KR102251445B1 - Customized pet food recommendation apparatus and method thereof - Google Patents

Abstract

The present invention relates to a customized pet food recommendation device and a method thereof. According to an embodiment, the customized pet food recommendation device comprises: a big data collection unit that collects big data information about a plurality of foods; an information receiving unit for receiving information about a pet of a user; a factor output unit that determines state information of the pet based on the received information about the pet and outputs a state factor corresponding to the determined state information; and a food recommendation unit for recommending at least one food among a plurality of foods based on the outputted state factor and the collected big data information.

Description

Customized pet food recommendation device and its method {CUSTOMIZED PET FOOD RECOMMENDATION APPARATUS AND METHOD THEREOF}

The present invention relates to a companion animal food recommendation apparatus and method thereof, and more particularly, to a technical idea of recommending companion animal food based on information on companion animals.

Recently, as the number of households and individuals raising companion animals increases, the feed market and pharmaceutical market for companion animals are growing rapidly.However, most non-professionals trust the brand rather than the ingredients of feed, so the supply of accurate nutrition for companion animals This is not being done.

Accordingly, there is an increasing need for a technology that identifies information on companion animals and recommends optimal feed for companion animals based on the identified information.

Korean Patent Laid-Open Patent No. 10-2018-0078458, "Method of providing customized food products for each animal" Korean Patent Publication No. 10-2018-0107630, "Method of providing selection information for companion animals" US Patent Publication No. 2014/0236622, "RECOMMENDING CONSUMER PRODUCTS USING PRODUCT-INGREDIENT EFFICACY AND/OR USER-PROFILE"

An object of the present invention is to provide a customized food recommendation device and method for recommending an optimal companion animal food based on information about a user's companion animal and big data information about the companion animal food.

In addition, the present invention provides a customized food recommendation device and method for quantitatively evaluating status information on companion animals based on information on companion animals and recommending optimal companion animal food corresponding to the quantitatively evaluated information. I want to.

A customized food recommendation device according to an embodiment includes a big data collection unit that collects big data information on a plurality of foods, an information receiving unit that receives information on a companion animal of a user, and information on the received companion animal. A factor output unit that determines the status information of the companion animal and outputs a status factor corresponding to the determined status information, and recommends at least one of a plurality of foods based on the output status factor and collected big data information. It may include a food recommendation.

According to one side, the food recommendation unit may pre-classify each of the plurality of foods according to the state factor, and may recommend at least one food corresponding to the output state factor among the pre-categorized foods.

According to one side, the collected big data information may include at least one of price information, brand information, authentication mark information, ingredient grade information, use age information, and review information for a plurality of foods.

According to one side, the received information on companion animals includes breed information, age information, weight information, BCS (body condition score) numerical information, basic metabolism information, daily metabolism information, food feeding amount information, allergy information, palatability information. , Activity amount information, neutralization information, and food purchase cost information.

According to one side, the food recommendation unit may recommend at least one food based on the received information on the companion animal and the collected big data information.

According to one side, the factor output unit outputs a preset first state factor if the companion animal's age is less than a preset first threshold age, and if the companion animal's age is greater than or equal to the first threshold age, and less than a preset second threshold age, A preset second state argument may be output.

According to one side, when the companion animal's age is equal to or greater than a preset second threshold age and the companion animal is in a non-generated state, the factor output unit may output a preset third state factor.

According to one side, the factor output unit may output a preset fourth state factor when the companion animal's age is equal to or greater than a preset second threshold age, the companion animal is in a non-generated state, and the companion animal is pregnant or lactating.

According to one side, when the companion animal's age is equal to or greater than a preset second threshold age and the companion animal is in a neutralized state, the factor output unit may output a preset fifth state factor.

According to one side, when the BCS value of the companion animal is less than or equal to '3', the factor output unit outputs a sixth state factor calculated through an operation of summing a fifth state factor with a value reflecting the BCS value in the fifth state factor, When the BCS value of the companion animal is equal to or greater than '6', a seventh state factor calculated through an operation of subtracting a value reflecting the BCS value in the fifth state factor from the fifth state factor may be output.

According to one side, the factor output unit outputs a preset eighth state factor based on the activity amount information when the companion animal's age is equal to or greater than a preset second threshold age and the companion animal is in a neutralized state, and the companion animal's BCS value is' If it is less than 3', the ninth state factor calculated through the operation of summing the 8th state factor and the value reflecting the BCS value in the 8th state factor is output. When the BCS value of the companion animal is '6' or more, the 8th A tenth state factor calculated through an operation of subtracting a value reflecting the BCS value in the state factor from the eighth state factor may be output.

