KR102063890B1 - Facial recognition type cafe system and method of providing service of threrof - Google Patents

Abstract

Face recognition type cafe system according to an embodiment of the present invention, the recognition unit for recognizing the face of the customer visiting the face recognition type cafe system; And manufacturing unit for manufacturing the order menu of the customer; And a control unit for controlling the recognition unit and the manufacturing unit, and if the customer is determined to be a regular customer of the face recognition cafe system.

Description

FACIAL RECOGNITION TYPE CAFE SYSTEM AND METHOD OF PROVIDING SERVICE OF THREROF}

The present invention relates to a facial recognition-type cafe system and a service providing method in the system, and more specifically, by recognizing the faces of customers who visit the cafe frequently, a facial that can provide customized services to regular customers unattended. A recognition cafe system and a service providing method in the system.

The customer who visited the cafe ordered the menu from the clerk and provided the service. The clerk can recognize whether the customer frequently visits the store and provide a customized service for the customer, thereby providing a differentiated service from other stores.

In general, there are various methods for determining whether a customer who visits a cafe frequently visits the store.

The clerk can remember the face of the visiting customer and recognize whether he visits the store frequently. However, it is not only difficult for the clerk to distinguish all the faces of the numerous customers who visit the store, but it is also impossible to accurately remember the number of visits. Furthermore, this method is only possible if the clerk resides.

You can also recognize whether you are a frequent visitor to your store by using earn or discount coupons. In this case, the clerk recognizes whether the customer frequently visits the store from the number of visits described in the accumulated or discounted coupon. However, according to this, there is a problem that the customer must have a coupon or a coupon is stored in the store, and the clerk must also be resident.

An object of the present invention is to provide a face-aware cafe system and a service providing method in the system that can provide customized services unattended to regular customers.

In addition, an object of the present invention is to provide a face-aware cafe system and a service providing method in the system that can provide customized services optimized for regular customers without time constraints on the store operating time.

Technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned above are clear to those skilled in the art to which the embodiments proposed by the following description belong. Can be understood.

Face recognition cafe system according to an embodiment of the present invention, the recognition unit for recognizing the face of the customer visiting the face recognition cafe system; And manufacturing unit for manufacturing the order menu of the customer; And a control unit for controlling the recognition unit and the manufacturing unit, and if the customer is determined to be a regular customer of the face recognition cafe system.

According to another aspect of the present invention, there is provided a method of providing a service in a face recognition cafe system, the method comprising: recognizing a face of a customer who has visited the face recognition cafe system; Manufacturing the order menu of the customer; And if it is determined that the customer is a regular customer of the face recognition cafe system, providing a service for the customer.

According to embodiments according to the present invention, while operating a store unattended, it is possible to provide customized services to regular customers.

In addition, according to embodiments of the present invention, it is possible to provide a customized service optimized for regular customers without time constraints on the store operating time.

1 is a view showing the appearance of a facial recognition cafe system according to an embodiment of the present invention.
2 is a block diagram showing the configuration of a facial recognition cafe system according to an embodiment of the present invention.
3A to 3C are diagrams for describing an example of recognizing a customer frequently visited by a facial recognition cafe system according to an exemplary embodiment of the present invention.
4 is a diagram illustrating an example of a service providing process in a face recognition cafe system according to an embodiment of the present invention.
5 is a diagram illustrating an example in which a face recognition cafe system receives an order for a service according to an embodiment of the present invention.
6 is a diagram illustrating another example in which a face-aware cafe system receives an order for a service according to an embodiment of the present invention.
FIG. 7 is a diagram illustrating another example in which a face recognition cafe system receives an order for a service according to an embodiment of the present invention.
8 is a diagram illustrating another example of a service providing process in a face recognition cafe system according to an embodiment of the present invention.
9 is a view illustrating a process of manufacturing a menu by a face recognition cafe system according to an embodiment of the present invention.
FIG. 10 is a diagram illustrating an example in which a face recognition cafe system manages a customer who frequently visits a store. Referring to FIG.

Hereinafter, specific embodiments of the present invention will be described in detail with reference to the drawings. However, the technical spirit of the present invention is not limited by the embodiments described below, and other embodiments included within the scope of other inventive inventions or the technical spirit of the present invention may be deteriorated by the addition, change, or deletion of other components. Examples can be easily suggested.

