A method, apparatus, storage medium, and electronic device for adjusting a diet plan.

Abstract

This specification discloses a method, apparatus, storage medium, and electronic device for adjusting a diet plan. The diet plan adjustment method includes: acquiring current diet plan information and user characteristic information; determining a preset evaluation model matching the user characteristic information based on the user characteristic information; evaluating the current diet plan information using the preset evaluation model; outputting adjustment information when the current diet plan information does not conform to the preset evaluation model; the adjustment information includes adjustments to at least one of energy, ingredient types, and food particle size; determining a target recipe from a preset recipe database that meets the adjustment information; and adjusting the target recipe into the current diet plan.

Description

Technical Field

[0001] This specification relates to the field of intelligent cooking technology, and in particular to a method, device, storage medium, and electronic device for adjusting a diet plan. Background Technology

[0002] As the dietary health of infants and young children receives increasing attention, various apps that recommend complementary food recipes for infants and young children have emerged, greatly facilitating the cooking process for parents.

[0003] However, current recipe recommendation methods typically only make recommendations based on infants' dietary preferences, without considering whether the complementary food recipes are suitable for the individual infant. This results in the complementary food recipes ultimately recommended to users failing to meet their infants' dietary needs, or even rendering the recommended complementary food recipes unusable, seriously affecting the user experience.

[0004] Therefore, how to recommend complementary food recipes suitable for users' children is an urgent problem to be solved. Summary of the Invention

[0005] This specification provides a method, apparatus, storage medium, and electronic device for adjusting a diet plan, in order to partially solve the aforementioned problems existing in the prior art.

[0006] The following technical solution is adopted in this specification:

[0007] This instruction manual provides a method for adjusting a diet plan, including:

[0008] Obtain current diet plan information and user characteristics information;

[0009] Based on the user characteristic information, a preset evaluation model matching the user characteristic information is determined, and the current diet plan information is evaluated using the preset evaluation model;

[0010] When the current diet plan information does not conform to the preset evaluation model, adjustment information is output, which includes adjusting at least one of energy, food type and food particle size.

[0011] The target recipe that meets the information to be adjusted is determined from the preset recipe database, and the target recipe is adjusted into the current diet plan.

[0012] Optionally, the current diet plan information is evaluated using the preset evaluation model, specifically including:

[0013] Based on the user characteristic information, determine the evaluation conditions corresponding to the evaluation model;

[0014] Using the preset evaluation model, it is determined whether the diet plan information conforms to the evaluation model based on the evaluation conditions.

[0015] Optionally, the evaluation conditions corresponding to the evaluation model are determined based on the user characteristic information, specifically including:

[0016] Determine the target energy required for infants of the corresponding age based on the user characteristic information, the update cycle for the types of new food ingredients to be added, and the target food particle size;

[0017] The evaluation condition is determined by at least one of the target energy, the update cycle, and the target food particle size.

[0018] Optionally, determining whether the diet plan information conforms to the evaluation model specifically includes:

[0019] Determine whether the energy density corresponding to the diet plan information is greater than the preset energy density;

[0020] If so, determine whether the energy value corresponding to the diet plan information is within the preset range of the target energy; otherwise, determine that the energy density corresponding to the diet plan information does not conform to the evaluation model.

[0021] If the energy value is not within the preset range of the target energy, then the energy value corresponding to the diet plan information is determined to be inconsistent with the evaluation model.

[0022] Optionally, determining whether the diet plan information conforms to the evaluation model specifically includes:

[0023] Based on the dietary plan information, determine whether new food items have been added to the current dietary plan after a new update cycle is reached. If not, determine that the food items corresponding to the dietary plan information do not conform to the evaluation model.

[0024] If so, determine the overlap rate between the diet plan information and the diet plan information corresponding to the diet plan used by the user the previous day;

[0025] If the repetition rate is greater than the preset repetition rate, then it is determined that the types of ingredients corresponding to the diet plan information do not conform to the evaluation model.

[0026] Optionally, the method further includes:

[0027] Determine whether the proportion of staple food content corresponding to the diet plan information is greater than the preset proportion. If not, determine that the diet plan information does not conform to the evaluation model.

