CN109299070B - Dish cooking method and system based on big data - Google Patents
Dish cooking method and system based on big data Download PDFInfo
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- CN109299070B CN109299070B CN201811050937.4A CN201811050937A CN109299070B CN 109299070 B CN109299070 B CN 109299070B CN 201811050937 A CN201811050937 A CN 201811050937A CN 109299070 B CN109299070 B CN 109299070B
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Abstract
The invention discloses a dish cooking method and a system based on big data, wherein a plurality of dishes are cooked for a plurality of times respectively, each dish generates a cooking data after being cooked, a plurality of cooking data are collected into a database as basic data, when the dishes are cooked, the dish name and the evaluation factor of the dish to be made are obtained, a plurality of cooking data with the same dish name as the dish name of the dish to be made and similar evaluation factor to the evaluation factor of the dish to be made are searched out from the database, one piece of cooking data with the highest dish score is selected from the plurality of searched cooking data, the cooking time of the piece of cooking data is the cooking time with the highest dish score, the cooking time is the optimal cooking time, the optimal cooking time is obtained by taking the characteristic data of food materials and environmental data into consideration, the optimal cooking time can ensure that the cooking effect of the dishes is better.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a dish cooking method and system based on big data.
Background
Cooking of dishes is a common cooking mode, cooking time of the dishes is usually controlled manually, the automation degree of manual cooking control of the dishes is not high, and a specially-assigned person is required to guard against over-cooking or under-fire. The problem that manual cooking consumes manpower is solved in current automatic cooking, does not need special messenger's management and control cooking, and it sets up the multiunit menu, and every vegetable sets up the time of cooking that corresponds, after the user input vegetable name and put into the steam ager with the vegetable edible material, can carry out the cooking of presetting the time of cooking to the vegetable automatically.
However, in the conventional automatic cooking method, the cooking time corresponding to each dish is fixed, and environmental factors (e.g., environmental humidity, environmental temperature, and environmental pressure) or characteristic data of food materials at that time are not considered, but the environmental factors and the characteristic data of the food materials affect the cooking time of the dishes, so that the dishes cannot be cooked according to the cooking time.
Disclosure of Invention
The invention aims to overcome the technical defects, provides a dish cooking method and system based on big data, and solves the technical problems in the prior art.
In order to achieve the technical purpose, the technical scheme of the invention provides a dish cooking method based on big data, which comprises the following steps:
s1, cooking multiple dishes, wherein each dish is cooked for multiple times, a cooking data is generated after each dish is cooked, the generated cooking data is stored in a database, one cooking data comprises the name of the dish cooked by the dish, an evaluation factor, the grade of the dish and the cooking duration, and the evaluation factor comprises the characteristic data and/or the environmental data of the food material cooked by the dish;
s2, acquiring the name and the evaluation factor of a dish to be made, searching a plurality of cooking data which have the same name and approximate evaluation factor to the evaluation factor of the dish to be made in a database, selecting one piece of cooking data with the highest dish evaluation from the plurality of pieces of cooking data and acquiring the cooking time of the piece of cooking data;
and S3, cooking the dish to be made for the cooking time length obtained in the S2.
The invention also provides a dish cooking system based on big data, which comprises:
a data acquisition module: cooking a plurality of dishes for a plurality of times respectively, generating cooking data after each dish is cooked, storing the generated cooking data in a database, wherein one cooking data comprises the name of the dish cooked by the dish, an evaluation factor, a dish score and cooking duration, and the evaluation factor comprises food material characteristic data and/or environment data cooked by the dish;
an optimal cooking time acquisition module: the method comprises the steps of obtaining the name and the evaluation factor of a dish to be made, searching a plurality of cooking data which have the same name and approximate evaluation factor, and selecting the cooking data with the highest dish score from the plurality of searched cooking data, and obtaining the cooking time of the cooking data;
a cooking execution module: and cooking the dish to be made for the cooking time length obtained by the optimal cooking time length obtaining module.
Compared with the prior art, the invention has the beneficial effects that: the method comprises the steps of cooking multiple dishes for multiple times respectively, generating cooking data after each dish is cooked, collecting numerous cooking data into a database as basic data, obtaining a dish name and an evaluation factor of a dish to be made when the dish is cooked, finding out multiple pieces of cooking data with the dish name identical to that of the dish to be made and the evaluation factor approximate to that of the dish to be made in the database, selecting one piece of cooking data with the highest dish score from the found multiple pieces of cooking data, and obtaining the cooking time of the piece of cooking data, wherein the cooking time is the cooking time with the highest score of the dish, the cooking time is the optimal cooking time, and the optimal cooking time takes the characteristic data (the score of the degree of cooking of easiness of the food material, the temperature of the food material) and the environmental data (the environmental humidity, the environmental temperature and the environmental data into consideration, Ambient temperature, ambient pressure), the optimal cooking duration can make the dish cooking effect better.
