-tailored recommended food. The recommended food purchase request information may be a signal indicating a desire to purchase a user-tailored recommended food through an online food sales service.

[0113] The food adjustment information generation unit (120) can transmit recommended food purchase request information to the food sales server (300). The food sales server (300) can process food purchases and payments for the user's subscriber ID or account based on the recommended food purchase request information.

[0114] Meanwhile, it may be desirable to generate information on a tailored diet based on the user's body information, including information on which foods to purchase more of and which to consume less of.

[0115] The user's body information may be information about the user that includes at least one of the user's age information, gender information, and weight information.

[0116] The aforementioned user's body information may be pre-stored in memory (160), or the user may input his or her own body information through the user terminal (200). Alternatively, the user terminal (200) may display a screen asking the user what body information he or she possesses. When the user inputs information corresponding to his or her body information, the diet control system (100) for dietary habits can set the corresponding personal information as the user's body information.

[0117] The nutrient information generation unit (140) can generate period-specific required nutrient information, which is information on the types and amounts of nutrients that a user must consume during a specific period, based on body information and eating habit style information.

[0118] Meanwhile, the necessary nutrient information for each period may be generated by the nutrient information generation unit (140) based on the body information and eating habit style information entered into the user terminal (200) as described above, but the user may also directly input the necessary nutrient information for each period through a screen displayed in the application of the user terminal (200).

[0119] The nutrient information generation unit (140) can generate at least one of insufficient nutrient information and excessive nutrient information based on information on required nutrients by period, purchased food list data, and information on expected intake period.

[0120] Meanwhile, the system for controlling diet by eating habit style (100) may generate the various types of information described above by performing calculations using a preset algorithm, but may also use an artificial intelligence model learned in advance through machine learning.

[0121] Machine learning utilizes models composed of multiple parameters and can mean optimizing those parameters based on given data. Depending on the type of learning problem, machine learning can include supervised learning, unsupervised learning, and reinforcement learning. Supervised learning learns mappings between inputs and outputs and is applicable when input-output pairs are given as data. Unsupervised learning is applicable when there are only inputs and no outputs, and can identify patterns between inputs, etc.

[0122] The machine learning unit (170) can generate an artificial intelligence model in various ways. For example, the machine learning unit (170) can learn features extracted from training data using a deep learning-based learning method. At this time, a CNN (Convolutional Neural Networks) structure that stacks multiple stages of convolution layers can be utilized to learn a method of extracting features from training data. However, the learning method of the machine learning unit (170) is not necessarily limited to a method utilizing the CNN structure. For example, the learning method of the machine learning unit (170) can be a method through a machine learning algorithm including an artificial neural network (ANN) or a recurrent neural network (RNN).

[0123] The nutrient information generation unit (140) can generate necessary nutrient information for each period using the first artificial intelligence model (161) based on the user's body information and eating habit style information.

[0124] The first artificial intelligence model (161) may be an artificial intelligence model used to determine necessary nutrient information for each period corresponding to the user based on the input user's physical information and eating habit style information.

[0125] The machine learning unit (170) can receive data such as users' physical information, eating habit style information set for each user, and appropriate nutritional information in advance as learning data.

[0126] The machine learning unit (170) sets learning body information and learning eating habit style information for learning users as input variables, and sets learning period-specific necessary nutrient information corresponding to learning meal data of each learning user as output variables, thereby generating a first artificial intelligence model (161) through a machine learning method.

[0127] The food adjustment information generation unit (120) can generate information on the type and quantity of food products recommended for purchase by the user using the second artificial intelligence model (162) based on the purchased food list data, information on the expected consumption period, and the user's eating habit style information.

[0128] The second artificial intelligence model (162) may be an artificial intelligence model used to determine information on the type and quantity of recommended food products for purchase that are customized for the user based on the input user's purchase food list data, information on the expected consumption period, and information on the user's eating habit style.

[0129] The machine learning unit (170) can receive data such as information on the expected consumption period set in advance for each user, purchase list data, food list data corresponding to the expected consumption period, and eating habit style information as learning data.

