Recommendation method and device of pension service products, equipment and storage medium

Abstract

The invention belongs to the technical field of artificial intelligence, and discloses an old-age service product recommendation method and device, equipment and a storage medium, and the method comprises the steps: receiving client house data, constructing a virtual old-age service space according to the client house data, and marking a high-risk region in the virtual old-age service space; receiving an interaction instruction, demonstrating a virtual risk scene in a high-risk area of the virtual pension space according to the interaction instruction, collecting behavior actions of a user during demonstration of the virtual risk scene, and generating a first interest value according to the behavior actions; recording and calculating a second interest value according to the residence time and the access frequency of the user in each high-risk area in the virtual pension space; based on each high-risk area, performing weighted summation on the first interest value and the second interest value to obtain a target interest value, determining a target recommended product according to the target interest value, and recommending the target old-age service product to the user; the method can be applied to an implementation scene of product recommendation in the financial field, and the customer conversion rate is improved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence, and in particular to a method, apparatus, device, and storage medium for recommending elderly care service products. Background Art

[0002] In the current booming insurance industry, elderly care services are a key business segment, and their promotion and explanation effectiveness are directly related to sales performance and customer conversion rate. Effective promotion and explanation can help customers deeply understand the product features and advantages, thereby stimulating their purchase intention and increasing market share.

[0003] The traditional insurance showroom operation model occupies a dominant position in the promotion of elderly care service products. This model mainly relies on customers' in-store experience. After the customers arrive at the store, the salesperson introduces the products to the customers with traditional display methods such as pictures and videos.

[0004] However, for the elderly customer group, due to the limitations of their physical functions and mobility, they face the problem of inconvenient transportation when going to offline exhibition halls. For the young customer group, their daily work and life rhythm are tight, and their leisure time is obviously fragmented. Both groups have difficulties in offline experience, resulting in a low success rate for sales staff to invite such customers. Even if customers have difficulty in customer service and go to the store for experience, the disadvantages of traditional display methods are also very prominent. Only through single information presentation methods such as pictures and videos, it is impossible to simulate the real use scenarios of insurance and elderly care service equipment. It is difficult for customers to intuitively feel the effects and advantages of the products in actual applications, which in turn limits the improvement of customer conversion rate.

[0005] To sum up, the customer conversion rate of existing elderly care service products is low. Summary of the Invention

[0006] The purpose of the embodiments of this application is to propose a recommendation method, device, equipment and storage medium for elderly care service products. Its main purpose is to improve the customer conversion rate of elderly care service products by simulating real insurance elderly care service equipment usage scenarios online.

[0007] First, in order to solve the above technical problems, the present application provides a method for recommending elderly care service products, which adopts the following technical solutions:

[0008] Receive customer housing data uploaded by users, build a virtual elderly care space based on the customer housing data, and mark high-risk areas in the virtual elderly care space;

[0009] receiving an interaction instruction initiated by the user, demonstrating a virtual risk scenario in the high-risk area of ​​the virtual elderly care space according to the interaction instruction, collecting the user's behavior during the demonstration of the virtual risk scenario, and generating a first interest value based on the behavior;

[0010] Recording the user's residence time and visit frequency in each high-risk area in the virtual elderly care space, and calculating a second interest value based on the residence time and visit frequency;

[0011] Based on each of the high-risk areas, the first interest value and the second interest value are weightedly summed to obtain a target interest value, a target recommended product is determined according to the target interest value, and the target elderly care service product is recommended to the user.

[0012] Secondly, in order to solve the above technical problems, the embodiments of the present application further provide a device for recommending elderly care service products, which adopts the following technical solutions:

[0013] A space construction module is used to receive customer housing data uploaded by users, construct a virtual elderly care space based on the customer housing data, and mark high-risk areas in the virtual elderly care space;

[0014] a first interest value calculation module, configured to receive an interaction instruction initiated by the user, demonstrate a virtual risk scenario in the high-risk area of ​​the virtual elderly care space according to the interaction instruction, collect the user's behavior during the demonstration of the virtual risk scenario, and generate a first interest value based on the behavior;

[0015] A second interest value calculation module is used to record the user's residence time and visit frequency in each high-risk area in the virtual elderly care space, and calculate a second interest value based on the residence time and visit frequency;

[0016] A product recommendation module is used to perform weighted summation of the first interest value and the second interest value based on each high-risk area to obtain a target interest value, determine a target recommended product according to the target interest value, and recommend the target elderly care service product to the user.

[0017] On the third aspect, in order to solve the above-mentioned technical problems, an embodiment of the present application also provides a computer device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for recommending elderly care service products as described above.

[0018] Fourthly, in order to solve the above technical problems, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for recommending elderly care service products as described above.

[0019] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0020] By receiving customer housing data uploaded by users, a personalized virtual elderly care space can be built based on each customer's specific housing situation, ensuring a high degree of consistency between the virtual elderly care space and the actual house, thereby improving the customer conversion rate of elderly care service products. Using customer housing data to build virtual elderly care spaces enables fast and accurate space modeling, improving the conversion efficiency of elderly care service products. By marking high-risk areas in the virtual elderly care space, users can pay more attention to the potential risks in high-risk areas, thereby improving the customer conversion rate of elderly care service products.

[0021] By receiving interactive instructions initiated by users, the system can accurately respond to user needs and demonstrate corresponding virtual risk scenarios in high-risk areas of the virtual elderly care space, improving the targeted interaction and thus also meeting the personalized needs of customers. During the virtual risk scenario demonstration, the user's behavior actions are collected and the first interest value is calculated based on the behavior actions. The system can accurately obtain user behavior actions and calculate the user's first interest value in each high-risk area based on the behavior actions. Subsequently, accurate recommendations are made based on the first interest value, thereby improving the customer conversion rate of elderly care service products;

[0022] By recording the user's residence time and visit frequency in each high-risk area in the virtual elderly care space, a second interest value is calculated based on the residence time and visit frequency, and accurate recommendations are subsequently made based on the second interest value, thereby improving the customer conversion rate of elderly care service products;

