CN111048181A - Method and device for predicting consumption of food materials, electrical equipment and storage medium - Google Patents
Method and device for predicting consumption of food materials, electrical equipment and storage medium Download PDFInfo
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- 235000013305 food Nutrition 0.000 title claims abstract description 280
- 239000000463 material Substances 0.000 title claims abstract description 278
- 238000000034 method Methods 0.000 title claims abstract description 46
- 235000012054 meals Nutrition 0.000 claims description 31
- 238000012937 correction Methods 0.000 claims description 24
- 230000015654 memory Effects 0.000 claims description 21
- 230000035945 sensitivity Effects 0.000 abstract description 9
- 235000007688 Lycopersicon esculentum Nutrition 0.000 description 9
- 240000003768 Solanum lycopersicum Species 0.000 description 9
- 238000010411 cooking Methods 0.000 description 7
- 239000002699 waste material Substances 0.000 description 5
- 241000220259 Raphanus Species 0.000 description 4
- 235000006140 Raphanus sativus var sativus Nutrition 0.000 description 4
- 235000013601 eggs Nutrition 0.000 description 3
- 230000008569 process Effects 0.000 description 3
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- 238000012545 processing Methods 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 230000036772 blood pressure Effects 0.000 description 1
- 230000036760 body temperature Effects 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
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Abstract
The invention discloses a method and a device for predicting the consumption of food materials, electric equipment and a storage medium, wherein the method for predicting the consumption of the food materials comprises the following steps: acquiring parameters for representing a physical state or/and a dining environment; obtaining dishes to be cooked, and respectively searching the corresponding relation between the physical state corresponding to each food material in the dishes to be cooked or/and the dining environment and the consumption of the food material; and obtaining the recommended amount of each food material by utilizing the parameters for representing the body state or/and the dining environment and the corresponding relation between the body state or/and the dining environment corresponding to each food material in the dish to be cooked and the food material consumption. By adopting the technical scheme, the sensitivity of the user to different food materials under the current condition can be embodied by utilizing the parameters for representing the physical state or/and the dining environment, and the recommended amount of the food materials is further obtained according to the difference of the sensitivity, so that the recommended amount of the food materials is more accurate.
Description
Technical Field
The invention relates to the technical field of household appliances, in particular to a method and a device for predicting the consumption of food materials, electric equipment and a storage medium.
Background
Currently, some electrical appliances give a recommended recipe. However, after cooking according to the recommended recipe, some dishes are not eaten by the user completely, so that the waste of food materials is caused, kitchen garbage is generated, the kitchen environment is affected, and finally, the user is annoyed. Therefore, how to provide a more humanized cooking scheme for a user, the cooking amount of dishes just can meet the requirements of the user, and the problem that unnecessary waste is not generated in the whole cooking and eating process is solved.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for predicting a consumption of a food material, an electrical device, and a storage medium, so as to solve a waste problem caused by a cooking amount greater than a consumption amount.
According to a first aspect, an embodiment of the present invention provides a method for predicting a consumption of a food material, including the following steps:
acquiring parameters for representing a physical state or/and a dining environment;
obtaining dishes to be cooked, and respectively searching the corresponding relation between the physical state corresponding to each food material in the dishes to be cooked or/and the dining environment and the consumption of the food material;
and obtaining the recommended amount of each food material by using the parameters for representing the physical state or/and the dining environment and the corresponding relation between the physical state or/and the dining environment of each food material and the consumption of the food material.
According to the method for predicting the consumption of the food materials, parameters for representing the body state or/and the dining environment and the corresponding relation between the body state or/and the dining environment corresponding to each food material in the dish to be cooked and the consumption of the food materials are respectively obtained; and obtaining the recommended amount of each food material by using the parameters for representing the body state or/and the dining environment and the corresponding relation between the body state or/and the dining environment corresponding to each food material in the dish to be cooked and the consumption of the food material. Because the sensitivity of the user to different food materials is different under different physical states and/or different dining environments, for example, the user prefers to eat cold dishes in summer and hot pot in winter; for example, when a patient is ill and likes to eat light food, the method and the device for recommending the food materials reflect the sensitivity degree of the user to different food materials under the current condition by using the parameters for representing the physical state or/and the dining environment, and further obtain the recommended amount of the food materials according to the difference of the sensitivity degree, so that the recommended amount of the food materials is more accurate, and the problem of waste caused by the fact that the cooking amount is larger than the eating amount is avoided.