[0130] The machine learning unit (170) sets information on the expected intake period for learning, data on the purchase list for learning users, and information on the eating habit style for learning as input variables, and sets data on the list of learning foods corresponding to each learning user and the expected intake period for learning as output variables, thereby generating a second artificial intelligence model (162) through a machine learning method.

[0131] In this way, the diet control system (100) by eating habit style can provide information that allows users to have a similar diet to people with the same or similar eating habit style as their own by using an artificial intelligence model that has been trained to recommend nutrients or foods that people prefer or actually consume according to various eating habit styles included in big data as learning data.

[0132] If a user changes his or her eating habits and inputs information about his or her changed eating habits style into the user terminal, the eating habits style-based diet control system (100) can use an artificial intelligence model learned to recommend nutrients or foods that people who correspond to the user's changed eating habits prefer or actually consume to provide information that allows the user to have a similar diet to people who have the same or similar eating habits style as the user's changed eating habits.

[0133] For example, if a user initially inputs information indicating that his or her eating style is vegan or allows foods corresponding to veganism into the user terminal (200), information on a vegan diet can be provided to the user using an artificial intelligence model trained to recommend nutrients or foods preferred or actually consumed by vegans. At this time, if the user additionally inputs information indicating that his or her eating style has changed to lacto into the user terminal (200), information can be provided to the user that allows him or her to have a diet similar to that of people with the changed eating style of lacto using an artificial intelligence model trained to recommend nutrients or foods preferred or actually consumed by people with the changed eating style of lacto. For example, a user who was vegan but changes his or her information to lacto can be permitted to purchase dairy products that were originally prohibited from being purchased and for which no information was provided, and can receive information on dairy products that can be consumed through the diet control system (100) for each eating style.

[0134] The artificial intelligence models, such as the first artificial intelligence model (161) and the second artificial intelligence model (162), may be stored in the memory (160) of the diet control system (100) according to the eating habit style. Meanwhile, the artificial intelligence models, such as the first artificial intelligence model (161) and the second artificial intelligence model (162), are not necessarily separate artificial intelligence models that are distinct from each other. For example, the first artificial intelligence model (161) and the second artificial intelligence model (162) may be completely identical artificial intelligence models, and the only difference between the artificial intelligence models is that there is only one artificial intelligence model according to the present invention, and one artificial intelligence model may perform all deep learning operations of the present invention.

[0135] FIG. 4 is a diagram illustrating a user terminal displaying a user-customized food adjustment analysis screen according to one embodiment.

[0136] Referring to FIG. 4, the display display screen generation unit (130) can generate information on the screen displayed on the display of the user terminal (200).

[0137] The user terminal (200) can display a screen on the display that allows the user to check or input information in real time based on the information on the screen.

[0138] At this time, the screen displayed on the display may be a screen showing information on insufficient nutrients, information on excessive nutrients, information on recommended foods to purchase, and information on foods to be withheld from consumption.

[0139] The display screen generation unit (130) can generate information on a user-customized food adjustment analysis screen (201) displayed on the display of the user terminal (200) based on at least one of information on the type and quantity of user-customized recommended purchase foods and information on the type and quantity of food to be withheld from consumption.

[0140] For example, if a user who has previously inputted physical information such as being 25 years old, weighing 45 kg, and having a lacto-ovo diet into the diet control system (100) for each eating style inputs a list of foods purchased while shopping, the display may display information indicating that the nutrients in the foods are insufficient in protein and excessive in dietary fiber based on the user's shopping cycle. In addition, the display may display information indicating that the recommended purchase foods are 3 eggs and 100 g of tofu, and that foods to be held off on until the next shopping trip are 300 g of kale and 200 g of broccoli. The user may input information indicating that he or she intends to purchase the 3 eggs and 100 g of tofu through online shopping through the user terminal (200). Alternatively, the purchase of the 3 eggs and 100 g of tofu may be automatically processed through the food sales server (300) of the online shopping mall without such input.

