An integrated teaching workbench for intelligent cooking teaching, a teaching method and system

Abstract

The application discloses an intelligent cooking teaching system, which comprises a cooking remote measurement self-starting module, a time vegetable feeding module, a cooking method collecting module, a cooking analysis module and an evaluation feedback module; the cooking remote measurement self-starting module and the time vegetable feeding module are connected to generate examination information; the cooking method collecting module collects cooking related parameters in the examination; the cooking analysis module analyzes the cooking based on the related parameters; and the evaluation feedback module obtains cooking analysis information and outputs cooking examination results. Compared with the prior art, the application has the advantages that the intelligent cooking teaching integrated teaching workbench, the teaching method and the system can effectively perform skill examination and targeted teaching according to technical defects.

Description

Technical Field

[0001] This invention relates to the field of culinary teaching technology, specifically to an integrated teaching workbench, teaching method, and system for intelligent culinary teaching. Background Technology

[0002] With the significant improvement in people's living standards, food is no longer just about satisfying basic needs; people's requirements for dishes are also increasing day by day.

[0003] Today, people not only pay attention to the taste of dishes, but also have higher expectations for their appearance and the professionalism of the cooking techniques. In various social occasions and family gatherings, a dish that is delicious, visually appealing, and appealing is often more appreciated and loved, which has prompted cooking to gradually transform from a life skill into an art and a professional craft.

[0004] Cooking skills directly determine the quality and appearance of dishes. Professional chefs can use their exquisite skills to bring out the best in ingredients and create satisfying dishes. Whether in the catering industry or for ordinary home cooking enthusiasts, mastering professional cooking skills is of great importance.

[0005] However, the training of culinary talents currently faces many challenges. Traditional culinary teaching methods and tools are, to some extent, unable to meet people's needs for learning culinary skills. Therefore, there is an urgent need for a more efficient, scientific, and systematic teaching method to cultivate professional culinary talents and improve their culinary skills. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to overcome the above-mentioned technical defects and provide an integrated teaching workbench, teaching method and system for intelligent cooking teaching that can effectively conduct skills assessment and provide targeted teaching for technical defects.

[0007] To solve the above-mentioned technical problems, the technical solution provided by the present invention is as follows: an intelligent cooking teaching system, comprising a cooking remote sensing self-starting module, a vegetable supply module, a cooking technique acquisition module, a cooking analysis module, and an evaluation feedback module; the cooking remote sensing self-starting module and the vegetable supply module are interconnected to generate assessment information; the cooking technique acquisition module collects cooking-related parameters during the assessment; the cooking analysis module performs cooking analysis based on the relevant parameters; and the evaluation feedback module obtains the cooking analysis information and outputs the cooking assessment score.

[0008] Preferably, the cooking technique acquisition module includes a cooking step specification data acquisition unit, an ingredient data acquisition unit, and an environmental data acquisition unit;

[0009] The cooking analysis module receives information from the cooking technique collection module, including the cooking operation standard analysis unit and the dish quality analysis unit. The evaluation feedback module obtains the output information from the cooking analysis module and outputs the cooking assessment results.

[0010] Preferably, the food remote sensing self-starting module includes a construction unit, a dish information database construction unit, and a question generation and formulation unit. The vegetable supply module includes a product monitoring unit and a distribution unit. The product monitoring unit uploads inventory information to the food remote sensing self-starting module, and the food remote sensing self-starting module generates assessment questions based on the inventory information.

[0011] Preferably, the building unit includes inputting the assessment outline based on the curriculum standards and formulating assessment criteria based on the students' learning progress and ability level;

[0012] The recipe information database construction unit obtains information on the ingredients, cooking steps, key techniques, nutritional value, and other information of the recipes from the recipe database, which is then used as the basis for the evaluation of the recipes.

[0013] The question generation unit randomly generates cooking assessment questions and requirements based on the recipe information database construction unit and the requirement construction unit.

[0014] The cooking assessment questions and requirements include requirements for dish preparation, ingredient preparation, cooking time, seasoning dosage, knife skills, and dish color.