The terms used in the present invention were selected as general terms widely used in connection with the present technology as much as possible at present, but in some cases, the terms arbitrarily selected by the applicant are described, and in this case, the meanings are described in detail in the corresponding description of the present invention. Therefore, it should be noted that the present invention should be grasped as the meaning of a term rather than a simple name of the term. In the descriptions that follow, the word 'comprising' does not exclude the presence of other elements or steps than those listed.

1 is a view showing the appearance of a facial recognition cafe system according to an embodiment of the present invention.

Face recognition cafe system 100 according to an embodiment of the present invention may be configured in the form of a container. In this case, the facial recognition cafe system 100 may be installed in a predetermined space on the ground or inside the building, or may be configured to be separated and moved therefrom.

In detail, the facial recognition cafe system 100 may include an order desk 110, cameras 120a and 120b, a pickup desk 130, a call notification board 135, and an advertisement board 140.

Order desk 110 may receive an order for a service from a customer. Here, the order for the service may include a beverage type, a size, a personal preference for the beverage, and the like.

The order desk 110 may receive an order for a service in a voice or touch input form.

The cameras 120a and 120b may recognize a face of a customer.

In detail, the cameras 120a and 120b may photograph a face image of a customer who visits the face recognition cafe system 100, and recognize the face of the customer from the captured image by using image recognition technology. In this case, the cameras 120a and 120b may determine whether the customer who recognizes the face is a customer who frequently visits the cafe system 100. According to an embodiment, the image recognition technology may be a face recognition technology. The face recognition technique will be described later in detail with reference to FIG. 3C.

The cameras 120a and 120b may be disposed corresponding to the order desk 110 and the pickup desk 130, respectively. In this case, the cameras 120a and 120b may photograph the face of the customer who is waiting for the order or receipt order at the order desk 110 and the pickup desk 130.

The pickup desk 130 may deliver the order menu to the customer.

In detail, the pickup desk 130 may move or locate a menu ordered by a customer to the corresponding pickup desk 130.

In addition, the pickup desk 130 may recognize the face of the customer waiting to receive the menu, and deliver the order menu to the customer. To this end, the pickup desk 130 may be configured as a mobile desk. According to an embodiment, the pickup desk 130 may be an artificial intelligence robot.

The call notification board 135 may perform notification about receipt of the order menu. Specifically, the call notification board 135 may notify the receipt of the order menu by video or audio when the order menu of the customer is delivered to the pickup desk 130. To this end, the call notification panel 135 may include a display for displaying an image and / or a speaker for outputting a voice.

The billboard 140 may announce or advertise matters related to the operation of the facial recognition cafe system 100. Here, the matters related to the operation of the facial recognition cafe system 100, the order and preparation and receipt of the menu process, the advertisement for the newly launched menu or promotions, the customer about the frequent visits to the store or customized services, etc. It may include.

To this end, the billboard 140 may be configured as a display for displaying an image. According to an embodiment, the billboard 140 may be a digital shinage.

2 is a block diagram showing the configuration of a facial recognition cafe system according to an embodiment of the present invention.

The facial recognition cafe system 100 according to an embodiment of the present invention may recognize a face of a visited customer unattended and provide a customized service to the corresponding customer. In detail, the face-aware cafe system 100 may process and manage an order, manufacture, delivery, and delivery of a menu selected by a customer unattended, and may recognize a visited customer's face and provide a customized service to the customer.

To this end, the face recognition cafe system 100 may be configured to include a recognition unit 210, a user interface 220, a manufacturing unit 230, a moving unit 240 and the control unit 250.

The recognition unit 210 may recognize the face of the visitor.

In detail, the recognition unit 210 may recognize the customer's face based on the scanned image of the visited customer's face, and determine whether the customer frequently visits the store. To this end, the recognition unit 210 may include a camera or a scanner.

According to an embodiment of the present disclosure, the recognizer 210 may recognize at least one or more visited customers existing within a predetermined range. Here, the predetermined range may be within a predetermined radius from at least one of the order desk 110 and / or pickup desk 130.

Meanwhile, the facial recognition algorithm varies depending on whether the recognition unit 210 recognizes one visited customer or a plurality of visited customers, which will be described later with reference to FIGS. 3A and 3B. do.

The user interface 220 may receive an order for a service from a customer. To this end, the user interface 220 may be implemented in the form of a screen or a button. According to an embodiment, the user interface 220 may receive an order for a service selected by a customer on a mobile terminal or online.