[0023] By taking the weighted sum of the first interest value and the second interest value to obtain the target interest value, product recommendations are made based on the target interest value, which can accurately match user needs and improve customer conversion rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the solutions in this application, a brief introduction will be given below to the drawings required for use in the description of the embodiments of this application. Obviously, the drawings described below are some embodiments of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0025] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0026] Figure 2 A flowchart of an embodiment of a method for recommending elderly care service products according to the present application;

[0027] Figure 3 is a structural diagram of an embodiment of a recommendation device for elderly care service products according to the present application;

[0028] Figure 4 It is a structural diagram of an embodiment of a device according to the present application. DETAILED DESCRIPTION

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which this application belongs. The terms used in the specification of the application are for the purpose of describing specific embodiments only and are not intended to limit this application. The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0030] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0031] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0032] like Figure 1 As shown, system architecture 100 may include a terminal device 101, a network 102, and a server 103. Terminal device 101 may be a laptop computer 1011, a tablet computer 1012, or a mobile phone 1013. Network 102 is a medium for providing a communication link between terminal device 101 and server 103. Network 102 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0033] The user can use the terminal device 101 to interact with the server 103 via the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0034] The terminal device 101 can be various electronic devices with a display screen and supporting web browsing. In addition to the laptop computer 1011, tablet computer 1012 or mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer and a desktop computer, etc.

[0035] The server 103 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal device 101 .

[0036] It should be noted that the method for recommending elderly care service products provided in the embodiments of the present application is generally executed by a server / terminal device, and accordingly, the device for recommending elderly care service products is generally set in the server / terminal device.

[0037] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0038] Continue to refer Figure 2 , shows a flowchart of an embodiment of a method for recommending elderly care service products according to the present application. Depending on different needs, the order of the steps in the flowchart can be changed, and some steps can be omitted. The method for recommending elderly care service products provided in the embodiment of the present application can be applied to any scenario where product recommendation scripts need to be generated, and the method for recommending elderly care service products can be applied to products in these scenarios. The method for recommending elderly care service products includes the following steps:

[0039] Step S201: Receive customer housing data uploaded by a user, construct a virtual elderly care space based on the customer housing data, and mark high-risk areas in the virtual elderly care space.

[0040] In this embodiment, the recommendation method for elderly care service products is executed on the electronic device (eg Figure 1The server / terminal device shown in the figure) can obtain the customer's premises data through a wired connection or a wireless connection. It should be noted that the above-mentioned wireless connection method may include but is not limited to 3G / 4G / 5G connection, Wi-Fi connection, Bluetooth connection, Wi MAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future.

[0041] In this embodiment, the real estate registration system is accessed through an API or a user-uploaded file is received, for example, customer house data uploaded by the user through an application (APP), a web upload port, or a specific hardware device (such as a smart scanner), wherein the customer house data includes a CAD drawing of the house, a floor plan (with detailed marking of the location, size, door and window locations of each room, etc.), three-dimensional structural information (such as floor height, etc.), and furniture placement data (such as furniture type, size, location, etc.); a virtual elderly care space is constructed based on the customer house data uploaded by the user, and high-risk areas are marked in the virtual elderly care space; the above-mentioned virtual elderly care space refers to a virtual 3D space constructed with the help of digital technology that can simulate a real elderly care living environment and has specific interactive functions, and users and sales staff can interact and simulate scenes in the virtual elderly care space; the above-mentioned high-risk areas refer to areas where accidents are prone to occur in customers' daily lives. For example, the elderly are prone to slipping in the bathroom, resulting in injuries to their hands, and the bathroom is a high-risk area.

[0042] In an implementable example A, the user clicks the "Upload Customer House Data" button on the APP, and the system pops up a file selection box. The user selects a file containing house information (the file format can be limited to common CAD drawing format, PDF format, 3D modeling file in a specific format, etc.) for upload. After receiving the customer house data uploaded by the user, a 3D virtual retirement space is constructed according to the specific content of the customer house data, and high-risk areas are identified in the virtual retirement space and marked with different colors (such as red, etc.).

[0043] In this embodiment, by receiving customer housing data uploaded by users, a personalized virtual elderly care space can be constructed according to the specific housing conditions of each customer, ensuring a high degree of consistency between the virtual elderly care space and the actual house, thereby improving the customer conversion rate of elderly care service products; using customer housing data to construct a virtual elderly care space realizes fast and accurate space modeling, thereby improving the conversion efficiency of elderly care service products; by marking high-risk areas in the virtual elderly care space, users can pay more attention to the potential risks in high-risk areas, thereby improving the customer conversion rate of elderly care service products.

[0044] In one embodiment, receiving customer housing data uploaded by a user and constructing a virtual retirement space based on the customer housing data includes:

[0045] Receiving the customer house data uploaded by the user, parsing the customer house data to obtain basic framework information and furniture information;

[0046] Identifying the information type of the basic framework information, calling a corresponding three-dimensional modeling algorithm according to the information type, and constructing a basic framework of the virtual elderly care space according to the basic framework information through the three-dimensional modeling algorithm;

[0047] Extracting features of the furniture information to obtain furniture features, performing similarity matching in a preset furniture information database based on the furniture features, and selecting three-dimensional furniture information from the preset furniture information database based on the similarity value;

[0048] According to the position information of the furniture information, the three-dimensional furniture information is added to the basic framework to obtain the virtual elderly care space.