With reference to the first aspect, in the first embodiment of the first aspect, obtaining the recommended amount of each food material by using the parameter for characterizing the physical state and the corresponding relationship between the physical state and the food material amount corresponding to each food material in the dish to be cooked includes:
and sequentially searching the corresponding relation between the physical state corresponding to each food material in the dish to be cooked and the food material consumption by using the parameter for representing the physical state to obtain a first demand of each food material, and taking the first demand of each food material as the recommended quantity of each food material.
With reference to the first aspect, in a second implementation manner of the first aspect, obtaining the recommended amount of each food material by using the parameter for characterizing the eating environment and the corresponding relationship between the eating environment and the food material consumption corresponding to each food material in the dish to be cooked includes:
and searching the corresponding relation between the dining environment corresponding to each food material in the dish to be cooked and the food material consumption in sequence by using the parameter for representing the dining environment to obtain a second demand of each food material, and taking the second demand of each food material as the recommended quantity of each food material.
With reference to the first aspect, in a third implementation manner of the first aspect, obtaining the recommended amount of each food material by using the parameters for characterizing the physical state and the eating environment, and the corresponding relationship between the physical state and the food material consumption corresponding to each food material in the dish to be cooked, includes:
searching in a corresponding relation between the body state corresponding to each food material in the dish to be cooked and the food material consumption in sequence by using the parameter for representing the body state to obtain a first demand of each food material;
searching in the corresponding relation between the dining environment corresponding to each food material in the dish to be cooked and the food material consumption in sequence by using the parameter for representing the dining environment to obtain a second demand of each food material;
adjusting the first meal volume by using a first adjustment coefficient to obtain a first adjusted meal volume;
adjusting the second meal volume by using a second adjustment coefficient to obtain a second adjusted meal volume;
and adding the first adjustment demand of each food material and the second adjustment demand corresponding to the food material to obtain the recommended amount of each food material.
With reference to the first aspect, in a fourth embodiment of the first aspect, the food material consumption prediction method further includes the following steps:
obtaining the total food material demand according to the recommended amount of each food material;
obtaining a first correction coefficient according to the total food material demand and the total current meal consumption;
and adjusting the recommended amount of each food material by using the first correction coefficient to obtain the corrected recommended amount of each food material.
With reference to the fourth embodiment of the first aspect, in the fifth embodiment of the first aspect, the current total meal amount is obtained by:
respectively acquiring parameters of each user for representing the body state or/and the dining environment and the corresponding relation between the body state or/and the dining environment of each user and the dining amount;
searching in the corresponding relation between the physical state or/and the dining environment of the user and the dining amount by using the parameters for representing the physical state or/and the dining environment of any user to obtain the dining amount of the user; traversing all users to obtain the dining amount of each user;
and adding the meal volume of each user to obtain the current total meal volume.
With reference to the first aspect, in a sixth embodiment of the first aspect, the food material consumption prediction method further includes the following steps:
acquiring the eating proportion of any food material, wherein the eating proportion is the ratio of the number of times of eating of the food material to the total number of times of eating;
obtaining a second correction coefficient of the food material according to the eating proportion;
and adjusting the recommended amount of the food material by using the second correction coefficient of the food material to obtain the corrected recommended amount of the food material.
With reference to the first aspect, in a seventh embodiment of the first aspect, the food material consumption prediction method further includes the following steps:
respectively acquiring the food material consumption of each food material of different dishes under different body states;
constructing a corresponding relation between the body state and the food material consumption of each food material of different dishes according to the food material consumption of each food material of different dishes under different body states;
and/or respectively acquiring the food material consumption of each food material of different dishes under different dining environments;
and constructing a corresponding relation between the dining environment and the food material consumption of each food material of different dishes according to the food material consumption of each food material of different dishes under different dining environments.
According to a second aspect, an embodiment of the present invention provides a food material consumption prediction apparatus, including:
the acquisition module is used for acquiring dishes to be cooked and parameters for representing the body state or/and the dining environment;
the corresponding relation searching module is used for searching the corresponding relation between the physical state corresponding to each food material in the dish to be cooked or/and the dining environment and the consumption of the food material;
and the food material consumption determining module is used for obtaining the recommended amount of each food material by utilizing the parameters for representing the body state or/and the dining environment and the corresponding relation between the body state or/and the dining environment of each food material and the food material consumption.
According to a third aspect, an embodiment of the present invention further provides an electrical device, which includes a memory and a processor, where the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions, so as to execute the food material usage prediction method according to the first aspect or any embodiment of the first aspect.