The user interface unit 220 may inform the customer of items related to the order for the service. In detail, the user interface 220 may perform notification of an order processing process, manufacture of an order menu, receipt of an order menu, and the like.

The manufacturing unit 230 may manufacture a menu ordered by a customer.

Specifically, the manufacturing unit 230 may mix the raw materials of the menu ordered by the customer, and may reflect the preference taste of the corresponding customer. According to an embodiment, the manufacturing unit 230 may recognize whether the customer frequently visits the corresponding store to reflect the taste of the corresponding customer, or may reflect the preferred taste selected by the corresponding customer. To this end, the manufacturing unit 230 may be configured as a fully automatic mechanical manufacturing apparatus.

The moving unit 240 may move the order menu.

In detail, when the manufacturing unit 230 completes the manufacturing of the order menu, the moving unit 240 may transmit the manufactured corresponding order menu to the pickup desk 130.

In addition, when the order menu is manufactured through several machines, the moving unit 240 may sequentially move the order menu to the corresponding machines. For example, if a user needs to go through an espresso extractor, a steam milk injector, and an ice grinder in order to produce an ice latte ordered, they may be sequentially moved to the machines.

The controller 250 controls the operations of the recognition unit 210, the user interface 220, the manufacturing unit 230, and the moving unit 240 in order to control overall operations related to the operation of the face recognition cafe system 100. Can be controlled.

If it is determined that the customer frequently visits the facial recognition cafe system 100, the controller 250 may provide the customer with a service for a regular customer. According to an embodiment of the present disclosure, the service for the regular customer may be to inquire whether to apply the personal preference of the regular customer to the order menu. According to another embodiment of the present disclosure, the service for the regular customer may include at least one of price discount, point accumulation, point use, and size upgrade.

3A to 3C are diagrams for describing an example of recognizing a customer frequently visited by a facial recognition cafe system according to an exemplary embodiment of the present invention.

3A illustrates a case where the face recognition cafe system 100 recognizes one customer. The camera 120a attached to the order desk 110 may recognize a customer entering a predetermined radius. In this case, the camera 120a may capture a face image of the visited customer and compare it with an image record stored in the server 310, and determine whether the customer is a customer who frequently visits the store based on face recognition technology. . To this end, information such as the face image of the customer, the visit history of the customer, etc. photographed by the camera 120a may be managed in the form of a database in the server 310.

Referring to FIG. 3A, the camera 120a captures a face image of a customer waiting in front of the order desk 110. In this case, the camera 120a compares the captured image with images stored in the server 310 and determines whether the corresponding customer frequently visits the store based on face recognition technology.

3B illustrates a case where the face recognition cafe system 100 recognizes a plurality of customers. The camera 120a attached to the order desk 110 may recognize a plurality of customers entering a predetermined radius. In detail, the camera 120a may measure distances to a plurality of customers, respectively, and determine a customer located at the closest distance as a visited customer. In this case, the camera 120a may determine the remaining customers other than the visiting customer as the party of the visiting customer or another standby customer based on the distance between the plurality of customers. For example, a customer located within a predetermined distance from the visited customer may be determined as the party of the visited customer, and a customer located outside the predetermined distance may be determined as another waiting customer.

In addition, the camera 120a may recognize faces of a plurality of customers who have visited the store, and may recognize the frequency of visits, the number of visitors, and the information of their companions.

Referring to FIG. 3B, a plurality of customers M, N, O, P, and R exist in front of the order desk 110. In this case, the camera 120a recognizes only the faces of the plurality of customers M, N, and O present in the predetermined range.

The camera 120a measures the distance between each of the recognized customers M, N, and O and the distance between the customers M, N, and O. In the case of FIG. 3B, the customer N is located at the closest distance from the camera 120a, and the customer M and the customer O are located within a predetermined distance from the customer N. Accordingly, the camera 120a determines the customer N as the visited customer and the customer M and the customer O as the customer N's party.

3C illustrates an example of a regular customer management method using face recognition technology. The face recognition technology is a technology for establishing a database of existing face photographs, and checking and recognizing whether or not the person is identified by comparing the image taken by the camera. Face recognition technology has the advantage of being able to identify the user in a natural manner without the need for the user's special actions or actions.

The face recognition technique may be performed through two steps of a face detection process and a face recognition process.