[0049] In this embodiment, the customer house data uploaded by the user is received and the customer house data is parsed. By identifying the file suffix, the CAD drawings, floor plan and three-dimensional structure information in the customer house data are summarized as basic framework information, and the furniture data is summarized as furniture information. Based on the basic framework information, it is identified whether the information type of the basic framework information is a two-dimensional information type or a three-dimensional information type. When the information type is identified as a two-dimensional information type, a parametric modeling algorithm is called to create a three-dimensional model through the parametric modeling algorithm. According to the specific parameters of the CAD drawings and three-dimensional structure in the basic framework information, the three-dimensional model is created through the parametric modeling algorithm. The wall structure is generated by the created three-dimensional model, and the wall structure is modified (such as cutting) according to the floor plan in the basic framework information to obtain the basic framework of the virtual elderly care space. For example, according to the door and window position and size information in the floor plan, the wall structure is cut to form the door and window openings; if the information type is three-dimensional information type, the three-dimensional model parsing library is used to read the geometric information of the basic framework information, and the geometric information includes vertex coordinates and facet information. According to the extracted vertex coordinates and facet information, the boundary information of each room structure is identified, and cutting is performed on the corresponding facet according to the floor plan of the basic framework information to obtain to the basic framework of the virtual elderly care space; based on the furniture information, obtain the size information of each furniture type, and use a shape descriptor (such as a Fourier descriptor) to extract the shape features of each furniture according to the size information of each furniture; based on the shape features and size information, traverse the shape features and size information of all candidate furniture information in a preset furniture information library, and calculate the similarity value between the shape features and size information of each furniture and the shape features and size information of the candidate furniture information, wherein the similarity calculation method includes but is not limited to the cosine similarity calculation method, jump from the preset furniture information library to the candidate furniture information with the highest similarity value as the three-dimensional furniture information, obtain the position information of the furniture from the furniture information, convert the position information into a coordinate position, and add the three-dimensional furniture information to the basic framework according to the coordinate position to generate a virtual elderly care space, wherein, during the process of adding the three-dimensional furniture information, collision detection can also be performed to check whether the three-dimensional furniture information collides with the basic framework or other added furniture. The collision detection can use a bounding box algorithm or a precise collision detection algorithm based on geometry. For example, an axis-aligned bounding box (AABB) is created for each component of the furniture and the basic framework, and whether the bounding boxes intersect is quickly determined to determine whether there is a collision. If there is a collision, the system automatically adjusts the position or angle of the furniture to avoid it.

[0050] In this embodiment, virtual retirement spaces are automatically generated based on customer housing data uploaded by users, avoiding manual drawing, improving construction efficiency, and being able to respond to user needs in a timely manner, thereby indirectly improving customer conversion rates. Moreover, the construction is based on customer housing data uploaded by users, which can fully take into account the uniqueness of each user's house and generate personalized virtual retirement spaces, thereby improving the customer conversion rate of elderly care service products.

[0051] In another embodiment, after receiving the client housing data uploaded by the user and constructing the virtual retirement space according to the client housing data, the method further includes:

[0052] Construct an interactive 3D simulation model through the preset 3D modeling software to obtain the target simulation model;

[0053] inserting a target simulation model and a physics engine into the virtual elderly care space according to a predefined model insertion position;

[0054] According to the input interactive instruction, a dangerous scenario is simulated in the virtual elderly care space through the target simulation model and the physical engine.

[0055] In this embodiment, based on the common risk factors of elderly care scenarios, the target simulation model that needs to be constructed is determined, such as a slippery floor in the bathroom, a fire in the kitchen, etc. Once the target simulation model that needs to be constructed is determined, professional 3D modeling software (such as 3dMax, Maya, Blender, etc.) is used to create a 3D simulation model to obtain the target simulation model. For example, to create a slippery floor model, a plane geometric body is created in the 3D modeling software, and its material properties are adjusted to set different reflectivity, glossiness and roughness to simulate different degrees of slippery effects to obtain the target simulation model; in the target simulation model, an interactive panel is set, and the interactive panel can respond to interactive instructions initiated by the user or respond to the user's behavioral actions of clicking on the interactive area; the constructed virtual elderly care space is layout analyzed to determine a suitable location for inserting the target simulation model. For example, a slippery ground model is inserted in areas prone to water accumulation, such as bathrooms and kitchens; the coordinate system and transformation function provided by the three-dimensional graphics library (such as OpenGL and Direct3D) are used to determine the position of the insertion point; the target simulation model created in the three-dimensional modeling software is exported to a format supported by the virtual elderly care space, and the target simulation model is loaded into the virtual elderly care space using the corresponding model loading function, and the model is placed in the correct position according to the position of the insertion point. According to the needs of the virtual elderly care space, a suitable physics engine is selected, such as Bullet Physics, PhysX, etc., and the physics engine can simulate real physical effects, such as collisions; interactive instructions uploaded by users are received in the interactive section, wherein the interactive instructions include text interactive instructions (such as demonstrating a slippery ground model in the bathroom) or action interactive instructions (such as clicking on the slippery ground model), the received interactive instructions are parsed and processed, and converted into operations in the virtual elderly care space, and dangerous scenes are modeled in the virtual elderly care space through the target simulation model and the physics engine.

[0056] In this embodiment, by implanting an interactive three-dimensional model in the virtual elderly care space and accurately restoring various objects and dangerous scene elements in reality through the three-dimensional model, users can intuitively see the dangerous factors, thereby improving customer conversion rate.

[0057] In one embodiment, marking high-risk areas in the virtual elderly care space includes:

[0058] A set of images to be identified is obtained by pre-setting a virtual camera to capture images in the virtual elderly care space;

[0059] Assigning a unique identifier to each image to be identified in the set of images to be identified, and extracting a feature vector of each image to be identified in the set of images to be identified using a pre-trained risk identification model to obtain a risk feature;

[0060] determining whether the image to be identified is a high-risk image according to the risk feature;

[0061] When the image to be identified is the high-risk image, the area corresponding to the high-risk image is marked as the high-risk area in the virtual elderly care space according to the unique identifier of the high-risk image.

[0062] In this embodiment, the above-mentioned pre-trained risk identification model refers to a convolutional neural network, including an input layer, a convolution layer, a pooling layer, a classification layer and an output layer; multiple virtual cameras are set in the virtual nursing space to cover all key areas, such as entrances, corridors, stairs, bathrooms, etc., and images are captured in the virtual nursing space through multiple virtual cameras, and the captured images are saved in a preset format (such as PNG, JPEG) to obtain a set of images to be identified, and a preprocessing operation is performed on each image to be identified in the set of images to be identified. The preprocessing operation includes normalization, denoising, etc., and a unique identifier is assigned to each image to be identified in the set of images to be identified, and each image to be identified in the set of images to be identified is input into the pre-trained risk identification model in turn, and a convolution operation is performed on the image to be identified through the risk identification model to obtain an initial risk feature, and the initial risk feature is obtained. The risk features are pooled (such as maximum pooling or average pooling) to generate risk features, and the risk features are classified in the classification layer of the risk identification model (such as classified as high-risk images or classified as non-high-risk images), and a confidence score is calculated. The confidence score is compared with the confidence score according to a pre-set confidence threshold. When the confidence score is greater than the confidence threshold, it is determined to be a high-risk image. Conversely, when the confidence score is less than or equal to the confidence threshold, it is determined to be a non-high-risk image. According to the risk determination result, all images determined to be high-risk are screened out, and the unique identifier of the high-risk image is used to locate the area corresponding to the high-risk image in the virtual elderly care space. In the virtual elderly care space, the high-risk area is marked by highlighting, marking symbols or text descriptions, and the marked high-risk area is displayed in the user interface of the virtual elderly care space.