[0015] Preferably, the item supervision unit includes statistics on the quantity and shelf life of ingredients, as well as replenishment reminders. After the distribution unit obtains the output information of the item generation unit, it transports the dishes to the assessment area.

[0016] Preferably, the cooking step specification data acquisition unit includes a sensor group and a camera group installed in the cooking area; the food data acquisition unit includes acquiring food weight, color, and nutritional composition analysis; and the environmental data acquisition unit acquires the temperature, humidity, and air quality of the cooking area.

[0017] The cooking operation standard analysis unit acquires information from the cooking step standard data collection unit to analyze the cooking operation. The dish quality analysis unit analyzes the appearance, color, and nutritional components of the dish. The evaluation feedback module evaluates the cooking performance and generates a report based on the output information from the cooking operation standard analysis unit and the dish quality analysis unit.

[0018] Another aspect of this invention discloses an intelligent cooking teaching method, comprising the following steps:

[0019] S1: Teachers develop an assessment outline based on classroom learning and input it into the building unit. The cooking remote sensing self-starting module is used to generate assessment information.

[0020] S2: After the trainees enter the assessment area, the assessment questions are generated by the question generation unit, and the cooking ingredients are delivered to the assessment area by the assigned unit.

[0021] S3: After reading the assessment requirements, trainees cook dishes according to the requirements. During this process, the cooking technique collection module collects the trainees' cooking parameter information.

[0022] S4: The cooking analysis module uses image recognition to analyze the parameters of the dishes, and at the same time analyzes the standardization of the cooking operation based on the cooking parameter information, and outputs the analysis results to the evaluation feedback module.

[0023] S5: The assessment and feedback module evaluates and reports cooking assessment results based on student data;

[0024] S6: Based on the cooking assessment results and reports, provide targeted instruction to address the students' weaknesses.

[0025] Another aspect of the present invention discloses an integrated workbench, which is further equipped with a cutting board, a seasoning board, a stove, a sensor unit group, a camera unit group, and an environmental data detection unit group.

[0026] The advantages of this invention compared to the prior art are:

[0027] By interconnecting the cooking remote sensing self-starting module with the seasonal vegetable supply module, the automatic generation of assessment questions and the precise distribution of food ingredients were realized, thereby improving the level of automation and intelligence in teaching.

[0028] The combined use of the cooking technique acquisition module, the cooking analysis module, and the evaluation feedback module in this invention can comprehensively collect and analyze the cooking parameter information of trainees, providing a scientific basis for the evaluation of cooking assessment results.

[0029] This invention identifies students' shortcomings based on their cooking assessment scores and reports, and provides corresponding teaching suggestions, which helps students improve their cooking skills quickly. The use of integrated workbenches and related equipment makes the entire teaching process smoother, more efficient, and easier to promote and use. Attached Figure Description

[0030] Figure 1 This is a structural diagram of the patent title of this invention.

[0031] Figure 2 This is a schematic diagram of the structure in use, as shown in the patent title of this invention. Detailed Implementation

[0032] The present invention will now be described in further detail with reference to the accompanying drawings.

[0033] Combined with appendix Figure 1As shown, an intelligent cooking teaching system includes a cooking remote sensing self-starting module, a vegetable supply module, a cooking technique acquisition module, a cooking analysis module, and an evaluation feedback module. The cooking remote sensing self-starting module and the vegetable supply module are interconnected to generate assessment information. The cooking technique acquisition module collects cooking-related parameters during the assessment. The cooking analysis module performs cooking analysis based on the relevant parameters. The evaluation feedback module obtains the cooking analysis information and outputs the cooking assessment score.

[0034] In a specific implementation of this invention, the cooking technique acquisition module includes a cooking step standard data acquisition unit, an ingredient data acquisition unit, and an environmental data acquisition unit; the cooking analysis module receives information from the cooking technique acquisition module, including a cooking operation standard analysis unit and a dish quality analysis unit; and the evaluation feedback module obtains the output information from the cooking analysis module and outputs the cooking assessment score.

[0035] The food remote sensing self-starting module includes a construction unit, a dish information database construction unit, and a question generation and formulation unit. The vegetable supply module includes a product supervision unit and a distribution unit. The product supervision unit uploads inventory information to the food remote sensing self-starting module, and the food remote sensing self-starting module generates assessment questions based on the inventory information.

