A catering service data processing system and method based on big data

Abstract

The present invention discloses a catering service data processing system and method based on big data, comprising: a public information collection module, a restaurant information database, a restaurant image scanning module, a motion track analysis module, a public data processing module and a dining information feedback module, wherein the seat distribution information of the restaurant and the walking stride data of the service personnel are collected to the restaurant information database through the public information collection module, the position of the service personnel and the vacant seats are monitored in real time through the restaurant image scanning module, and image data are obtained, and the service personnel's dish serving route is predicted through the motion track analysis module, and the stride parameter is added in the process of calculating the dish serving route, and the service personnel who currently serves the fastest dishes are analyzed and selected, and arranged to serve the dishes, and the service personnel's dish serving information is fed back to the customer in time through the dining information feedback module, thereby speeding up the dish serving speed, improving the customer's dining comfort, and realizing the public information exchange between the kitchen, service personnel and customers.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a catering service data processing system and method based on big data. Background Art

[0002] Public information is everywhere. Whether it is system operation or the management of large and small enterprises, public information is needed as a bridge. The dissemination of public information can help the system run normally and help enterprises coordinate and manage various departments. For a long time, the dissemination of public information has inherent problems: the information provided by the public data platform is delayed and updated in a timely manner. The normal management of the restaurant also requires the existence of public information. Good information communication is required between the service staff in the kitchen and dining area to serve the dishes in an orderly manner and speed up the serving speed. However, although information technology is developing rapidly, some small restaurants still serve in the traditional way, requiring service staff to go to the serving table to serve the dishes, and even when serving the dishes, the service staff still need to speak out to find the customers, and the customers will respond after hearing the voice, which not only affects the serving speed and leads to customer loss, but also increases the fatigue of the service staff and affects work efficiency. These are all due to the kitchen. This is caused by the untimely communication of public information with the service staff. Public information data is retrieved and collected through big data technology. Since the service staff are always active in the dining area, their location needs to be monitored in real time. The activity trajectories of the service staff at different locations, that is, the serving routes, are predicted based on the layout of the restaurant. The serving distance is analyzed. Since different people have different walking strides, a short distance does not mean that they will serve the dishes quickly. By retrieving the stride data of the restaurant service staff through big data technology as a weighted serving distance, more accurate analysis results can be obtained, information can be fed back in a timely manner, the fastest personnel can be arranged to serve the dishes, and the service staff information can be fed back to the customers, which is conducive to speeding up the serving of dishes. In addition, after the restaurant is full, it is timely to inquire whether the customers who placed items on the empty seats are willing to share the table, without the need for other customers to ask themselves, which improves the comfort of customers' dining and realizes the exchange of public information between the kitchen, service staff and customers.

[0003] Therefore, people need a catering service data processing system and method based on big data to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a catering service data processing system and method based on big data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: A catering service data processing system based on big data: the system comprises: a public information collection module, a restaurant information database, a restaurant image scanning module, an action trajectory analysis module, a public data processing module and a dining information feedback module;

