Using method of bionic control core equipment suitable for business hall

Abstract

The invention discloses a use method of bionic control core equipment suitable for a business hall. The use method comprises the following steps: step 1, collecting behavior data of a customer; 2, analyzing the behavior data of the customer, and extracting feature information of the customer; 3, constructing a feature and service strategy association model, inputting the feature information of the customer into the association model, and outputting a service strategy by the association model; and step 4, serving the customer according to the service strategy. By collecting and analyzing the behavior data of the customer, the demand and the preference of the customer can be known more deeply, and the personalized service strategy is output according to the demand and the preference, so that the service better meets the actual demand of the customer, and the satisfaction degree and the experience of the customer are improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a method for using a bionic control core device suitable for use in a business hall. Background Art

[0002] With the continuous development of science and technology, unmanned or less-staffed power supply business halls have become a new trend in the power supply industry. However, there are some problems with unmanned or less-staffed power supply business halls, such as the lack of manual service. Customers may not get timely and effective help when they encounter complex problems, resulting in a poor experience; the services of unmanned or less-staffed power supply business halls are often relatively standardized, making it difficult to provide flexible services based on customers' personalized needs. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art that the services of unmanned or sparsely staffed power supply business halls are relatively standardized and the customer experience is poor, and to provide a method for using a bionic control core device suitable for use in business halls.

[0004] The purpose of the present invention is achieved through the following technical solutions: The method for using the bionic control core device suitable for use in a business hall includes the following steps: Step 1: Collect customer behavior data; Step 2: Analyze the customer's behavior data and extract the customer's characteristic information; Step 3: construct a feature and service strategy association model, input the customer's feature information into the association model, and the association model outputs the service strategy; Step 4: Provide services to customers according to the service strategy.

[0005] Preferably, in the step 1, the customer's behavior data collected includes the customer's portrait-related information and the customer's interaction information.

[0006] Preferably, the method for obtaining the client's portrait-related information is: The collection includes customer image and video data, and cameras or camera arrays are deployed in the business hall to monitor and photograph customers in real time; Collect the interaction records between customers and business processing equipment in the business hall, and record the customer's access information and usage habits through the interaction records.

[0007] Preferably, in step 2, the customer's behavior data is analyzed to extract the customer's characteristic information, specifically: Use the face recognition model to process and analyze the customer images and video data obtained by the camera, identify the customer's face, and judge the customer's age and gender based on the face; The face recognition model is trained through deep learning algorithms to improve the accuracy and robustness of face recognition.

[0008] Preferably, the face recognition model is trained by a deep learning algorithm, specifically: Collect a large amount of image and video data containing human faces. The image and video data contain faces of different ages, genders, races, and expressions. Preprocess the image and video data, including cropping, scaling, and normalization, to ensure data consistency for the input face recognition model; The preprocessed image and video data are divided into a training set and a validation set. The convolutional neural network is used as the deep learning model architecture, and the model is trained using the training set data. The model learns to extract useful features from the input face images. During the training process, the validation set is used to evaluate the performance of the model, and the model parameters are adjusted to improve the performance of the model. The trained model is deployed in the bionic control core equipment of the business hall for face recognition.

[0009] Preferably, in step 3, the method for constructing the feature and service strategy association model is: dividing the customers into different groups through cluster analysis based on their feature information, and each group has a corresponding service strategy.

[0010] Preferably, the method of dividing the customers into different groups by clustering analysis based on their characteristic information is as follows: The characteristic information of customers includes age, gender, visit frequency, and type of business handled, and the characteristic information is normalized; customers are clustered using the K-means clustering algorithm, which divides them into different clusters based on the similarities between customers, and each cluster represents a group.

[0011] Preferably, the step 4 is specifically as follows: Customers are guided to designated areas through voice or video, and the corresponding business processing equipment is operated. The business processing equipment prioritizes the business modules that customers are most likely to visit, and adjusts the environmental data of the business hall, including lighting, background music and temperature.

[0012] The beneficial effect of the present invention is that by collecting and analyzing customer behavior data, the present invention can have a deeper understanding of customer needs and preferences, output personalized service strategies based on the needs and preferences, make the service more in line with the actual needs of the customer, and thus improve customer satisfaction and experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0014] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0015] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0016] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0017] Example: The method of using the bionic control core equipment used in business halls, such as Figure 1 As shown, the following steps are included: Step 1: Collect customer behavior data; Step 2: Analyze the customer's behavior data and extract the customer's characteristic information; Step 3: construct a feature and service strategy association model, input the customer's feature information into the association model, and the association model outputs the service strategy; Step 4: Provide services to customers according to the service strategy.