[0141] At least one component may be added or deleted in response to the performance of the components described above. Furthermore, those skilled in the art will readily understand that the relative positions of the components may be altered in response to the performance or structure of the system.

[0142] Figure 5 is a flowchart illustrating a control method for a diet control system based on eating habits according to one embodiment. This is merely a preferred embodiment for achieving the purpose of the present invention, and it is understood that certain components may be added or deleted as needed.

[0143] Referring to FIG. 5, the data receiving unit (110) can receive purchased food list data and information on the expected consumption period (1001).

[0144] The nutrient information generation unit (140) can generate insufficient nutrient information and excessive nutrient information based on the purchased food list data and the expected consumption period information (1002).

[0145] The food adjustment information generation unit (120) can generate information on the type and quantity of food recommended for purchase by the user and information on the type and quantity of food to be withheld from consumption based on information on insufficient nutrients, information on excessive nutrients, and information on eating habit style (1003).

[0146] The recipe information generation unit (150) can determine the food to be consumed by the user during the expected consumption period based on the changed food list data generated by adding user-customized purchase recommendation foods to purchased foods and removing foods to be withheld from consumption (1004).

[0147] The recipe information generation unit (150) can generate information on a recipe for cooking food determined as food included in the food list data (1005).

[0148] The display screen generation unit (130) can generate information on a user-customized food adjustment analysis screen (201) displayed on the display of a user terminal (200) based on information on the type and quantity of user-customized recommended food to purchase and information on the type and quantity of food to be withheld from consumption (1006).

[0149] The display of the user terminal (200) can receive information from the user-customized food adjustment analysis screen (201) and display the user-customized food adjustment analysis screen (201) (1007).

[0150] FIG. 6 is a flowchart of a control method of a diet control system for automatically purchasing recommended foods according to an eating habit style according to one embodiment.

[0151] Referring to FIG. 6, the data receiving unit (110) can receive purchased food list data from at least one of a food sales server (300) and a user terminal (200) providing an online food sales service (2001).

[0152] The nutrient information generation unit (140) can generate necessary nutrient information for each period for the user based on the user's body information and eating habit style information (2002).

[0153] The nutrient information generation unit (140) can generate information on insufficient nutrients and information on excessive nutrients based on information on required nutrients by period, purchased food list data, and information on expected intake period (2003).

[0154] The food adjustment information generation unit (120) can generate recommended food purchase request information indicating that the user wishes to purchase the customized recommended food through an online food sales service based on information on the type and quantity of the customized recommended food (2004).

[0155] The food adjustment information generation unit (120) can transmit recommended food purchase request information to the food sales server (300). The food sales server (300) can process food purchases and payments for the user's subscriber ID or account based on the recommended food purchase request information (2005).

[0156] Meanwhile, data generated by the diet control system (100) according to eating habit style can be transmitted to the user terminal (200). At this time, the information to be transmitted to the user terminal (200) may be information on an application screen generated by the display screen generation unit (130). The user terminal can control the display so that the application screen is displayed based on the information on the received application screen. That is, information on the type and amount of user-customized purchase recommendation foods generated by the diet control system (100) according to eating habit style, information on the type and amount of foods to be withheld from consumption, information on insufficient nutrients, information on excessive nutrients, changed food list data, information on foods to be consumed during the expected consumption period, information on generated recipes, etc. can be displayed on the screen of the user terminal as various UI screens.

[0157] FIG. 7 is a main screen of an application provided by a diet control system according to an eating habit style according to one embodiment, and FIG. 8 is an input screen of an application through which a user can input eating habit style information according to one embodiment.

[0158] Referring to FIG. 8 and FIG. 8, a user can run an application for diet control considering eating habits and input his or her eating habits style information through a user terminal.

[0159] An application for diet control based on eating habits is stored on a server and can be downloaded by user terminals by receiving data from the central server. Terminals with the application installed can transmit and receive data with a diet control system (100) based on eating habits located on the central server.

[0160] FIG. 9 is an input screen of an application that allows a user to input his or her body information according to one embodiment.