The face detection process is a process of recognizing a position where a face exists in an image. The face of the person is shaped according to the direction of the face or side according to the direction of gaze, the degree of tilting the head from side to side, various expressions, the size of the face image according to the distance from the camera, and the brightness in the face due to the lighting. It can vary depending on external changes, such as differences in color, complex backgrounds, or other objects of indistinguishable color from faces. In the face detection process, a knowledge based method, a feature based method, a template matching method, or the like may be used. Here, the knowledge-based method is a method of detecting a face based on the researcher's knowledge on the premise that the human face includes eyebrows, nose, mouth, etc., and each facial component has a certain distance and position convention. . The feature-based method is a method of detecting a face using information on the size and shape of facial feature components, correlation, facial color and texture information, or a mixture of these elements. In addition, the template matching method is a method of detecting a face by making a standard template for all faces to be compared with the input image.

The face recognition process may be performed by a face recognition algorithm. The face recognition algorithm analyzes an image of a face to determine main components such as eyes, nose, ears, and mouth, and then extracts characteristics according to individual faces, and may include a 2D algorithm or a 3D algorithm. For example, individual facial features can be extracted according to values such as the distance between two eyes, the thickness of the nose, the height and shape of the cheekbones, and the ratio of the width and height of the forehead to the face.

The facial recognition cafe system 100 according to an embodiment of the present invention may manage a regular customer who frequently visits a store by using face recognition technology. In detail, the facial recognition cafe system 100 may recognize a face of a visiting customer and determine and manage a regular index for the corresponding customer. Referring to FIG. 3C, the regular index 320 for the customer may include the number of visits, the regular index, preference menus, coupons and services, and whether membership can be managed by the membership member.

4 is a diagram illustrating an example of a service providing process in a face recognition cafe system according to an embodiment of the present invention.

The user visits and purchases a drink (S401).

The user may visit the facial recognition cafe system 100 and purchase a beverage selected from the menu. In this case, the facial recognition cafe system 100 may recognize the visit of the customer by recognizing the user's face. Thereby, the face recognition cafe system 100 can accept a drink order unattended, even without the clerk's order acceptance.

Recognize the face of the user (S402).

In detail, the face recognition cafe system 100 may recognize a face of a user using face recognition technology. In this case, the face recognition cafe system 100 may compare the face image of the user photographed with the camera with the image stored in the server.

It is determined whether the visit frequency of the user exceeds N (S403).

The facial recognition cafe system 100 may determine whether the user frequently visits the corresponding store based on various factors such as the frequency of the visit of the user, the number of the cumulative purchase drinks, and the sum of the cumulative purchase prices. According to an embodiment of the present disclosure, if the visit frequency of the user exceeds N, it may be determined that the visited the store frequently.

If the visit frequency of the user exceeds N (S403-Yes), the face recognition cafe system 100 searches for the recorded user information (S404).

The facial recognition cafe system 100 applies the information corresponding to the visited user (S405). In detail, the facial recognition cafe system 100 may apply the menu order when the user frequently visits the store and the order history and personal preference of the user exist. For example, if it is determined that the user always adds syrup as a regular customer, the facial recognition cafe system 100 may recommend adding syrup when ordering the menu.

The facial recognition cafe system 100 manufactures a drink ordered by a user (S406).

When the beverage is manufactured, the facial recognition cafe system 100 may recognize whether the customer frequently visits the corresponding store to reflect the taste of the corresponding customer, or may reflect the preferred taste selected by the corresponding customer.

On the other hand, if it is determined in step S403 that the visit frequency of the user is N or less (S403-No), the facial recognition cafe system 100 determines that the user is not a regular customer of the store and manufactures a drink (S406).

The facial recognition cafe system 100 delivers the manufactured beverage to the pickup desk 130 (S407).

5 is a diagram illustrating an example in which a face recognition cafe system receives an order for a service according to an embodiment of the present invention.

The facial recognition cafe system 100 according to an exemplary embodiment may receive an order for a service from a visiting customer. To this end, the order desk 110 may include speakers 510a and 510b, an output display 520, and an input display 530.

The speakers 510a and 510b may receive an order for a service input in a voice form. Specifically, when the visiting customer waiting in front of the order desk 110 speaks the order menu, the speakers 510a and 510b may recognize the order menu through voice recognition.