[0063] In this embodiment, through a pre-set virtual camera and a pre-trained risk identification model, high-risk identification in the virtual elderly care space can be automatically identified, thereby improving the efficiency and accuracy of risk identification; and a unique identifier is used to correspond high-risk images to specific areas in the virtual elderly care space, thereby achieving accurate labeling of high-risk areas, allowing users to pay more attention to the potential risks in high-risk areas, thereby improving the customer conversion rate of elderly care service products.

[0064] Step S202: receiving an interaction instruction initiated by the user, demonstrating a virtual risk scenario in the high-risk area of ​​the virtual elderly care space according to the interaction instruction, collecting the user's behavior actions during the virtual risk scenario demonstration, and generating a first interest value based on the behavior actions.

[0065] In this embodiment, user-initiated interaction commands are received, including voice interaction commands, handle interaction commands, or touch screen interaction commands. Voice interaction commands refer to interaction commands initiated by the user via voice, handle interaction commands refer to interaction commands initiated by the user via the handle, and touch screen interaction commands refer to interaction commands generated by the user clicking on a high-risk area. The user-input interaction command is parsed, and based on the parsed interaction command (e.g., viewing a specific high-risk area or triggering a certain risk scenario), a virtual risk scenario (e.g., a slip in the bathroom, a slip in the kitchen, etc.) corresponding to the interaction command is presented in the virtual elderly care space. The selected risk scenario is loaded from a scenario library of the virtual elderly care space, and the risk scenario is presented using an interactive target simulation model. The user is allowed to interact in real time during the scenario presentation, such as adjusting the viewing angle, pausing, or resuming the scenario presentation. During the presentation of the virtual risk scenario, the user's behavior and actions are monitored in real time using sensors and cameras in a virtual reality (VR) device. The user's behavior and actions are collected in real time, and the user's first interest value in the virtual demonstration of the high-risk area is calculated by analyzing the user's behavior and actions, such as a special attention to certain high-risk areas or a positive response to certain safety prompts.

[0066] Continuing with the above-mentioned feasible example A, after a virtual retirement space is generated based on the customer's housing information uploaded by the user, the virtual retirement space is loaded, and the customer enters the virtual retirement space through a mobile phone or VR device. In the virtual retirement space, interactive instructions are initiated through voice, touch or manipulation, and the interactive instructions are parsed to determine a location in the virtual retirement space to demonstrate a virtual risk scenario. During the demonstration of the virtual risk scenario, the user's behavioral actions are collected, and the user's first interest value in the risk scenario is calculated based on the behavioral actions.

[0067] In this embodiment, by receiving interactive instructions initiated by users, the system can accurately respond to user needs and demonstrate corresponding virtual risk scenarios in high-risk areas of the virtual elderly care space, thereby improving the targeted interaction and thus improving the personalized needs of customers. During the demonstration of the virtual risk scenario, the user's behavior actions are collected and the first interest value is calculated based on the behavior actions. The user's behavior actions can be accurately obtained, and the user's first interest value in each high-risk area can be calculated based on the behavior actions. Subsequently, accurate recommendations can be made based on the first interest value, thereby improving the customer conversion rate of elderly care service products.

[0068] In one embodiment, receiving the interaction instruction initiated by the user and demonstrating a virtual risk scenario in the high-risk area of ​​the virtual elderly care space according to the interaction instruction includes:

[0069] receiving the multimodal interaction instruction initiated by the user, and identifying the instruction type of the interaction instruction;

[0070] According to the instruction type, the interactive instruction is parsed using a corresponding instruction parsing method to obtain an instruction parsing result;

[0071] Determining high-risk areas for demonstration in the virtual elderly care space based on the instruction parsing result;

[0072] The target simulation model of the high-risk area is called, pre-set environmental factors are inserted into the target simulation model, and a virtual risk scenario is demonstrated in the high-risk area based on the environmental factors and the target simulation model.

[0073] In this embodiment, it is mentioned above that users can initiate interactive instructions in a variety of ways, such as voice commands, gesture recognition, touch screen operations or keyboard input, etc., that is, it supports users to upload multimodal interactive instructions, receive multimodal interactive instructions initiated by users, and identify the instruction type of interactive instructions initiated by users, including voice instructions, such as users say the instruction "View the slip risk scenario in the bathroom" through a microphone, touch screen instructions, such as on a device that supports a touch screen or keyboard, users directly enter instructions or select menu options, handle interaction instructions, such as users use a handle joystick to enter instructions, and perform pre-processing operations according to the instruction type of the instruction, such as noise reduction processing for voice instructions, mapping user gestures to standard instruction actions, etc.; according to the instruction type, call the corresponding instruction parsing method to parse the interactive instruction to obtain the instruction parsing result, such as for voice instructions, through ASR conversion technology The voice commands are converted into text form, and the text-based voice commands are parsed through NLP technology to extract the key entities of the commands, such as "bathroom", "slip", etc. The key entities are mapped to executable operations, such as "load bathroom slip risk scenario". For touch screen commands, the input text is directly parsed to extract the operation type and parameters; according to the area name or identifier in the command parsing result, the scene mapping is performed in the virtual elderly care space to determine the specific coordinates and range of the high-risk area in the virtual space; according to the determined high-risk area, the target simulation model corresponding to the high-risk area is called, and the pre-set environmental factors, such as sunny or rainy days, daytime or nighttime, etc., are inserted into the target simulation model; the corresponding lighting conditions, ground wetness, etc. are set according to the environmental factors; according to the target simulation model and environmental factors, the virtual risk scenario is demonstrated in the high-risk area.