[0161] Referring to Figure 9, a user can input his / her own body information via a user terminal (200). For example, the user may input information indicating that his / her height is 160.2 cm. At this time, the user terminal may transmit the inputted body information, such as the user's height, weight, and age, to a diet control system (100) for each eating habit style.

[0162] FIG. 10 is an input screen of an application that allows a user to directly input his / her period-specific nutrient requirements information according to one embodiment.

[0163] Referring to FIG. 10, a user can input his / her period-specific nutritional needs through a user terminal (200). For example, a user may input information indicating that his / her daily calorie needs are 1900 calories and the daily carbohydrate needs are 50 g. At this time, the user terminal may transmit the user's period-specific nutritional needs, such as calories, carbohydrates, and vitamins, to a diet control system (100) based on eating habits.

[0164] Meanwhile, the user's period-specific nutritional needs are not necessarily limited to a method in which the user directly inputs the information. For example, the processor of the user terminal (200) can calculate the amount of calories and nutrients required for the user per day based on the user's physical information, such as height, weight, and age, input through the input screen of an application that allows the user to input physical information. At this time, the display can automatically display the daily required calories and nutrients. For example, if the user inputs information indicating that he or she is 160.2 cm tall and weighs 45 kg, the display can automatically display information indicating that the user's daily required calories are 1900 calories and the daily required amount of carbohydrates is 50 g. Furthermore, if the user additionally inputs information indicating that he or she is exercising or dieting, the display can automatically display the daily required calories and nutrients that reflect this information.

[0165] FIG. 11 is an input screen of an application that allows a user to input a list of food items to be purchased according to one embodiment, and FIG. 12 is an input screen of an application that displays a list of food items to be purchased entered by a user according to one embodiment.

[0166] Referring to FIGS. 11 and 12, a user can input a list of purchased food items via a user terminal (200). For example, a user can input a list of purchased food items, such as 100g of rice, 20g of peas, 200g of tofu, and 5 eggs, purchased from an offline store or online shopping mall. At this time, the user terminal can transmit the inputted list of purchased food items to a diet control system (100) for each eating habit style.

[0167] FIG. 13 is a screen of an application that displays the amount of nutrients that a user can consume during an expected consumption period based on a list of purchased foods according to one embodiment.

[0168] Referring to FIG. 13, a user can check the nutritional components that can be consumed based on a list of foods purchased for a specific period of time through the screen of a user terminal (200).

[0169] At this time, the user can check the information on insufficient and excessive nutrients based on the purchased food list data and the expected intake period information. For example, the display of the user terminal may display the appropriate standard for each nutrient as 100, and when the user can consume an appropriate amount of the nutrient during a specific period based on the purchased food list data, the user's nutritional content for the corresponding nutrient during the corresponding period may be displayed as 100. At this time, if the user is expected to consume an insufficient amount of the nutrient during the corresponding period based on the purchased food list data, the display may display the user's nutritional content for the corresponding nutrient during the corresponding period as a value less than 100, indicating that the nutrient is insufficient.

[0170] FIG. 14 is a screen of an application displaying shopping items that can be purchased according to one embodiment.

[0171] Referring to Figure 14, a user can check a list of foods that can be purchased through the diet control system (100) according to eating habit style on the screen of a user terminal (200). At this time, the foods available for purchase can be displayed in the following order: name, number of views, sales volume, price, etc.

[0172] FIG. 15 is a screen of an application displaying user-tailored purchase recommendation foods according to one embodiment, and FIG. 16 is a screen of an application displaying food items purchased by a user according to one embodiment.

[0173] Referring to FIGS. 15 and 16, a user can check the user-customized purchase recommendation food items that can be purchased through the diet control system (100) according to eating habit style on the screen of the user terminal (200). At this time, the diet control system (100) according to eating habit style can transmit information on the generated user-customized purchase recommendation food items to the user terminal.