According to a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and the computer instructions are configured to enable the computer to execute the food material consumption prediction method according to the first aspect or any implementation manner of the first aspect.
Drawings
The features and advantages of the present invention will be more clearly understood by reference to the accompanying drawings, which are illustrative and not to be construed as limiting the invention in any way, and in which:
fig. 1 is a schematic flow chart of a method for predicting food material consumption in embodiment 1 of the present invention;
fig. 2 is a schematic structural diagram of a food material consumption prediction device in embodiment 2 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
The embodiment 1 of the invention provides a method for predicting the consumption of food materials. Fig. 1 is a schematic flow chart of a method for predicting the consumption of food materials in embodiment 1 of the present invention, and as shown in fig. 1, the method for predicting the consumption of food materials in embodiment 1 of the present invention includes the following steps:
s101: parameters for characterizing a physical state or/and a dining environment are obtained.
In a specific example, the parameter used to characterize the physical state may be body temperature; of course, in other examples, the parameter for representing the physical state may also be blood pressure, blood sugar, etc., and in addition, other parameters besides the above parameters, such as energy consumption, etc., may also be included, and may be set reasonably as needed.
In a specific example, the parameter used to characterize the dining environment may be the current temperature; of course, in other examples, the parameter used for characterizing the dining environment may also be the current humidity, and the like, and in addition, other parameters besides the above parameters may also be included, such as the scene where the parameter is located, and the parameter may be set reasonably as needed.
S102: obtaining dishes to be cooked, and respectively searching the corresponding relation between the physical state or/and the dining environment corresponding to each food material in the dishes to be cooked and the consumption of the food material.
The dishes may be made of one food material or a plurality of food materials, and the amount of the same food material is different when different dishes are made, so that the corresponding relationship between the physical state and/or the dining environment and the amount of the food material to be established in embodiment 1 of the present invention needs to correspond to each food material in each dish. For example, in a dish of tomato fried eggs, the corresponding relation between the body state or/and the dining environment and the tomato usage and the corresponding relation between the body state or/and the dining environment and the egg usage need to be established. In another dish, namely tomato sirloin, which also uses tomatoes, the corresponding relation between the body state or/and the eating environment and the tomato dosage and the corresponding relation between the body state or/and the eating environment and the sirloin dosage are also required to be constructed. The corresponding relation between the body state or/and the dining environment of the tomato fried egg dish and the tomato dosage and the corresponding relation between the body state or/and the dining environment of the tomato sirloin dish and the tomato dosage cannot be mixed.
Specifically, the following method can be adopted to construct the corresponding relationship between the physical state and the food material consumption of each food material of different dishes: respectively acquiring the food material consumption of each food material of different dishes under different body states; and constructing a corresponding relation between the body state and the food material consumption of each food material in different dishes according to the food material consumption of each food material in different dishes under different body states. Specifically, the following method can be adopted to construct the corresponding relationship between the dining environment and the food material consumption of each food material of different dishes: respectively acquiring the food material consumption of each food material of different dishes under different dining environments; and constructing a corresponding relation between the dining environment and the food material consumption of each food material of different dishes according to the food material consumption of each food material of different dishes under different dining environments. More specifically, the weight of the food materials before and after the user has a meal can be acquired through the intelligent electronic scale, and the electrical equipment is connected with the intelligent electronic scale to acquire data; the dining environment can be obtained through a temperature sensor and a humidity sensor; the user's physical state may be manually entered by the user or obtained by connecting a medical device.
S103: and obtaining the recommended amount of each food material by using the parameters for representing the physical state or/and the dining environment and the corresponding relation between the physical state or/and the dining environment of each food material and the consumption of the food material.
As a specific implementation manner, the following technical solution may be adopted to obtain the recommended amount of each food material by using the parameter for representing the physical state and the corresponding relationship between the physical state and the food material amount corresponding to each food material in the dish to be cooked: and sequentially searching the corresponding relation between the physical state corresponding to each food material in the dish to be cooked and the food material consumption by using the parameter for representing the physical state to obtain a first demand of each food material, and taking the first demand of each food material as the recommended quantity of each food material.
As another specific implementation manner, the following technical scheme may be adopted to obtain the recommended amount of each food material by using the parameter for characterizing the dining environment and the corresponding relationship between the dining environment corresponding to each food material in the dish to be cooked and the food material consumption: and searching the corresponding relation between the dining environment corresponding to each food material in the dish to be cooked and the food material consumption in sequence by using the parameter for representing the dining environment to obtain a second demand of each food material, and taking the second demand of each food material as the recommended quantity of each food material.