[0006] The public information collection module collects the seat distribution information of the restaurant and the walking stride data of all service personnel when serving dishes, locates the restaurant's serving table, transmits the location information of the serving table and all seats and the walking stride data of the service personnel to the restaurant information database, stores the walking stride data of the service personnel, and updates the data when the restaurant recruits new employees. The restaurant information database transmits the received location information of the serving table and all seats to the restaurant image scanning module, which models the entire restaurant with the serving table as the center, monitors the activity location of the service personnel in real time, obtains restaurant images through monitoring, measures the vertical distance between the serving table and the nearest dining table based on the image data, transmits the service personnel's activity location information and the measured distance data to the motion trajectory analysis module, and monitors the seats in the restaurant at the same time, transmits the information on whether there are empty seats to the public data processing module, and builds the motion trajectory analysis module. A dining simulation environment is provided, and the action trajectory of the service personnel, that is, the route for serving dishes, is predicted according to the real-time position of the service personnel, and the walking stride data of the service personnel in the restaurant information database are retrieved, and the serving efficiency of all service personnel is analyzed according to the predicted serving route: on the basis of analyzing the serving distance, the walking stride parameters of each service personnel are used as weighted values, and the number of steps required for the service personnel to take from the current position to the serving table is predicted, and the predicted number of steps is transmitted to the public data processing module, and the public data processing module selects the service personnel who serve the fastest according to the predicted number of steps, and reminds them to serve dishes, and transmits the information of no empty seats to the dining information feedback module when the table is full, and the dining information feedback module inquires whether the customers who place items on the empty seats agree to share the table, and if they do not agree, reminds the later customers that there are no empty seats temporarily, and at the same time, the information of the service personnel is fed back to the seated customers, thereby improving the problem of untimely and delayed public information dissemination in the restaurant, and achieving the goal of timely public information exchange between the kitchen, service personnel and customers.

[0007] Furthermore, the public information collection module includes a seat layout collection unit, a serving table positioning unit, a restaurant seat fixing unit and a walking data collection unit. The seat layout collection unit is used to collect the seat distribution of the restaurant, the serving table positioning unit confirms the position of the serving table, the restaurant seat fixing unit confirms the position of the restaurant seat, and the walking data collection unit is used to collect the walking stride data of the restaurant service staff when serving dishes, and all the collected data are transmitted to the restaurant information database.

[0008] Furthermore, the restaurant image scanning module includes a restaurant modeling unit, a dynamic point monitoring unit, a static distance measurement unit and an empty seat monitoring unit. The restaurant modeling unit establishes a two-dimensional coordinate system with the serving table as the center, performs dimensionality reduction processing on the restaurant to make it on the same plane, and monitors the position of the service personnel in real time through the dynamic point monitoring unit to confirm their coordinates on the plane. The vertical distance between the table closest to the serving table and the serving table is measured through the static distance measurement unit. The empty seat monitoring unit monitors the restaurant in real time whether there are vacancies, transmits the vacancy information to the common data processing module, and transmits the distance and coordinate data to the motion trajectory analysis module; the motion trajectory analysis module includes a dining environment simulation unit, a motion trajectory prediction unit and a dish serving efficiency analysis unit. The dining environment simulation unit establishes a simulated dining environment, the motion trajectory prediction unit predicts the serving route of the service personnel based on their real-time position, and the dish serving efficiency analysis unit predicts the number of steps the service personnel need to take from the current position to the serving table based on the weighted dish serving distance.

[0009] Furthermore, the public data processing module includes a dish serving information reminder unit, a restaurant service terminal and a full seat information reminder unit. The dish serving information reminder unit is used to confirm the service staff who currently serves dishes the fastest and send information to the restaurant service terminal to remind him to go to the serving table to serve dishes. The full seat information reminder unit is used to retrieve monitoring information, and after the restaurant is full, the no vacant seat information is transmitted to the dining information feedback module; the dining information feedback module includes a table sharing willingness inquiry unit, a service information feedback unit and a dining staff terminal. After the restaurant is full, the table sharing willingness inquiry unit is used to inquire whether the customer who placed items on the empty seat is willing to share the table. If the customer agrees, the customer who has not yet sat down is seated; if the customer disagrees, the customer who has not yet sat down is reminded that the seat is full, and the service information feedback unit sends the service staff information to the dining staff terminal where the corresponding customer is located.

[0010] A method for processing catering service data based on big data: comprising the following steps:

[0011] S1: Collect the distribution data of the restaurant's seats and serving tables, as well as the walking stride data of the restaurant's service staff;

[0012] S2: Monitor the overall environment of the restaurant, obtain the location of the service staff in real time based on the image data, and measure the vertical distance between the dining table and the nearest table;

[0013] S3: Simulate the dining environment, monitor whether there are empty seats in the restaurant, predict the service routes of service staff based on their real-time locations, and analyze the service efficiency of all staff;

[0014] S4: Select the person with the highest efficiency in serving dishes and remind him to go to the serving table to serve dishes;

[0015] S5: When it is detected that there are no empty seats in the restaurant, the customer who has placed items on the empty seat is asked whether he or she is willing to share the table, and other customers are arranged to sit, and the service staff information is fed back to the corresponding customer.