Drawings
FIG. 1 is a flow chart of a cooking method of dishes based on big data provided by the invention;
fig. 2 is a block diagram of a cooking system based on big data according to the present invention.
In the drawings: 1. the cooking system comprises a dish cooking system based on big data, 11, a data acquisition module, 12, an optimal cooking time length acquisition module and 13, and a cooking execution module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a dish cooking method based on big data, which comprises the following steps:
s1, cooking multiple dishes, wherein each dish is cooked for multiple times, a cooking data is generated after each dish is cooked, the generated cooking data is stored in a database, one cooking data comprises the name of the dish cooked by the dish, an evaluation factor, the grade of the dish and the cooking duration, and the evaluation factor comprises the characteristic data and/or the environmental data of the food material cooked by the dish;
s2, acquiring the name and the evaluation factor of a dish to be made, searching a plurality of cooking data which have the same name and approximate evaluation factor to the evaluation factor of the dish to be made in a database, selecting one piece of cooking data with the highest dish evaluation from the plurality of pieces of cooking data and acquiring the cooking time of the piece of cooking data;
and S3, cooking the dish to be made for the cooking time length obtained in the S2.
According to the dish cooking method based on the big data, in the step S1, multiple dishes are cooked for multiple times respectively, each dish generates cooking data after being cooked, and the generated cooking data is stored in a database; after the dishes are cooked for multiple times, a large amount of cooking data generated are stored in the database and used as basic data to provide big data support for the subsequent cooking operation of the dishes to be made. After a dish is cooked for a cooking time under the current evaluation factor, manually scoring the cooking result of the dish, wherein the scoring result is dish scoring, the dish scoring can measure whether the cooking time of the dish under the current evaluation factor is proper or not, and when the dish scoring is higher, the cooking time is more proper;
the evaluation factor comprises characteristic data and/or environmental data of food materials cooked in the dishes, the characteristic data of the food materials comprise scores of the degree of ripeness of the food materials and the temperature of the food materials, and the environmental data comprise ambient humidity, ambient temperature and ambient air pressure for cooking the dishes; the evaluation factors include the score of the degree of ripeness of the food material, the temperature of the food material, the ambient humidity, the ambient temperature and the ambient air pressure, which all may influence the cooking result of the dishes.
The method for cooking dishes based on big data, disclosed by the invention, for acquiring the evaluation factor of the dishes to be made in the step S2 specifically comprises the following steps:
the evaluation factors of the dishes to be made can be freely configured as required, and specifically, one or more of the score of the degree of doneness of the food material, the temperature of the food material, the ambient humidity, the ambient temperature and the ambient air pressure of the dishes to be made are selected as the evaluation factors according to the operation of a user or default settings.
The method for cooking dishes based on big data, disclosed by the invention, comprises the following steps of searching a plurality of cooking data which have the same name as the dish name of the dish to be made and approximate evaluation factors to the evaluation factors of the dish to be made in a database in step S2:
the method comprises the steps of finding out a first data set with the same dish name as that of a dish to be made in a database, wherein the first data set comprises a plurality of cooking data, finding out a second data set with an evaluation factor approximate to that of the dish to be made in the first data set, wherein the second data set comprises a plurality of cooking data, the dish name of each cooking data in the second data set is the same as that of the dish to be made, and the evaluation factor is approximate to that of the dish to be made.
In the cooking method for dishes based on big data according to the present invention, the method of finding out the second data set with the evaluation factor approximate to the evaluation factor of the dish to be made in the first data set in step S2 specifically comprises:
and comparing the evaluation factors of the cooking data in the first data set with the evaluation factors of the dishes to be made, searching a plurality of cooking data with the difference between the numerical value of the evaluation factor and the numerical value of the evaluation factor corresponding to the dishes to be made within a preset range in the first data set, and forming a second data set by the searched cooking data.