The input display 530 may receive an order for a service input in the form of image information. In detail, when the visiting customer waiting in front of the order desk 110 selects an image for the order menu through the input display 530, the input display 530 may recognize the order menu corresponding to the selected image.

The output display 520 may display information related to the service provided by the facial recognition cafe system 100 in an image form. Here, the information related to the service may be information about a detailed menu, a menu price, an order processing process, a menu receipt, and the like.

According to an embodiment of the present disclosure, when the camera 120a of the order desk 110 photographs the front and recognizes that the customer has visited, the output display 520 may display information related to the service in the form of an image.

Referring to FIG. 5, when the customer approaches the front of the order desk 110, the camera 120a captures a front image to recognize that the customer has visited. The output display 520 displays information related to the service in the form of an image. In this case, the customer orders the service by voice through the speakers 510a and 510b or selects an image through the input display 530 to order the service.

6 is a diagram illustrating another example in which a face-aware cafe system receives an order for a service according to an embodiment of the present invention.

The facial recognition cafe system 100 according to an exemplary embodiment may receive an order for a service from a visiting customer. To this end, the order desk 110 may include speakers 510a and 510b, an output display 520, and an artificial intelligence robot 610. Meanwhile, since the speakers 510a and 510b and the output display 520 are similar to those described with reference to FIG. 5, the description thereof will be omitted below.

The artificial intelligence robot 610 may perform two-way communication with the visiting customer in connection with the order for the service.

In detail, when the artificial intelligence robot 610 recognizes that the customer has visited, the artificial intelligence robot 610 may output information related to the service in the form of voice through the speakers 510a and 510b or display the image in the form of an image on the output display 520. Here, the information related to the service may be information about a detailed menu, a menu price, an order processing process, a menu receipt, and the like.

The artificial intelligence robot 610 may respond to the visiting customer. For example, the artificial intelligence robot 610 may output a greeting when recognizing the approach of the customer, and may output a greeting including the name of the customer when it is determined that the customer visits frequently through facial recognition. In addition, when the regular customer orders a menu, the artificial intelligence robot 610 may determine the personal taste of the corresponding customer by referring to the customer data stored in the server, and may recommend or query the customer whether it is applied.

According to an embodiment of the present disclosure, when the artificial intelligence robot 610 recognizes that the camera 120a provided at the order desk 110 photographs the front visited by the customer, the artificial intelligence robot 610 may switch to the active state and start the operation. .

Referring to FIG. 6, when the customer approaches the front of the order desk 110, the camera 120a captures a front image to recognize that the customer has visited. The artificial intelligence robot 610 switches to an active state and responds to the visiting customer. In this case, the artificial intelligence robot 610 may guide the menu to the customer, answer the question from the customer, determine the personal taste of the regular customer, and ask the customer whether it is applied.

FIG. 7 is a diagram illustrating another example in which a face recognition cafe system receives an order for a service according to an embodiment of the present invention.

The facial recognition cafe system 100 according to an embodiment of the present invention may deliver an order menu to a visitor. To this end, the pickup desk 130 may include a menu pickup shelf 710.

The menu pickup shelf 710 may deliver the order menu to the visiting customer. In detail, the menu pickup shelf 710 may deliver the order menu to the customer when the order menu is manufactured and transported to the pickup desk 130. In this case, when the camera 120b included in the pickup desk 130 recognizes the customer who ordered the corresponding order menu through face recognition, the menu pickup shelf 710 may move to the recognized customer direction and deliver the order menu. .

The menu pickup shelf 710 may determine the number of customers and the density of customers that exist around the pickup desk 130, and may change the moving path and the moving speed of the order menu based on this.

According to one embodiment, the menu pickup shelf 710 may have a robot arm shape.

Referring to FIG. 7, the camera 120b provided in the pickup desk 130 recognizes the positions of customers who ordered the order menu by recognizing faces of waiting customers. In this case, the menu pick-up shelf 710 moves according to the set moving path and moving speed, and delivers the order menu to the recognized customer.

8 is a diagram illustrating another example of a service providing process in a face recognition cafe system according to an embodiment of the present invention.

The user visits and purchases a drink (S801).

The user may visit the facial recognition cafe system 100 and purchase a beverage selected from the menu. In this case, the facial recognition cafe system 100 may recognize the visit of the customer by recognizing the user's face. Thereby, the face recognition cafe system 100 can accept a drink order unattended, even without the clerk's order acceptance.

Recognize the face of the user (S802).

