CN110555579B - Cooking grading method, intelligent cooking equipment, server and storage medium - Google Patents
Cooking grading method, intelligent cooking equipment, server and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a cooking scoring method, which comprises the following steps: obtaining effective cooking information data, wherein the effective cooking information data are used for representing multi-dimensional data obtained by matching cooking food materials with cooking tools and cooking behaviors in a cooking process; inputting effective cooking information data into a preset cooking grading model, and outputting a cooking grading result of the time, wherein the preset cooking grading model is used for representing a judgment rule of a cooking effect; and sending the cooking grading result to the intelligent cooking equipment. The embodiment of the invention also discloses intelligent cooking equipment, a server and a storage medium.
Description
Technical Field
The invention relates to an intelligent home technology in the field of communication, in particular to a cooking grading method, intelligent cooking equipment, a server and a storage medium.
Background
With the networking and intelligence of home appliances, intelligent cooking devices are beginning to appear in people's daily life. For example, a program control module is arranged, and an intelligent electric cooker and the like capable of realizing network communication are arranged.
In the research and development process of the intelligent cooking equipment, technicians simply research the characteristics of the related food materials and develop a cooking program to control and realize the cooking process by combining the performance of the intelligent cooking equipment. At present, innovations on the hardware performance level of intelligent cooking equipment are considered in the control process of the cooking process, for example, innovations on various heating control technologies and the like cannot be considered and judged in the application aspect of cooking information technologies and cooking results and cannot visually express the cooking results.
Disclosure of Invention
In order to solve the technical problems, embodiments of the present invention provide a cooking scoring method, an intelligent cooking device, a server, and a storage medium, which can judge a cooking result, provide a basis for improving a cooking effect, and improve intelligence of cooking.
The technical scheme of the invention is realized as follows:
the embodiment of the invention provides a cooking scoring method, which is applied to a server and comprises the following steps:
obtaining effective cooking information data, wherein the effective cooking information data are used for representing multi-dimensional data obtained by matching cooking food materials with cooking tools and cooking behaviors in a cooking process;
inputting the effective cooking information data into a preset cooking grading model, and outputting a cooking grading result of the time, wherein the preset cooking grading model is used for representing a judgment rule of a cooking effect;
and sending the cooking grading result to intelligent cooking equipment.
In the above method, the acquiring valid cooking information data includes:
receiving cooking information data uploaded by the intelligent cooking equipment;
and filtering the cooking information data to obtain the effective cooking information data.
In the above method, before the inputting the effective cooking information data into a preset cooking scoring model and outputting the current cooking scoring result, the method further includes:
and establishing the preset cooking grading model.
In the above method, the establishing the preset cooking score model includes:
acquiring a positive sample and a negative sample according to a preset configuration proportion, wherein the positive sample and the negative sample are corresponding relations between historical effective cooking information data and cooking results;
calling a set training model to process the positive sample or the negative sample to obtain a first training result;
and continuously detecting the training model until the first training result meets a preset condition, taking the training model with the first training result meeting the preset condition as the preset cooking grading model, wherein the preset condition is used for representing that the accuracy of the actual cooking grading result of the corresponding obtained sample is higher than a historical threshold value when a data output result obtained according to the preset cooking grading model is applied to determining the cooking grading result.
The embodiment of the invention also provides a cooking scoring method, which is applied to intelligent cooking equipment and comprises the following steps:
in the cooking process, cooking information data are collected, and the cooking information data are used for representing multi-dimensional data obtained by matching cooking food materials with cooking tools and cooking behaviors in the cooking process;
and when the cooking is finished, sending the cooking information data to a server for scoring the cooking.
In the above method, when cooking is completed, the cooking information data is sent to a server, and after cooking scoring is performed, the method further includes:
receiving a cooking grading result sent by the server;
obtaining cooking parameters according to the cooking grading result, wherein the cooking parameters are used for representing cooking requirement parameters in the cooking process;
and according to the cooking parameters, carrying out the next cooking process of the same cooking type.
In the above method, the collecting cooking information data during the cooking process includes:
collecting picture information of cooking food materials, picture information and data of cooking tools and cooking behavior data in a cooking process;
converting the picture information of the cooking food material and the picture information of the cooking tool to obtain cooking food material data and cooking tool data;
and taking the cooking food material data, the cooking tool data and the cooking behavior data as collected cooking information data.
An embodiment of the present invention provides a server, including:
the cooking system comprises a first obtaining unit, a second obtaining unit and a control unit, wherein the first obtaining unit is used for obtaining effective cooking information data, and the effective cooking information data are used for representing multi-dimensional data obtained by matching cooking food materials with a cooking tool and cooking behaviors in a cooking process;
the calling unit is used for inputting the effective cooking information data into a preset cooking grading model and outputting a cooking grading result of the time, and the preset cooking grading model is used for representing a judgment rule of a cooking effect;
and the first sending unit is used for sending the cooking grading result to the intelligent cooking equipment.
An embodiment of the present invention further provides a server, including:
the cooking grading method comprises a first receiver, a first transmitter, a first processor and a first storage medium, wherein the first storage medium stores first processor executable instructions, received data of the first receiver and transmitted data of the first transmitter, the first receiver, the first transmitter and the first storage medium depend on the first processor through a first communication bus to perform operations, and when the instructions are executed by the first processor, the cooking grading method on the server side is executed.
The embodiment of the invention provides intelligent cooking equipment, which comprises:
the cooking system comprises a collecting unit, a processing unit and a control unit, wherein the collecting unit is used for collecting cooking information data in the cooking process, and the cooking information data is used for representing multi-dimensional data obtained by matching cooking food materials with a cooking tool and cooking behaviors in the cooking process;
and the second sending unit is used for sending the cooking information data to a server to perform cooking scoring when cooking is finished.
An embodiment of the present invention further provides an intelligent cooking apparatus, including:
a second receiver, a second transmitter, a second processor and a second storage medium storing instructions executable by the second processor, data received by the second receiver and data transmitted by the second transmitter, wherein the second receiver, the second transmitter and the second storage medium operate in dependence on the second processor through a second communication bus, and when the instructions are executed by the second processor, the cooking grading method of the intelligent cooking apparatus side is executed.
