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CN115471281B - Big data platform analysis system based on dining service robot and its control method - Google Patents

Big data platform analysis system based on dining service robot and its control method Download PDF

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CN115471281B
CN115471281B CN202211316989.8A CN202211316989A CN115471281B CN 115471281 B CN115471281 B CN 115471281B CN 202211316989 A CN202211316989 A CN 202211316989A CN 115471281 B CN115471281 B CN 115471281B
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Abstract

本发明涉及一种基于用餐服务机器人的大数据平台分析系统及其控制方法，包括：与商家处理模块连接的餐饮后台模块、与餐饮后台模块连接的点餐数据模块、对话数据模块、过滤模块、筛选模块、提取模块、综合分析模块、菜品调整模块和话术调整模块；本发明的优点是：通过智能点餐机械人点餐产生点餐数据，客户通过语音与智能点餐机械人交互的时候也会产生大量的交流信息，通过对这些信息的分析，会反向对餐厅的运营产生一定的作用。

The present invention relates to a big data platform analysis system based on a dining service robot and a control method thereof, comprising: a dining service backend module connected to a merchant processing module, an ordering data module connected to the dining service backend module, a dialogue data module, a filtering module, a screening module, an extraction module, a comprehensive analysis module, a dish adjustment module and a speech adjustment module; the advantages of the present invention are: ordering data is generated by ordering through an intelligent ordering robot, and a large amount of communication information is also generated when customers interact with the intelligent ordering robot through voice, and the analysis of this information will have a certain effect on the operation of the restaurant in reverse.

Description

Big data platform analysis system based on dining service robot and control method thereof
Technical Field
The invention relates to the technical field of dining robots, in particular to a dining service robot-finished big data platform analysis system based on a dining table top and a control method thereof.
Background
With the progress and development of technology, robots are increasingly widely applied, the technology of the existing robots is very developed, the degree of intelligence is very high, and various robots with advanced technology play an important role in our lives and works.
In the prior art, the ordering robot placed on a dining table only has an ordering function and has single functions, and based on the problems, I develop a robot for dining table top to finish dining service, and Chinese patent publication No. 114997857A can realize intelligent ordering recommendation on the dining table. However, the above intelligent ordering recommendation method cannot realize comprehensive analysis of multiple dimensions on a big data platform, and a big data analysis system capable of realizing intelligent ordering is needed first.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a large data platform analysis system based on a dining service robot and a control method thereof, which are used for helping restaurants to timely adjust dishes provided by the dining service robot to meet the demands of clients, so as to overcome the defects of the prior art.
The invention provides a control method of a big data platform analysis system based on a dining service robot, which specifically comprises the following steps:
Step S1, comprehensively analyzing dish type, ingredients, taste and cooking modes of data of customer ordering by using a catering background module connected with a merchant processing module, and knowing the understanding of customers on the taste, ingredients and cooking methods of dishes provided by restaurants, wherein the specific data are the dish information of the customer ordering and the taste and cooking modes of remark instructions;
Step S2, extracting ordering data about clients and merchant dish information in the dining background module by utilizing an ordering data module connected with the dining background module, wherein the ordering data comprises the dish information ordered by the clients, the taste and cooking mode of remark instructions, and the default taste and cooking mode of the merchant dish information;
step S3, filtering voice interaction data about customers in a catering background module by utilizing a dialogue data module in combination with a filtering module, a screening module and an extracting module, extracting problem dialogue information about the operating range, characteristics and dishes of the restaurant by the customers and comprehensively analyzing the problem dialogue information, wherein moderate adjustment suggestions are provided for different dishes by combining time, weather changes, the operating range and the characteristics of the restaurant, and attention of the customers to the special dishes and recommended dishes of the restaurant and attention of taste and cooking modes of the dishes of the whole restaurant are known in time;
S4, adjusting the taste, ingredients and cooking modes of dishes in the dish adjusting module by utilizing the comprehensively analyzed results of the dish outlet mode, ingredients, taste and cooking modes so as to meet the demands of customers;
Step S5, analyzing interactive dialogue data by using a dialogue adjusting module according to the analysis result of the comprehensive analysis module, and then adjusting the characteristics of the customers concerned, the answering operation of the recommended problems and the display picture of the restaurant, so that the customers can understand the characteristics and the recommended information of the restaurant faster and better;
and S6, transmitting the adjustment result of the conversation adjustment module to the merchant processing module and the kitchen processing module for synchronous adjustment.