The customized food recommendation method according to an embodiment includes the steps of collecting big data information on a plurality of foods in the big data collection unit, receiving information on the user's companion animal in the information receiving unit, and receiving it in the acceptance output unit. Determining the status information of the companion animal based on the information on the companion animal and outputting a status factor corresponding to the determined status information, and a plurality based on the status factor output from the food recommendation unit and the collected big data information. It may include the step of recommending at least one food of the food.

According to an embodiment, the present invention may recommend an optimal companion animal food based on information about a user's companion animal and big data information about the companion animal food.

According to an embodiment, the present invention may quantitatively evaluate status information on a companion animal based on information on the companion animal, and recommend an optimal companion animal food corresponding to the quantitatively evaluated information.

1 is a view for explaining a customized food recommendation device according to an embodiment.
2 is a view for explaining a detailed configuration of a customized food recommendation device according to an embodiment.
3 is a diagram for explaining a questionnaire-type membership registration process performed through a customized food recommendation device according to an embodiment.
4 is a view for explaining a companion animal food recommendation process performed through a customized food recommendation device according to an embodiment.
5 is a diagram illustrating an age definition process performed through a questionnaire-type input process according to an exemplary embodiment.
6 is a diagram for describing a first state argument output process performed through a questionnaire-type input process according to an exemplary embodiment.
7 is a diagram for describing a second state argument output process performed through a questionnaire-type input process according to an exemplary embodiment.
8 is a diagram for explaining a method for recommending customized food according to an embodiment.

Specific structural or functional descriptions of embodiments according to the concept of the present invention disclosed in the present specification are exemplified only for the purpose of describing embodiments according to the concept of the present invention, and embodiments according to the concept of the present invention They may be implemented in various forms and are not limited to the embodiments described herein.

Since the embodiments according to the concept of the present invention can apply various changes and have various forms, the embodiments will be illustrated in the drawings and described in detail in the present specification. However, this is not intended to limit the embodiments according to the concept of the present invention to specific disclosed forms, and includes changes, equivalents, or substitutes included in the spirit and scope of the present invention.

Terms such as first or second may be used to describe various elements, but the elements should not be limited by the terms. The terms are only for the purpose of distinguishing one component from other components, for example, without departing from the scope of the rights according to the concept of the present invention, the first component may be referred to as the second component, Similarly, the second component may also be referred to as a first component.

When a component is referred to as being "connected" or "connected" to another component, it is understood that it may be directly connected or connected to the other component, but other components may exist in the middle. It should be. On the other hand, when a component is referred to as being "directly connected" or "directly connected" to another component, it should be understood that there is no other component in the middle. Expressions describing the relationship between components, for example, "between" and "just between" or "directly adjacent to" should be interpreted as well.

The terms used in the present specification are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In the present specification, terms such as "comprise" or "have" are intended to designate that the specified features, numbers, steps, actions, components, parts, or combinations thereof exist, but one or more other features or numbers, It is to be understood that the presence or addition of steps, actions, components, parts, or combinations thereof does not preclude the possibility of preliminary exclusion.

Unless otherwise defined, all terms used herein including technical or scientific terms have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs. Terms as defined in a commonly used dictionary should be construed as having a meaning consistent with the meaning of the related technology, and should not be interpreted as an ideal or excessively formal meaning unless explicitly defined in the present specification. Does not.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, the scope of the patent application is not limited or limited by these embodiments. The same reference numerals shown in each drawing indicate the same members.

1 is a view for explaining a customized food recommendation device according to an embodiment.

Referring to FIG. 1, the customized food recommendation apparatus 100 according to an embodiment may recommend an optimal companion animal food based on information on companion animals and big data information on the companion animal food.

In addition, the customized food recommendation device 100 may quantitatively evaluate status information on the companion animal based on the information on the companion animal, and recommend an optimal companion animal food corresponding to the quantitatively evaluated status information.

Specifically, the customized food recommendation device 100 may recommend a companion animal food most suitable for a companion animal of a user based on big data information on a plurality of foods and a customized food analysis algorithm.

For example, the plurality of foods may be at least one of pet food and snacks, and the big data information includes price information, brand information, certification mark information, ingredient grade information, age information and reviews of the plurality of foods. May contain information.

According to one side, the customized food analysis algorithm can receive information about the user's companion animal as an input, and detect meaningful patterns or rules based on the information about the companion animal received using a machine learning technique. In addition, at least one of a plurality of foods may be recommended to a user through big data analysis based on a detected pattern or rule.

For example, the machine learning technique may include at least one of a content-based filter technique, a collaboative filtering technique, and a nearest neighbor technique.

Meanwhile, the customized food analysis algorithm can derive a status factor by quantitatively evaluating the status information on the companion animal based on the information on the companion animal, and recommends at least one food to the user based on the derived status factor. I can.

A customized food recommendation device according to an embodiment will be described in more detail with reference to FIG. 2 in the following embodiment.

2 is a view for explaining a detailed configuration of a customized food recommendation device according to an embodiment.