The embodiment of the invention provides a computer storage medium which is applied to a server and stores machine instructions, wherein when the machine instructions are executed by one or more first processors, the first processors execute a cooking grading method on the server side; or, the method is applied to an intelligent cooking device, machine instructions are stored, and when the machine instructions are executed by one or more second processors, the second processors execute the cooking scoring method on the intelligent cooking device side.
The embodiment of the invention provides a cooking scoring method, intelligent cooking equipment, a server and a storage medium, which are used for acquiring effective cooking information data, wherein the effective cooking information data is used for representing multi-dimensional data obtained by matching cooking food materials with cooking tools and cooking behaviors in a cooking process; inputting effective cooking information data into a preset cooking grading model, and outputting a cooking grading result of the time, wherein the preset cooking grading model is used for representing a judgment rule of a cooking effect; and sending the cooking grading result to the intelligent cooking equipment. Adopt above-mentioned technical implementation scheme, because the culinary art information data of culinary art in-process can be gathered to intelligent cooking equipment, cook promptly and eat the multi-dimensional data etc. that material cooperation culinary art instrument and culinary art action obtained, consequently, the server just can be according to the culinary art information data that reports, just can obtain the effect of this time culinary art through calling preset the culinary art model, the culinary art score the result promptly and transmit for intelligent cooking equipment, thus, when the culinary art is accomplished, intelligent cooking equipment just can demonstrate the culinary art result of this time, thereby can be according to the culinary art score result of this time, improve the process of carrying out the culinary art of the same type next time, realize the judgement of culinary art result, provide the basis for improving the culinary art effect, the intelligence of culinary art has been improved.
Drawings
Fig. 1 is a first flowchart of a cooking scoring method according to an embodiment of the present invention;
FIG. 2 is a first diagram of an exemplary cooking scoring system according to an embodiment of the present invention;
FIG. 3 is a second exemplary cooking scoring system architecture diagram provided in accordance with an embodiment of the present invention;
fig. 4 is a diagram illustrating an exemplary cooking score result provided by an embodiment of the present invention;
fig. 5 is a flowchart of a cooking scoring method according to an embodiment of the present invention;
fig. 6 is a flowchart of a cooking scoring method according to an embodiment of the present invention;
fig. 7 is a flowchart of a cooking scoring method according to an embodiment of the present invention;
fig. 8 is an interaction diagram of a cooking scoring method according to an embodiment of the present invention;
fig. 9 is a first schematic structural diagram of a server according to an embodiment of the present invention;
fig. 10 is a schematic structural diagram of a server according to an embodiment of the present invention;
fig. 11 is a first schematic structural diagram of a cooking apparatus according to an embodiment of the present invention;
fig. 12 is a schematic structural diagram of a cooking apparatus according to an embodiment of the present invention.
Detailed Description
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.
Machine learning: based on theories such as probability theory, statistics, nerve propagation and the like, the computer can simulate the learning behavior of human beings so as to acquire new knowledge or skills and reorganize the existing knowledge structure to continuously improve the performance of the computer.
Model training: and inputting the manually selected samples into a machine learning system, and continuously adjusting model parameters to ensure that the accuracy of the final model for sample identification is optimal.
Example one
An embodiment of the present invention provides a cooking scoring method, as shown in fig. 1, applied in a server, where the method may include:
s101, obtaining effective cooking information data, wherein the effective cooking information data are used for representing multi-dimensional data obtained by matching cooking food materials with cooking tools and cooking behaviors in a cooking process;
the cooking scoring method provided by the embodiment of the invention is realized based on the architecture of a cooking scoring system. As shown in fig. 2, the cooking scoring system may include: one or more servers 1, intelligent cooking devices 2, and a network 3, wherein the network 3 includes network entities such as routers, gateways, etc., which are not shown in fig. 2. The intelligent cooking device 2 interacts data information with the server 1 through a network, so that the generated cooking information data is obtained from the intelligent cooking device 2 and transmitted to the server 1. The type of the intelligent cooking device 2 may include an intelligent electric cooker, an intelligent electric pressure cooker, and the like. The intelligent cooking device 2 in the embodiment of the present invention may be a cooking device with a network communication function, an intelligent program control function, and a data acquisition function, such as an intelligent electric cooker, and the embodiment of the present invention is not limited.
It should be noted that, in the embodiment of the present invention, in the cooking process of the intelligent cooking device, the cooking information data may be collected through a sensor, a camera, a main control module of the intelligent cooking device, or an electronic scale, and the cooking information data represents all multidimensional data of factors affecting the cooking process, which are obtained by matching the cooking food with the cooking tool, the cooking behavior, and the like in the cooking process.
In the embodiment of the invention, the server is a cloud server corresponding to the intelligent cooking equipment, and can perform information data interaction with the intelligent cooking equipment so as to better complete a cooking process.
That is to say, the server in the embodiment of the present invention may acquire the cooking information data collected by the intelligent cooking device through network transmission from the intelligent cooking device when cooking is implemented.
However, the cooking information data reported by the intelligent cooking device may be all valid (i.e. the cooking information data is already valid cooking information data), or may include invalid data. Therefore, the server can filter the cooking information data containing invalid data, screen out valid cooking information data, and realize the processing of the cooking score by using the valid cooking information data.
Here, the server receives cooking information data uploaded by the intelligent cooking device; the server filters the cooking information data to obtain effective cooking information data.
In the embodiment of the present invention, the effective cooking information data may be cooking material data, cooking tool data, cooking behavior data, and the like, where the cooking material data is used to represent at least one of characteristics and types of food materials and proportions of each food material, the cooking tool data is used to represent characteristics such as materials of cooking tools, and the cooking behavior data is used to represent factors of cooking operations, such as at least one of a cooking sequence, a cooking time, or a cooking power value. The cooking behavior data is used to represent operation-related data such as the frequency or the number of times of cooking operations.
It should be noted that, in the embodiment of the present invention, the server may acquire the multi-dimensional cooking related data. In this way, the reliability of the data source of the cooking grading processing performed by the server can be ensured.
In the embodiment of the invention, the cooking information data, the cooking scoring result and the like can be stored in the memory of the server.