[0036] Based on the above embodiments:

[0037] The assessment unit includes: inputting the assessment syllabus based on the curriculum standards; establishing assessment criteria based on students' learning progress and ability levels; a recipe information database construction unit, which obtains information on ingredient pairings, cooking steps, key techniques, nutritional value, and recipes selected for assessment from a recipe database; a question generation and formulation unit, which randomly generates cooking assessment questions and requirements based on the recipe information database construction unit and the assessment unit; cooking assessment questions and requirements include requirements for dish preparation, ingredient preparation, cooking time, seasoning dosage, knife skills, and dish color; an item monitoring unit, which includes statistics on ingredient quantity and shelf life, and also provides replenishment reminders; and a distribution unit, which transports the dishes to the assessment area after receiving the output information from the question generation and formulation unit.

[0038] Based on the above embodiments:

[0039] The cooking procedure standard data acquisition unit includes a sensor group and a camera group installed in the cooking area; the ingredient data acquisition unit acquires the weight, color, and nutritional composition of the ingredients; and the environmental data acquisition unit acquires the temperature, humidity, and air quality of the cooking area. The cooking operation standard analysis unit uses the information from the cooking procedure standard data acquisition unit to analyze the cooking operation; the dish quality analysis unit analyzes the appearance, color, and nutritional composition of the dish; and the evaluation feedback module evaluates the cooking performance and generates a report based on the output information from the cooking operation standard analysis unit and the dish quality analysis unit.

[0040] A smart cooking teaching method includes the following steps: S1: The teacher develops an assessment outline based on classroom learning and inputs it into the construction unit, using a cooking remote sensing self-starting module to generate assessment information; S2: After entering the assessment area, students generate assessment questions through a question generation module, and the unit delivers cooking ingredients to the assessment area; S3: After reading the assessment requirements, students cook the ingredients according to the requirements, during which a cooking technique acquisition module collects the students' cooking parameter information; S4: A cooking analysis module uses image recognition to analyze the parameters of the ingredients, and simultaneously analyzes the standardization of cooking operations based on the cooking parameter information, outputting the analysis results to an evaluation feedback module; S5: The evaluation feedback module evaluates and reports the cooking assessment results based on the student data; S6: Based on the cooking assessment results and report, targeted teaching is provided to address the students' shortcomings.

[0041] An integrated teaching workbench for intelligent cooking instruction includes an integrated workbench, which is further equipped with a cutting board, a seasoning board, a stove, a sensor unit group, a camera unit group, and an environmental data detection unit group.

[0042] The contents not described in detail in this specification are existing technologies known to those skilled in the art.

[0043] In this invention, teachers log into the system, enter the assessment outline in the construction unit according to the curriculum standards and students' learning progress, and set the evaluation criteria. The system automatically selects dish information that meets the outline requirements from the dish database and generates corresponding cooking assessment questions and requirements. At the same time, the item monitoring unit uploads the current inventory information, and the system adjusts the ingredient selection in the assessment questions according to the inventory situation. The question generation unit randomly generates assessment questions that include dish preparation requirements, ingredient preparation requirements, cooking time requirements, etc.

[0044] The distribution unit generates output information for the designated unit based on the question items and transports the required ingredients to the assessment area. At this time, the trainees enter the assessment area and prepare to start cooking. The trainees begin cooking, and the cooking procedure standard data acquisition unit (sensor group, camera group) collects cooking operation data in real time.

[0045] The ingredient data acquisition unit records information such as the weight, color, and nutritional components of the ingredients. After cooking, the cooking analysis module receives information from the cooking technique acquisition module and performs analysis on the standardization of cooking operations and the quality of the dishes. The dish quality analysis unit analyzes and scores the dishes based on their appearance, color, and nutritional components, thereby outputting cooking assessment results and detailed reports. After the assessment, teachers and students can view the cooking assessment results and reports to understand the students' performance in terms of cooking operation standardization and dish quality, and thus conduct targeted teaching and training.