The dish cooking method based on big data, disclosed by the invention, comprises the steps of obtaining the name and the evaluation factor of a dish to be made in step S2, searching a plurality of cooking data which have the same name and approximate evaluation factor, and the highest cooking data and the cooking duration of the cooking data in the plurality of searched cooking data, wherein the cooking data comprises the following principles:
the optimal cooking time of the same dish with different evaluation factors is different, a large amount of cooking data are stored in a database, a plurality of pieces of cooking data with the same dish name and the same evaluation factor as those of the dish to be made are searched in the database, the evaluation factors in the cooking data are similar, but the cooking time is different, and the scores of the dish are different due to the different cooking time, the evaluation factors are considered to be the same under the condition of similar evaluation factors by using a single variable principle, the cooking data with the highest score of the dish is selected and the cooking time of the cooking data is obtained, the obtained cooking time is the optimal cooking time of the dish under the evaluation factors, and the cooking of the dish with the optimal cooking time is carried out to ensure that the cooking result of the dish is the best.
The present invention also provides a dish cooking system 1 based on big data, comprising:
the data acquisition module 11: cooking a plurality of dishes for a plurality of times respectively, generating cooking data after each dish is cooked, storing the generated cooking data in a database, wherein one cooking data comprises the name of the dish cooked by the dish, an evaluation factor, a dish score and cooking duration, and the evaluation factor comprises food material characteristic data and/or environment data cooked by the dish;
the optimal cooking time period acquisition module 12: the method comprises the steps of obtaining the name and the evaluation factor of a dish to be made, searching a plurality of cooking data which have the same name and approximate evaluation factor, and selecting the cooking data with the highest dish score from the plurality of searched cooking data, and obtaining the cooking time of the cooking data;
the cooking execution module 13: and cooking the dish to be made for the cooking time length obtained by the optimal cooking time length obtaining module.
According to the dish cooking system 1 based on big data, disclosed by the invention, the food material characteristic data in the data acquisition module 11 comprise the score of the degree of cooking easiness of the food material and the temperature of the food material, and the environmental data comprise the environmental humidity, the environmental temperature and the environmental air pressure for cooking dishes.
In the cooking system 1 based on big data of dishes, the optimal cooking duration obtaining module 12 is configured to select one or more of the score of the degree of doneness of the food material, the temperature of the food material, the ambient humidity, the ambient temperature, and the ambient air pressure of the dish to be made as evaluation factors according to the operation of the user or default settings.
In the big data based dish cooking system 1, the optimal cooking time obtaining module 12 is configured to find a first data set in the database, where the name of the dish is the same as the name of the dish to be made, where the first data set includes a plurality of cooking data, and find a second data set in the first data set, where the evaluation factor is similar to the evaluation factor of the dish to be made, where the second data set includes a plurality of cooking data, and the name of the dish in each cooking data in the second data set is the same as the name of the dish to be made, and the evaluation factor is similar to the evaluation factor of the dish to be made.
In the big data based dish cooking system 1, the optimal cooking time obtaining module 12 is used for comparing the evaluation factors of the cooking data in the first data set and the evaluation factors of the dishes to be made, searching a plurality of cooking data with the difference between the numerical value of the evaluation factor and the numerical value of the evaluation factor corresponding to the dishes to be made within a preset range in the first data set, and forming a second data set by the searched cooking data.
Compared with the prior art, the invention has the beneficial effects that: the method comprises the steps of cooking multiple dishes for multiple times respectively, generating cooking data after each dish is cooked, collecting numerous cooking data into a database as basic data, obtaining a dish name and an evaluation factor of a dish to be made when the dish is cooked, finding out multiple pieces of cooking data with the dish name identical to that of the dish to be made and the evaluation factor approximate to that of the dish to be made in the database, selecting one piece of cooking data with the highest dish score from the found multiple pieces of cooking data, and obtaining the cooking time of the piece of cooking data, wherein the cooking time is the cooking time with the highest score of the dish, the cooking time is the optimal cooking time, and the optimal cooking time takes the characteristic data (the score of the degree of cooking of easiness of the food material, the temperature of the food material) and the environmental data (the environmental humidity, the environmental temperature and the environmental data into consideration, Ambient temperature, ambient pressure), the optimal cooking duration can make the dish cooking effect better.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention. Any other corresponding changes and modifications made according to the technical idea of the present invention should be included in the protection scope of the claims of the present invention.