[0016] Further, in step S1-S2: the seat layout collection unit is used to collect the seat distribution position of the restaurant, the table positioning unit is used to confirm the position of the table, and the walking data collection unit is used to collect the walking stride data set of the restaurant service staff as B={B1, B2, ..., B n}, transmit the stride data to the restaurant information database, and use the restaurant image scanning module to monitor the restaurant environment: obtain the image, and obtain the current location coordinate set of all idle service personnel based on the image data as (x, y) = {(x1, y1), (x2, y2), ..., (x n ,y n )}, where n represents the number of idle waiters in the restaurant. The vertical distance between the serving table and the nearest table is measured as d based on the image data. The position coordinates and distance data are transmitted to the motion trajectory analysis unit.

[0017] Further, in steps S3-S4: after confirming the specific location of the serving table, the restaurant modeling unit is used to establish a two-dimensional coordinate system with the serving table as the center, and the action trajectory analysis unit predicts the serving routes of the service personnel based on their location coordinates, and calculates the number of steps M that a random idle service personnel needs to walk from the current position to the serving table according to the following formula: i :

[0018] ,

[0019] Among them, x i ,y i Respectively represent the horizontal and vertical coordinates of the current location of the corresponding service personnel, B i represents the walking stride of the corresponding service personnel, and the number of steps required for all idle service personnel to walk is M={M1, M2, ..., M n}, if present , directly select The idle waiter corresponding to the coordinate with the smallest value goes to the serving table to serve the dishes; if there is no : Compare all the walking steps in the set M: if the number of steps is large, it means that the corresponding service personnel takes a long time to serve dishes at the table and serves dishes slowly; if the number of steps is small, it means that the corresponding service personnel takes a short time to serve dishes at the table and serves dishes quickly. The comparison result is transmitted to the serving efficiency analysis unit, and the serving efficiency analysis unit is used to screen out the service personnel who serves dishes the fastest and most efficiently. The number of walking steps of this service personnel is M min, use the dish serving reminder unit to remind them to go to the serving table to serve dishes, send the customer's location to the corresponding service personnel, and calculate the dish serving distance based on the predicted dish serving route according to the service personnel's real-time location and the vertical distance between the serving table and the nearest table. On this basis, add the walking stride parameters of different service personnel to obtain the final number of steps required for different personnel to reach the serving table. The purpose is to predict the serving speed and efficiency of the service personnel based on the number of steps, which improves the roughness of the traditional method of judging the serving speed based only on the distance to the serving table.

[0020] Furthermore, in step S5: the full seat reminder unit is used to retrieve the empty seat monitoring information, and when it is monitored that there are no empty seats in the restaurant, the full seat information is transmitted to the table sharing willingness inquiry unit, and the table sharing willingness inquiry unit is used to inquire whether the customers who have placed items on the empty seats are willing to share the table: if the customers agree, the customers who have not been seated are arranged to be seated; if the customers disagree, the customers who have not been seated are reminded that the seats are full and other customers are arranged to be seated, and the service staff information is fed back to the corresponding customers. After the restaurant is full, it is timely inquired whether the customers who have placed items on the empty seats are willing to share the table, without the need for other customers to ask themselves, thereby improving the customer's dining comfort. The timely feedback of information realizes public information exchange between the kitchen, service staff and customers.