As the preference of the invention, the method also comprises the step S7 of dining scene selection;
Step S71, obtaining dining person information through a head camera and performing analysis, wherein the analysis data is one or more of the information of the number of people, the gender and the age group;
and step 72, the analysis data in the step 71 is sent to a server, and the server forms a preliminary ordering menu according to the business characteristics of the store and the preset characteristic recommended dishes of the store, wherein the business characteristics are dishes, chafing dish and barbecue, and the recommended dishes contain time order recommendation.
Step 73, guiding a customer to order and recording the preference and taste of the customer aiming at the dishes ordered by the customer according to the preliminary recommended menu formed in the step 72, wherein the order is the characteristic of recommending the store, the present recommendation and the present recommendation, and the taste is slightly spicy and slightly light;
and S74, according to the ordering categories and the quantity of the clients and the dining person information acquired in the step S71, proposing the dishes ordered by the clients, wherein the more meat dishes are proposing auxiliary green dishes, and the more women and children recommend desserts.
The invention further aims to provide a big data platform analysis system based on the dining service robot, which comprises a dining background module connected with a merchant processing module, a food ordering data module connected with the dining background module, a dialogue data module, a filtering module, a screening module, an extraction module, a comprehensive analysis module, a dish adjustment module and a speaking adjustment module;
the catering background module is used for extracting data information stored in the client module, the merchant processing module, the robot processing module and the kitchen processing module;
the ordering data module is used for storing ordering data of clients and dish information of merchants, wherein the ordering data comprises the dish information of the clients and the taste and cooking mode of remark instructions, and the default taste and cooking mode of the dish information of the merchants;
The dialogue data module is used for collecting data of voice interaction between a client and the robot processing module, wherein the collecting stage is divided into a meal ordering time period, a meal consumption time period and a postprandial time period;
the filtering module is used for filtering out unnecessary information;
the screening module is used for extracting keywords prepared by merchants, wherein the keywords are question dialogue information related to the operating range, the characteristics and the dishes of the restaurant;
the extraction module is used for extracting necessary information, wherein the extracted information is classified;
the comprehensive analysis module is used for comprehensively analyzing the data of the meal ordering data module and the data of the extraction module, wherein moderate adjustment suggestions are provided for different dishes by combining time, weather changes and restaurant operation ranges and characteristics;
The dish adjusting module is used for adjusting the taste, ingredients and cooking modes of dishes according to the adjusting advice so as to meet the requirements of customers;
The speaking and operation adjusting module is used for adjusting the characteristics of the restaurant concerned by the client, the answering and operation of the recommended problem and the display picture according to the analysis result of the comprehensive analysis module, so that the client can understand the characteristics and the recommended information of the restaurant faster and better.
The invention has the advantages and positive effects that:
1. according to the intelligent ordering recommendation big data platform, ordering data are generated through the intelligent ordering robot, a large amount of communication information is generated when a client interacts with the intelligent ordering robot through voice, and a certain effect is generated on the operation of a restaurant in a reverse direction through analysis of the information.
2. The intelligent ordering recommendation big data platform disclosed by the invention comprehensively analyzes the plurality of dimensions of dishes, ingredients, tastes, cooking modes and the like of the data (including the dish information of the ordering of the clients, the tastes of remarks, the cooking modes and the like) of the ordering of the clients, so that the understanding and acceptance of the clients on the tastes, ingredients and cooking methods of the dishes provided by the dining room are known.
3. According to the intelligent ordering recommendation big data platform, through filtering data of voice interaction between a client and an intelligent ordering robot, problem dialogue information about the operating range, characteristics and dishes of a restaurant is extracted from the data, comprehensive analysis is performed on the problem dialogue information, and attention of the client to the characteristics dishes and recommended dishes of the restaurant, and attention of the client to taste and cooking modes of the dishes of the whole restaurant are known in time.
4. According to the invention, through comprehensive analysis of data, moderate adjustment suggestions (such as tastes, ingredients and cooking modes) are provided for different dishes by combining time, weather changes and restaurant operation ranges and characteristics, so that the restaurant is helped to timely adjust the dishes provided by the restaurant to meet the demands of clients, the ordering amount of the clients is increased, and the income is increased.
5. According to the invention, through analysis of interactive dialogue data, the restaurant is helped to adjust answering operation and display pictures of problems such as characteristics, recommendation and the like which are concerned by the client, so that the client can understand the characteristics and recommendation information of the restaurant more quickly and better, and the ordering experience of the client is enhanced.
Drawings
Other objects and attainments together with a more complete understanding of the invention will become apparent and appreciated by referring to the following description taken in conjunction with the accompanying drawings. In the drawings:
FIG. 1 is a block flow diagram of an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be evident, however, that such embodiment(s) may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to facilitate describing one or more embodiments.
