Research On Air Fryer Control System For Intelligent Recommended Cooking Mode

Air fryers are favored by people for their oil-free,healthier and easy-to-clean features.In the context of a fast-paced society,many young people want to enjoy delicious and healthy food,but have little cooking experience and the current air fryer cannot meet their needs.To this end,this paper studies an air fryer control system for intelligently recommending cooking modes,which realizes the user’s control of the air fryer through wireless communication technology,and the intelligent recommendation of cooking modes.The main research contents of this paper are as follows:(1)Aiming at the situation that the intelligent control degree of air fryers is low,this paper designs the control system of air fryers.The system is composed of air fryer controller,cloud server and mobile client.Air fryer controller to achieve data interaction with the cloud server;Cloud server to achieve the mobile client and air fryer controller data interaction and storage functions;Mobile client to achieve information upload and user interaction and other functions.In this paper,the above functions are tested by building a system test platform.The test results show that the system can realize the data interaction between the air fryer controller,the cloud server and the mobile client,and the desired effect was achieved.(2)In view of the situation that the current air fryer can not provide users with an intelligent cooking mode,this paper studies the method of intelligent recommended cooking mode based on the air fryer control system.Based on convolutional neural network and K-means clustering algorithm,this paper studies the intelligent recommendation method of air fryer cooking mode.Firstly,the food data,cooking model data and user rating data in the database were converted into number list to get the data set suitable for training.Then,the convolutional neural network model was built and the data set was trained.After the training,the scores of all foods under all cooking modes were obtained.Finally,appropriate cooking patterns are automatically recommended based on the food uploaded by users.In addition,for the new food uploaded by users,the K-means clustering algorithm is used to make cluster analysis between it and the old food,and the old food with high similarity is found for intelligent recommendation.The simulation results show that the proposed method can realize the intelligent recommendation of air fryer cooking mode.In summary,the control system designed in this paper realizes the intelligent interaction between the user and the air fryer,reduce the cumbersome operation of the user when using the air fryer,and intelligently recommend the appropriate cooking mode for the food cooked,which greatly improves the user’s use.experience.