[0028] Optionally, determining whether the diet plan information conforms to the evaluation model specifically includes:

[0029] Determine whether the food granularity corresponding to the diet plan information matches the target food granularity;

[0030] If not, then the food granularity corresponding to the diet plan information does not conform to the evaluation model.

[0031] This instruction manual provides a diet plan adjustment device, including:

[0032] The acquisition module retrieves current diet plan information and user characteristic information;

[0033] The determination module determines a preset evaluation model that matches the user characteristic information based on the user characteristic information, and evaluates the current diet plan information using the preset evaluation model.

[0034] The output module outputs adjustment information when the current diet plan information does not conform to the preset evaluation model. The adjustment information includes adjusting at least one of energy, food type and food particle size.

[0035] The adjustment module determines a target recipe that meets the information to be adjusted from a preset recipe database and adjusts the target recipe into the current diet plan.

[0036] This specification provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described dietary plan adjustment method.

[0037] This specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described dietary plan adjustment method.

[0038] The above-mentioned technical solutions adopted in this specification can achieve the following beneficial effects:

[0039] In the diet plan adjustment method provided in this specification, the client obtains current diet plan information and user characteristic information, determines a preset evaluation model that matches the user characteristic information based on the user characteristic information, and evaluates the current diet plan information using the preset evaluation model. When the current diet plan information does not conform to the preset evaluation model, adjustment information is output. The adjustment information includes adjusting at least one of energy, ingredient type, and food particle size. A target recipe that meets the adjustment information is determined from a preset recipe database, and the target recipe is adjusted into the current diet plan.

[0040] As can be seen from the above method, this solution can evaluate the current diet plan through an evaluation model that matches the user's characteristic information. When the diet plan information does not conform to the evaluation model, it outputs information to be adjusted to determine the target recipe, thereby completing the update of the diet plan. In this way, not only can the original diet plan be evaluated, but also the recipes in the original diet plan can be updated based on the evaluation results, which greatly improves the user experience and fully meets the user's needs. Attached Figure Description

[0041] The accompanying drawings, which are included to provide a further understanding of this specification and form part of this specification, illustrate exemplary embodiments and are used to explain this specification, but do not constitute an undue limitation thereof. In the drawings:

[0042] Figure 1 This is a flowchart illustrating a dietary plan adjustment method provided in this instruction manual;

[0043] Figure 2 This is a schematic diagram illustrating the process of determining a diet plan provided in this instruction manual;

[0044] Figure 3 This is a schematic diagram of a diet plan adjustment device provided in this instruction manual;

[0045] Figure 4 This specification provides a corresponding Figure 1 A schematic diagram of an electronic device. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this specification will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of them. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this specification.

[0047] The technical solutions provided in the various embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0048] Figure 1 This is a flowchart illustrating a dietary plan adjustment method provided in this instruction manual, including the following steps:

[0049] S101: Obtain current diet plan information and user characteristic information.

[0050] As infants' and young children's nutritional health issues receive increasing attention, various dietary plans for infants and young children have emerged. However, due to individual differences among infants and young children, existing dietary plan recommendations often cannot guarantee that the recommended dietary plans and the complementary food recipes included can meet the nutritional and energy needs of their infants and young children. Furthermore, since there are significant differences in the complementary foods that infants and young children can eat at different ages, current methods cannot guarantee that the recommended dietary plans are suitable for the current infants and young children.

[0051] Based on this, this specification provides a method for adjusting a diet plan, which enables the client to evaluate the currently recommended diet plan based on user characteristic information. When the current diet plan information does not conform to the evaluation model, the method outputs information to be adjusted, and then determines a complementary food recipe that matches the current infant and toddler based on the adjustment information and adjusts it into the current diet plan.

[0052] In this manual, the executing entity for implementing the dietary plan adjustment method can be a client installed on a designated device such as a mobile phone, tablet, or laptop, or a client installed on a smart cooking device such as a smart baby food maker or a smart cooker. Of course, it can also be a server. For ease of understanding, this manual only uses the client as the executing entity as an example to illustrate one dietary plan adjustment method provided in this manual.