In detail, the face recognition cafe system 100 may recognize a face of a user using face recognition technology. In this case, the face recognition cafe system 100 may compare the face image of the user photographed with the camera with the image stored in the server.

It is determined whether the visit frequency of the user exceeds N (S803).

The facial recognition cafe system 100 may determine whether the user frequently visits the corresponding store based on various factors such as the frequency of the visit of the user, the number of the cumulative purchase drinks, and the sum of the cumulative purchase prices. According to an embodiment of the present disclosure, if the visit frequency of the user exceeds N, it may be determined that the visited the store frequently.

If the visit frequency of the user exceeds N (S803-Yes), the face recognition cafe system 100 searches for the recorded user information (S804).

The facial recognition cafe system 100 applies the information corresponding to the visited user (S805). In detail, the facial recognition cafe system 100 may apply the menu order when the user frequently visits the store and the order history and personal preference of the user exist. For example, if it is determined that the user always adds syrup as a regular customer, the facial recognition cafe system 100 may invite or query the customer whether or not to add syrup when ordering a menu.

The facial recognition cafe system 100 manufactures a drink ordered by a user (S806).

When the beverage is manufactured, the facial recognition cafe system 100 may recognize whether the customer frequently visits the corresponding store to reflect the taste of the corresponding customer, or may reflect the preferred taste selected by the corresponding customer.

On the other hand, if it is determined that the visit frequency of the user is less than N (S803-No) in step S803, the facial recognition cafe system 100 determines that the user is not a regular customer of the store and manufactures a drink (S806).

The facial recognition cafe system 100 recognizes the location of the user (S807).

Specifically, the facial recognition cafe system 100 may recognize the faces of the waiting customers, the location of the customer who ordered the menu. In this case, the facial recognition cafe system 100 may photograph facial images of waiting customers, and compare the facial images with facial recognition information or images that were taken or analyzed when ordering a menu.

The facial recognition cafe system 100 sets the movement direction (S808).

The facial recognition cafe system 100 may set a moving direction of the order menu based on the recognized user's location.

The facial recognition cafe system 100 delivers a drink to the user (S809).

In this case, the facial recognition cafe system 100 determines the location of the user and the number of customers and the density of customers around the pickup desk 130, and based on this, the movement path and the moving speed of the order menu are changed differently. Can be.

9 is a view illustrating a process of manufacturing a menu by a face recognition cafe system according to an embodiment of the present invention.

When receiving a menu order, the facial recognition cafe system 100 may manufacture a menu ordered by the customer. To this end, the face recognition cafe system 100 may include a cup holder 910, a beverage spray nozzle 921, 922, 923, 924, 925, an additive spray nozzle 930, and a packing unit 940. . In this case, the face recognition cafe system 100 is ordered through the cup holder 910, beverage spray nozzles 921, 922, 923, 924, 925, additive spray nozzle 930 and the packaging unit 940 sequentially The menu 950 can be completed.

The cup holder 910 may store a plurality of beverage containers for containing an order menu. Here, the beverage container may include a disposable paper cup or a plastic cup. The plurality of beverage containers may be arranged in a stacked form, and may be sequentially separated one by one in response to the receipt of the order.

The beverage spray nozzles 921, 922, 923, 924, 925 may hold each of the menus provided by the facial recognition cafe system 100. The beverage container separated from the cup holder 910 may move and stop for a predetermined time at the lower end of any one of the beverage spray nozzles 921, 922, 923, 924, and 925. In this case, the corresponding beverage spray nozzles 921, 922, 923, 924, and 925 may spray the beverage stored in the beverage container located at the bottom. The amount of the injection may vary depending on the size of the menu ordered by the customer.

The additive spray nozzle 930 may store additives that may be added to the menu. Here, the additive may be various kinds of powder or syrup that can be added to the menu. The beverage container moved from the beverage spray nozzles 921, 922, 923, 924, and 925 passes over the additive spray nozzle 930 or stops for a predetermined time at the bottom of the additive spray nozzle 930 according to the personal preference of the ordering customer. can do. In this case, the additive injection nozzle 930 may inject the additive stored in the beverage container located at the bottom. The additive injection amount may vary in response to the personal taste of the customer.

The packaging unit 940 may package a beverage container. In detail, when the beverage container moves from the additive injection nozzle 930 to reach the packaging unit 940, the packaging unit 940 may seal and package the beverage container.