[0074] In this embodiment, by calling the target simulation model of the high-risk area and inserting pre-set environmental factors into it, the system can simulate a more realistic and vivid virtual risk scenario, which not only enhances the credibility of the scenario, but also provides users with an immersive experience; and can dynamically demonstrate virtual risk scenarios in high-risk areas based on environmental factors and target models, so that users can intuitively see the occurrence process of risk events, thereby more deeply realizing the severity of the risk and the importance of preventive measures, thereby improving the customer conversion rate of elderly care service products.

[0075] In one embodiment, during the demonstration of the virtual risk scenario, collecting the user's behavior and generating a first interest value based on the behavior includes:

[0076] During the virtual risk scenario demonstration, the user's behavior and actions are collected in real time through visual sensors and auditory sensors, wherein the behavior and actions include voice movements, body movements, and facial movements;

[0077] For the voice action, convert the voice action into voice text, extract voice keywords from the voice text and extract voice features of the voice action, and calculate the interest value based on the keywords and voice features to obtain a voice interest value;

[0078] For the limb movement, skeleton tracking is performed on the limb movement to obtain key joint points, specific movements are identified based on the key joint points, and interest values ​​are calculated according to the specific movements to obtain limb interest values;

[0079] For the facial action, facial emotion technology is used to extract features of the facial action to obtain facial features, the emotional state is identified based on the facial features, and the interest value is calculated based on the emotional state to obtain a facial interest value;

[0080] The voice interest value, the body interest value, and the facial interest value are weightedly summed to obtain the first interest value.

[0081] In this embodiment, the above-mentioned visual sensors include but are not limited to cameras, such as mobile phone cameras, and the above-mentioned auditory sensors include but are not limited to microphone arrays, such as mobile phone microphone arrays. Body movements and facial movements are captured by visual sensors, and voice movements are captured by auditory sensors. For voice movements, voice movements are converted into voice text by voice conversion technologies such as ASR, and voice features are extracted from voice movements by a voice feature extraction model to obtain voice features. Keywords of the voice text are identified by NLP technologies (such as TF-IDF, BERT, etc.), and the voice features and voice keywords are input into a voice interest value scoring model to obtain a voice interest value. For body movements, skeleton tracking is performed on the collected body movement images by computer vision technologies (such as OpenPose, deep learning models, etc.) to identify the key joints of the user (such as the hands). The motion trajectory of the body (such as the hands and feet), pre-defines a series of specific actions related to risk scenarios, such as waving hands, giving a thumbs-up, etc., matches the motion trajectory of key joints with the pre-defined specific actions, identifies the specific actions the user is performing, builds a limb interest value scoring model, calculates the interest value of the specific action through the limb interest value scoring model, and obtains the limb interest value; for facial movements, facial emotion recognition technology, such as FaceNet or OpenFace, is used to extract facial features from the collected facial expression images, and identifies the user's emotional state (such as surprise, tension, relaxation, etc.) based on the extracted facial features, and analyzes the correlation between different emotional states and the user's interest level. For example, a user showing tension or surprise may indicate a high degree of concern about the risk scenario. Based on the correlation between emotional state and interest level, a scoring model is constructed. For example, an interest value score can be assigned to each emotional state to indicate the degree of influence of the emotional state on the overall interest value. The identified emotional state is input into the scoring model to calculate the facial interest value. According to actual needs and application scenarios, corresponding weights are assigned to the voice interest value, body interest value and facial interest value. The calculated voice interest value, body interest value and facial interest value are weighted and summed according to the assigned weights to obtain the final first interest value. The first interest value reflects the user's interest level based on the high-risk area. The above-mentioned behavioral actions are all input into the interest value scoring model. The interest value scoring model is an evaluation model based on multimodal data fusion, including a voice interest value scoring model, a body interest value scoring model and a facial interest value scoring model. Through feature extraction, interest value calculation and other steps, the voice interest, body interest value and facial interest value are calculated respectively, and finally a comprehensive first interest value is obtained through weighted summation.

[0082] In this embodiment, the voice interest value, body interest value and facial interest value are calculated according to the characteristics of voice, body and facial movements respectively, and the voice interest value, body interest value and facial interest value are weighted and summed to obtain a comprehensive first interest value. By calculating the comprehensive interest value with the help of multimodal features, the first interest value of the user in each high-risk area can be accurately calculated, and accurate recommendations can be made based on the first interest value in the future, thereby improving the customer conversion rate of elderly care service products.

[0083] In another embodiment, during the virtual risk scenario demonstration, the method further comprises:

[0084] Pre-configure the preset trigger conditions for the salesperson to intervene in the virtual risk scenario;

[0085] Continuously detecting the status of the virtual risk scenario, and when the status meets the preset trigger condition, initiating an intervention reminder to the business through a preset communication interface, and granting the business operator access to the virtual risk scenario;

[0086] Receive the explanation content entered by the salesperson in the virtual risk scenario, and synchronize the explanation content to the user's user terminal in real time.

[0087] In this embodiment, preset trigger conditions for the salesperson to intervene in the virtual risk scenario demonstration are pre-configured and stored. The trigger conditions include user instruction triggering, such as when a user is monitored saying "Please help me explain the risks of this area and the corresponding service products", and scene status triggering, such as when the virtual risk scenario demonstration progress reaches a preset key node (such as a high-risk action simulation stage, a safety protection measure display stage, etc.), etc., an intervention reminder message is sent to the target salesperson terminal through a preset communication interface (such as message push, voice prompt, etc.), and the salesperson terminal is granted permission to access the current virtual risk scenario, and receives the salesperson's input device in the virtual risk scenario. The system records the explanation content through a microphone (such as a handwriting board, etc.), and the explanation content includes but is not limited to risk scenario descriptions, safety protection knowledge, emergency response measures, and introductions to corresponding elderly care service products; the system synchronizes the received explanation content to the user end in real time, wherein the synchronization methods include voice synchronization: transmitting the voice signal of the explanation content to the user end in real time, and playing it through the audio playback device of the user end, text synchronization: converting the voice signal of the explanation content into text information, and displaying it in real time on the interface of the user end, and action synchronization: synchronizing the salesperson's actions in the virtual risk scenario (such as marking, underlining, highlighting, etc. in the virtual scene) to the user end in real time.