Referring to FIG. 2, the customized food recommendation device 200 according to an embodiment may include a big data collection unit 210, an information receiving unit 220, a takeover output unit 230, and a food recommendation unit 240. have.

Specifically, the big data collection unit 210 according to an embodiment may collect big data information on a plurality of foods.

According to one side, the collected big data information may include at least one of price information, brand information, authentication mark information, ingredient grade information, use age information, and review information for a plurality of foods.

For example, the plurality of foods may be at least one of pet foods and snacks, and may be at least one of animal foods, plant foods, and additive foods.

In addition, the ingredient grade information may mean a result of quantitatively evaluating the nutritional properties and stability of a plurality of foods consumed by the companion animal.

For a more specific example, component grade information may be derived through Table 1 below.

Ingredient characteristics Animal Vegetable additive Remark Is it a component classified into Group 1 and Group 2A by the International Cancer Research Institute (IARC)? 6 6 6 International Cancer Research Institute (IARC) data check Is it a component classified as Group A or Group B by the US Environmental Protection Agency (USEPA)? 6 6 6 US Environmental Protection Agency (USEPA) data check Is the component classified as Cat 1 or Cat 2 by the European Chemicals Agency (ECHA)? 6 6 6 European Chemicals Agency (ECHA) data verification Is the ingredient classified K,R under the National Toxicology Program (NTP)? 6 6 6 US National Toxicology Program (NTP) data verification Is it a high-risk component among the Ingredient Concerns of the Environmental Working Group (EWG)? 6 6 6 EWG (Environmental Working Group) data check Does ingestion cause incurable diseases or death? 6 6 6 Confirmation of related thesis or data from a well-known institution Is the composition completely unknown? 5 5 5 - Is it possible to contain 4D-animals (Dead, Diseased, Dying, Disabled) by FDA such as meat meal, animal digest, animal fat, meat and bone powder (meat and bone meal, etc.), poultry by-products, unspecified fat and oil? 5 - - - Are the sources of animal sources unclear and the type unknown? Ex) Animal broth, animal soup 5 - - - Is it a component classified as Group 2B and Group 3 substances by the International Cancer Institute (IARC)? 4 4 4 International Cancer Research Institute (IARC) data check Is it a component classified by the US Environmental Protection Agency (USEPA) into Groups C and D? 4 4 4 US Environmental Protection Agency (USEPA) data check Is the component classified as Cat 3 by the European Chemicals Agency (ECHA)? 4 4 4 European Chemicals Agency (ECHA) data verification Is it a component in the medium-risk group among the Ingredient Concerns of the Environmental Working Group (EWG)? 4 4 4 EWG (Environmental Working Group) data check Of animal raw materials, the source is clear, but the type is unknown? Ex) Poultry, poultry meal, fish meal, poultry liver, poultry internal organs 3 - - - Among animal raw materials, is the source clear and the part is unclear? Ex) Chicken intestine, cow intestine, pig intestine 3 - - - Is it an ingredient that went through the rendering process among animal raw materials? Ex) Dehydrated~, dried~, ~wheat, ~min, ~powder 3 - - Ingestion efficacy has not been proven, and does ingestion cause curable diseases? 3 3 3 Is there a research result that has not been defined by a well-established institution, but has been found to be toxic as a result of animal testing? 3 3 3 - Is it a limiting ingredient in the feed management method? 3 3 3 - Is the source of the plant ingredients clear and the type of raw material unknown? Ex) Vegetables~, plants~ - 3 - - Is it helpful when ingested in an appropriate amount, but does a curable disease occur when ingested in large amounts? 2 2 2 Are the types and parts of animal raw materials a clear visceral part? 2 - - Is the source and raw material clear, and is it a growth-oriented animal protein? One - - - Is it the purpose of additives for product composition? 0 0 0 -

That is, the ingredient grade information according to an embodiment is the International Cancer Institute (IARC), the US Environmental Protection Agency (USEPA), the European Chemicals Agency (ECHA), the US toxicology program (NTP), and the US Environmental Protection Agency (USEPA). , EWG (environmental working group) and other companion animal research institutes collected from at least one of the relevant institutions related to food ingredients related big data is risk (6), caution (5), caution 2 (4), caution 1 (3). ), normal (2), good (1), and unspecified (0) grades.

According to one side, the big data collection unit 210 may calculate ingredient grade information using big data data related to food ingredients collected from at least one related organization.

The information receiving unit 220 according to an embodiment may receive information on a companion animal of a user.

According to one side, the received information on companion animals includes breed information, age information, weight information, BCS (body condition score) numerical information, basic metabolism information, daily metabolism information, food feeding amount information, allergy information, palatability information. , Activity amount information, neutralization information, and food purchase cost information.

For example, the information receiving unit 220 may be collected from a medical institution that has examined a user or a companion animal.