[0053] The client needs to obtain the current diet plan information and user characteristic information. This user characteristic information can be specific to infants and toddlers, including: the infant's age in months, sensitive foods (such as allergens or disliked foods), height, weight, and historical dietary records. Of course, it may also include other information such as the infant's health status (e.g., whether they are sick), date of birth, etc., but this manual does not specify specific limitations on this.

[0054] It should be noted that users can set user characteristic information only once in the client, and the client can automatically obtain it during subsequent use. In addition, users can also update the above user characteristic information in real time during use, such as changing the daily status of infants and young children, including whether they are sick, their weight, height, etc.

[0055] The aforementioned diet plan can be a default diet plan automatically recommended by the client based on user characteristics (such as a diet plan that matches the infant's age), or it can be a diet plan that the user chooses from a variety of diet plans recommended by the client for different ages that match their infant's age. Of course, it can also be a diet plan that the user downloads from other websites or applications and then inputs into the client.

[0056] In this instruction manual, the diet plan may include recipes for multiple meals. Therefore, the diet plan information mentioned above may include the types of ingredients, energy values, energy density, and food particle size corresponding to each recipe. Of course, it may also include other diet plan information such as the percentage of staple food content and cooking methods. This instruction manual does not make specific limitations on this.

[0057] S102: Based on the user characteristic information, determine a preset evaluation model that matches the user characteristic information, and use the preset evaluation model to evaluate the current diet plan information.

[0058] Specifically, the client can determine the target energy required by the infant in the specified month based on the infant's age in the user's feature information, the update cycle of the new ingredients required, and the target food particle size, and use the target energy, update cycle, and target food particle size as evaluation conditions.

[0059] In practical applications, the target energy requirement per day is 200 kcal for infants aged 7-9 months, 300 kcal for infants aged 10-12 months, and 550 kcal for infants aged 13-24 months. Clients can use ±10% (±5-15%, preferably 10%) of the target energy for each of the above age groups as the preset range for the target energy.

[0060] It should be noted that the diet plan in this instruction manual can be a complementary food recipe that includes all meals for infants and young children in a day (including breakfast, lunch and dinner). The client can determine the corresponding energy for each meal based on the target energy required for each age group each day.

[0061] For example, the client can calculate the average energy of each meal based on the number of meals per day, thereby determining the target energy for each meal. Alternatively, it can allocate the target energy required for each month of age according to the time period corresponding to each meal, thereby determining the target energy for each meal.

[0062] In addition, the client can define food categories according to the infant complementary food introduction guide. Among them, grains, root vegetables and tubers include: flour, rice, millet, sweet potato, potato, etc.

[0063] Meat includes: livestock meat, poultry, fish and their offal, etc.

[0064] Dairy products include milk, yogurt, cheese, etc.

[0065] Eggs include: chicken eggs, duck eggs, quail eggs, etc.

[0066] Fruits and vegetables rich in Vitamin A (excluding juice) include: carrots, kale, pumpkin, bok choy, mango, and tangerines;

[0067] Other fruits and vegetables (excluding fruit juice) include: bok choy, baby bok choy, cauliflower, broccoli, apples, pears, etc.

[0068] Legumes and their products / nuts include: legumes and their products include soybeans, tofu, etc., and nuts include peanuts, walnuts, cashews, etc.

[0069] To ensure that infants and young children receive nutrition appropriate for their age, new foods need to be introduced at regular intervals. The frequency of introducing new foods varies depending on the infant's age. For 6-month-old infants, there is usually no restriction on the frequency of introducing new foods. For 7-month-old infants, new foods (different from those in the previous cycle) need to be introduced every 3-4 days. For 8-month-old infants, new foods need to be introduced every 2-3 days. For 9-month-old infants, new foods need to be introduced every 1-2 days. For infants aged 10-12 months, new foods need to be introduced every 2-5 days.

[0070] In this manual, the update cycle for 7-month-old babies can be set to 4 days, for 8-month-old babies to 3 days, for 9-month-old babies to 2 days, and for babies aged 10-12 months to 3 days.