[0088] In this embodiment, by presetting trigger conditions, it is possible to intelligently determine when a salesperson needs to intervene in the demonstration of a virtual risk scenario, thereby improving the degree of automation and response speed, allocating salesperson resources more reasonably, and avoiding unnecessary intervention and waste of resources; at the same time, by supporting the same-screen display of salespersons and users, the efficiency of salespersons' explanations is improved, thereby improving the customer conversion rate of elderly care service products.

[0089] Step S203: Record the user's residence time and visit frequency in each high-risk area in the virtual elderly care space, and calculate a second interest value based on the residence time and visit frequency.

[0090] In this embodiment, the timestamps of users entering and leaving each high-risk area are recorded, the length of time users stay in each area is calculated, and the number of times users enter each high-risk area within a preset time period is counted through the interaction log recording module to obtain residence time data and access frequency data; the residence time data and access frequency data are preprocessed to obtain preprocessed residence time data and access frequency data, wherein the preprocessing operation includes but is not limited to removing outliers: such as deleting invalid data with a stay time of less than 5s or more than two hours, and removing invalid data of access frequency corresponding to a stay time of less than 5s, and calculating a second interest value based on the residence time and the access frequency.

[0091] In one embodiment, the formula for calculating the second interest value based on the residence time and the visit frequency includes:

[0092]

[0093] Wherein, the I refers to the second interest value, the a and the b refer to the preset weights, and the T eff Refers to the total time spent in all high-risk areas, T max Refers to the maximum stay time in each high-risk area, and F refers to the frequency of users visiting each high-risk area. avg Refers to the average frequency of visits to all high-risk areas.

[0094] In this embodiment, by recording the user's residence time and visit frequency in each high-risk area in the virtual elderly care space, a second interest value is calculated based on the residence time and visit frequency, and accurate recommendations are subsequently made based on the second interest value, thereby improving the customer conversion rate of elderly care service products.

[0095] Step S204: Based on each of the high-risk areas, perform weighted summation on the first interest value and the second interest value to obtain a target interest value, determine a target recommended product according to the target interest value, and recommend the target elderly care service product to the user.

[0096] In this embodiment, in order to eliminate the dimensional difference between the first interest value and the second interest value, the first interest value and the second interest value are normalized, and the interest value is mapped to the interval of (0-1]. Based on each high-risk area, the first interest value and the second interest value are weighted and summed according to the preset interest value weight to obtain the target interest value. The target interest value is compared with the corresponding interest value threshold. When the target interest value is less than or equal to the interest value threshold, it is judged that the user is not interested in the elderly care service product corresponding to the high-risk area. When the target interest value is greater than the target interest value threshold, the elderly care service product corresponding to the high-risk area is obtained, and the elderly care service product is used as the target recommended product, and the target recommended product is recommended to the user.

[0097] In this embodiment, the target interest value is obtained by weighted summing the first interest value and the second interest value, and product recommendations are made based on the target interest value, which can accurately match user needs and improve customer conversion rate.

[0098] It should be emphasized that in order to further ensure the privacy and security of the above-mentioned customer housing data, the above-mentioned customer housing data can also be stored in a blockchain node.

[0099] The blockchain referred to in this application refers to a new application model for computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Blockchain is essentially a decentralized database, a series of data blocks generated using cryptographic methods. Each data block contains information about a batch of network transactions, which is used to verify the validity of the information (to prevent counterfeiting) and generate the next block. Blockchain can include the blockchain underlying platform, the platform product service layer, and the application service layer.

[0100] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0101] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0102] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware via computer-readable instructions. The computer-readable instructions can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes in the above-described method embodiments. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0103] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0104] Further references Figure 3 , as a response to the above Figure 2 In order to realize the method shown in the figure, the present application provides an embodiment of a device for recommending elderly care service products. Figure 2 Corresponding to the method embodiment shown, the apparatus can be specifically applied to various computer devices.

[0105] like Figure 3 As shown, the elderly care service product recommendation device 300 of this embodiment includes: a space construction module 301, a first interest value calculation module 302, a second interest value calculation module 303, and a product recommendation module 304. Among them:

[0106] The space construction module 301 is used to receive customer housing data uploaded by users, construct a virtual elderly care space based on the customer housing data, and mark high-risk areas in the virtual elderly care space;

[0107] In one embodiment, the space construction module includes:

[0108] A data parsing submodule is used to receive the customer house data uploaded by the user, parse the customer house data, and obtain basic framework information and furniture information;

[0109] A basic framework construction submodule is used to identify the information type of the basic framework information, call the corresponding three-dimensional modeling algorithm according to the information type, and construct the basic framework of the virtual elderly care space according to the basic framework information through the three-dimensional modeling algorithm;

[0110] a furniture matching submodule, configured to extract features of the furniture information to obtain furniture features, perform similarity matching in a preset furniture information library based on the furniture features, and select three-dimensional furniture information from the preset furniture information library based on the similarity value;

[0111] The furniture adding submodule is used to add the three-dimensional furniture information to the basic framework according to the position information of the furniture information to obtain the virtual elderly care space.

[0112] In another embodiment, the space construction module further includes:

[0113] The simulation model construction submodule is used to construct an interactive three-dimensional simulation model through a preset three-dimensional modeling software to obtain a target simulation model;

[0114] A model insertion submodule, configured to insert a target simulation model and a physics engine into the virtual elderly care space according to a predefined model insertion position;

[0115] The scene simulation submodule is used to simulate dangerous scenes in the virtual elderly care space through the target simulation model and the physical engine according to the input interactive instructions.

[0116] In one embodiment, the space construction module includes:

[0117] An image capture submodule, configured to capture images in the virtual elderly care space by pre-setting a virtual camera to obtain a set of images to be identified;

[0118] A high-risk feature extraction submodule is used to assign a unique identifier to each image to be identified in the set of images to be identified, and to extract a feature vector of each image to be identified in the set of images to be identified using a pre-trained risk identification model to obtain a risk feature;

[0119] a high-risk image identification submodule, configured to determine whether the image to be identified is a high-risk image based on the risk characteristics;

[0120] The high-risk area marking submodule is used to mark the area corresponding to the high-risk image as the high-risk area in the virtual elderly care space according to the unique identifier of the high-risk image when the image to be identified is the high-risk image.