S102, inputting effective cooking information data into a preset cooking grading model, and outputting a cooking grading result of the time, wherein the preset cooking grading model is used for representing a judgment rule of a cooking effect;
after the server acquires the effective cooking information data, the server can perform cooking scoring by using the effective cooking information data. The server in the embodiment of the invention can establish the preset scoring model which is used for representing the judgment rule of the cooking effect and reflecting the corresponding relation between the cooking information data and the cooking scoring result, so that the server can substitute the effective cooking information data by calling the preset cooking scoring model to obtain the cooking scoring result of the cooking.
It should be noted that the preset cooking grading model in the embodiment of the present invention may be obtained through model training, and the preset cooking grading model may be trained according to the historical cooking information data and the historical cooking effect as samples. When the cooking scoring model is trained for the first time, the cooking effect obtained according to the first cooking information data and the judgment of the user can be used as the first sample data, and the specific embodiment of the invention is not limited. The detailed training process of the preset cooking score model will be described in the following embodiments.
It should be noted that, in the embodiment of the present invention, the scoring result after one cooking may include various information such as an evaluation of the cooking effect and a defect parameter of the cooking, and the embodiment of the present invention is not limited.
In the embodiment of the invention, the server quantifies or grades the evaluation of the cooking effect, so that the cooking effect can be easily and clearly obtained. For example, the cooking effect is divided into different sections according to different color, aroma and taste, so that cooking effects of different grades such as grade 1, grade 2 and grade 3 are obtained, and the cooking effect is represented to be worse when the grade is larger. Or scoring the cooking effect according to different color, aroma and taste standards to obtain the score of each cooking, wherein the higher the score is, the better the cooking effect is represented. Alternatively, the cooking effect may be embodied in various forms and standards such as colors or icons, and the embodiment of the present invention is not limited.
For example, assume that the ratio of rice to water is 100 when the intelligent electric cooker (intelligent cooking device) is steaming rice: 3, the cooking time is 30 minutes, the intelligent electric cooker is made of stainless steel and covers for 2 times during cooking, and then, the server inputs the cooking related information into the preset cooking scoring model to obtain the suggestion that the humidity of the rice is level 3 (the level with high humidity) and the water is added too much because the preset cooking scoring model represents the corresponding relation between the cooking information data and the cooking scoring result.
It can be understood that, after obtaining the evaluation of the cooking effect, the server may obtain the cooking defect (for example, the cooking time is too long, or the cooking power value is small, etc., and the embodiment of the present invention is not limited) in the cooking process based on the evaluation of the cooking effect, so that the user may adjust the cooking process when performing the same type of cooking next time, thereby achieving a better cooking effect.
S103, sending the cooking grading result to the intelligent cooking equipment.
After the server obtains the cooking grading result, the server can be in network communication with the intelligent cooking equipment, so that the server can send the cooking grading result to the intelligent cooking equipment, the intelligent cooking equipment can show the cooking grading result to a user, and the cooking effect is visual.
It should be noted that the cooking scoring method provided by the embodiment of the present invention is implemented on the premise that the intelligent cooking device is in communication with the server.
Further, the architecture of a cooking scoring system provided by the embodiment of the present invention may also be as shown in fig. 3, and the cooking scoring system may include: one or more servers 1, intelligent cooking devices 2, terminals 4 and a network 3, wherein the network 3 includes network entities such as routers, gateways and the like, which are not shown in fig. 3. The intelligent cooking device 2 interacts data information with the server 1 through a network so as to acquire generated cooking information data from the intelligent cooking device 2 and transmit the cooking information data to the server 1, and the terminal 4 also interacts data information with the server 1 through the network so as to transmit a cooking grading result to the terminal 4 through the server 1. The type of the intelligent cooking device 2 may include a type of an intelligent electric rice cooker, an intelligent electric pressure cooker, and the like. The intelligent cooking device 2 in the embodiment of the present invention may be a cooking device with a network communication function, an intelligent program control function, and a data acquisition function, such as an intelligent electric cooker, and the embodiment of the present invention is not limited. The types of the terminal devices are shown in fig. 3, and include a mobile phone (terminal 4-3), a tablet computer or PDA (terminal 4-5), a desktop computer (terminal 4-2), a PC (4-4), an all-in-one machine (4-1), and the like. The terminal 4 is installed with various application function modules required by the user, such as applications with entertainment functions (e.g., video applications, audio playing applications, game applications, and reading software), applications with service functions (e.g., map navigation applications, group purchase applications, and shooting applications), and system functions such as setting applications. In the embodiment of the present invention, a cooking application is installed in the terminal 4.
In this way, in the embodiment of the present invention, after acquiring the current cooking scoring result, the server may send the current cooking scoring result to the terminal corresponding to the user, so that the terminal (an electronic device, such as a mobile phone, etc., on which a cooking application is installed, and the embodiment of the present invention is not limited) may display the current cooking scoring result on the cooking application. Here, the server is a background server of the cooking application, and the server may communicate with the terminal and transmit the cooking scoring result to the terminal when the cooking scoring result is obtained.
That is to say, the embodiment of the present invention does not limit to which device the cooking scoring result is transmitted, and may ultimately allow the user to know the result. For example, when the intelligent cooking device has a display screen, the server may send the cooking grading result to the intelligent cooking device, and the intelligent cooking device displays the cooking grading result; when the intelligent cooking equipment is not provided with the display screen, the server can also send the cooking grading result to the terminal through the network, and the terminal displays the cooking grading result for the user.
For example, as shown in fig. 4, it is assumed that a display screen is provided on the intelligent electric rice cooker (intelligent cooking device), so that the server can transmit the obtained cooking scoring result of "the humidity of rice is level 3 (high humidity level) and the water is added too much" to the intelligent electric rice cooker, and the intelligent electric rice cooker can display "the humidity of rice is level 3 (high humidity level) and the water is added too much" on the display screen.
It can be understood that because the culinary art information data of culinary art in-process can be gathered to intelligent cooking equipment, cook promptly and eat the multi-dimensional data that material cooperation culinary art instrument and culinary art action obtained etc, consequently, the server just can be according to the culinary art information data that reports, just can obtain the effect of this time culinary art through transferring to predetermine the culinary art model, culinary art grading result promptly transmits for intelligent cooking equipment, thus, when the culinary art is accomplished, intelligent cooking equipment just can show the culinary art result of this time, thereby can be according to the culinary art grading result of this time, improve the process of carrying out the culinary art of the same type next time, realize judging of culinary art result, provide the basis for improving the culinary art effect, the intelligence of culinary art has been improved.