[0174] For example, if a user has purchased a week's worth of groceries, but the food purchased at the store does not provide the appropriate amount of carbohydrates, iron, vitamin C, and vitamin E for the week, the user terminal may display information on the screen about recommended foods that the user should purchase additionally because they can provide carbohydrates, iron, vitamin C, and vitamin E. In this case, the application screen may display information on foods such as broccoli and spinach that the user has purchased for the week and that can provide the vitamin C that the user lacks.

[0175] FIG. 17 is a screen of an application displaying information on recommended food determined according to one embodiment, and FIG. 18 is a screen of an application displaying information on a recipe generated according to one embodiment.

[0176] Referring to FIGS. 17 and 18, the user can check the recipe information generated by the diet control system (100) according to the eating habit style through the user terminal (200). For example, the user can check the recipe information for spinach pasta generated based on the user's eating habit style and the purchased food list information indicating that the user purchased spaghetti noodles, spinach, garlic, olive oil, and oyster sauce through the application screen.

[0177] At this time, when the user inputs a command to select one of the lists of foods (List A, List B) that the user has already purchased, the user can check the recipe information for the food generated based on the user's previously input eating habit style and the selected list of purchased foods through the application's screen. In addition, when the user inputs information to select a list of recommended foods to purchase (recommended purchase food list) that the user has been recommended and will consume in the future, the user can check the recipe information for the food generated based on the user's previously input eating habit style and the selected user-customized recommended purchase food information through the application's screen.

[0178] The data receiving unit (110), food adjustment information generating unit (120), display display screen generating unit (130), nutrient information generating unit (140), recipe information generating unit (150), and machine learning unit (170) may be any one of a plurality of processors included in the diet control system (100) according to eating habit style. In addition, the control method of the diet control system (100) according to the embodiments of the present invention described so far and the embodiments to be described in the future may be implemented in the form of a program that can be driven by a processor.

[0179] Here, the program may include program commands, data files, and data structures, either singly or in combination. The program may be designed and produced using machine language code or high-level language code. The program may be specifically designed to implement the control method of the aforementioned eating habit style-specific diet control system (100), or may be implemented using various functions or definitions that are known and available to those skilled in the art of computer software. The program for implementing the control method of the aforementioned eating habit style-specific diet control system (100) may be recorded on a recording medium readable by a processor. In this case, the recording medium may be a memory (160).

[0180] The memory (160) can store a program that performs the operations described above and the operations described below, and the memory (160) can execute the stored program. In the case where there are multiple processors and memories (160), they can be integrated into a single chip or provided in physically separate locations. The memory (160) can include volatile memory such as Static Random Access Memory (S-RAM) and Dynamic Random Access Memory (D-RAM) for temporarily storing data. In addition, the memory (160) can include nonvolatile memory such as Read Only Memory (ROM), Erasable Programmable Read Only Memory (EPROM), and Electrically Erasable Programmable Read Only Memory (EEPROM) for long-term storage of control programs and control data.

[0181] The processor may include various logic circuits and operation circuits, process data according to a program provided from memory (160), and generate a control signal according to the processing result.

[0182] The disclosed embodiments have been described with reference to the attached drawings as described above. Those skilled in the art will understand that the present invention can be implemented in forms other than the disclosed embodiments without altering the technical spirit or essential features of the present invention. The disclosed embodiments are illustrative and should not be construed as limiting.

Claims

1. In a diet control system according to eating habits style including at least one processor, The above processor: It is configured to receive purchased food list data including information on the type and quantity of purchased food by the user and information on the expected consumption period, which is the food purchase cycle planned and set in advance by the user; and Based on the above-mentioned purchase food list data, the information on the above-mentioned expected consumption period, and the information on the user's eating habit style, at least one of information on the type and amount of user-tailored purchase recommendation food that should be additionally purchased and information on the type and amount of food that should not be consumed and should be left until the next food purchase period is generated. The above eating habit style information is a diet control system by eating habit style, which is preset based on at least one of personal eating habit preferences, ethical considerations, health considerations, and environmental considerations.