In addition, the BCS value refers to a value that can be used to determine whether the companion animal is underweight, solid, or maintains an appropriate weight, and the BCS value can be expressed as any one of values from '1' to '9'. have.

More specifically, if the BCS value is '1' to '3', it may be underweight, if it is '4' to '5', it may be in a normal state, and if it is '6' to '9', it may be in a solid state.

The argument output unit 230 according to an embodiment determines the status information of the companion animal based on the information on the companion animal received through the information receiving unit 220, and outputs a status factor corresponding to the determined status information. I can. As an example, the state argument may be a positive real value.

For example, the status information of the companion animal may include at least one of information about whether or not to be neutralized, whether to be pregnant, whether to breastfeed, an activity level, and a BCS value. In other words, the argument output unit 230 comprehensively analyzes the status of the companion animal according to whether the companion animal is neutralized, pregnant, lactating, activity, and BCS, and expresses the analysis result as a quantitative value (status factor). I can.

According to one side, the factor output unit 230 outputs a preset first state factor if the companion animal's age is less than a preset first threshold age, and the companion animal's age is greater than or equal to the first threshold age and a preset second threshold If it is less than the age, a preset second state factor may be output.

More specifically, when the age of the companion animal is less than 4 months, which is the first threshold age, the factor output unit 230 may output a first state factor, where the first state factor is '3' when the companion animal is individual. It is determined as', and in the case of a cat, it can be determined as '2.5'.

In addition, when the age of the companion animal is 4 months or more, which is the first critical age, and less than 12 months, which is the second critical age, the factor output unit 230 may output a second state factor, where the second state factor is' It can be determined as 2'.

According to one side, the factor output unit 230 may output a preset third state factor when the companion animal's age is greater than or equal to the second threshold age and the companion animal is in a non-generated state.

More specifically, when the age of the companion animal is 12 months or more and the companion animal is in a non-neutralized state, the argument output unit 230 may output a third state factor, where the third state factor is when the companion animal is individual. In the case of a cat, it can be determined as '1.8', and in the case of a cat, it can be determined as '1.4'.

According to one side, the factor output unit 230 may output a preset fourth state factor when the age of the companion animal is greater than or equal to the second threshold age, the companion animal is in a non-generated state, and the companion animal is pregnant or lactating.

More specifically, the argument output unit 230 may output a fourth state factor when the companion animal is 12 months or more in age and the companion animal is in a non-neutralized state and is pregnant, where the fourth state factor is '3'. Can be determined.

In addition, the argument output unit 230 may output a fourth state factor when the companion animal is 12 months or longer in age, and the companion animal is in a non-neutralized state and is nursing, where the fourth state factor is '4'. Can be determined as

According to one side, when the age of the companion animal is equal to or greater than the second threshold age and the companion animal is in a neutralized state, the factor output unit 230 may output a preset fifth state factor.

More specifically, when the age of the companion animal is 12 months or more and is in a neutralized state, the argument output unit 230 may output a fifth state factor, where the fifth state factor is '1.6 when the companion animal is individual. ', and in the case of a cat, it can be determined as '1.2'.

According to one side, when the BCS value of the companion animal is less than or equal to '3', the factor output unit 230 is a sixth state factor calculated through an operation that adds a value reflecting the BCS value to the fifth state factor and the fifth state factor. Is output, and when the BCS value of the companion animal is equal to or greater than '6', a seventh state factor calculated through an operation of subtracting a value reflecting the BCS value in the fifth state factor from the fifth state factor may be output.

More specifically, when the companion animal is a cat, the age is 12 months or more, is in a neutralized state, and the BCS value is '3' or less or '6' or more, the fifth state factor '1.2' and the BCS value are Each of the sixth state argument and the seventh state argument may be output through an operation.

According to one side, when the companion animal is a cat, the age is 12 months or more, is in a non-neutralized state, and is not pregnant or lactating, the BCS value is '3' or less or '6' or more, the third Each of the sixth state argument and the seventh state argument may be output through the operation of the state argument '1.4' and the BCS value.

Meanwhile, in the process of calculating the sixth state argument and the seventh state argument, if the BCS value is '1', the value '0.3' is reflected in the fifth state argument, and if the BCS value is '2', the fifth state argument is '0.2. 'Reflects a value, and if the BCS value is '3', a value of '0.1' may be reflected in the fifth state argument.

In addition, if the BCS value is '6', the value of '0.1' is reflected in the fifth state factor, if the BCS value is '7', the value of '0.2' is reflected in the fifth state factor, and if the BCS value is '8', the value is zero. A value of '0.3' may be reflected in the 5 state argument, and a value of '0.4' may be reflected in the fifth state argument if the BCS value is '9'.