Further, before 102, a cooking scoring method provided by an embodiment of the present invention may further include: and S104. The following were used:
and S104, establishing a preset cooking grading model.
In the embodiment of the invention, the server can establish the preset cooking grading model based on the historical cooking information data and the historical cooking effect. The preset cooking score model is formed based on a machine learning technique.
That is to say, based on the description of the implementation process of the above embodiment, the embodiment of the present invention provides a preset cooking scoring model formed by introducing a machine learning technique, and multi-dimensional data is considered and then comprehensively determined for each cooking classification. In the initial stage of forming the preset cooking grading model, the cooking information data (sample data) with multiple dimensions as much as possible still needs to be manually selected for training of the machine learning model, and the data description is determined according to the discrimination of the cooking information data on the first training result, so that the problem of manual intervention for parameter selection basically does not exist, and the machine learning can learn proper parameters by itself; because the meaning of the features is more visual than that of the parameters without meaning, the features are easier to understand in combination with the distribution of the features; firstly, the real-time comprehensive evaluation based on the machine learning model relates to the comprehensive consideration of a plurality of dimensional information data, and improves the accuracy of comprehensive scoring. In addition, the model has the function of evolutionary learning. Even if the allowable range is updated or deleted, the determination of the new allowable range can be identified and the adjustment of the preset cooking grading model can be carried out by simply carrying out model training again (sometimes needing to carry out fine adjustment on data), so that the accuracy of the comprehensive grading result is ensured.
The machine learning technology can be freely shared and spread in the comprehensive scoring of multiple dimensions, and the comprehensive scoring of machine learning is comprehensive and can be evolved by self without aiming at a specific cooking process, so that a comprehensive scoring method based on a machine learning model can be disclosed even for different cooking processes of the same intelligent cooking device. Based on the foregoing embodiment, as shown in fig. 5, a process of establishing a preset cooking scoring model in the cooking scoring method provided by the embodiment of the present invention includes: S1041-S1044. The following were used:
s1041, acquiring a positive sample and a negative sample according to a preset configuration proportion, wherein the positive sample and the negative sample are corresponding relations between historical effective cooking information data and a cooking result;
here, in the actual operation process, there may be a certain proportion, that is, a configuration proportion, in which the composite scoring result (i.e., the cooking effect or the cooking scoring result) is superior (positive sample) and the composite scoring result is inferior (negative sample), and when the preset cooking scoring model is formed, the configuration of the training data (the sample with the existing user property and the corresponding cooking effect) by the server also needs to be set according to the configuration proportion. The positive sample and the negative sample are corresponding relations between the historical effective cooking information data and the cooking result.
S1042, calling a set training model to process the positive sample or the negative sample to obtain a first training result;
it will be appreciated that the more complete the allowable ranges referred to by the positive and negative examples in the embodiments of the present invention, the more accurate the subsequent assessment of the cooking score.
S1043, continuously detecting the training model until the first training result meets a preset condition, taking the training model with the first training result meeting the preset condition as a preset cooking grading model, wherein the preset condition is used for representing that when a data output result obtained according to the preset cooking grading model is applied to determining a cooking grading result, the accuracy of the actual cooking grading result of the corresponding obtained sample is higher than a historical threshold value.
In the embodiment of the invention, no matter what training model is adopted, at the beginning of training, the input of the training model comprises the features of the plurality of dimensions, after a plurality of tests, if the features do not have favorable influence or errors on the first training result, the weight of the features or data of the dimensions is reduced, if the features have favorable influence on the first training result, the weight of the features or data is increased, and if the weight of one parameter is reduced to 0, the features do not play any role in the training model. Through the final experiment of the embodiment of the invention, what the above-mentioned features of different dimensions can finally have a positive effect on the first training result is the long-term feature (i.e. the cooking information data in the embodiment of the invention). Assuming that the feature of different dimensions only includes valid cooking information data of multiple dimensions (i.e. other inconsistent data has been excluded), the forming process of the preset cooking score model roughly includes: inputting effective cooking information data of multiple dimensions of a positive sample or a negative sample into a training model (namely calling the training model), and obtaining a first training result from the training model; wherein the constructed training model has corresponding weight value with effective cooking information data; and continuously monitoring the first training result until a preset condition is met, and taking the training model as a preset cooking grading model.
Optionally, the preset condition in the embodiment of the present invention may be that when the data output result obtained according to the preset cooking scoring model is applied to determine the cooking scoring result, the accuracy of the actual cooking scoring result of the corresponding obtained sample is higher than a historical threshold, that is, the accuracy of the cooking scoring result reaches the historical threshold, and the historical threshold may be 99%.
As can be seen from the above flows, 1) the embodiment of the invention adopts a cooking scoring mode based on the preset cooking scoring, when a terminal is constructed and cooking information data in the cooking process is subjected to cooking scoring based on multiple dimensions, historical cooking information data in each cooking process on the terminal is fully utilized to obtain a preset cooking scoring model, an index reflecting the credibility degree of each cooking on the terminal can be effectively obtained, and the evaluation of each cooking process on related intelligent cooking equipment is realized; 2) according to the embodiment of the invention, various different dimensions of historical cooking information data of different cooking types are introduced to train the training model, and the final verified comprehensive scoring of the cooking effect in different cooking types is determined according to the first training result, so that the accuracy of the comprehensive scoring in the cooking process is improved. 3) The preset cooking scoring model adopted by the embodiment of the invention has the remarkable characteristic that the model can evolve by itself, the weight can be automatically adjusted according to the transformable cooking information data with multiple dimensions, and the frequent manual intervention of adjusting parameters based on rules is avoided.
It can be understood that in the embodiment of the invention, the cooking information data with multiple dimensions are used as the main data source, the grading process and the model construction process are simple and easy to implement, and various complex coding, clustering and screening means are not required to carry out complex construction and processing on the features, so that the workload of data processing is greatly reduced, and the preset cooking grading model is simple and available.