[0021] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0022] 1. The present invention collects the seat distribution information of the restaurant and the walking stride data of all service personnel when serving dishes to the restaurant information database through the public information collection module, retrieves the data in the information database through the big data technology, and uses the restaurant image scanning module to monitor the restaurant in real time, mainly monitoring the real-time position and empty seat situation of the service personnel, and simulates the dining environment through the action trajectory analysis module, predicts the action trajectory of the service personnel according to their real-time position, that is, the route of serving dishes, retrieves the walking stride parameters of different service personnel, and obtains the final number of steps required for different personnel to the serving table, and predicts the serving speed and efficiency of the service personnel according to the number of steps, thereby improving the roughness of judging the serving speed only according to the distance to the serving table in the traditional method, arranging the service personnel who serves dishes the fastest at present to serve dishes at the serving table, thereby speeding up the serving rate; in addition, after the restaurant is full, it promptly inquires whether the customers who place items on the empty seats accept the shared table, without other customers asking by themselves, thereby improving the dining comfort of customers, and timely feeding back the service personnel information to the corresponding customers is conducive to realizing the public information exchange between the back kitchen, service personnel and customers. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0024] Figure 1 It is a system structure diagram of a catering service data processing system and method based on big data of the present invention;

[0025] Figure 2 It is a method step diagram of a catering service data processing system and method based on big data of the present invention;

[0026] Figure 3 It is a schematic diagram of restaurant environment simulation of the present invention. DETAILED DESCRIPTION

[0027] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0028] See also Figure 1-Figure 3 ,The present invention provides a technical solution: a catering service data processing system based on big data: the system includes: a public information collection module, a restaurant information database, a restaurant image scanning module, an action trajectory analysis module, a public data processing module and a dining information feedback module;

[0029] The public information collection module collects the seat distribution information of the restaurant and the walking stride data of all service personnel when serving dishes, locates the restaurant's serving table, and transmits the location information of the serving table and all seats and the walking stride data of the service personnel to the restaurant information database. The restaurant information database stores the walking stride data of the service personnel and updates the data when the restaurant recruits new employees. The restaurant information database transmits the received location information of the serving table and all seats to the restaurant image scanning module. The restaurant image scanning module models the entire restaurant with the serving table as the center, monitors the activity location of the service personnel in real time, obtains restaurant images through monitoring, measures the vertical distance between the serving table and the nearest dining table based on the image data, transmits the service personnel's activity location information and the measured distance data to the motion trajectory analysis module, and at the same time monitors the seats in the restaurant, transmits the information on whether there are empty seats to the public data processing module, and the motion trajectory analysis module establishes a dining model. In the virtual environment, the action trajectory of the service staff, that is, the route for serving dishes, is predicted according to their real-time position, and the walking stride data of the service staff in the restaurant information database is retrieved. The serving efficiency of all service staff is analyzed according to the predicted serving route: on the basis of analyzing the serving distance, the respective walking stride parameters are used as weighted values ​​to predict the number of steps the service staff needs to take from the current position to the serving table, and the predicted number of steps is transmitted to the public data processing module. The public data processing module selects the service staff who serves the fastest dishes according to the predicted number of steps and reminds them to serve dishes. When the restaurant is full, the information of no empty seats is transmitted to the dining information feedback module. The dining information feedback module inquires whether the customers who place items on the empty seats agree to share the table. If they do not agree, the later customers are reminded that there are no empty seats for the time being. At the same time, the information of the service personnel is fed back to the seated customers, which is convenient for improving the problem of untimely and delayed public information dissemination in restaurants and realizes the goal of timely public information exchange between the kitchen, service staff and customers.

[0030] The public information collection module includes a seat layout collection unit, a serving table positioning unit, a restaurant seat fixed point unit and a walking data collection unit. The seat layout collection unit collects the seat distribution of the restaurant, the serving table positioning unit confirms the position of the serving table, the restaurant seat fixed point unit confirms the position of the restaurant seat, and the walking data collection unit collects the walking stride data of the restaurant service staff when serving dishes, and all collected data are transmitted to the restaurant information database.