Claims (6)
1. A dish cooking method based on big data is characterized by comprising the following steps:
s1, cooking multiple dishes, wherein each dish is cooked for multiple times, a cooking data is generated after each dish is cooked, the generated cooking data is stored in a database, one cooking data comprises the name of the dish cooked by the dish, an evaluation factor, the score of the dish and the cooking duration, and the evaluation factor comprises the characteristic data and/or the environmental data of the food material cooked by the dish;
s2, acquiring the name of the dish to be made and the evaluation factor, searching a plurality of cooking data which have the same name and approximate evaluation factor, and selecting the cooking data with the highest dish score from the plurality of searched cooking data, and acquiring the cooking time of the cooking data;
s3, cooking the dish to be made for the cooking time length obtained in the step S2;
the method for searching the plurality of cooking data with the same dish name as the dish name of the dish to be made and similar evaluation factors to the dish to be made in the database in the step S2 specifically comprises the following steps:
searching a first data set with the same dish name and dish name of a dish to be made in a database, wherein the first data set comprises a plurality of cooking data, searching a second data set with an evaluation factor approximate to the evaluation factor of the dish to be made in the first data set, the second data set comprises a plurality of cooking data, the dish name of each cooking data in the second data set is the same as the dish name of the dish to be made, and the evaluation factor is approximate to the evaluation factor of the dish to be made;
the method for finding out the second data set with the evaluation factor approximate to the evaluation factor of the dish to be made in the first data set in step S2 specifically includes:
and comparing the evaluation factors of the cooking data in the first data set with the evaluation factors of the dishes to be made, searching a plurality of cooking data with the difference between the numerical value of the evaluation factor and the numerical value of the evaluation factor corresponding to the dishes to be made within a preset range in the first data set, and forming the second data set by the searched cooking data.
2. The big data based dish cooking method according to claim 1, wherein the food material characteristic data in the step S1 comprises a food material doneness score and a food material temperature, and the environmental data comprises an environmental humidity, an environmental temperature and an environmental air pressure for cooking dishes.
3. The cooking method of dishes based on big data according to claim 2, wherein the method of obtaining the evaluation factor of the dish to be made in step S2 is specifically:
and selecting one or more of the score of the degree of ripeness of the food material, the temperature of the food material, the ambient humidity, the ambient temperature and the ambient air pressure of the dish to be made as evaluation factors according to the operation of the user or default settings.
4. A big data based dish cooking system, comprising:
a data acquisition module: cooking a plurality of dishes for a plurality of times respectively, generating cooking data after each dish is cooked, storing the generated cooking data in a database, wherein one cooking data comprises the name of the dish cooked by the dish, an evaluation factor, the grade of the dish and the cooking duration, and the evaluation factor comprises the characteristic data and/or the environmental data of the food material cooked by the dish;
an optimal cooking time acquisition module: the method comprises the steps of obtaining the name and the evaluation factor of a dish to be made, searching a plurality of cooking data which have the same name and approximate evaluation factor, and selecting the cooking data with the highest dish score from the plurality of searched cooking data, and obtaining the cooking time of the cooking data;
a cooking execution module: the cooking time length acquisition module is used for acquiring the cooking time length of the dish to be made;
the optimal cooking duration obtaining module is used for searching a first data set with the same dish name as that of a dish to be made in a database, the first data set comprises a plurality of cooking data, a second data set with an evaluation factor approximate to that of the dish to be made is searched in the first data set, the second data set comprises a plurality of cooking data, the dish name of each cooking data in the second data set is the same as that of the dish to be made, and the evaluation factor is approximate to that of the dish to be made;
the optimal cooking duration obtaining module is used for comparing the evaluation factors of the cooking data in the first data set and the evaluation factors of the dishes to be made, searching a plurality of cooking data with the difference between the numerical value of the evaluation factor and the numerical value of the evaluation factor corresponding to the dishes to be made within a preset range in the first data set, and forming the second data set by the searched cooking data.
5. The big data based dish cooking system of claim 4, wherein the food material characteristic data in the data collection module comprises a food material doneness score and a food material temperature, and the environmental data comprises an ambient humidity, an ambient temperature and an ambient air pressure for cooking dishes.
6. The big-data-based dish cooking system according to claim 5, wherein the optimal cooking time period obtaining module is configured to select one or more of a food material doneness degree score, a food material temperature, an ambient humidity, an ambient temperature, and an ambient air pressure of the dish to be cooked as the evaluation factor according to a user operation or a default setting.
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| CN114617282B (en) * | 2022-04-25 | 2022-12-06 | 华中科技大学 | Quality-improvement-oriented tobacco leaf curing process optimizing method, system and terminal |
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