As another specific implementation manner, the following technical scheme may be adopted to obtain the recommended amount of each food material by using the parameters for characterizing the body state and the dining environment, and the corresponding relationship between the body state and the food material consumption corresponding to each food material in the dish to be cooked, and the corresponding relationship between the dining environment and the food material consumption: searching in a corresponding relation between the body state corresponding to each food material in the dish to be cooked and the food material consumption in sequence by using the parameter for representing the body state to obtain a first demand of each food material; searching in the corresponding relation between the dining environment corresponding to each food material in the dish to be cooked and the food material consumption in sequence by using the parameter for representing the dining environment to obtain a second demand of each food material; adjusting the first meal volume by using a first adjustment coefficient to obtain a first adjusted meal volume; adjusting the second meal volume by using a second adjustment coefficient to obtain a second adjusted meal volume; and adding the first adjustment demand of each food material and the second adjustment demand corresponding to the food material to obtain the recommended amount of each food material. For example, for white radish, the first consumption obtained according to the corresponding relationship between the physical state and the food material consumption is 120g, and the first consumption obtained according to the corresponding relationship between the dining environment and the food material consumption is 80 g; the first adjustment coefficient is 5/8, and the second adjustment coefficient is 3/8, the recommended amount of white radish is 120 × 5/8+80 × 3/8.
According to the method for predicting the consumption of the food materials, provided by the embodiment 1 of the invention, parameters for representing the body state or/and the dining environment and the corresponding relation between the body state or/and the dining environment corresponding to each food material in the dish to be cooked and the consumption of the food materials are respectively obtained; and obtaining the recommended amount of each food material by using the parameters for representing the body state or/and the dining environment and the corresponding relation between the body state or/and the dining environment corresponding to each food material in the dish to be cooked and the consumption of the food material. Because the sensitivity of the user to different food materials is different under different physical states and/or different dining environments, for example, the user prefers to eat cold dishes in summer and hot pot in winter; for example, when a patient is ill and likes to eat light food, the method and the device for recommending the food materials reflect the sensitivity degree of the user to different food materials under the current condition by using the parameters for representing the physical state or/and the dining environment, and further obtain the recommended amount of the food materials according to the difference of the sensitivity degree, so that the recommended amount of the food materials is more accurate, and the problem of waste caused by the fact that the cooking amount is larger than the eating amount is avoided.
As an improved technical solution, the method for predicting the consumption of food materials in embodiment 1 of the present invention further includes the following steps: obtaining the total food material demand according to the recommended amount of each food material; obtaining a first correction coefficient according to the total food material demand and the total current meal consumption; and adjusting the recommended amount of each food material by using the first correction coefficient to obtain the corrected recommended amount of each food material. Specifically, the ratio of the total food material demand to the total current meal consumption can be calculated, and the calculated ratio is used as the first correction coefficient. Through the correction, the recommended amount of each food material can be more accurate. For example, when a plurality of work packages need to be prepared, the parameter for representing the physical state or/and the dining environment obtained in step S101 is only one person, and at this time, if only the parameter for representing the physical state or/and the dining environment of the person is selected, the parameter has no general meaning, in order to make the recommended amount of the food material more accurate, the recommended amount of the food material may be corrected by using the above method, because the corrected recommended amount takes the current total dining amount into account, and the current total dining amount is the total dining amount of a plurality of persons, the corrected recommended amount is more accurate.
As a further improved technical solution, the total current meal amount can be obtained by the following method: respectively acquiring parameters of each user for representing the body state or/and the dining environment and the corresponding relation between the body state or/and the dining environment of each user and the dining amount; searching in the corresponding relation between the physical state or/and the dining environment of the user and the dining amount by using the parameters for representing the physical state or/and the dining environment of any user to obtain the dining amount of the user; traversing all users to obtain the dining amount of each user; and adding the meal volume of each user to obtain the current total meal volume. By utilizing the technical scheme, the meal volume of the user is also associated with the parameters for representing the body state or/and the meal environment, so that the meal volume can also change along with the change of the body state or/and the meal environment, the obtained meal volume is more accurate, and the first correction coefficient is further more accurate.