[0031] The restaurant image scanning module includes a restaurant modeling unit, a dynamic point monitoring unit, a static distance measurement unit and an empty seat monitoring unit. The restaurant modeling unit establishes a two-dimensional coordinate system with the serving table as the center, performs dimensionality reduction processing on the restaurant to make it on the same plane, monitors the position of the service staff in real time through the dynamic point monitoring unit to confirm their coordinates on the plane, measures the vertical distance between the table closest to the serving table and the serving table through the static distance measurement unit, monitors the restaurant in real time whether there are vacancies through the empty seat monitoring unit, transmits the vacancy information to the public data processing module, and transmits the distance and coordinate data to the motion trajectory analysis module; the motion trajectory analysis module includes a dining environment simulation unit, a motion trajectory prediction unit and a dish serving efficiency analysis unit. The dining environment simulation unit establishes a simulated dining environment, the motion trajectory prediction unit predicts the serving route of the service staff based on their real-time position, and the dish serving efficiency analysis unit predicts the number of steps the service staff needs to take from the current position to the serving table based on the weighted dish serving distance.

[0032] The public data processing module includes a dish serving information reminder unit, a restaurant service terminal and a full seat information reminder unit. The dish serving information reminder unit is used to confirm the service staff who currently serves dishes the fastest and send information to the restaurant service terminal to remind him to go to the serving table to serve dishes. The full seat information reminder unit is used to retrieve monitoring information, and after the restaurant is full, the no vacant seat information is transmitted to the dining information feedback module; the dining information feedback module includes a table sharing willingness inquiry unit, a service information feedback unit and a dining staff terminal. After the restaurant is full, the table sharing willingness inquiry unit is used to inquire whether the customer who places items on the empty seat is willing to share the table. If the customer agrees, the customer who has not yet sat down is seated; if the customer disagrees, the customer who has not yet sat down is reminded that the seat is full, and the service information feedback unit sends the service staff information to the dining staff terminal where the corresponding customer is located.

[0033] A method for processing catering service data based on big data: comprising the following steps:

[0034] S1: Collect the distribution data of the restaurant's seats and serving tables, as well as the walking stride data of the restaurant's service staff;

[0035] S2: Monitor the overall environment of the restaurant, obtain the location of the service staff in real time based on the image data, and measure the vertical distance between the dining table and the nearest table;

[0036] S3: Simulate the dining environment, monitor whether there are empty seats in the restaurant, predict the service routes of service staff based on their real-time locations, and analyze the service efficiency of all staff;

[0037] S4: Select the person with the highest efficiency in serving dishes and remind him to go to the serving table to serve dishes;

[0038] S5: When it is detected that there are no empty seats in the restaurant, the customer who has placed items on the empty seat is asked whether he or she is willing to share the table, and other customers are arranged to sit, and the service staff information is fed back to the corresponding customer.

[0039] In step S1-S2: the seat layout acquisition unit is used to collect the seat distribution position of the restaurant, the table positioning unit is used to confirm the position of the table, and the walking data acquisition unit is used to collect the walking stride data set of the restaurant service staff as B={B1, B2, ..., B n}, transmit the stride data to the restaurant information database, and use the restaurant image scanning module to monitor the restaurant environment: obtain the image, and obtain the current location coordinate set of all idle service personnel based on the image data as (x, y) = {(x1, y1), (x2, y2), ..., (x n ,y n )}, where n represents the number of idle waiters in the restaurant. The vertical distance between the serving table and the nearest table is measured as d based on the image data. The position coordinates and distance data are transmitted to the motion trajectory analysis unit.