Example two
The embodiment of the invention also provides a cooking scoring method, as shown in fig. 6, which is applied to intelligent cooking equipment, and the method can further comprise the following steps:
s201, in the cooking process, collecting cooking information data, wherein the cooking information data are used for representing multi-dimensional data obtained by matching cooking food materials with a cooking tool and cooking behaviors in the cooking process;
the intelligent cooking equipment and the server in the embodiment of the invention establish network connection communication. Moreover, the intelligent cooking device in the embodiment of the present invention has high intelligence, and the intelligent cooking device may be a cooking device having a network communication function, an intelligent program control function, and a data acquisition function, such as an intelligent electric cooker, and the embodiment of the present invention is not limited.
Here, in the embodiment of the present invention, in a cooking process of the intelligent cooking device, the cooking information data may be collected through a sensor, a camera, a main control module of the intelligent cooking device, an electronic scale, and other components, and the cooking information data represents all multi-dimensional data obtained by matching cooking ingredients with a cooking tool, a cooking behavior, and the like in the cooking process.
That is to say, in the culinary art process, intelligent cooking equipment can gather the picture information of cooking food and the picture information of cooking tool through the camera device that sets up on it, can also gather culinary art action data through sensor and timer etc.. When the intelligent cooking equipment acquires image information, the image information of the cooking food and the image information of the cooking tool need to be converted or quantized into numbers when the image information passes through the image information of the cooking food and the image information of the cooking tool, so that cooking food data and cooking tool data are obtained; and then the intelligent cooking equipment takes the cooking food material data, the cooking tool data and the cooking behavior data as the collected cooking information data.
In an embodiment of the present invention, the cooking information data may include: the cooking food material data, the cooking tool data, the cooking behavior data, and the like may further include: the cooking system comprises data affecting cooking effects, such as cooking environment information and the like, wherein the cooking food material data is used for reflecting at least one of characteristics and types of food materials and proportions of the food materials, the cooking tool data is used for reflecting characteristics of materials and the like of cooking tools, and the cooking behavior data is used for reflecting factors of cooking operations, such as at least one of cooking sequence, cooking time or cooking fire value and the like. The cooking behavior data is used to represent operation-related data such as the frequency or the number of times of cooking operations.
The cooking food material data is used for embodying characteristics of food materials and can be divided into main food material data and added food material data, the main food material data can include food material factory data (such as rice factory data) and water factory data, the rice factory data is taken as an example for explanation, and the rice factory data includes rice commodity information (such as numbers, weights, various types and the like), physicochemical characteristic information, physicochemical reaction characteristic information and related data information of links such as breeding, planting, storing, processing, packaging, transporting and storing. The information is subdivided into a plurality of items, for example, the processing information can be subdivided into chaff rate, roughness rate, angle of repose, uniformity, scattering property, relative density, processing technology, aging method, harmful substance components and contents, and the like; the physical characteristic information can be subdivided into freshness, smell, color, surface state, length, width, thickness and ratio, rice grain strength, transparency and the like; chemical characteristics and content information are subdivided into vitamin B1, amylose, water, crude fiber, aging characteristics, pesticide residue and the like; the physical and chemical reaction characteristic information can be subdivided into the evaluation of heating water absorption rate, dissolution rate, extensibility, expansion rate, rice water solid content, gelatinization time and the like. The water source delivery information comprises water commodity information (such as information of numbers, weights, types of water and the like), physical and chemical characteristic information of water, physical and chemical reaction characteristic information of water, and link information of water source places, processing, packaging, transportation, storage and the like. The above information is subdivided into many items, for example, the water category can be subdivided into tap water, direct drinking water, natural water, purified water, distilled water, health water (with added nutrients), mineral water, magnetized water, etc.; the processing information can be subdivided into sterilization treatment methods, processing techniques, additives, harmful substance components and contents and the like; chemical composition information can be subdivided into specific trace elements, minerals, and the like. The data of the added food materials can comprise factory data of oat, tea, milk, vinegar and oil, and is used for seasoning rice or enhancing nutrition. In addition, the rice and water detail data also comprises the data of the builder of the detail data, the compiling time, which method or which instrument or which enterprise laboratory is adopted for measuring, and according to which national industry standard and the like.
It should be noted that, in the embodiment of the present invention, the intelligent cooking device may perform processing such as quantization of picture information by using a picture recognition technology, and the embodiment of the present invention does not limit the manner of the processing technology.
And S202, when the cooking is finished, sending the cooking information data to a server for cooking scoring.
After intelligent cooking equipment gathers culinary art information data, because culinary art information data all gathered at whole culinary art in-process, consequently, intelligent cooking equipment can obtain complete culinary art information data when the culinary art is accomplished, uploads to the server again to the server can carry out the culinary art of this time culinary art effect according to complete culinary art information data and grade and handle, can improve the accuracy that the server judges this time culinary art result of grading like this.
It can be understood that in the embodiment of the invention, the cooking information data with multiple dimensions are used as the main data source, the grading process and the model construction process are simple and easy to implement, and various complex coding, clustering and screening means are not required to carry out complex construction and processing on the features, so that the workload of data processing is greatly reduced, and the preset cooking grading model is simple and available.
Further, as shown in fig. 7, after S202, the cooking scoring method provided by the embodiment of the present invention may further include: S203-S205. The following were used:
s203, receiving a cooking grading result sent by the server;
s204, obtaining cooking parameters according to the cooking grading result, wherein the cooking parameters are used for representing cooking requirement parameters in the cooking process;
and S205, carrying out the next cooking process of the same cooking type according to the cooking parameters.
Based on the framework of fig. 2, after the intelligent cooking device uploads the cooking information data to the server, because the server can obtain the cooking grading result of the cooking process according to the cooking information data and the preset cooking grading model, after the server analyzes, the server can transmit the cooking grading result obtained by the server back to the intelligent cooking device, namely, the intelligent cooking device receives the cooking grading result sent by the server, and then the intelligent cooking device can analyze the cooking grading result to obtain the cooking parameters for representing the cooking requirement parameters in the cooking process, so that the intelligent cooking device can adopt the cooking parameters and is used when the cooking process of the same cooking type is carried out next time.