Through this process, the order menu 950 may be completed and delivered to the order customer.

FIG. 10 is a diagram illustrating an example in which a face recognition cafe system manages a customer who frequently visits a store. Referring to FIG.

The face-aware cafe system according to an embodiment of the present invention recognizes a regular customer who frequently visits the store by recognizing the faces of the customers who have visited the store, and may display an advertisement for the regular customer on the billboard 140. have.

Here, the advertisement for the regular customer may include information such as a face image of the regular customer, a nickname, a point score and a rating, and a benefit provided.

Referring to FIG. 10, the billboard 140 displays photographic images and nicknames of regular customers.

Although the above description has been made based on the embodiments, these are merely examples and are not intended to limit the present invention. Those skilled in the art to which the present invention pertains are not illustrated above within the scope not departing from the essential characteristics of the present embodiments. It will be appreciated that various modifications and applications are possible. For example, each component specifically shown in the embodiment may be modified. And differences relating to such modifications and applications will have to be construed as being included in the scope of the invention defined in the appended claims.

100: facial recognition cafe system 110: order desk
120a, 120b: Camera 130: Pickup Desk
135: call notification board 140: billboard
210: recognition unit 220: user interface unit
230: manufacturing unit 240: moving unit
250: control unit 310: server
320: regular indicators for customers 510a, 510b: speakers
520: output display 530: input display
610: artificial intelligence robot 710: menu pickup shelf
910 cup holder
921, 922, 923, 924, 925: beverage spray nozzles
930: additive injection nozzle 940: packing part
950: Order Menu

Claims (12)

In the facial recognition cafe system,
A recognition unit for recognizing a face of a customer who visited the face recognition cafe system;
Manufacturing unit for manufacturing the order menu of the customer;
A menu pickup shelf configured in the form of a robot arm to deliver the order menu to the customer; And
And a controller which controls the recognition unit, the manufacturing unit, and the menu pickup shelf, and provides a service to the customer when the customer is determined to be a regular customer of the face recognition cafe system.
The service for the regular customer includes at least one of a price discount, point accumulation, point use, and size upgrade,
The control unit,
The menu pickup shelf is moved toward the customer to recognize the location of the customer and deliver the order menu to the customer, and the menu is based on the number of customers and the degree of customer density present around the pickup desk that picks up the order menu. A facial-aware café system that changes at least one of the travel path and travel speed of the pickup shelf. The method of claim 1,
Service for the regular customer,
The facial recognition cafe system further comprises querying or recommending whether or not to apply the personal preferences of the regular customer to the order menu. delete delete delete The method of claim 1,
The control unit,
Face recognition cafe system for activating the recognition unit when the customer enters a predetermined radius from the face recognition cafe system. The method of claim 1,
The control unit,
The face recognition cafe system for controlling the recognition unit to recognize the face of the customer located within a predetermined radius from the face recognition cafe system. The method of claim 1,
The control unit,
And a face recognition cafe system that controls the recognition unit to recognize the customer's face in consideration of at least one of a tilt, a front gaze, a face front angle, an expression, and a mouth movement. The method of claim 1,
The recognition unit,
Facial recognition cafe system implemented in the form of artificial intelligent robot. The method of claim 1,
The customer includes a plurality of customers,
The control unit,
The distance between the face-aware cafe system and each of the plurality of customers is measured to determine any one customer located at the closest distance as the visited customer, and the remaining customers except the visited customer among the plurality of customers are the visited customers. Face-aware cafe system judged by customers. The method of claim 1,
The control unit,
Face recognition cafe system that determines that the customer is a regular customer when the customer visited the face recognition cafe system more than a predetermined number of times. In the service providing method in the facial recognition cafe system,
Recognizing a face of a customer who visited the face recognition cafe system by a recognition unit;
A manufacturing unit manufacturing the order menu of the customer;
Delivering the order menu to the customer by a menu pickup shelf configured in the form of a robot arm; And
If the control unit determines that the customer is a regular customer of the face recognition cafe system includes providing a service for the customer to the customer,
The service for the regular customer includes at least one of a price discount, point accumulation, point use, and size upgrade,
The control unit moves the menu pick-up shelf toward the customer to recognize the location of the customer and deliver the order menu to the customer, based on the number of customers and the density of customers present around the pickup desk that picks up the order menu. And changing at least one of a moving path and a moving speed of the menu pickup shelf.

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