[0071] In addition, the size of food particles that infants and toddlers can eat or absorb varies depending on their age. Infants aged 6-7 months mainly eat pureed complementary foods with a particle size of ≤2mm. Infants aged 7-8 months can eat complementary foods containing tiny particles (2-5mm in size, preferably 3mm). Infants aged 8-9 months can eat complementary foods with small particles (preferably around 2-10mm in size). Infants aged 10-12 months can eat complementary foods with larger particles (preferably around 6-20mm in size). Infants aged 1-1.5 years can eat complementary foods with particles close to those of adults (preferably 10mm or larger).

[0072] Therefore, the client can set the target granularity for 7-8 months of age to 2-5mm, for 8-9 months of age to 2-10mm, for 10-12 months of age to 6-20mm, and for 13-18 months of age to ≥10mm.

[0073] Once the above evaluation criteria are determined, the client can use these criteria to evaluate the information of each diet plan corresponding to the current diet plan, thereby determining whether the information of each diet plan matches the user's characteristic information.

[0074] After the client recommends the current diet plan to the user, the client can prompt the user to evaluate the current diet plan through pop-up windows or prompt boxes. When the user performs the evaluation operation (such as clicking the evaluation button), the client can start the evaluation process of the current diet plan.

[0075] In this specification, the client can evaluate the current diet plan through a pre-deployed evaluation model, and take user characteristic information and diet plan information as input to the model. Based on the evaluation conditions determined by the user characteristic information, the model judges each diet plan information and outputs diet plan information that does not match the user characteristic information (does not conform to the evaluation model).

[0076] The client can use an evaluation model to determine whether each diet plan meets the aforementioned evaluation criteria. If it does, the diet plan matches the user's characteristics; otherwise, it does not, and the recipes in the diet plan need to be adjusted. It should be noted that the client can evaluate the energy value, ingredient types, and food particle size of the current diet plan sequentially, or simultaneously.

[0077] For the energy value corresponding to the current diet plan, the client can first determine whether the energy density corresponding to the current diet plan information is greater than the preset energy density. The preset energy density can be calculated based on the type, quantity and cooking method of the ingredients. In this manual, the preset energy density can be set to 80kcal / 100ml (100g).

[0078] If the energy density is less than the preset energy density, the client can determine that the energy density of the current diet plan does not meet the evaluation model and output "The energy density of the current diet plan is too low". If the energy density is greater than the preset energy density, the client can further determine whether the energy value corresponding to the diet plan is within the preset range of the target energy. For example, when the infant's age is 7-9 months, the preset range of the target energy should be 180kcal-220kcal. If the energy value corresponding to the current diet plan is outside the preset range, the client can determine that the energy value corresponding to the current diet plan does not meet the evaluation model.

[0079] Regarding the types of ingredients in the current diet plan, the client can first determine whether the number of types of ingredients corresponding to the current diet plan information is greater than the preset number of types, which can be set to 4. If not, the types of ingredients in the current diet plan do not meet the evaluation model, and the client can output "The variety of ingredients in the current diet plan is insufficient".

[0080] If so, the system further determines whether new food items have been added to the current diet plan after a new update cycle is reached, based on the historical diet information contained in the user's characteristic information. If not, the client can determine that the food items in the current diet plan do not meet the evaluation model.

[0081] For example, when an infant is 7 months old, the corresponding update cycle is 3 days, which means that the types of food need to be added every 3 days. If the current diet plan is the diet plan for the 4th day, and the types of food in the current diet plan are the same as those in the previous 3 days (that is, no new types of food are added after the update cycle is reached), then the types of food in the current diet plan do not meet the evaluation model.

[0082] If new ingredient types are added after the update cycle, the client can determine the overlap rate between the current diet plan and the diet plan used by the user the previous day. If this overlap rate is greater than a preset overlap rate, the client can determine that the ingredient types in the current diet plan do not meet the evaluation criteria. The preset overlap rate can be set according to actual conditions; for example, the client can set it to 75%.