[0040] In step S3-S4: after confirming the specific location of the serving table, the restaurant modeling unit is used to establish a two-dimensional coordinate system with the serving table as the center. The action trajectory analysis unit predicts the serving routes of the service personnel based on their location coordinates, and calculates the number of steps M that a random idle service personnel needs to walk from the current position to the serving table according to the following formula: i :

[0041] ,

[0042] Among them, x i ,y i Respectively represent the horizontal and vertical coordinates of the current location of the corresponding service personnel, B i represents the walking stride of the corresponding service personnel, and the number of steps required for all idle service personnel to walk is M={M1, M2, ..., M n}, if present , directly in Select the corresponding service personnel The idle waiter corresponding to the position coordinate with the smallest value goes to the serving table to serve the dishes; if there is no : Compare all the walking steps in the set M: if the number of steps is large, it means that the corresponding service staff takes a long time to serve dishes at the table and serves dishes slowly; if the number of steps is small, it means that the corresponding service staff takes a short time to serve dishes at the table and serves dishes quickly. The comparison result is transmitted to the serving efficiency analysis unit, and the serving efficiency analysis unit is used to screen out the service staff with the fastest and highest efficiency. The number of steps of this service staff is M min, use the dish serving reminder unit to remind them to go to the serving table to serve dishes, send the customer's location to the corresponding service personnel, and calculate the dish serving distance based on the predicted dish serving route according to the service personnel's real-time location and the vertical distance between the serving table and the nearest table. On this basis, add the walking stride parameters of different service personnel to obtain the final number of steps required for different personnel to reach the serving table. The purpose is to predict the serving speed and efficiency of the service personnel based on the number of steps, which can improve the roughness of the traditional method of judging the serving speed based only on the distance to the serving table.

[0043] In step S5: the full seat reminder unit is used to retrieve the empty seat monitoring information. When it is monitored that there are no empty seats in the restaurant, the full seat information is transmitted to the table sharing willingness inquiry unit. The table sharing willingness inquiry unit is used to inquire the customers who have placed items on the empty seats whether they are willing to share the table: if the customer agrees, the customers who have not been seated are arranged to be seated; if the customer disagrees, the customers who have not been seated are reminded that the seats are full and other customers are arranged to be seated, and the service staff information is fed back to the corresponding customers. After the restaurant is full, it is timely inquired whether the customers who have placed items on the empty seats are willing to share the table, without the need for other customers to ask by themselves, which is convenient for improving the dining comfort of customers. The timely feedback of information achieves the goal of timely public information exchange between the kitchen, service staff and customers.

[0044] Embodiment 1: Use the seat layout acquisition unit to collect the seat distribution position of the restaurant, use the table positioning unit to confirm the position of the table, use the walking data acquisition unit to collect the walking stride data set of the restaurant service staff as B={B1, B2, B3}={0.6, 0.7, 0.45}, the unit is: meter / step, transmit the stride data to the restaurant information database, and use the restaurant image scanning module to monitor the restaurant environment: obtain an image, and obtain the current location coordinate set of all service staff according to the image data as (x, y)={( x1, y1), (x2, y2), (x3, y3)}={(-10, -8), (12, -3), (5, -5)}, based on the image data, the vertical distance between the serving table and the nearest table is measured to be d=3 meters, and the position coordinates and distance data are transmitted to the motion trajectory analysis unit. After confirming the specific position of the serving table, the restaurant modeling unit is used to establish a two-dimensional coordinate system with the serving table as the center. The position coordinates of the serving table are (0, 0). The motion trajectory analysis unit predicts the respective serving routes based on the position coordinates of the service personnel. There is no :According to the formula The number of steps that all service personnel need to walk is obtained as M={M1, M2, M3}={26 steps, 18 steps, 17 steps}, , use the serving efficiency analysis unit to select the fastest and most efficient serving staff, the number of steps the serving staff walks is M min=M3=Step 17, using the dish serving reminder unit to remind service staff 3 to go to the serving table to serve dishes, and sending the customer location to service staff 3.

