Image recognition-based menu pushing method and system

Abstract

The invention discloses an image recognition-based menu pushing method and system. The method comprises the following steps of: S1, acquiring image data of a dinner customer and carrying out face recognition on the acquired image data to recognize face feature data of the dinner customer; S2, matching the recognized face feature data of the dinner customer with records in a customer portrait analysis library and generating a corresponding personalized menu according to the matching result; S3, outputting and displaying the generated personalized menu through terminal equipment; S4, receiving an order placing payment request and entering step S5 after the payment succeeds; and S5, storing dining information of the dinner customer in the customer portrait analysis library so as to update thecustomer portrait analysis library. The device and system provided by the invention are capable of enhancing the service efficiency and accuracy of restaurant operators and effectively saving the catering service time.

Description

technical field [0001] The invention relates to the technical field of catering management, in particular to a method and system for pushing menus based on image recognition. Background technique [0002] The traditional way of ordering food is generally manual, that is, the waiter uses pen and paper to record the content of the customer's order. This traditional way of ordering food with pen and paper requires the service staff to go back and forth between the tables, pass the menu and record the customer's needs. menu, and finally transmit the order to the service desk and kitchen for preparation. [0003] With the popularization of mobile technology, people's pace of life is getting faster and faster, and the traditional manual way of ordering meals can no longer meet people's requirements for efficiency. Recently, the use of handheld devices to order food has appeared, which is similar to the traditional method, except that the paper orders are changed to be recorded by...

AI Technical Summary

Problems solved by technology

[0003] With the popularization of mobile technology, people's pace of life is getting faster and faster, and the traditional manual way of ordering meals can no longer meet people's requirements for efficiency

Recently, the use of handheld devices to order food has appeared, which is similar to the traditional method, except that the paper orders are changed to be recorded by handheld devices. The traditional and handheld device ordering methods need to be recorded by service personnel, plus manual preparation. Sequences are chaotic, understaffed or slow to serve during peak dining hours, resulting in dissatisfied customers due to long wait times

[0004] At the same time, when ordering dishes, due to the innovation of restaurants, people tend to face thicker and thicker menus. It is often necessary for users to browse a lot of menus to choose a dish that matches the diner's personal dietary information among a large number of dishes. The dishes that users do not need also increase the time and difficulty of meal selection for diners. In addition, when ordering, guests often need to spend a certain amount of time because they are in the middle of tangled choices, which further leads to work efficiency in the restaurant. However, in the existing catering system, there is no menu push system that can push accurate menus to different customers, so as to improve the service efficiency and quality of the restaurant, as well as improve the dining experience of the guests.

[0005] On the other hand, in the current catering field, products such as cameras, face recognition, and POS hardware devices are also used, but in the current catering field, the surveillance camera lens is still only used for monitoring. There are many access control identifications; catering POS hardware devices are only traditional catering services, which cannot combine user data to provide effective marketing solutions. At present, the above three are independent. Although they can help catering operations to a certain extent, they cannot be effective. Save time for catering services, and cannot provide effective marketing plans in real time, and obtain user data in real time for analysis to achieve the purpose of precise marketing

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