It should be noted that, in the embodiment of the present invention, since the cooking scoring result after one cooking may include information in various aspects, such as the evaluation of the cooking effect and the defect parameter of the cooking, when the intelligent cooking device obtains the cooking scoring result, the defect parameter of the cooking may be obtained, and then the intelligent cooking device may adjust the defect parameter of the cooking according to the preset standard of the cooking type to obtain the cooking parameter, so that the intelligent cooking device may automatically perform the next cooking process of the same cooking type according to the cooking parameter to obtain a better cooking scoring result than the cooking effect of the cooking. Secondly, when the intelligent cooking equipment obtains the cooking parameters, the cooking parameters can be displayed to the user, and the user is prompted to realize the cooking process of the same cooking type according to the cooking parameters in the next time.
Optionally, in the embodiment of the present invention, the cooking parameter may be a cooking time, a cooking power value, a ratio of cooking materials, or a material of a cooking tool.
In the embodiment of the present invention, the cooking type may be various, for example, steamed rice, fried dish, soup, and the like, and the embodiment of the present invention is not limited.
In this way, the automatic adjustment can be directly carried out when the intelligent cooking equipment is used for cooking the next time aiming at the cooking parameters which can be automatically controlled by the intelligent cooking equipment; for the cooking parameters which cannot be automatically controlled by the intelligent cooking equipment, the required cooking parameters can be displayed to the user by the intelligent cooking equipment, and the user intervenes to finish the next cooking process of the same cooking type.
Further, based on the architecture of fig. 3, in the embodiment of the present invention, the server may further transmit the cooking scoring result to the terminal, so that the terminal (an electronic device installed with a cooking application, such as a mobile phone, and the like, but not limited to the embodiment of the present invention) may display the cooking scoring result on the cooking application. Here, the server is a background server of the cooking application, and the server can communicate with the terminal, send the cooking scoring result to the terminal after obtaining the cooking scoring result, show the cooking parameters to the user through the terminal, and prompt the user to realize the cooking process of the same cooking type according to the cooking parameters in the next time.
It can be understood that, after obtaining the evaluation of the cooking effect, the server may obtain the cooking defect (for example, the cooking time is too long, or the cooking power value is small, and the like, and the embodiments of the present invention are not limited) in the cooking process based on the evaluation of the cooking effect, and after sending the cooking scoring result to the intelligent cooking device or the terminal, the user may adjust the cooking in the next time of performing the same type of cooking, thereby achieving a better cooking effect.
EXAMPLE III
Based on the implementation of the first embodiment and the second embodiment, an embodiment of the present invention provides a cooking scoring method, as shown in fig. 8, the method may include:
s301, in the cooking process, the intelligent cooking equipment collects cooking information data, and the cooking information data is used for representing multi-dimensional data obtained by matching cooking food materials with cooking tools and cooking behaviors in the cooking process;
in the embodiment of the present invention, a description process of "the intelligent cooking device collects cooking information data used for representing multi-dimensional data obtained by matching cooking ingredients with cooking tools and cooking behaviors in the cooking process" is consistent with the description of S201 in the second embodiment, and is not described herein again.
S302, when the intelligent cooking equipment finishes cooking, the cooking information data are sent to a server for cooking scoring;
the description process of "the intelligent cooking device sends the cooking information data to the server for cooking scoring when the cooking is completed" in the embodiment of the present invention is consistent with the description of S202 in the second embodiment, and is not repeated here.
S303, the server filters the cooking information data to obtain effective cooking information data;
the description process of the server for filtering the cooking information data to obtain the effective cooking information data in the embodiment of the present invention is consistent with the description of S101 in the first embodiment, and is not repeated here.
S304, the server establishes a preset cooking grading model;
the description process of "the server establishes the preset cooking scoring model" in the embodiment of the present invention is consistent with the description of S104 in the first embodiment, and details are not repeated here.
S305, the server inputs the effective cooking information data into a preset cooking grading model, outputs the current cooking grading result, and the preset cooking grading model is used for representing a judgment rule of a cooking effect;
the description process of the server inputting the effective cooking information data into the preset cooking scoring model and outputting the cooking scoring result of this time in the embodiment of the present invention is consistent with the description of S102 in the first embodiment, and is not repeated here.
S306, the server sends the cooking grading result to the intelligent cooking equipment;
the description process of the "server sends the cooking scoring result to the intelligent cooking device" in the embodiment of the present invention is consistent with the description of S103 in the first embodiment, and is not described herein again.
S307, the intelligent cooking equipment acquires cooking parameters according to the cooking grading result, wherein the cooking parameters are used for representing cooking requirement parameters in the current cooking process;
the description process of the intelligent cooking device obtaining the cooking parameters according to the cooking scoring result in the embodiment of the present invention is consistent with the description of S204 in the second embodiment, and is not repeated here.
And S308, the intelligent cooking equipment carries out the next cooking process of the same cooking type according to the cooking parameters.
The description process of the "intelligent cooking device performs the cooking process of the next same cooking type according to the cooking parameters" in the embodiment of the present invention is consistent with the description of S205 in the second embodiment, and is not repeated here.
It can be understood that, after obtaining the evaluation of the cooking effect, the server may obtain the cooking defect (for example, the cooking time is too long, or the cooking power value is small, etc., and the embodiment of the present invention is not limited thereto) in the cooking process based on the evaluation of the cooking effect, and after sending the cooking scoring result to the intelligent cooking device or the terminal, the user may adjust the cooking process in the next time of the same type of cooking, so as to achieve a better cooking effect.
Example four
Based on the same inventive concept of the first embodiment and the third embodiment, as shown in fig. 9, an embodiment of the present invention provides a server 1, and the server 1 may include:
the first obtaining unit 10 is configured to obtain effective cooking information data, where the effective cooking information data is used to represent multi-dimensional data obtained by matching cooking food materials with a cooking tool and cooking behaviors in a cooking process;
the calling unit 11 is configured to input the effective cooking information data into a preset cooking scoring model, and output a cooking scoring result of this time, where the preset cooking scoring model is used to represent a judgment rule of a cooking effect;
and the first sending unit 12 is used for sending the cooking grading result to the intelligent cooking equipment.
Optionally, the server 1 further includes: a first receiving unit 13.