[0045] Finally, it should be noted that the above description is only a preferred example of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A catering service data processing method based on big data, characterized in that: The following steps are involved: S1: Collect the distribution data of the restaurant's seats and serving tables, as well as the walking stride data of the restaurant's service staff; S2: Monitor the overall environment of the restaurant, obtain the location of the service staff in real time based on the image data, and measure the vertical distance between the dining table and the nearest table; S3: Simulate the dining environment, monitor whether there are empty seats in the restaurant, predict the service routes of service staff based on their real-time locations, and analyze the service efficiency of all staff; S4: Select the person with the highest efficiency in serving dishes and remind him to go to the serving table to serve dishes; S5: When it is detected that there are no empty seats in the restaurant, the customer who has placed items on the empty seat is asked whether he or she is willing to share the table, and other customers are arranged to sit, and the service staff information is fed back to the corresponding customer; In step S1-S2: the seat layout acquisition unit is used to collect the seat distribution position of the restaurant, the table positioning unit is used to confirm the position of the table, and the walking data acquisition unit is used to collect the walking stride data set of the restaurant service staff as B={B1, B2, ..., B n }, transmit the stride data to the restaurant information database, and use the restaurant image scanning module to monitor the restaurant environment: obtain the image, and obtain the current location coordinate set of all idle service personnel based on the image data as (x, y) = {(x1, y1), (x2, y2), ..., (x n ,y n )}, where n represents the number of idle waiters in the restaurant. The vertical distance between the serving table and the nearest table is measured as d based on the image data, and the position coordinates and distance data are transmitted to the action trajectory analysis unit; In step S3-S4: after confirming the specific location of the serving table, the restaurant modeling unit is used to establish a two-dimensional coordinate system with the serving table as the center. The action trajectory analysis unit predicts the serving routes of the service personnel based on their location coordinates, and calculates the number of steps M that a random idle service personnel needs to walk from the current position to the serving table according to the following formula: i : ， Among them, x i ,y i Respectively represent the horizontal and vertical coordinates of the current location of the corresponding service personnel, B i represents the walking stride of the corresponding service personnel, and the number of steps required for all idle service personnel to walk is M={M1, M2, ..., M n }, if present , directly in Select the corresponding service personnel The idle waiter corresponding to the coordinate with the smallest value goes to the serving table to serve the dishes; if there is no : Compare all the walking steps in the set M: if the number of steps is large, it means that the corresponding service personnel takes a long time to serve dishes at the table and serves dishes slowly; if the number of steps is small, it means that the corresponding service personnel takes a short time to serve dishes at the table and serves dishes quickly. The comparison result is transmitted to the serving efficiency analysis unit, and the serving efficiency analysis unit is used to screen out the service personnel who serves dishes the fastest and most efficiently. The number of walking steps of this service personnel is M min , use the dish serving reminder unit to remind them to go to the serving table to serve dishes, and send the customer's location to the corresponding service personnel.

2. A method for processing catering service data based on big data according to claim 1, characterized in that: In step S5: the full seat reminder unit is used to retrieve the empty seat monitoring information. When it is monitored that there are no empty seats in the restaurant, the full seat information is transmitted to the table sharing willingness inquiry unit. The table sharing willingness inquiry unit is used to inquire customers who have placed items on the empty seats whether they are willing to share the table: if the customer agrees, the unseated customers are seated; if the customer disagrees, the unseated customers are reminded that the seats are full and other customers are seated, and the service staff information is fed back to the corresponding customers.