Example 1
Fig. 1 shows a schematic overall structure according to an embodiment of the present invention.
As shown in fig. 1, the control method of the big data platform analysis system based on the dining service robot provided by the embodiment of the invention specifically comprises the following steps:
Step S1, comprehensively analyzing dish type, ingredients, taste and cooking modes of data of customer ordering by using a catering background module connected with a merchant processing module, and knowing the understanding of customers on the taste, ingredients and cooking methods of dishes provided by restaurants, wherein the specific data are the dish information of the customer ordering and the taste and cooking modes of remark instructions;
Step S2, extracting ordering data about clients and merchant dish information in the dining background module by utilizing an ordering data module connected with the dining background module, wherein the ordering data comprises the dish information ordered by the clients, the taste and cooking mode of remark instructions, and the default taste and cooking mode of the merchant dish information;
step S3, filtering voice interaction data about customers in a catering background module by utilizing a dialogue data module in combination with a filtering module, a screening module and an extracting module, extracting problem dialogue information about the operating range, characteristics and dishes of the restaurant by the customers and comprehensively analyzing the problem dialogue information, wherein moderate adjustment suggestions are provided for different dishes by combining time, weather changes, the operating range and the characteristics of the restaurant, and attention of the customers to the special dishes and recommended dishes of the restaurant and attention of taste and cooking modes of the dishes of the whole restaurant are known in time;
S4, adjusting the taste, ingredients and cooking modes of dishes in the dish adjusting module by utilizing the comprehensively analyzed results of the dish outlet mode, ingredients, taste and cooking modes so as to meet the demands of customers;
Step S5, analyzing interactive dialogue data by using a dialogue adjusting module according to the analysis result of the comprehensive analysis module, and then adjusting the characteristics of the customers concerned, the answering operation of the recommended problems and the display picture of the restaurant, so that the customers can understand the characteristics and the recommended information of the restaurant faster and better;
and S6, transmitting the adjustment result of the conversation adjustment module to the merchant processing module and the kitchen processing module for synchronous adjustment.
Example 2
The dining scene selection in the embodiment comprises the following steps of;
Step S71, obtaining dining person information through a head camera and performing analysis, wherein the analysis data is one or more of the information of the number of people, the gender and the age group;
and step 72, the analysis data in the step 71 is sent to a server, and the server forms a preliminary ordering menu according to the business characteristics of the store and the preset characteristic recommended dishes of the store, wherein the business characteristics are dishes, chafing dish and barbecue, and the recommended dishes contain time order recommendation.
Step 73, guiding a customer to order and recording the preference and taste of the customer aiming at the dishes ordered by the customer according to the preliminary recommended menu formed in the step 72, wherein the order is the characteristic of recommending the store, the present recommendation and the present recommendation, and the taste is slightly spicy and slightly light;
and S74, according to the ordering categories and the quantity of the clients and the dining person information acquired in the step S71, proposing the dishes ordered by the clients, wherein the more meat dishes are proposing auxiliary green dishes, and the more women and children recommend desserts.
Example 3
The embodiment provides a big data platform analysis system based on a dining service robot, which comprises a dining background module connected with a merchant processing module, a food ordering data module connected with the dining background module, a dialogue data module, a filtering module, a screening module, an extraction module, a comprehensive analysis module, a dish adjustment module and a speaking operation adjustment module;
the catering background module is used for extracting data information stored in the client module, the merchant processing module, the robot processing module and the kitchen processing module;
the ordering data module is used for storing ordering data of clients and dish information of merchants, wherein the ordering data comprises the dish information of the clients and the taste and cooking mode of remark instructions, and the default taste and cooking mode of the dish information of the merchants;
The dialogue data module is used for collecting data of voice interaction between a client and the robot processing module, wherein the collecting stage is divided into a meal ordering time period, a meal consumption time period and a postprandial time period;
the filtering module is used for filtering out unnecessary information;
the screening module is used for extracting keywords prepared by merchants, wherein the keywords are question dialogue information related to the operating range, the characteristics and the dishes of the restaurant;
the extraction module is used for extracting necessary information, wherein the extracted information is classified;
the comprehensive analysis module is used for comprehensively analyzing the data of the meal ordering data module and the data of the extraction module, wherein moderate adjustment suggestions are provided for different dishes by combining time, weather changes and restaurant operation ranges and characteristics;
The dish adjusting module is used for adjusting the taste, ingredients and cooking modes of dishes according to the adjusting advice so as to meet the requirements of customers;
The speaking and operation adjusting module is used for adjusting the characteristics of the restaurant concerned by the client, the answering and operation of the recommended problem and the display picture according to the analysis result of the comprehensive analysis module, so that the client can understand the characteristics and the recommended information of the restaurant faster and better.