[0018] In the step 1, the customer's behavior data is collected including the customer's portrait-related information and the customer's interaction information.

[0019] The method for obtaining the client's portrait-related information is as follows: The collection includes customer image and video data, and cameras or camera arrays are deployed in the business hall to monitor and photograph customers in real time; Collect the interaction records between customers and business processing equipment in the business hall, and record the customer's access information and usage habits through the interaction records.

[0020] In step 2, the customer's behavior data is analyzed to extract the customer's characteristic information, specifically: the customer's image and video data acquired by the camera are processed and analyzed using a face recognition model to identify the customer's face, and the customer's age and gender are determined based on the face; The face recognition model is trained through deep learning algorithms to improve the accuracy and robustness of face recognition.

[0021] The face recognition model is trained by deep learning algorithm, specifically: Collect a large amount of image and video data containing human faces. The image and video data contain faces of different ages, genders, races, and expressions. Preprocess the image and video data, including cropping, scaling, and normalization, to ensure data consistency for the input face recognition model; The preprocessed image and video data are divided into a training set and a validation set. The convolutional neural network is used as the deep learning model architecture, and the model is trained using the training set data. The model learns to extract useful features from the input face images. During the training process, the validation set is used to evaluate the performance of the model, and the model parameters are adjusted to improve the performance of the model. The trained model is deployed in the bionic control core equipment of the business hall for face recognition.

[0022] In step 3, the method for constructing the feature and service strategy association model is: dividing the customers into different groups through cluster analysis based on their feature information, and each group has a corresponding service strategy.

[0023] The method of dividing customers into different groups by clustering analysis based on their characteristic information is as follows: The characteristic information of customers includes age, gender, visit frequency, and type of business handled, and the characteristic information is normalized; customers are clustered using the K-means clustering algorithm, which divides them into different clusters based on the similarities between customers, and each cluster represents a group.

[0024] The step 4 is specifically as follows: Customers are guided to designated areas through voice or video, and the corresponding business processing equipment is operated. The business processing equipment prioritizes the business modules that customers are most likely to visit, and adjusts the environmental data of the business hall, including lighting, background music and temperature.

[0025] In this embodiment, the bionic control core equipment of the unmanned or low-manned power supply business hall includes a camera arrangement array, an analysis control center and control equipment. The control equipment includes a virtual greeter, intelligent self-service facilities, lighting control, temperature and humidity control and a remote background.

[0026] Specifically, the bionic control core device has the following capabilities: It has the ability to interact with the face recognition device. It can obtain the customer's age range, gender, business familiarity and other information provided by the face recognition device. Research equipment design and develop interfaces for interacting with the face recognition device to obtain the customer's age range, gender, business familiarity and other information. Using existing face recognition technology, design interface protocols and data transmission formats to achieve data interaction with the face recognition device. Network communication technology, such as TCP / IP protocol, can be used to communicate data with the face recognition device through a network connection. At the same time, combined with artificial intelligence technology, the acquired face data is analyzed and processed to extract customer feature information.

[0027] Have the ability to interact with the virtual person in the business hall. Be able to obtain information such as customer business needs and customer activity areas provided by the virtual person. Develop an interface for interacting with the virtual person in the business hall to obtain information such as customer business needs and activity areas. Research and design the virtual person interaction interface to realize data transmission and communication between the virtual person and the control core equipment. Speech recognition and natural language processing technology can be used to realize the recognition and understanding of customer voice input. Collect customer needs and feedback information through the virtual person's voice output and dialogue interaction.

[0028] Control lighting and display equipment by classification and zoning. Design intelligent control algorithms to achieve zoning and classification control of lighting and display equipment in different areas of the business hall. Then, conduct a spatial analysis of the business hall to determine the functions and uses of different areas. Combine customer behavior and needs to design a classification control strategy for lighting and display equipment, and make intelligent adjustments based on the customer's location and behavior characteristics. Sensor data and customer behavior models can be used to monitor the customer's location and activities in real time, and control lighting and display equipment based on algorithm strategies.