[0083] For example, the client can compare the recipes in the current diet plan with the historical recipes used by the user (infant) the previous day. If the repetition rate is less than 75%, it means that the types of ingredients in the current diet plan do not meet the evaluation model.

[0084] In addition, the client can also determine the proportion of staple food (such as rice, noodles, etc.) in the current diet plan. If the proportion of staple food is less than the preset proportion (such as 40%), it means that the current diet plan cannot meet the nutritional needs of infants and young children. At this time, it can be determined that the types of ingredients in the current diet plan do not meet the evaluation model.

[0085] The client can determine whether the food granularity of the current diet plan matches the target food granularity.

[0086] In practice, older infants can usually eat complementary foods with particle sizes corresponding to their age, as well as those corresponding to younger infants. For example, an 8-month-old baby can eat complementary foods with particle sizes of 2-10mm, as well as those smaller than 2mm, while a 6-month-old baby can only eat complementary foods smaller than 2mm and cannot eat complementary foods larger than 2mm.

[0087] Therefore, when determining whether the food granularity of the current diet plan meets the target granularity, the client can consider it to meet the evaluation criteria as long as the food granularity of the current diet plan is smaller than the food granularity corresponding to the current age. Conversely, it does not meet the evaluation model if the food granularity of the current diet plan is smaller than the food granularity corresponding to the current age. In this case, the client can output "The food granularity of the current diet plan is unreasonable" to the user.

[0088] Of course, the client can also consider the food granularity of the current diet plan to be inconsistent with the evaluation model if the food granularity of the current diet plan does not match the target food granularity.

[0089] It should be noted that the client can output an evaluation result after evaluating each type of diet plan information. Of course, it can also output the evaluation results of all diet plan information after evaluating all diet plan information.

[0090] Additionally, in this manual, if the current diet plan is automatically recommended by the client based on the infant's age in months, then it is not necessary to determine the food granularity. However, if the diet plan is manually selected or entered by the user, then it is necessary to determine the food granularity. The size of the food granularity can be the default setting or manually selected by the user.

[0091] When users manually select and set the food particle size, the client can display the target food particle size corresponding to each age group, making it easy for users to select.

[0092] If the current diet plan does not explicitly indicate the specific particle size, the client can also use the recipe name / recipe image in the diet plan to determine it. For example, carrot puree and rice cereal are puree with a particle size of ≤2mm, while carrot and spinach noodles have a particle size of 2-10mm. In addition, the particle size can also be determined based on the program's function time; the longer the blending time, the smaller the particle size.

[0093] S103: When the current diet plan information does not conform to the preset evaluation model, the information to be adjusted is output, which includes adjusting at least one of energy, ingredient type and food particle size.

[0094] S104: Determine a target recipe that meets the information to be adjusted from the preset recipe database, and adjust the target recipe into the current diet plan.

[0095] After obtaining the evaluation results of the current diet plan, the client can respond to the user's replacement operation and, based on the evaluation results, output the adjustment information corresponding to the diet plan information that does not conform to the evaluation model through the pre-deployed replacement model.

[0096] Specifically, if the energy value of the current diet plan does not meet the evaluation criteria, i.e. does not meet the evaluation model, the client can calculate the total energy value of the current diet plan. When the current diet plan contains multiple recipes (such as the recipes corresponding to each meal), the total energy value can be the sum of the energy values ​​corresponding to each recipe.

[0097] The client can then determine the energy gap Δt based on the total energy value and the target energy, i.e., Δt = target energy - total energy value.

[0098] Furthermore, the client can determine adjustment information for adjusting the energy of the current diet plan, and search for other recipes in the preset recipe library based on the adjustment information, so that the energy value of the recipe is within the new energy value range determined by the target energy range and energy deficit, and at least some of the ingredients (such as the main ingredient) of the recipe are in the same category as the main ingredient of the current diet plan, and the recipe is used as the target recipe.

[0099] It should be noted that when the current diet plan contains multiple recipes, the client can determine the target recipes that meet the assessment criteria for each sub-recipe. For example, when the diet plan contains three recipes A, B, and C, the client can determine the corresponding energy values ​​and energy deficits for A, B, and C respectively, and then determine the target recipes to replace A, B, and C, thereby determining the final target recipes and replacing each recipe in the original diet plan.