The foregoing is merely illustrative embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think about variations or substitutions within the technical scope of the present invention, and the invention should be covered. Therefore, the protection scope of the invention is subject to the protection scope of the claims.

Claims (3)

1.一种基于用餐服务机器人的大数据平台分析系统的控制方法，其特征在于，包括以下步骤：1. A control method for a big data platform analysis system based on a dining service robot, characterized in that it comprises the following steps: 步骤S1：利用与商家处理模块连接的餐饮后台模块对客户点餐的数据进行菜式、配料、口味及烹饪方式进行综合分析，了解客户对餐厅提供的菜品的口味、配料及烹饪方法的理解，其中，具体数据为客户点餐的菜品信息以及备注说明的口味及烹饪方式；Step S1: using the catering backend module connected to the merchant processing module to comprehensively analyze the dishes, ingredients, taste and cooking methods of the customer's order data to understand the customer's understanding of the taste, ingredients and cooking methods of the dishes provided by the restaurant, wherein the specific data is the dish information ordered by the customer and the taste and cooking method described in the remarks; 步骤S2：利用与餐饮后台模块连接的点餐数据模块提取餐饮后台模块内关于客户点餐的数据、商家菜品信息，其中点餐数据包含客户点餐的菜品信息以及备注说明的口味及烹饪方式，以及商家菜品信息的默认口味及烹饪方式；Step S2: using the order data module connected to the catering backend module to extract the data about the customer's order and the merchant's dish information in the catering backend module, wherein the order data includes the dish information ordered by the customer and the flavor and cooking method of the remarks, as well as the default flavor and cooking method of the merchant's dish information; 步骤S3：利用对话数据模块配合过滤模块、筛选模块和提取模块对餐饮后台模块中关于客户的语音交互数据进行过滤，提取其中客户对餐厅的经营范围、特色及菜品相关的问题对话信息并进行综合分析，其中，分析方式为结合时令、天气变化及餐厅经营范围与特色针对不同的菜品提出适度的调整建议，及时了解客户对餐厅的特色菜品、推荐菜品的关注度，以及餐厅整体的菜品的口味、烹饪方式的关注；Step S3: Filter the voice interaction data of customers in the catering backend module by using the dialogue data module in conjunction with the filtering module, the screening module and the extraction module, extract the dialogue information of customers on the business scope, characteristics and dishes of the restaurant and conduct a comprehensive analysis, wherein the analysis method is to make appropriate adjustment suggestions for different dishes in combination with the season, weather changes and the business scope and characteristics of the restaurant, and timely understand the customers' attention to the restaurant's special dishes, recommended dishes, and the overall taste and cooking methods of the restaurant's dishes; 步骤S4：利用综合分析的出菜式、配料、口味及烹饪方式的结果，调整菜品调整模块内菜品的口味、配料、烹饪方式，以满足客户的需求；Step S4: using the results of the comprehensive analysis of the dish style, ingredients, taste and cooking method, adjusting the taste, ingredients and cooking method of the dish in the dish adjustment module to meet the needs of the customer; 步骤S5：利用话术调整模块根据综合分析模块分析后的结果，对交互对话数据进行分析后将餐厅调整客户关心的特色、推荐问题的解答话术以及展示图片，让客户更快更好的理解餐厅的特色及推荐信息；Step S5: Utilizing the speech adjustment module to analyze the interactive dialogue data based on the results of the comprehensive analysis module, the restaurant adjusts the features that customers care about, the answering speech of the recommended questions, and the display pictures, so that customers can understand the restaurant's features and recommended information faster and better; 步骤S6：将话术调整模块的调整结果传输给商家处理模块和厨房处理模块进行同步调整。Step S6: The adjustment results of the speech adjustment module are transmitted to the merchant processing module and the kitchen processing module for synchronous adjustment. 2.根据权利要求1所述的一种基于用餐服务机器人的大数据平台分析系统的控制方法，其特征在于，还包括步骤S7：就餐场景选择；2. The control method of the big data platform analysis system based on the dining service robot according to claim 1, characterized in that it also includes step S7: dining scene selection; 步骤S71：通过头部摄像头获取就餐人信息并执行分析，其中，分析数据为：人数、性别、年龄段信息中的一个或者多个；Step S71: obtaining diners' information through the head camera and performing analysis, wherein the analysis data is: one or more of the number of people, gender, and age group information; 步骤S72：将步骤S71的分析数据发送给服务端，服务端根据门店的经营特色结合门店预定的特色推荐菜品形成初步点餐菜谱，其中，经营特色为菜系、火锅、烧烤；推荐菜品含时令推荐；Step S72: Send the analysis data of step S71 to the server, and