2. In paragraph 1, The above processor: Based on the above-mentioned purchased food list data and the information on the expected consumption period, it is configured to generate at least one of insufficient nutrient information and excessive nutrient information; and Based on at least one of the above-mentioned insufficient nutrient information and the above-mentioned excessive nutrient information and the above-mentioned eating habit style information, it is configured to generate at least one of the information on the type and amount of the above-mentioned customized purchase recommendation food and the information on the type and amount of the above-mentioned withheld food, The above-mentioned insufficient nutrient information is information on nutrients that the user must consume during the expected consumption period based on the purchased food list data and the expected consumption period information, but that cannot be consumed or are insufficient with the purchased food. The above-mentioned excessive nutrient information is information on nutrients that will be excessively consumed if the user consumes all of the purchased food during the expected consumption period based on the purchased food list data and the expected consumption period information, a diet control system according to eating habit style.

3. In paragraph 2, The above processor, A diet control system according to eating habit style, configured to generate information on a user-customized food adjustment analysis screen displayed on a display of a user terminal based on at least one of information on the type and amount of the above-mentioned user-customized purchase recommendation food and information on the type and amount of the above-mentioned food to be withheld from consumption.

4. In paragraph 2, The above processor, A diet control system according to eating habit style, which determines foods to be consumed by the user during the expected consumption period based on changed food list data in which the user-customized purchase recommendation foods are added to the above-mentioned purchased foods and the above-mentioned intake-reserved foods are removed, and generates information on a recipe for cooking the determined foods using foods included in the food list data.

5. In paragraph 2, The above processor, A diet control system according to eating habit style, wherein when information on a user's chronic disease that requires the user to not consume a specific food group is received, information on the type and amount of recommended food items for purchase customized for the user excluding the specific food group is generated based on information on the chronic disease, the purchased food list data, the expected consumption period information, and the user's eating habit style information.

6. In paragraph 2, The above processor: After receiving the above-mentioned purchased food list data and the above-mentioned food purchase cycle has passed, the second purchased food list data is received; Generate stored food list data including information on the type and quantity of purchased food included in the above secondary purchased food list data and information on the type and quantity of the above reserved food; and A diet control system according to eating habit style, configured to generate information on the type and amount of the user-tailored purchase recommendation food based on the above-mentioned stored food list data, the information on the expected consumption period, and the user's eating habit style information.

7. In paragraph 2, The above processor, A diet control system according to eating habit style, configured to receive the purchased food list data input from a user terminal through an input unit of the user terminal.

8. In paragraph 2, The above processor, A diet control system according to eating habit style, configured to receive, from at least one of a food sales server and a user terminal providing an online food sales service, purchased food list data including information on the type and quantity of purchased food purchased by the user through the online food sales service based on food purchase request input information entered into the user terminal indicating a desire to purchase the purchased food.

9. In paragraph 8, The above processor: Based on the information on the type and quantity of the above user-customized purchase recommendation food, a recommendation food purchase request information is generated with the intention of purchasing the above user-customized purchase recommendation food through the above online food sales service; and A diet control system according to eating habit style, configured to transmit the above recommended food purchase request information to the above food sales server.

10. In paragraph 2, The above processor: Based on the user's body information including at least one of the user's age information, gender information, and weight information and the eating habit style information, period-specific required nutrient information is generated, which is information on the types and amounts of nutrients that the user should consume during a specific period; and A diet control system according to eating habit style, configured to generate at least one of insufficient nutrient information and excessive nutrient information based on the necessary nutrient information for the above period, the purchased food list data, and the information on the expected intake period.

11. In paragraph 10, The above processor, A diet control system according to eating habit style, configured to generate necessary nutrient information for each period using a first artificial intelligence model based on the user's body information and eating habit style information.

12. In paragraph 11, The above processor, A diet control system according to eating habit style, configured to generate the first artificial intelligence model through a machine learning method by setting learning body information and learning eating habit style information for learning users as input variables and setting learning period-specific necessary nutrient information corresponding to learning meal data of each learning user as output variables.

13. In paragraph 2, The above processor, A diet control system according to eating habit style, configured to generate information on the type and amount of the recommended purchase food for the user using a second artificial intelligence model based on the above-mentioned purchase food list data, the information on the expected consumption period, and the information on the user's eating habit style.