[0100] If the types of ingredients and the size of food particles in the current diet plan meet the evaluation criteria, then the types of ingredients and the size of food particles in the target diet must also meet the evaluation criteria, that is, the types of ingredients and the size of food particles must both conform to the evaluation model.

[0101] If the number of food types in the current diet plan is less than the preset number, the client can determine the adjustment information for adjusting the number of food types in the current diet plan, and based on the adjustment information, determine the target recipe in the recipe library that has a greater number of food types than the preset number and meets the target energy value and target food particle size.

[0102] When the current diet plan reaches its update cycle but no new ingredients are added, the client can obtain the infant's historical information (the historical diet plan used in the previous update cycle) and determine the ingredients that need to be added compared to the historical diet plan. Based on the above adjustment information, the client can select a recipe from the preset recipe library that contains the new ingredient and meets other evaluation conditions (energy information and food particle size are both matched with the evaluation conditions) as the target recipe, and then replace the recipes in the original diet plan.

[0103] If the current diet plan has a higher overlap rate with the previous day's diet plan than the preset overlap rate (≥75%), the client can select a recipe from the preset recipe library that has different ingredients than the historical diet plan and meets other evaluation conditions as the target recipe based on the above adjustment information.

[0104] If the proportion of staple food in the current diet plan is less than the preset proportion (<40%), the client can calculate the rice and noodle staple food content of each recipe in the current diet plan, and then select target recipes with higher rice and noodle staple food content and meeting other evaluation conditions from the recipe library based on the above adjustment information to replace the recipes in the current diet plan, so that the proportion of rice and noodle staple food content in the final determined diet plan is ≥40%.

[0105] When the food granularity of the current diet plan does not meet the evaluation criteria, the client can determine the adjustment information for adjusting the food granularity of the current diet plan. Then, based on the adjustment information, the client can determine the target diet plan from the recipe library that meets the target food granularity and other evaluation criteria (energy information and ingredient types match the evaluation criteria) and replace the current diet plan.

[0106] Of course, the client can also adjust the food granularity of the current diet plan, thereby adjusting the granularity of the current diet plan to the target food granularity while ensuring that the current diet plan meets other assessment conditions (target energy and types of ingredients).

[0107] After generating a new diet plan, the client can directly display it to the user. Alternatively, it can continue to evaluate the diet plan until a plan is determined that matches the current user's characteristics and that all diet plan information conforms to the evaluation model (satisfies all evaluation conditions). For ease of understanding, this manual provides a schematic diagram of the diet plan determination process, such as... Figure 2 As shown.

[0108] Figure 2 This is a schematic diagram illustrating the process of determining a diet plan provided in this instruction manual.

[0109] Users can input their user characteristics in the client and then select a diet plan recommended by the client. After the user performs an evaluation of the current diet plan, the evaluation model determines whether the current diet plan meets the evaluation conditions. If not, it outputs the diet plan information that does not meet the evaluation conditions.

[0110] When a user performs a replacement operation on the current diet plan, the client can re-determine multiple diet plans that match the user's characteristics based on the above judgment information, and send the user the specified diet plan as the target diet plan and display it to the user.

[0111] In this specification, the client can generate multiple diet plans that match the user's characteristic information. In this case, the client can prioritize and recommend diet plans based on the user's evaluation of historical diet plans, that is, prioritize diet plans with higher evaluation and that meet all evaluation conditions.

[0112] In addition, if the identified diet plan contains a target recipe with poor historical reviews or user feedback indicating that the baby cannot eat it or has experienced adverse reactions, then the diet plan will not be recommended to the user.

[0113] It should be noted that users can select a specific diet plan from the multiple diet plans output by the replacement model for further evaluation. The evaluation model will then output qualified diet plan information and before-and-after comparison information (such as a 10% increase in energy, which meets the baby's needs).

[0114] If the replacement plan after evaluation is still unsatisfactory, information on the unsatisfactory diet plan, as well as before-and-after comparison information and comparison information with the standard value, should also be output to help users determine whether further replacement is necessary.