As another improved technical solution, the method for predicting the consumption of food materials in embodiment 1 of the present invention further includes the following steps: acquiring the eating proportion of any food material; obtaining a second correction coefficient of the food material according to the eating proportion; and adjusting the recommended amount of the food material by using the second correction coefficient of the food material to obtain the corrected recommended amount of the food material. For example, if the number of white radishes eaten by the user is 78 and the total number of white radishes eaten is 400, the eating ratio is 78/400-19.5%, and the correction coefficient corresponding to the eating ratio is 0.6. For example, the correspondence relationship between the eating rate and the second correction factor may be defined as follows: when the edible proportion is 0.8-1, the second correction coefficient is 1.1; when the edible proportion is 0.6-8, the second correction coefficient is 1; when the edible proportion is 0.4-0.6, the second correction coefficient is 0.9; when the edible proportion is 0.3-0.4, the second correction coefficient is 0.8; when the edible proportion is 0.2-0.3, the second correction coefficient is 0.7; the second correction coefficient is 0.6 when the edible ratio is 0-0.2. The ready-to-eat ratio is proportional to the second correction factor. The food material recommendation amount can be further corrected according to the sensitivity of the user to the food materials, so that the food material recommendation amount is more accurate.
Example 2
The embodiment 2 of the invention provides a food material consumption prediction device. Fig. 2 is a schematic structural diagram of a food material consumption prediction apparatus in embodiment 2 of the present invention, and as shown in fig. 2, the food material consumption prediction apparatus in embodiment 2 of the present invention includes an obtaining module 20, a correspondence relation searching module 22, and a food material consumption determining module 24.
In particular, the obtaining module 20 is used for obtaining the dish to be cooked and the parameters for characterizing the physical state or/and the dining environment.
The corresponding relation searching module 22 is configured to search for a corresponding relation between a physical state corresponding to each food material in the dish to be cooked or/and a dining environment and a consumption of the food material.
And the food material consumption determining module 24 is configured to obtain the recommended amount of each food material by using the parameter for representing the physical state or/and the eating environment and the corresponding relationship between the physical state or/and the eating environment of each food material and the food material consumption.
The food material consumption prediction device provided in embodiment 2 of the present invention can implement the food material consumption prediction method according to embodiment 1 of the present invention, and has the same technical effects, which are not described herein again.
Example 3
The embodiment of the invention also provides the electrical equipment which can comprise a processor and a memory, wherein the processor and the memory can be connected through a bus or in other manners.
As a specific embodiment, the electrical device may be a refrigerator, a range hood, or the like.
The processor may be a Central Processing Unit (CPU). The Processor may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or a combination thereof.
The memory, which is a non-transitory computer-readable storage medium, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions/modules corresponding to the food material usage prediction method in the embodiment of the present invention (for example, the obtaining module 20, the correspondence relation searching module 22, and the food material usage determining module 24 shown in fig. 2). The processor executes various functional applications and parameter processing of the processor by running the non-transitory software program, instructions and modules stored in the memory, that is, the food material usage amount prediction method in the above method embodiment is implemented.
The memory may include a storage program area and a storage parameter area, wherein the storage program area may store an operating system, an application program required for at least one function; the parameter storage area may store parameters created by the processor, and the like. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and such remote memory may be coupled to the processor via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory, and when executed by the processor, perform the food material usage prediction method in the embodiment shown in fig. 1.
The details of the electrical apparatus may be understood by referring to the corresponding related description and effects in the embodiment shown in fig. 1, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD) or a Solid State Drive (SSD), etc.; the storage medium may also comprise a combination of memories of the kind described above.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.
Claims (11)
1. A method for predicting the consumption of food materials is characterized by comprising the following steps:
acquiring parameters for representing a physical state or/and a dining environment;
obtaining dishes to be cooked, and respectively searching the corresponding relation between the physical state corresponding to each food material in the dishes to be cooked or/and the dining environment and the consumption of the food material;
and obtaining the recommended amount of each food material by utilizing the parameters for representing the body state or/and the dining environment and the corresponding relation between the body state or/and the dining environment corresponding to each food material in the dish to be cooked and the food material consumption.
2. The method of predicting the amount of food material used according to claim 1, wherein the obtaining of the recommended amount of each food material by using the parameter for representing the physical state and the corresponding relationship between the physical state and the amount of the food material corresponding to each food material in the dish to be cooked comprises:
and sequentially searching the corresponding relation between the physical state corresponding to each food material in the dish to be cooked and the food material consumption by using the parameter for representing the physical state to obtain a first demand of each food material, and taking the first demand of each food material as the recommended quantity of each food material.