For a more specific example, if the companion animal is a cat, the age is 12 months or more, is in a neutralized state, and the BCS value is 2, the calculation of "1.2 + (1.2 x 0.2)" 6 '1.44' can be output as a status argument.

In addition, if the companion animal is a cat, the age is 12 months or more, is in a neutralized state, and the BCS value is 8, the argument output unit 230 is used as a seventh state factor through an operation of '1.2-(1.2 x 0.3)'. '0.84' can be output.

According to one side, when the age of the companion animal is equal to or greater than the second threshold age and the companion animal is in a neutralized state, the factor output unit 230 may output a preset eighth state factor based on the activity amount information.

More specifically, when the companion animal is a dog, the age is 12 months or more, and is in a neutralized state, the acceptance output unit 230 may analyze the activity amount of the companion animal based on the activity amount information, and based on the analyzed companion animal activity amount. The eighth state argument can be output. Here, the eighth state factor is determined as '2' when the companion animal's activity amount is analyzed as "light activity amount", and is determined as '3' when it is analyzed as "normal activity amount", and '5' when it is determined as "high activity amount" Can be determined as

According to one side, when the companion animal is a dog, the age is 12 months or more, is in a non-neutralized state, and is not pregnant or lactating, the amount of activity of the companion animal can be analyzed based on the activity amount information. The eighth state factor may be output based on the amount of activity of the companion animal.

For example, the factor output unit 230 may determine whether "light activity amount", "normal activity amount", and "high activity amount" by using the activity amount information of the companion animal and preset activity amount threshold values.

According to one side, when the BCS value of the companion animal is less than or equal to '3', the factor output unit 230 is a ninth state factor calculated through an operation that adds a value reflecting the BCS value to the eighth state factor and the eighth state factor. When the BCS value of the companion animal is '6' or more, a tenth state factor calculated through an operation of subtracting a value reflecting the BCS value in the eighth state factor from the eighth state factor may be output.

More specifically, the argument output unit 230 analyzes the companion animal as an activity amount of any one of a dog, an age of 12 months or more, a neutralized state, and an activity amount of "light activity amount", "normal activity amount", and "high activity amount" And, when the BCS value is less than or equal to '3' or greater than or equal to '6', each of the ninth state argument and the tenth state argument may be output through the calculation of the value of the eighth state factor and the BCS value.

Meanwhile, in the process of calculating the ninth state argument and the tenth state argument, if the BCS value is '1', the value '0.3' is reflected in the eighth state argument, and if the BCS value is '2', the eighth state argument is '0.2. 'Reflects the value, and if the BCS value is '3', the value '0.1' may be reflected in the eighth state argument.

In addition, if the BCS value is '6', the value of '0.1' is reflected in the eighth state factor, if the BCS value is '7', the value of '0.2' is reflected in the eighth state factor, and if the BCS value is '8', the value is zero. A value of '0.3' may be reflected in the 8 state argument, and a value of '0.4' may be reflected in the eighth state argument if the BCS value is '9'.

For a more specific example, if the companion animal is a dog, the age is 12 months or more, and is in a neutralized state, the activity amount is "normal activity amount" and the BCS value is '3', "3 + (3 x 0.1)" '3.3' may be outputted as the ninth state argument through the operation of.

In addition, the argument output unit 230 is a companion animal is a dog, age is 12 months or more, is in a neutralized state, the activity amount is "light activity amount" and the BCS value is '8', through the calculation of "2-(2 x 0.3)" '1.4' can be output as the tenth state argument.

The food recommendation unit 240 according to an embodiment includes at least one food among a plurality of foods based on the state argument output through the take-out output unit 230 and the big data information collected through the big data collection unit 210. Can be recommended to users.

According to one side, the food recommendation unit 240 may classify each of the plurality of foods according to a state factor in advance and recommend at least one food corresponding to the output state factor among the previously categorized foods.

For example, the food recommendation unit 240 may recommend to the user at least one food corresponding to the status factor 1.44 among previously classified foods when the status factor output from the take-out output unit 230 is 1.44. .

For a more specific example, the food recommended in response to the condition factor of 1.44 may be a food that is neutralized at the age of 12 months or more and contains nutrients necessary for a cat having a BCS value of '2'.

According to one side, the food recommendation unit 240 may recommend at least one food based on the received information on the companion animal and the collected big data information.

In other words, the food recommendation unit 240 may recommend food using information on companion animals directly received from the information receiving unit 220 as well as food recommendation using a state factor.

For a more specific example, the food recommendation unit 240 may analyze and recommend food suitable for the companion animal breed based on the breed information of the companion animal.

In addition, the food recommendation unit 240 may analyze and recommend food suitable for the age of the companion animal based on the age information.

In addition, the food recommendation unit 240 may analyze and recommend foods for minimum daily and recommended nutritional intake based on at least one of weight information, basic metabolic amount information, daily metabolic amount information, and food feeding amount information.