The first receiving unit 13 is configured to receive cooking information data uploaded by the intelligent cooking device;
the first obtaining unit 10 is specifically configured to filter the cooking information data to obtain the effective cooking information data.
Optionally, the server 1 further includes: a building unit 14.
The establishing unit 14 is configured to establish a preset cooking scoring model before inputting the effective cooking information data into the preset cooking scoring model and outputting the current cooking scoring result.
Optionally, the establishing unit 14 is specifically configured to obtain a positive sample and a negative sample according to a preset configuration ratio, where the positive sample and the negative sample are corresponding relations between historical effective cooking information data and a cooking result; calling a set training model to process the positive sample or the negative sample to obtain a first training result; and continuously detecting the training model until the first training result meets a preset condition, and taking the training model with the first training result meeting the preset condition as the preset cooking scoring model, wherein the preset condition is used for representing that the accuracy of the actual cooking scoring result of the corresponding obtained sample is higher than a historical threshold when a data output result obtained according to the preset cooking scoring model is applied to determining the cooking scoring result.
In practical applications, the first obtaining Unit 10, the calling Unit 11, and the establishing Unit 14 may be implemented by a processor 15 located on the server 1, specifically, implemented by a Central Processing Unit (CPU), a Microprocessor Unit (MPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), or the like, the first sending Unit 12 may be implemented by a sender 16, and the first receiving Unit 13 may be implemented by a receiver 17.
As shown in fig. 10, an embodiment of the present invention further provides a server, including:
a first receiver 17, a first transmitter 16, a first processor 15, and a first storage medium 18 storing instructions executable by the first processor 15, data received by the first receiver 17, and data transmitted by the first transmitter 16, the first receiver 17, the first transmitter 16, and the first storage medium 18 relying on the first processor 15 to perform operations via a first communication bus 19, the instructions when executed by the first processor 15 performing the cooking scoring method described in the first and third embodiments.
It should be noted that, in practical applications, the various components in the server are coupled together by a first communication bus 19. It will be appreciated that the first communication bus 19 is used to enable connection communication between these components. The first communication bus 19 includes a power bus, a control bus, and a status signal bus in addition to a data bus. But for clarity of illustration the various buses are labeled as first communication bus 19 in figure 10.
It can be understood that, because the culinary art information data of culinary art in-process can be gathered to intelligent cooking equipment, cook promptly and eat the multi-dimensional data that material cooperation culinary art instrument and culinary art action obtained etc, consequently, the server just can be according to the culinary art information data that reports, just can obtain the effect of this time culinary art through calling preset the culinary art model, the culinary art grades the result and transmits for intelligent cooking equipment promptly, thus, when the culinary art was accomplished, intelligent cooking equipment just can demonstrate the culinary art result of this time, thereby can grade the result according to this time culinary art, improve the process of carrying out the culinary art of the same type next time, realize the judgement of culinary art result, provide the basis for improving the culinary art effect, the intelligence of culinary art has been improved.
The embodiment of the invention provides a computer storage medium which is applied to a server and stores machine instructions, and when the machine instructions are executed by one or more first processors, the first processors execute the cooking grading method in the first embodiment and the third embodiment.
The computer-readable storage medium may be a magnetic random access Memory (FRAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical Disc, or a Compact Disc Read-Only Memory (CD-ROM), among others.
Based on the same inventive concept of the second embodiment and the third embodiment, as shown in fig. 11, the second embodiment of the present invention provides an intelligent cooking device 2, and the intelligent cooking device 2 may include:
the acquisition unit 20 is used for acquiring cooking information data in the cooking process, wherein the cooking information data is used for representing multi-dimensional data obtained by matching cooking food materials with cooking tools and cooking behaviors in the cooking process;
and a second sending unit 21, configured to send the cooking information data to a server when cooking is completed, so as to perform cooking scoring.
Optionally, the intelligent cooking device 2 further includes: a second receiving unit 22, a second acquiring unit 23 and a cooking unit 24.
The second receiving unit 22 is configured to send the cooking information data to a server when cooking is completed, and receive a cooking scoring result sent by the server after the cooking scoring is performed;
the second obtaining unit 23 is configured to obtain a cooking parameter according to the cooking scoring result, where the cooking parameter is used to represent a cooking requirement parameter in the current cooking process;
and the cooking unit 24 is used for performing the next cooking process of the same cooking type according to the cooking parameters.
Optionally, the collecting unit 20 is specifically configured to collect picture information of cooking food materials, picture information and data of cooking tools, and cooking behavior data during a cooking process; converting the picture information of the cooking food material and the picture information of the cooking tool to obtain cooking food material data and cooking tool data; and taking the cooking food material data, the cooking tool data and the cooking behavior data as collected cooking information data.
In practical applications, the acquiring unit 20, the second acquiring unit 23, and the cooking unit 24 may be implemented by a processor 25, specifically, a CPU, an MPU, a DSP, or an FPGA, located on the intelligent cooking apparatus 2, the second transmitting unit 21 may be implemented by a transmitter 26, and the second receiving unit 22 may be implemented by a receiver 27.
As shown in fig. 12, an embodiment of the present invention further provides an intelligent cooking apparatus, including:
a second receiver 27, a second transmitter 26, a second processor 25, and a second storage medium 28 storing instructions executable by the second processor 25, data received by the second receiver 27, and data transmitted by the second transmitter 26, the second receiver 27, the second transmitter 26, and the second storage medium 28 relying on the second processor 25 to perform operations via a second communication bus 29, the instructions, when executed by the second processor 25, performing the cooking scoring method as described in the second and third embodiments.
It should be noted that, in practical applications, the various components in the intelligent cooking device are coupled together by the second communication bus 29. It will be appreciated that the second communication bus 29 is used to enable connection communication between these components. The second communication bus 29 includes a power bus, a control bus, and a status signal bus in addition to a data bus. But for clarity of illustration the various buses are labeled as the second communication bus 29 in figure 12.