3. The method for predicting the consumption of food materials according to claim 1, wherein the obtaining of the recommended amount of each food material by using the parameter for representing the dining environment and the corresponding relationship between the dining environment and the consumption of the food material corresponding to each food material in the dish to be cooked comprises:
and searching the corresponding relation between the dining environment corresponding to each food material in the dish to be cooked and the food material consumption in sequence by using the parameter for representing the dining environment to obtain a second demand of each food material, and taking the second demand of each food material as the recommended quantity of each food material.
4. The method for predicting the consumption of food materials according to claim 1, wherein the obtaining of the recommended amount of each food material by using the parameters for representing the physical state and the eating environment, and the corresponding relationship between the physical state and the consumption of the food material corresponding to each food material in the dish to be cooked and the corresponding relationship between the eating environment and the consumption of the food material comprises:
searching in a corresponding relation between the body state corresponding to each food material in the dish to be cooked and the food material consumption in sequence by using the parameter for representing the body state to obtain a first demand of each food material;
searching in the corresponding relation between the dining environment corresponding to each food material in the dish to be cooked and the food material consumption in sequence by using the parameter for representing the dining environment to obtain a second demand of each food material;
adjusting the first meal volume by using a first adjustment coefficient to obtain a first adjusted meal volume;
adjusting the second meal volume by using a second adjustment coefficient to obtain a second adjusted meal volume;
and adding the first adjustment demand of each food material and the second adjustment demand corresponding to the food material to obtain the recommended amount of each food material.
5. The food material consumption prediction method of claim 1, further comprising:
obtaining the total food material demand according to the recommended amount of each food material;
obtaining a first correction coefficient according to the total food material demand and the total current meal consumption;
and adjusting the recommended amount of each food material by using the first correction coefficient to obtain the corrected recommended amount of each food material.
6. The food material consumption prediction method according to claim 5, wherein the current total meal consumption is obtained by:
respectively acquiring parameters of each user for representing the body state or/and the dining environment and the corresponding relation between the body state or/and the dining environment of each user and the dining amount;
searching in the corresponding relation between the physical state or/and the dining environment of the user and the dining amount by using the parameters for representing the physical state or/and the dining environment of any user to obtain the dining amount of the user; traversing all users to obtain the dining amount of each user;
and adding the meal volume of each user to obtain the current total meal volume.
7. The food material consumption prediction method of claim 1, further comprising:
acquiring the eating proportion of any food material, wherein the eating proportion is the ratio of the number of times of eating of the food material to the total number of times of eating;
obtaining a second correction coefficient of the food material according to the eating proportion;
and adjusting the recommended amount of the food material by using the second correction coefficient of the food material to obtain the corrected recommended amount of the food material.
8. The food material consumption prediction method of claim 1, further comprising:
respectively acquiring the food material consumption of each food material of different dishes under different body states;
constructing a corresponding relation between the body state and the food material consumption of each food material of different dishes according to the food material consumption of each food material of different dishes under different body states;
and/or respectively acquiring the food material consumption of each food material of different dishes under different dining environments;
and constructing a corresponding relation between the dining environment and the food material consumption of each food material of different dishes according to the food material consumption of each food material of different dishes under different dining environments.
9. An apparatus for predicting a consumption of a food material, comprising:
the acquisition module is used for acquiring dishes to be cooked and parameters for representing the body state or/and the dining environment;
the corresponding relation searching module is used for searching the corresponding relation between the physical state corresponding to each food material in the dish to be cooked or/and the dining environment and the consumption of the food material;
and the food material consumption determining module is used for obtaining the recommended amount of each food material by utilizing the parameters for representing the body state or/and the dining environment and the corresponding relation between the body state or/and the dining environment of each food material and the food material consumption.
10. An electrical device, comprising:
a memory and a processor, wherein the memory and the processor are connected in communication with each other, the memory stores computer instructions, and the processor executes the computer instructions to execute the food material usage prediction method according to any one of claims 1 to 8.
11. A computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions for causing the computer to execute the food material usage prediction method according to any one of claims 1-8.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105825048A (en) * | 2016-03-11 | 2016-08-03 | 深圳还是威健康科技有限公司 | Diet planning method and device |
| CN108461122A (en) * | 2018-03-07 | 2018-08-28 | 美的集团股份有限公司 | A kind of method, equipment and computer storage media that food materials are recommended |
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2019
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105825048A (en) * | 2016-03-11 | 2016-08-03 | 深圳还是威健康科技有限公司 | Diet planning method and device |
| CN108461122A (en) * | 2018-03-07 | 2018-08-28 | 美的集团股份有限公司 | A kind of method, equipment and computer storage media that food materials are recommended |
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Application publication date: 20200421 |