[0121] The first interest value calculation module 302 is used to receive an interaction instruction initiated by the user, demonstrate a virtual risk scenario in the high-risk area of ​​the virtual elderly care space according to the interaction instruction, collect the user's behavior actions during the virtual risk scenario demonstration, and generate a first interest value based on the behavior actions.

[0122] In one embodiment, the first interest value calculation module includes:

[0123] An instruction type identification submodule, configured to receive the multimodal interaction instruction initiated by the user and identify the instruction type of the interaction instruction;

[0124] The instruction parsing submodule is used to parse the interactive instruction according to the instruction type and adopt the corresponding instruction parsing method to obtain the instruction parsing result;

[0125] a high-risk area determination submodule, configured to determine a high-risk area for demonstration in the virtual elderly care space according to the instruction parsing result;

[0126] The virtual risk scenario demonstration submodule is used to call the target simulation model of the high-risk area, insert pre-set environmental factors into the target simulation model, and demonstrate the virtual risk scenario in the high-risk area based on the environmental factors and the target simulation model.

[0127] In one embodiment, the first interest value calculation module includes:

[0128] A behavior and action collection submodule is used to collect the user's behavior and actions in real time through visual sensors and auditory sensors during the virtual risk scenario demonstration, wherein the behavior and actions include voice movements, body movements, and facial movements;

[0129] A voice interest value calculation submodule is used to convert the voice action into voice text, extract voice keywords from the voice text and voice features of the voice action, and calculate the interest value based on the keywords and voice features to obtain the voice interest value;

[0130] a limb interest value calculation submodule, configured to perform skeleton tracking on the limb movement to obtain key joint points, identify specific movements based on the key joint points, and calculate an interest value based on the specific movement to obtain a limb interest value;

[0131] A facial interest value calculation submodule is used to extract features of the facial actions using facial emotion technology to obtain facial features, identify emotional states based on the facial features, and calculate interest values ​​based on the emotional states to obtain facial interest values;

[0132] A weighting submodule is configured to perform weighted summation on the voice interest value, the body interest value, and the facial interest value to obtain the first interest value.

[0133] In another embodiment, the apparatus further comprises:

[0134] A trigger condition setting module, used to pre-configure the preset trigger conditions for the salesperson to intervene in the virtual risk scenario;

[0135] An intervention reminder module is used to continuously detect the status of the virtual risk scenario. When the status meets the preset trigger condition, it initiates an intervention reminder to the business through a preset communication interface and grants the business operator access to the virtual risk scenario;

[0136] The content synchronization module is used to receive the explanation content entered by the salesperson in the virtual risk scenario and synchronize the explanation content to the user's user terminal in real time.

[0137] A second interest value calculation module 303 is configured to record the user's residence time and visit frequency in each high-risk area in the virtual elderly care space, and calculate a second interest value based on the residence time and visit frequency;

[0138] The product recommendation module 304 is used to perform weighted summation of the first interest value and the second interest value based on each high-risk area to obtain a target interest value, determine a target recommended product according to the target interest value, and recommend the target elderly care service product to the user.

[0139] In this embodiment, by receiving customer housing data uploaded by users, a personalized virtual elderly care space can be constructed based on the specific housing conditions of each customer, ensuring a high degree of consistency between the virtual elderly care space and the actual housing, thereby improving the customer conversion rate of elderly care service products; using customer housing data to construct virtual elderly care spaces achieves fast and accurate space modeling, improving the conversion efficiency of elderly care service products; by marking high-risk areas in the virtual elderly care space, users can pay more attention to the potential risks in high-risk areas, thereby improving the customer conversion rate of elderly care service products;

[0140] By receiving interactive instructions initiated by users, the system can accurately respond to user needs and demonstrate corresponding virtual risk scenarios in high-risk areas of the virtual elderly care space, improving the targeted interaction and thus also meeting the personalized needs of customers. During the virtual risk scenario demonstration, the user's behavior actions are collected and the first interest value is calculated based on the behavior actions. The system can accurately obtain user behavior actions and calculate the user's first interest value in each high-risk area based on the behavior actions. Subsequently, accurate recommendations are made based on the first interest value, thereby improving the customer conversion rate of elderly care service products;

[0141] By recording the user's residence time and visit frequency in each high-risk area in the virtual elderly care space, a second interest value is calculated based on the residence time and visit frequency, and accurate recommendations are subsequently made based on the second interest value, thereby improving the customer conversion rate of elderly care service products;

[0142] By taking the weighted sum of the first interest value and the second interest value to obtain the target interest value, product recommendations are made based on the target interest value, which can accurately match user needs and improve customer conversion rate.

[0143] In order to solve the above technical problems, the embodiment of the present application also provides a device (computer device). Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0144] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 4 with a memory 41, a processor 42, and a network interface 43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc.

[0145] The computer device may be a desktop computer, notebook computer, PDA, cloud server, etc. The computer device may interact with the user via a keyboard, mouse, remote control, touchpad, or voice control device.

[0146] The memory 41 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk equipped on the computer device 4, a smart memory card (SMC), a secure digital (SD) card, a flash card, etc. Of course, the memory 41 can also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions for the recommendation method of elderly care service products. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0147] In some embodiments, the processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to execute computer-readable instructions or process data stored in the memory 41, such as computer-readable instructions for executing the method for recommending elderly care service products.