[0046] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

[0047] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0048] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0049] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature being directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0050] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. An intelligent cooking teaching system, characterized in that: It includes a cooking remote sensing self-starting module, a seasonal vegetable supply module, a cooking technique acquisition module, a cooking analysis module, and an evaluation and feedback module; The cooking remote sensing self-starting module and the seasonal vegetable supply module are interconnected to generate assessment information. The cooking technique acquisition module collects cooking-related parameters during the assessment. The cooking analysis module performs cooking analysis based on the relevant parameters. The evaluation feedback module obtains the cooking analysis information and outputs the cooking assessment score.

2. The intelligent cooking teaching system according to claim 1, characterized in that: The cooking technique data acquisition module includes a cooking step standard data acquisition unit, an ingredient data acquisition unit, and an environmental data acquisition unit. The cooking analysis module receives information from the cooking technique collection module, including the cooking operation standard analysis unit and the dish quality analysis unit. The evaluation feedback module obtains the output information from the cooking analysis module and outputs the cooking assessment results.

3. The intelligent cooking teaching system according to claim 1, characterized in that: The food remote sensing self-starting module includes a construction unit, a dish information database construction unit, and a question generation and formulation unit. The vegetable supply module includes a product supervision unit and a distribution unit. The product supervision unit uploads inventory information to the food remote sensing self-starting module, and the food remote sensing self-starting module generates assessment questions based on the inventory information.

4. The intelligent cooking teaching system according to claim 3, characterized in that: The building blocks include inputting assessment outlines based on curriculum standards and developing assessment criteria based on students' learning progress and ability levels. The recipe information database construction unit obtains information on the ingredients, cooking steps, key techniques, nutritional value, and other information of the recipes from the recipe database, which is then used as the basis for the evaluation of the recipes. The question generation unit randomly generates cooking assessment questions and requirements based on the recipe information database construction unit and the requirement construction unit. The cooking assessment questions and requirements include requirements for dish preparation, ingredient preparation, cooking time, seasoning dosage, knife skills, and dish color.

5. The intelligent cooking teaching system according to claim 3 or 4, characterized in that: The item monitoring unit includes statistics on the quantity and shelf life of ingredients, as well as replenishment reminders. After the distribution unit obtains the output information of the item generation unit, it transports the dishes to the assessment area.

6. The intelligent cooking teaching system according to claim 2, characterized in that: The cooking step standard data acquisition unit includes a sensor group and a camera group installed in the cooking area; the food data acquisition unit includes acquiring food weight, color, and nutritional composition analysis; and the environmental data acquisition unit acquires the temperature, humidity, and air quality of the cooking area. The cooking operation standard analysis unit acquires information from the cooking step standard data collection unit to analyze the cooking operation. The dish quality analysis unit analyzes the appearance, color, and nutritional components of the dish. The evaluation feedback module evaluates the cooking performance and generates a report based on the output information from the cooking operation standard analysis unit and the dish quality analysis unit.

7. An intelligent cooking teaching method, applied to the intelligent cooking teaching system according to any one of claims 1-6, characterized in that: Includes the following steps: S1: Teachers develop an assessment outline based on classroom learning and input it into the building unit. The cooking remote sensing self-starting module is used to generate assessment information. S2: After the trainees enter the assessment area, the assessment questions are generated by the question generation unit, and the cooking ingredients are delivered to the assessment area by the assigned unit. S3: After reading the assessment requirements, trainees cook dishes according to the requirements. During this process, the cooking technique collection module collects the trainees' cooking parameter information. S4: The cooking analysis module uses image recognition to analyze the parameters of the dishes, and at the same time analyzes the standardization of the cooking operation based on the cooking parameter information, and outputs the analysis results to the evaluation feedback module. S5: The assessment and feedback module evaluates and reports cooking assessment results based on student data; S6: Based on the cooking assessment results and reports, provide targeted instruction to address the students' shortcomings.

8. An integrated teaching workbench for intelligent cooking instruction, applied to the intelligent cooking teaching system according to any one of claims 1-6, characterized in that: It includes an integrated workbench, which is also equipped with a vegetable cutting station, a seasoning station, a stove, a sensor unit group, a camera unit group, and an environmental data detection unit group.

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