[0029] Speech device output interface. Design the speech device output interface to realize the speech output and interaction functions for customers. Develop speech synthesis technology to realize the speech conversion and output of text content. Design the speech interaction interface to realize the speech guidance and response to customers. Speech recognition and synthesis technology can be used in combination with natural language processing algorithms to realize the recognition and processing of customer voice input, as well as speech output and interaction with customers.

[0030] The bionic control core device also adjusts the temperature and humidity in the business hall in a timely manner based on the recognition of the person's gender, age, the number of people in the business hall, and environmental parameters. The temperature can be adjusted through air conditioning, and the humidity can be adjusted through a humidifier.

[0031] Furthermore, in this embodiment, the customer's residence time and frequency in a certain area are considered as one of the parameters to cluster the customers, so as to improve the accuracy of clustering. The business hall area is divided into coarse-grained and fine-grained rectangular areas, and the areas are modeled and marked using digital technology. Data such as the customer's residence time and activity frequency in different areas are collected, and the monitoring equipment in the business hall is used to monitor the customer's residence time in different areas in real time. Combined with the business processing system, the customer's business processing process and accuracy are recorded. A correlation model between the customer's residence time and the accuracy of business processing is established to analyze the customer's familiarity. According to the analysis results, the service measures are adjusted to provide personalized service guidance and support for customers with different familiarity levels.

[0032] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0033] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for using a bionic control core device suitable for use in a business hall, characterized in that: The following steps are involved: Step 1: Collect customer behavior data; Step 2: Analyze the customer's behavior data and extract the customer's characteristic information; Step 3: construct a feature and service strategy association model, input the customer's feature information into the association model, and the association model outputs the service strategy; Step 4: Provide services to customers according to the service strategy.

2. The method for using the bionic control core device suitable for use in a business hall according to claim 1 is characterized in that: In the step 1, the customer's behavior data is collected including the customer's portrait-related information and the customer's interaction information.

3. The method for using the bionic control core device suitable for use in a business hall according to claim 2 is characterized in that: The method for obtaining the client's portrait-related information is as follows: The collection includes customer image and video data, and cameras or camera arrays are deployed in the business hall to monitor and photograph customers in real time; Collect the interaction records between customers and business processing equipment in the business hall, and record the customer's access information and usage habits through the interaction records.

4. The method for using the bionic control core device suitable for use in a business hall according to claim 3 is characterized in that: In step 2, the customer's behavior data is analyzed to extract the customer's characteristic information, specifically: Use the face recognition model to process and analyze the customer images and video data obtained by the camera, identify the customer's face, and judge the customer's age and gender based on the face; The face recognition model is trained through deep learning algorithms to improve the accuracy and robustness of face recognition.

5. The method for using the bionic control core device suitable for use in a business hall according to claim 4 is characterized in that: The face recognition model is trained by deep learning algorithm, specifically: Collect a large amount of image and video data containing human faces. The image and video data contain faces of different ages, genders, races, and expressions. Preprocess the image and video data, including cropping, scaling, and normalization, to ensure data consistency for the input face recognition model; The preprocessed image and video data are divided into a training set and a validation set. The convolutional neural network is used as the deep learning model architecture. The model is trained using the training set data. The model learns to extract useful features from the input face image. During the training process, the validation set is used to evaluate the performance of the model and the model parameters are adjusted to improve the performance of the model; The trained model is deployed in the bionic control core equipment of the business hall for face recognition.

6. The method for using the bionic control core device suitable for use in a business hall according to claim 1, characterized in that: In step 3, the method for constructing the feature and service strategy association model is: dividing the customers into different groups through cluster analysis based on their feature information, and each group has a corresponding service strategy.

7. The method for using the bionic control core device suitable for use in a business hall according to claim 6 is characterized in that: The method of dividing customers into different groups by clustering analysis based on their characteristic information is as follows: The customer's characteristic information includes age, gender, access frequency, and type of business, and the characteristic information is normalized; Customers are clustered using the K-means clustering algorithm, which divides customers into different clusters based on their similarities, and each cluster represents a group.

8. The method for using the bionic control core device suitable for use in a business hall according to claim 1 is characterized in that: The step 4 is specifically as follows: Customers are guided to designated areas through voice or video, and the corresponding business processing equipment is operated. The business processing equipment prioritizes the business modules that customers are most likely to visit, and adjusts the environmental data of the business hall, including lighting, background music and temperature.

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