[0115] Of course, in this specification, the client can also directly determine the evaluation conditions based on the user's input user characteristics information, and then determine and output a diet plan that matches the evaluation conditions. In this case, the client does not need to obtain the current diet plan.

[0116] As can be seen from the above method, this solution can evaluate the current diet plan through an evaluation model that matches the user's characteristic information. When the diet plan information does not conform to the evaluation model, it outputs information to be adjusted to determine the target recipe, thereby completing the update of the diet plan. In this way, not only can the original diet plan be evaluated, but also the recipes in the original diet plan can be updated based on the evaluation results, which greatly improves the user experience and fully meets the user's needs.

[0117] The above are one or more methods for implementing dietary plan adjustments as described in this manual. Based on the same concept, this manual also provides corresponding dietary plan adjustment devices, such as... Figure 3 As shown.

[0118] Figure 3 A schematic diagram of a diet plan adjustment device provided in this specification includes:

[0119] Module 301 is used to acquire current diet plan information and user characteristic information;

[0120] The determining module 302 is used to determine a preset evaluation model that matches the user characteristic information based on the user characteristic information, and to evaluate the current diet plan information using the preset evaluation model;

[0121] The output module 303 is used to output adjustment information when the current diet plan information does not conform to the preset evaluation model. The adjustment information includes adjusting at least one of energy, food type and food particle size.

[0122] The adjustment module 304 is used to determine the target recipe that meets the information to be adjusted from the preset recipe database, and adjust the target recipe into the current diet plan.

[0123] Optionally, the determining module 302 is specifically used to: determine the evaluation conditions corresponding to the evaluation model based on the user characteristic information; and use the preset evaluation model to determine whether the diet plan information conforms to the evaluation model based on the evaluation conditions.

[0124] Optionally, the determining module 302 is specifically used to determine the target energy required by the infants of the corresponding age according to the user feature information, the update cycle of the new food types to be added, and the target food particle size; and to determine at least one of the target energy, the update cycle, and the target food particle size as the evaluation condition.

[0125] Optionally, the determining module 302 is specifically used to determine whether the energy density corresponding to the diet plan information is greater than a preset energy density; if so, determine whether the energy value corresponding to the diet plan information is within a preset range of the target energy; otherwise, determine that the energy density corresponding to the diet plan information does not conform to the evaluation model; if the energy value is not within the preset range of the target energy, then determine that the energy value corresponding to the diet plan information does not conform to the evaluation model.

[0126] Optionally, the determining module 302 is specifically used to determine, based on the diet plan information, whether new food types have been added to the current diet plan after a new update cycle has been reached; if not, determine that the food types corresponding to the diet plan information do not conform to the evaluation model; if so, determine the overlap rate between the diet plan information and the diet plan information corresponding to the diet plan used by the user the previous day; if the overlap rate is greater than a preset overlap rate, then determine that the food types corresponding to the diet plan information do not conform to the evaluation model.

[0127] Optionally, the determining module 302 is specifically used to determine whether the proportion of staple food content corresponding to the diet plan information is greater than a preset proportion; if not, it is determined that the diet plan information does not conform to the evaluation model.

[0128] Optionally, the determining module 302 is specifically used to determine whether the food granularity corresponding to the diet plan information matches the target food granularity; if not, it is determined that the food granularity corresponding to the diet plan information does not conform to the evaluation model.

[0129] This specification also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 This provides a method for adjusting a diet plan.

[0130] This instruction manual also provides Figure 4 One of the corresponding Figure 1 A schematic diagram of the structure of an electronic device. (e.g.) Figure 4 At the hardware level, the electronic device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for the business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it to achieve the above-mentioned functions. Figure 1 The dietary plan adjustment method described above. Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of hardware and software, etc. In other words, the execution subject of the following processing flow is not limited to individual logic units, but can also be hardware or logic devices.

[0131] Improvements in a technology can be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many improvements to the methodology can now be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that an improvement in methodology cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog are the most commonly used. Those skilled in the art should understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0132] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0133] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0134] For ease of description, the above devices are described in terms of function, divided into various units. Of course, in implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware components.