It can be understood that, because the culinary art information data of culinary art in-process can be gathered to intelligent cooking equipment, cook promptly and eat the multi-dimensional data that material cooperation culinary art instrument and culinary art action obtained etc, consequently, the server just can be according to the culinary art information data that reports, just can obtain the effect of this time culinary art through calling preset the culinary art model, the culinary art score result promptly and transmit for intelligent cooking equipment, thus, when the culinary art was accomplished, intelligent cooking equipment just can demonstrate the culinary art result of this time, thereby can be according to the culinary art score result of this time, improve the process of carrying out the culinary art of the same type next time, realize the judgement of culinary art result, provide the basis for improving the culinary art effect, the intelligence of culinary art has been improved.
The embodiment of the invention provides a computer storage medium which is applied to intelligent cooking equipment and stores machine instructions, and when the machine instructions are executed by one or more second processors, the second processors execute the cooking grading method in the second embodiment and the third embodiment.
The computer readable storage medium may be memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention 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, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may 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 means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention.
Claims (12)
1. A cooking grading method is applied to a server and comprises the following steps:
obtaining effective cooking information data, wherein the effective cooking information data are used for representing multi-dimensional data obtained by matching cooking food materials with cooking tools and cooking behaviors in a cooking process;
inputting the effective cooking information data into a preset cooking grading model, and outputting a cooking grading result of the time, wherein the preset cooking grading model is used for representing a judgment rule of a cooking effect; the cooking grading result comprises the evaluation of the cooking effect and the defect parameter corresponding to the cooking process; the defect parameters comprise defect parameters corresponding to cooking behaviors in the cooking process;
and sending the cooking grading result to intelligent cooking equipment.
2. The method of claim 1, wherein the obtaining valid cooking information data comprises:
receiving cooking information data uploaded by the intelligent cooking equipment;
and filtering the cooking information data to obtain the effective cooking information data.
3. The method of claim 1, wherein before inputting the effective cooking information data into a preset cooking scoring model and outputting a cooking scoring result of the time, the method further comprises:
and establishing the preset cooking grading model.
4. The method of claim 3, wherein said establishing said pre-set cooking score model comprises:
acquiring a positive sample and a negative sample according to a preset configuration proportion, wherein the positive sample and the negative sample are corresponding relations between historical effective cooking information data and cooking results;
calling a set training model to process the positive sample or the negative sample to obtain a first training result;
and continuously detecting the training model until the first training result meets a preset condition, taking the training model with the first training result meeting the preset condition as the preset cooking grading model, wherein the preset condition is used for representing that the accuracy of the actual cooking grading result of the corresponding obtained sample is higher than a historical threshold value when a data output result obtained according to the preset cooking grading model is applied to determining the cooking grading result.
5. A cooking grading method is applied to intelligent cooking equipment and comprises the following steps:
in the cooking process, cooking information data are collected, wherein the cooking information data are used for representing multi-dimensional data obtained by matching cooking food materials with a cooking tool and cooking behaviors in the cooking process;
when cooking is finished, sending the cooking information data to a server, and carrying out cooking grading to obtain a cooking grading result, wherein the cooking grading result comprises the evaluation of the cooking effect and the defect parameter corresponding to the cooking process; the defect parameters comprise defect parameters corresponding to cooking behaviors in the cooking process.
6. The method of claim 5, wherein the cooking information data is transmitted to a server when cooking is completed, and after the cooking is scored, the method further comprises:
receiving a cooking grading result sent by the server;
obtaining cooking parameters according to the cooking grading result, wherein the cooking parameters are used for representing cooking requirement parameters in the cooking process;
and according to the cooking parameters, carrying out the next cooking process of the same cooking type.
7. The method of claim 5, wherein collecting cooking information data during the cooking process comprises:
collecting picture information of cooking food materials, picture information and data of cooking tools and cooking behavior data in a cooking process;
converting the picture information of the cooking food material and the picture information of the cooking tool to obtain cooking food material data and cooking tool data;
and taking the cooking food material data, the cooking tool data and the cooking behavior data as collected cooking information data.
8. A server, comprising:
the cooking system comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring effective cooking information data, and the effective cooking information data is used for representing multi-dimensional data obtained by matching cooking food materials with cooking tools and cooking behaviors in a cooking process;
the calling unit is used for inputting the effective cooking information data into a preset cooking grading model and outputting a cooking grading result of the time, and the preset cooking grading model is used for representing a judgment rule of a cooking effect; the cooking grading result comprises the evaluation of the cooking effect and the defect parameter corresponding to the cooking process; the defect parameters comprise defect parameters corresponding to cooking behaviors in the cooking process;
and the first sending unit is used for sending the cooking grading result to the intelligent cooking equipment.
9. A server, comprising:
a first receiver, a first transmitter, a first processor and a first storage medium storing instructions executable by the first processor, data received by the first receiver and data transmitted by the first transmitter, the first receiver, the first transmitter and the first storage medium operating on the first processor via a first communication bus, the instructions when executed by the first processor performing the cooking grading method of any of claims 1 to 4 above.
10. An intelligent cooking device, comprising:
the cooking system comprises a collecting unit, a processing unit and a control unit, wherein the collecting unit is used for collecting cooking information data in the cooking process, and the cooking information data is used for representing multi-dimensional data obtained by matching cooking food materials with a cooking tool and cooking behaviors in the cooking process;
the second sending unit is used for sending the cooking information data to a server when cooking is finished, and performing cooking grading to obtain a cooking grading result, wherein the cooking grading result comprises the evaluation of the cooking effect and the defect parameter corresponding to the cooking process; the defect parameters comprise defect parameters corresponding to cooking behaviors in the cooking process.
11. An intelligent cooking device, comprising:
a second receiver, a second transmitter, a second processor and a second storage medium storing instructions executable by the second processor, data received by the second receiver and data transmitted by the second transmitter, the second receiver, the second transmitter and the second storage medium operating in dependence on the second processor via a second communication bus, the instructions when executed by the second processor performing the cooking scoring method of any one of claims 5 to 7 above.
12. A computer storage medium applied to a server and storing machine instructions, wherein when the machine instructions are executed by one or more first processors, the first processors execute the cooking scoring method according to any one of claims 1 to 4; or, in an intelligent cooking device, storing machine instructions which, when executed by one or more second processors, carry out the cooking scoring method according to any one of claims 5 to 7.
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| CN107819812A (en) * | 2016-09-14 | 2018-03-20 | 佛山市顺德区美的电热电器制造有限公司 | The evaluation method and device of cooking quality |
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