In addition, the food recommendation unit 240 may analyze and recommend food that does not contain allergic components of companion animals based on the allergy information.

In addition, the food analysis unit 240 may analyze and recommend food that meets a user's desired price based on the food purchase cost information.

In addition, the food analysis unit 240 may analyze and recommend foods preferred by the companion animal of the user based on the preference information.

Meanwhile, the food analysis unit 240 analyzes the ingredient grade score, the authentication mark score, and the brand score based on the ingredient grade information, the authentication mark information, and the brand information received from the big data collection unit 210, and calculates the analyzed score. You can recommend food based on it.

In addition, the food analysis unit 240 may recommend food through a user-based analysis based on the review information received from the big data collection unit 210.

According to one side, the customized food recommendation device 200 according to an embodiment may be implemented as a separate software or app, and the customized food recommendation device 200 implemented as a software or app is a'question-type member subscription. Process' and'companion animal food recommendation process' can be performed.

The'question-type member registration process' and the'companion animal food recommendation process' performed through the customized food recommendation device according to an embodiment will be described in more detail later with reference to FIGS. 3 to 7.

3 is a diagram for explaining a questionnaire-type membership registration process performed through a customized food recommendation device according to an exemplary embodiment.

Referring to FIG. 3, the questionnaire-type member sign-up process 300 according to an embodiment may be performed when a user who desires to use a customized food recommendation device according to an embodiment first uses it.

Specifically, the questionnaire-type member registration process 300 may receive initial information about the user's companion animal and the user's e-mail information from the user.

For example, the initial information input from the user includes information about the type (variety) of the companion animal, date of birth (age) information, weight information, BCS numerical information, status (pregnancy, lactation, activity level, etc.) information, allergy information, preference information, and It may include at least one of monthly food purchase cost information.

Thereafter, the user may receive a recommendation for food suitable for the companion animal through the information input through the questionnaire-type membership registration process 300.

4 is a view for explaining a companion animal food recommendation process performed through a customized food recommendation device according to an embodiment.

4, the companion animal food recommendation process 400 according to an embodiment may include a questionnaire-type input process 410 and a customized food analysis process 420, and the questionnaire-type input process 410 is shown in FIG. It can also be replaced by the questionnaire-type membership registration process described in step 3.

Specifically, in the questionnaire-type input process 410, information about the user's companion animal may be input by the user.

For example, information on companion animals includes type (variety) information, date of birth (age) information, weight information, BCS level information, status (pregnancy, lactation, activity level, etc.) information, basic metabolism information, daily metabolism information , Daily feeding amount information, allergy information, preference information, and monthly food purchase cost information may be included.

In addition, in the questionnaire-type input process 410, the age definition process may be performed based on the input date of birth, and the state factor output process may be performed based on the input state information.

The age definition process and the state factor output process according to an embodiment will be described in more detail with reference to FIGS. 5 to 7 of the following embodiments.

On the other hand, in the customized food analysis process 420, based on the information on the companion animal input through the questionnaire-type input process 410 and big data information on a plurality of foods, breed analysis, age analysis, minimum nutrition analysis, and allergy At least one of ingredient analysis, ingredient grade analysis, certification mark analysis, brand analysis, price analysis, palatability analysis, user-based analysis, and status factor analysis can be performed, and at least one food that matches the analysis result is provided to the user. I can recommend it.

5 is a diagram illustrating an age definition process performed through a questionnaire-type input process according to an exemplary embodiment.

Referring to FIG. 5, in the age definition process 500, the age of the companion animal may be defined based on the date of birth information of the user's companion animal and the current date.

Specifically, in the age definition process 500, if the companion animal is less than 1 year old, it is defined as'Puffy' or'Ketten', and if the age is 1 year or more and less than 7 years, it is defined as'adult', and the age is 7 years. If it is above, it can be defined as senior.

6 is a diagram for describing a first state argument output process performed through a questionnaire-type input process according to an exemplary embodiment.

Referring to FIG. 6, the first state argument output process 600 is a process performed when the breed of the companion animal is'dog', and when the breed of the companion animal is'cat', it will be described later with reference to FIG. A second state argument output process may be performed.

Specifically, the first status factor output process 600 outputs the status factor '3' when the companion animal is less than 4 months old, and outputs the status factor '2' when the age is more than 4 months and less than 12 months. can do.

In addition, the first status argument output process 600 may output the status factor '1.8' when the companion animal's age is 12 months or more and is in a non-neutralized state, and the companion animal is 12 months or more and is in a non-neutralized state. In case of pregnancy, the status factor '3' is output. In the case of the age of the companion animal is 12 months or more, non-neutralized, and nursing, the status variable '4' can be output.

In addition, the first state factor output process 600 may output a state factor '1.6' when the companion animal is 12 months or longer in age and is in a neutralized state.