[0135] Those skilled in the art will understand that embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0136] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0137] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0138] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0139] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0140] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0141] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0142] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0143] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0144] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0145] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0146] The above description is merely an embodiment of this specification and is not intended to limit this specification. Various modifications and variations can be made to this specification by those skilled in the art. Any modifications, equivalent adjustments, improvements, etc., made within the spirit and principles of this specification should be included within the scope of the claims of this specification.

Claims

1. A dietary plan adjustment method, characterized by, The method comprises the following steps: obtaining current diet plan information and user characteristic information; inputting the diet plan information and the user characteristic information into a preset evaluation model to evaluate the current diet plan information by using the preset evaluation model; when the current diet plan information does not meet the preset evaluation model, outputting to-be-adjusted information, the to-be-adjusted information comprising at least one of adjustment of energy, food material types and food granularity; wherein, if the diet plan information does not meet the evaluation condition determined by the user characteristic information, it is determined that the current diet plan information does not meet the preset evaluation model; determining a target recipe from a preset recipe database that meets the to-be-adjusted information, and adjusting the target recipe into the current diet plan.

2. The method of claim 1, wherein, The evaluation of the current diet plan information by using the preset evaluation model comprises the following steps: determining an evaluation condition corresponding to the evaluation model according to the user characteristic information; judging whether the diet plan information meets the evaluation model based on the evaluation condition by using the preset evaluation model.

3. The method of claim 2, wherein, The determination of the evaluation condition corresponding to the evaluation model according to the user characteristic information comprises the following steps: determining target energy required by an infant at a corresponding age under the user characteristic information, an update period of newly added food material types and target food granularity; determining at least one of the target energy, the update period and the target food granularity as the evaluation condition.

4. The method of claim 3, wherein, The judgment of whether the diet plan information meets the evaluation model comprises the following steps: judging whether an energy density corresponding to the diet plan information is greater than a preset energy density; if yes, judging whether an energy value corresponding to the diet plan information is within a preset range of the target energy, otherwise, determining that the energy density corresponding to the diet plan information does not meet the evaluation model; if the energy value is not within the preset range of the target energy, it is determined that the energy value corresponding to the diet plan information does not meet the evaluation model.

5. The method of claim 3, wherein, The judgment of whether the diet plan information meets the evaluation model comprises the following steps: judging whether new food material types are added in the current diet plan after a new update period is reached according to the diet plan information; if no, it is determined that the food material types corresponding to the diet plan information do not meet the evaluation model; if yes, determining a repetition rate of diet plan information corresponding to the diet plan information and diet plan used by the user on the previous day; if the repetition rate is greater than a preset repetition rate, it is determined that the food material types corresponding to the diet plan information do not meet the evaluation model.

6. The method of claim 1, wherein, The method further comprises the following steps: judging whether a staple food content ratio corresponding to the diet plan information is greater than a preset ratio; if no, it is determined that the diet plan information does not meet the evaluation model.

7. The method of claim 3, wherein, The judgment of whether the diet plan information meets the evaluation model comprises the following steps: judging whether a food granularity corresponding to the diet plan information matches the target food granularity; if no, it is determined that the food granularity corresponding to the diet plan information does not meet the evaluation model.

8. A dietary plan adjustment apparatus, characterized by, The method comprises the following steps: an obtaining module, which obtains current diet plan information and user characteristic information; The determining module inputs the diet plan information and the user feature information into a preset evaluation model to evaluate the current diet plan information by using the preset evaluation model; The output module outputs to-be-adjusted information when the current diet plan information does not conform to the preset evaluation model, the to-be-adjusted information including adjustment of at least one of energy, food material types and food granularity; wherein, if the diet plan information does not conform to an evaluation condition determined by the user feature information, it is determined that the current diet plan information does not conform to the preset evaluation model; The adjusting module determines a target recipe from a preset recipe database that satisfies the to-be-adjusted information, and adjusts the target recipe into the current diet plan.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program is executed by the processor to implement the method in any one of claims 1-7.

10. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the method in any one of claims 1-7.

Images