the server forms a preliminary ordering menu based on the store's business characteristics and the store's scheduled special recommended dishes, where the business characteristics are cuisine, hot pot, and barbecue; the recommended dishes include seasonal recommendations; 步骤S73：根据步骤S72形成的初步推荐菜谱，引导客户点餐并针对客户所点菜品记录客户的偏好、口味，其中，点餐为推荐本店特色、今日推荐、时令推荐，口味为微辣、略淡；Step S73: Based on the preliminary recommended menu formed in step S72, guide the customer to order and record the customer's preferences and tastes for the dishes ordered by the customer, wherein the order is recommended for the restaurant's specialties, today's recommendations, seasonal recommendations, and the taste is slightly spicy or slightly light; 步骤S74：根据客户点餐品类和数量，结合步骤S71中取得的就餐人信息，对客户所点菜品提出建议，其中，肉菜偏多是建议辅助青菜，女士、儿童偏多推荐甜品。Step S74: Based on the type and quantity of the customer's order and the diners' information obtained in step S71, suggestions are made for the dishes ordered by the customer. For meat dishes, green vegetables are recommended as a side dish, and desserts are recommended for ladies and children. 3.一种基于用餐服务机器人的大数据平台分析系统，其特征在于，包括：与商家处理模块连接的餐饮后台模块、与餐饮后台模块连接的点餐数据模块、对话数据模块、过滤模块、筛选模块、提取模块、综合分析模块、菜品调整模块和话术调整模块；3. A big data platform analysis system based on a dining service robot, characterized in that it includes: a dining background module connected to a merchant processing module, an ordering data module connected to the dining background module, a conversation data module, a filtering module, a screening module, an extraction module, a comprehensive analysis module, a dish adjustment module, and a speech adjustment module; 所述餐饮后台模块用于提取客户端模块、商家处理模块、机器人处理模块、以及厨房处理模块内储存的数据信息；The catering backend module is used to extract data information stored in the client module, the merchant processing module, the robot processing module, and the kitchen processing module; 所述点餐数据模块用于储存客户点餐的数据、商家菜品信息，其中点餐数据包含客户点餐的菜品信息以及备注说明的口味及烹饪方式，以及商家菜品信息的默认口味及烹饪方式；The ordering data module is used to store customer ordering data and merchant dish information, wherein the ordering data includes the dish information ordered by the customer and the flavor and cooking method of the notes, as well as the default flavor and cooking method of the merchant dish information; 所述对话数据模块用于通过对客户与机器人处理模块的语音交互的数据进行收集，其中收集阶段分为点餐时间段、用餐时间段、餐后时间段；The dialogue data module is used to collect data on the voice interaction between the customer and the robot processing module, wherein the collection phase is divided into the ordering time period, the dining time period, and the post-meal time period; 所述过滤模块用于过滤出非必要信息；The filtering module is used to filter out unnecessary information; 所述筛选模块用于提炼出与商家准备的关键词，其中，关键词为餐厅的经营范围、特色及菜品相关的问题对话信息；The screening module is used to extract keywords prepared by the merchant, wherein the keywords are question dialogue information related to the restaurant's business scope, characteristics and dishes; 所述提取模块用于将必要信息提取，其中，将提取信息进行分类；The extraction module is used to extract necessary information, wherein the extracted information is classified; 所述综合分析模块用于对点餐数据模块和提取模块的数据进行综合分析，其中，结合时令、天气变化及餐厅经营范围与特色针对不同的菜品提出适度的调整建议；The comprehensive analysis module is used to conduct a comprehensive analysis on the data from the ordering data module and the extraction module, wherein appropriate adjustment suggestions are made for different dishes in combination with seasonal and weather changes and the business scope and characteristics of the restaurant; 所述菜品调整模块用于根据调整建议调整菜品的口味、配料、烹饪方式，以满足客户的需求；The dish adjustment module is used to adjust the taste, ingredients, and cooking methods of the dishes according to the adjustment suggestions to meet the needs of customers; 所述话术调整模块用于根据综合分析模块分析后的结果，对交互对话数据进行分析后将餐厅调整客户关心的特色、推荐问题的解答话术以及展示图片，让客户更快更好的理解餐厅的特色及推荐信息。The wording adjustment module is used to adjust the restaurant's features that customers care about, answer wording for recommended questions, and display pictures after analyzing the interactive dialogue data based on the results of the comprehensive analysis module, so that customers can understand the restaurant's features and recommended information faster and better.
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