In addition, the first state factor output process 600 outputs a state factor '2' when the companion animal's age is 12 months or more and is in a neutralized state, and the activity amount analysis result is "light activity amount", and is "normal activity amount". In this case, the argument '3' can be output, and in the case of the "high activity amount", the status argument '5' can be output.

Meanwhile, when the BCS value of the companion animal is less than or equal to '3', the first state factor output process 600 performs an operation of summing a value that reflects the BCS value to the factor output through the activity level analysis and the factor output through the activity level analysis. The argument calculated through can be output.

In addition, when the BCS value of the companion animal is '6' or more, the first state factor output process 600 performs an operation of subtracting a value that reflects the BCS value in the factor output through the activity level analysis from the factor output through the activity level analysis. The argument calculated through can be output.

7 is a diagram for describing a second state argument output process performed through a questionnaire-type input process according to an exemplary embodiment.

Referring to FIG. 7, the second state argument output process 700 is a process performed when the breed of the companion animal is'cat', and when the breed of the companion animal is'dog', the first state argument output process 700 is described with reference to FIG. The status argument output process can be performed.

Specifically, the second state factor output process 700 outputs the state factor '2.5' when the companion animal's age is less than 4 months, and outputs the state factor '2' when the age is more than 4 months and less than 12 months. can do.

In addition, the second status argument output process 700 outputs the status factor '1.4' when the companion animal's age is 12 months or more and is in a non-negative state, and the companion animal is 12 months or more and is in a non-neutralized state and is pregnant. In the case of being in the process, the status factor '3' is output, and when the companion animal is 12 months or older and is in a non-neutralized state, and in lactation, the status variable '4' can be output.

In addition, the first state factor output process 600 may output a state factor '1.2' when the companion animal is 12 months or longer in age and is in a neutralized state.

Meanwhile, when the BCS value of the companion animal is less than or equal to '3', the first status argument output process 600 sets the status factor '1.2' or '1.4' to reflect the BCS value and the status factor '1.2' or '1.4'. Factors calculated through the summing operation can be output.

In addition, when the BCS value of the companion animal is '6' or more, the first status argument output process 600 applies a value reflecting the BCS value to the status argument '1.2' or '1.4' in the status argument '1.2' or '1.4'. An argument calculated through a subtraction operation can be output.

8 is a diagram for explaining a method for recommending customized food according to an exemplary embodiment.

In other words, FIG. 8 is a diagram illustrating a method of operating a customized food recommendation device according to an embodiment described with reference to FIGS. 1 to 7, and a customized food recommendation device according to an embodiment of the contents described later with reference to FIG. 8. Descriptions that are overlapping with the content described through will be omitted.

Referring to FIG. 8, in step 810, in the method for recommending a customized food according to an embodiment, the big data collection unit may collect big data information on a plurality of foods.

Next, in step 820, the customized food recommendation method according to an embodiment may receive information on the companion animal of the user from the information receiving unit.

Next, in step 830, the personalized food recommendation method according to an embodiment determines the status information of the companion animal based on the information on the companion animal received from the receiving output unit, and outputs a status factor corresponding to the determined status information. can do.

Next, in step 840, the customized food recommendation method according to an embodiment may recommend at least one of the plurality of foods based on the state factor output from the food recommendation unit and the collected big data information.

In the end, using the present invention, it is possible to recommend an optimal companion animal food based on information on the companion animal and big data information on the companion animal food.

In addition, the present invention may quantitatively evaluate status information about a companion animal based on information about the companion animal, and recommend an optimal companion animal food corresponding to the quantitatively evaluated status information.

As described above, although the embodiments have been described by the limited drawings, various modifications and variations can be made from the above description to those of ordinary skill in the art. For example, the described techniques are performed in an order different from the described method, and/or components such as devices, structures, devices, and circuits described are combined or combined in a form different from the described method, or other components Alternatively, even if substituted or substituted by an equivalent, an appropriate result can be achieved.

Therefore, other implementations, other embodiments, and those equivalent to the claims also fall within the scope of the claims to be described later.

200: customized food recommendation device 210: big data collection unit
220: information receiving unit 230: argument output unit
240: food recommendation department

Claims (12)