14. In paragraph 13, The above processor, A diet control system according to eating habit style, configured to generate the second artificial intelligence model through a machine learning method by setting information on expected intake periods for learning, data on learning purchase lists for learning users, and information on learning eating habit styles as input variables, and setting data on learning food lists corresponding to each of the learning users and the expected intake periods for learning as output variables.

15. A step of receiving, by a processor, a purchase food list data including information on the type and quantity of purchased food by the user and information on an expected consumption period, which is a food purchase cycle planned and set in advance by the user; A step of generating at least one of insufficient nutrient information and excessive nutrient information based on the purchased food list data and the expected intake period information by the processor; and A step of generating, by a processor, at least one of the information on the type and amount of information on a user-customized recommended food item that should be additionally purchased based on at least one of the information on the insufficient nutrient and the information on the excessive nutrient and the information on the user's eating habit style, and at least one of the information on the type and amount of information on a food item that should not be consumed and should be left until the next food purchase time, The above eating habit style information is preset based on at least one of personal eating habits preferences, ethical considerations, health considerations, and environmental considerations. The above-mentioned insufficient nutrient information is information on nutrients that the user must consume during the expected consumption period based on the purchased food list data and the expected consumption period information, but that cannot be consumed or are insufficient with the purchased food. The above-mentioned excessive nutrient information is information on nutrients that will be excessively consumed if the user consumes all of the purchased food during the expected consumption period based on the purchased food list data and the information on the expected consumption period, and is a control method for a diet control system according to eating habit style.

16. In paragraph 15, A control method for a diet control system according to eating habit style, further comprising the step of determining food to be consumed by the user during the expected consumption period based on changed food list data generated by adding the user-customized purchase recommendation food to the purchased food and removing the food withheld from consumption by the processor, and generating information on a recipe for cooking the determined food with food included in the food list data.

17. In paragraph 15, A step of receiving secondary purchased food list data after the food purchase cycle has elapsed after receiving the purchased food list data by the processor; A step of generating, by the processor, a storage food list data including information on the type and quantity of purchased food included in the secondary purchased food list data and information on the type and quantity of the food to be reserved for consumption; and Further comprising a step of generating information on the type and amount of the user-customized recommended purchase food based on the stored food list data, the expected intake period information, and the user's eating habit style information by the processor, The step of generating information on the type and amount of the above customized purchase recommendation food is as follows: A control method for a diet control system according to eating habit style, comprising the step of generating information on the type and amount of recommended food for purchase by the user, excluding the specific food group, based on the information on the chronic disease, the purchased food list data, the information on the expected consumption period, and the eating habit style information of the user, when information on the user's chronic disease that requires him or her not to consume a specific food group is received by the processor.

18. In paragraph 15, A step of receiving, by the processor, from at least one of a food sales server providing an online food sales service and a user terminal, a purchase food list data including information on the type and quantity of purchased food that the user has purchased through the online food sales service based on food purchase request input information entered into the user terminal indicating a desire to purchase the purchased food; A step of generating a recommended food purchase request information with the intention of purchasing the user-customized recommended food through the online food sales service based on the information on the type and amount of the user-customized recommended food by the processor; and A control method for a diet control system according to eating habit style, further comprising a step of transmitting the recommended food purchase request information to the food sales server by the processor.

19. In Article 15, The method further comprises a step of generating period-specific required nutrient information, which is information on the types and amounts of nutrients that the user should consume during a specific period, based on the user's body information including at least one of the user's age information, gender information, and weight information, and the eating habit style information, by the processor. The step of generating at least one of the above-mentioned insufficient nutrient information and excess nutrient information is: A control method for a diet control system according to eating habit style, comprising the step of generating at least one of insufficient nutrient information and excessive nutrient information based on the necessary nutrient information for each period, the purchased food list data, and the information on the expected intake period by the processor.

20. A non-transitory recording medium having stored thereon a computer-readable computer program that executes the control method of the diet control system according to the eating habit style of Article 15.

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