Cooking method based on image recognition and temperature sensing

Abstract

The invention discloses a cooking method based on image recognition and temperature sensing. The cooking method comprises the following steps: S1, collecting image information and temperature information of a current cooking behavior; S2, processing the image information and the temperature information, recognizing the current cooking behavior according to the processing result, and calculating the target temperature of cooking of the next stage by recognizing the current cooking behavior; S3, adjusting the fire power of the cooking equipment according to the target temperature to cook the next stage; S4, repeating the steps S1 to S3 until the last cooking stage; and S5, inspecting the dishes in the last cooking stage through image recognition. The firepower of the next stage can be accurately controlled, the cooking quality of each stage is guaranteed, the cooking experience of a user is improved, and the quality of discharged dishes is guaranteed. The invention is applied to the technical field of cooking.

Description

technical field [0001] The invention relates to the technical field of cooking, in particular to a cooking method based on image recognition and temperature induction. Background technique [0002] At present, there are more and more kitchen appliances with Ai smart cooking function. Many Ai smart cooking algorithms on the market basically use two-dimensional parameters of temperature and time for algorithm calculation. [0003] In the prior art, due to the single reference value of the Ai intelligent cooking algorithm, there are many sources of interference in parameters such as temperature, which are generally affected by factors such as the environment, cooking utensil materials, and food weight. At the same time, because most of the intelligent cooking algorithms use solidified programs, in the case of human interference, it is easy to cause program errors and program failures, which eventually lead to poor cooking experience for users and poor quality of cooked dishes. ...

AI Technical Summary

Problems solved by technology

[0003] In the existing technology, due to the single reference value of the Ai intelligent cooking algorithm, there are many sources of interference in the parameters of the temperature, which are generally affected by factors such as the environment, cooker material, and food weight.

At the same time, because most of the intelligent cooking algorithms use solidified programs, in the case of human interference, it is easy to cause program errors and program failures, which will eventually lead to poor cooking experience for users and poor quality of cooked dishes.

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