A big data collection unit that collects big data information on a plurality of foods;
An information receiving unit for receiving information on the user's companion animal;
A factor output unit that determines status information of the companion animal based on the received information on the companion animal and outputs a status factor corresponding to the determined status information; and
A food recommendation unit that recommends at least one of the plurality of foods based on the output state factor and the collected big data information
Including,
The information receiving unit collects information on the companion animal through a questionnaire-type input process,
The questionnaire-type input process,
The companion animal type information, breed information, and date of birth information are sequentially input, and based on the input date of birth information, a process of defining an age in at least three age groups based on 1 and 7 years is performed, and the age After the process of defining is performed, weight information, body condition score (BCS) numerical information, and state information are sequentially input, and a state factor output process is performed based on the sequentially input information, and basic metabolic amount information, Daily metabolic information, daily feeding information, allergy information, preference information, monthly food purchase cost information are sequentially input,
The food recommendation unit,
Recommend at least one of the plurality of foods through a customized food analysis process,
The customized food analysis process,
Using the information on the companion animals collected in the questionnaire-type input process, the process of analyzing food suitable for the breed to be fed, the process of analyzing food suitable for the age of the feeding target, analyzing the minimum nutritional food, and products containing allergen Exclusion process, ingredient grade score calculation process, certification mark score calculation process, brand score calculation process, price analysis calculation process, palatability analysis calculation process, user-based recommendation process, and status factor-based recommendation process are sequentially processed to A customized food recommendation device that recommends at least one food product. The method of claim 1,
The food recommendation unit,
Classifying each of the plurality of foods in advance according to a state factor, and recommending the at least one food corresponding to the output state factor among the pre-categorized foods
Custom food recommendation device. The method of claim 1,
The collected big data information,
Including at least one of price information, brand information, authentication mark information, ingredient grade information, use age information, and review information for the plurality of foods
Custom food recommendation device. delete delete The method of claim 1,
The argument output unit,
If the age of the companion animal is less than a preset first threshold age, a preset first state factor is output, and
If the age of the companion animal is greater than or equal to the first threshold age and less than a preset second threshold age, outputting a preset second state factor
Custom food recommendation device. The method of claim 1,
The argument output unit,
If the age of the companion animal is greater than or equal to a preset second threshold age, and the companion animal is in a non-generated state, outputting a preset third state factor
Custom food recommendation device. The method of claim 1,
The argument output unit,
Outputting a preset fourth state factor when the companion animal's age is greater than or equal to a preset second threshold age, the companion animal is in a non-neutralized state, and the companion animal is pregnant or lactating.
Custom food recommendation device. The method of claim 1,
The argument output unit,
If the age of the companion animal is greater than or equal to a preset second threshold age, and the companion animal is in a neutralized state, outputting a preset fifth state factor
Custom food recommendation device. The method of claim 9,
The argument output unit,
When the BCS value of the companion animal is less than or equal to '3', a sixth state factor calculated through an operation of summing the fifth state factor with a value reflecting the BCS value and the fifth state factor is output,
When the BCS value of the companion animal is '6' or more, outputting a seventh state factor calculated through an operation of subtracting a value reflecting the BCS value from the fifth state factor
Custom food recommendation device. The method of claim 1,
The argument output unit,
If the age of the companion animal is equal to or greater than a preset second threshold age and the companion animal is in a neutralized state, outputting a preset eighth state factor based on activity amount information among the received companion animal information,
When the BCS value of the companion animal is less than or equal to '3', a ninth state factor calculated through an operation of summing the eighth state factor with a value reflecting the BCS value in the eighth state factor is output,
When the BCS value of the companion animal is '6' or more, outputting a tenth state factor calculated through an operation of subtracting a value reflecting the BCS value in the eighth state factor from the eighth state factor
Custom food recommendation device. In the big data collection unit, collecting big data information on a plurality of foods;
Receiving information on the companion animal of the user, at the information receiving unit;
In a factor output unit, determining status information of the companion animal based on the received information on the companion animal, and outputting a status factor corresponding to the determined status information; and
In a food recommendation unit, recommending at least one of the plurality of foods based on the output state factor and the collected big data information
Including,
In the information receiving unit, the step of receiving information on the companion animal of the user,
Collecting information on the companion animal through a questionnaire-type input process, the questionnaire-type input process,
The companion animal type information, breed information, and date of birth information are sequentially input, and based on the input date of birth information, a process of defining an age in at least three age groups based on 1 and 7 years is performed, and the age After the process of defining is performed, weight information, body condition score (BCS) numerical information, and state information are sequentially input, and a state factor output process is performed based on the sequentially input information, and basic metabolic amount information, Including the step of sequentially inputting daily metabolic information, daily feeding information, allergy information, preference information, and monthly food purchase cost information,
The step of recommending at least one of the plurality of foods,
Recommend at least one of the plurality of foods through a customized food analysis process, the customized food analysis process,
Using the information on the companion animals collected in the questionnaire-type input process, the process of analyzing food suitable for the breed to be fed, the process of analyzing food suitable for the age of the feeding target, analyzing the minimum nutritional food, and products containing allergic foods Exclusion process, ingredient grade score calculation process, certification mark score calculation process, brand score calculation process, price analysis calculation process, palatability analysis calculation process, user-based recommendation process, and status factor-based recommendation process are sequentially processed to Recommending at least one food
Custom food recommendation method comprising a.

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