3. A catering service data processing system based on big data, applied to the catering service data processing method based on big data as claimed in claim 1, characterized in that: The system includes: a public information collection module, a restaurant information database, a restaurant image scanning module, a motion trajectory analysis module, a public data processing module and a dining information feedback module; The public information collection module collects the seat distribution information of the restaurant and the walking stride data of all service personnel when serving dishes, locates the position of the restaurant's serving table, and transmits the position information of the serving table and all seats and the walking stride data of the service personnel to the restaurant information database. The restaurant information database stores the walking stride data of the service personnel and updates the data when the restaurant recruits new employees. The restaurant information database transmits the received position information of the serving table and all seats to the restaurant image scanning module. The restaurant image scanning module models the entire restaurant with the serving table as the center, monitors the activity location of the service personnel in real time, obtains the restaurant image through monitoring, measures the vertical distance between the serving table and the nearest dining table based on the image data, transmits the service personnel's activity position information and the measured distance data to the action trajectory analysis module, and monitors the seats in the restaurant at the same time, and transmits the information on whether there are empty seats. The data is input into the public data processing module, the action trajectory analysis module establishes a dining simulation environment, predicts the action trajectory of the service personnel according to their real-time position, that is, the route for serving dishes, retrieves the walking stride data of the service personnel in the restaurant information database, and analyzes the serving efficiency of all service personnel according to the predicted serving route: on the basis of analyzing the serving distance, the respective walking stride parameters are used as weighted values ​​to predict the number of steps the service personnel need to take from the current position to the serving table, and the predicted number of steps is transmitted to the public data processing module, the public data processing module selects the service personnel who serve the dishes the fastest according to the predicted number of steps, reminds them to serve dishes, and transmits the no vacant seat information to the dining information feedback module when the table is full, the dining information feedback module inquires whether the customer who places items on the empty seat agrees to share the table, if not, reminds the later customers that there are no vacant seats for the time being, and at the same time feeds back the information of the service personnel for the seated customers.

4. A catering service data processing system based on big data according to claim 3, characterized in that: The public information collection module includes a seat layout collection unit, a serving table positioning unit, a restaurant seat fixed point unit and a walking data collection unit. The seat layout collection unit is used to collect the seat distribution of the restaurant. The serving table positioning unit confirms the position of the serving table. The restaurant seat fixed point unit confirms the position of the restaurant seat. The walking data collection unit collects the walking stride data of the restaurant service staff when serving dishes. All collected data are transmitted to the restaurant information database.

5. The catering service data processing system based on big data according to claim 3 is characterized by: The restaurant image scanning module includes a restaurant modeling unit, a dynamic point monitoring unit, a static distance measurement unit and an empty seat monitoring unit. The restaurant modeling unit establishes a two-dimensional coordinate system with the serving table as the center, performs dimensionality reduction processing on the restaurant to make it on the same plane, monitors the position of the service personnel in real time through the dynamic point monitoring unit to confirm their coordinates on the plane, measures the vertical distance between the table closest to the serving table and the serving table through the static distance measurement unit, monitors the restaurant in real time whether there are vacancies through the empty seat monitoring unit, transmits the vacancy information to the public data processing module, and transmits the distance and coordinate data to the motion trajectory analysis module; the motion trajectory analysis module includes a dining environment simulation unit, a motion trajectory prediction unit and a dish serving efficiency analysis unit. The dining environment simulation unit establishes a simulated dining environment, the motion trajectory prediction unit predicts the dish serving route of the service personnel based on their real-time position, and the dish serving efficiency analysis unit predicts the number of steps the service personnel need to take from the current position to the serving table based on the weighted dish serving distance.

6. The catering service data processing system based on big data according to claim 3 is characterized by: The public data processing module includes a dish serving information reminder unit, a restaurant service terminal and a full seat information reminder unit. The dish serving information reminder unit is used to confirm the service staff who currently serves dishes the fastest and send information to the restaurant service terminal to remind them to go to the serving table to serve dishes. The full seat information reminder unit is used to retrieve monitoring information, and after the restaurant is full, the no vacant seat information is transmitted to the dining information feedback module; the dining information feedback module includes a table sharing willingness inquiry unit, a service information feedback unit and a dining staff terminal. After the restaurant is full, the table sharing willingness inquiry unit is used to inquire whether the customers who place items on the empty seats are willing to share the table. If the customers agree, the customers who have not sat down are seated; if the customers disagree, the customers who have not sat down are reminded that the seats are full, and the service information feedback unit sends the service staff information to the dining staff terminal where the corresponding customers are located.

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