[0148] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0149] During implementation, the electronic device of the present application receives customer housing data uploaded by users and can construct a personalized virtual elderly care space based on the specific housing conditions of each customer, ensuring a high degree of consistency between the virtual elderly care space and the actual housing, thereby improving the customer conversion rate of elderly care service products; using customer housing data to construct the virtual elderly care space achieves rapid and accurate space modeling, thereby improving the conversion efficiency of elderly care service products; by marking high-risk areas in the virtual elderly care space, users can pay more attention to the potential risks in high-risk areas, thereby improving the customer conversion rate of elderly care service products;

[0150] By receiving interactive instructions initiated by users, the system can accurately respond to user needs and demonstrate corresponding virtual risk scenarios in high-risk areas of the virtual elderly care space, improving the targeted interaction and thus also meeting the personalized needs of customers. During the virtual risk scenario demonstration, the user's behavior actions are collected and the first interest value is calculated based on the behavior actions. The system can accurately obtain user behavior actions and calculate the user's first interest value in each high-risk area based on the behavior actions. Subsequently, accurate recommendations are made based on the first interest value, thereby improving the customer conversion rate of elderly care service products;

[0151] By recording the user's residence time and visit frequency in each high-risk area in the virtual elderly care space, a second interest value is calculated based on the residence time and visit frequency, and accurate recommendations are subsequently made based on the second interest value, thereby improving the customer conversion rate of elderly care service products;

[0152] By taking the weighted sum of the first interest value and the second interest value to obtain the target interest value, product recommendations are made based on the target interest value, which can accurately match user needs and improve customer conversion rate.

[0153] The present application also provides another embodiment, namely, providing a storage medium (computer-readable storage medium), wherein the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the above-mentioned method for recommending elderly care service products.

[0154] During implementation, the computer-readable storage medium of the present application receives customer housing data uploaded by users and can construct a personalized virtual elderly care space based on the specific housing conditions of each customer, ensuring a high degree of consistency between the virtual elderly care space and the actual housing, thereby improving the customer conversion rate of elderly care service products. Using customer housing data to construct the virtual elderly care space achieves rapid and accurate spatial modeling, thereby improving the conversion efficiency of elderly care service products. By marking high-risk areas in the virtual elderly care space, users can pay more attention to the potential risks in high-risk areas, thereby improving the customer conversion rate of elderly care service products.

[0155] By receiving interactive instructions initiated by users, the system can accurately respond to user needs and demonstrate corresponding virtual risk scenarios in high-risk areas of the virtual elderly care space, improving the targeted interaction and thus also meeting the personalized needs of customers. During the virtual risk scenario demonstration, the user's behavior actions are collected and the first interest value is calculated based on the behavior actions. The system can accurately obtain user behavior actions and calculate the user's first interest value in each high-risk area based on the behavior actions. Subsequently, accurate recommendations are made based on the first interest value, thereby improving the customer conversion rate of elderly care service products;

[0156] By recording the user's residence time and visit frequency in each high-risk area in the virtual elderly care space, a second interest value is calculated based on the residence time and visit frequency, and accurate recommendations are subsequently made based on the second interest value, thereby improving the customer conversion rate of elderly care service products;

[0157] By taking the weighted sum of the first interest value and the second interest value to obtain the target interest value, product recommendations are made based on the target interest value, which can accurately match user needs and improve customer conversion rate.

[0158] The non-Company software tools or components appearing in the embodiments of this application are merely examples and do not represent actual use.

[0159] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0160] Obviously, the embodiments described above are only some of the embodiments of the present application, rather than all of the embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions described in the aforementioned specific embodiments, or to make equivalent replacements for some of the technical features therein. Any equivalent structure made using the contents of the present application specification and the accompanying drawings, directly or indirectly used in other related technical fields, is also within the scope of patent protection of the present application.

Claims

1. A method for recommending elderly care service products, characterized in that: The method comprises: Receive customer housing data uploaded by users, build a virtual elderly care space based on the customer housing data, and mark high-risk areas in the virtual elderly care space; receiving an interaction instruction initiated by the user, demonstrating a virtual risk scenario in the high-risk area of ​​the virtual elderly care space according to the interaction instruction, collecting the user's behavior during the demonstration of the virtual risk scenario, and generating a first interest value based on the behavior; Recording the user's residence time and visit frequency in each high-risk area in the virtual elderly care space, and calculating a second interest value based on the residence time and visit frequency; Based on each of the high-risk areas, the first interest value and the second interest value are weightedly summed to obtain a target interest value, a target recommended product is determined according to the target interest value, and the target elderly care service product is recommended to the user.

2. The method for recommending elderly care service products according to claim 1, wherein: The receiving of customer housing data uploaded by a user and constructing a virtual elderly care space according to the customer housing data includes: Receiving the customer house data uploaded by the user, parsing the customer house data to obtain basic framework information and furniture information; Identifying the information type of the basic framework information, calling a corresponding three-dimensional modeling algorithm according to the information type, and constructing a basic framework of the virtual elderly care space according to the basic framework information through the three-dimensional modeling algorithm; Extracting features of the furniture information to obtain furniture features, performing similarity matching in a preset furniture information database based on the furniture features, and selecting three-dimensional furniture information from the preset furniture information database based on the similarity value; According to the position information of the furniture information, the three-dimensional furniture information is added to the basic framework to obtain the virtual elderly care space.

3. The method for recommending elderly care service products according to claim 2, wherein: After receiving the client housing data uploaded by the user and constructing the virtual retirement space according to the client housing data, the method further includes: Construct an interactive 3D simulation model through the preset 3D modeling software to obtain the target simulation model; inserting a target simulation model and a physics engine into the virtual elderly care space according to a predefined model insertion position; According to the input interactive instruction, a dangerous scenario is simulated in the virtual elderly care space through the target simulation model and the physical engine.

4. The method for recommending elderly care service products according to claim 1, wherein: The marking of high-risk areas in the virtual elderly care space includes: A set of images to be identified is obtained by pre-setting a virtual camera to capture images in the virtual elderly care space; Assigning a unique identifier to each image to be identified in the set of images to be identified, and extracting a feature vector of each image to be identified in the set of images to be identified using a pre-trained risk identification model to obtain a risk feature; determining whether the image to be identified is a high-risk image according to the risk feature; When the image to be identified is the high-risk image, the area corresponding to the high-risk image is marked as the high-risk area in the virtual elderly care space according to the unique identifier of the high-risk image.

5. The method for recommending elderly care service products according to claim 1, wherein: The receiving the interaction instruction initiated by the user and demonstrating a virtual risk scenario in the high-risk area of ​​the virtual elderly care space according to the interaction instruction includes: receiving the multimodal interaction instruction initiated by the user, and identifying the instruction type of the interaction instruction; According to the instruction type, the interactive instruction is parsed using a corresponding instruction parsing method to obtain an instruction parsing result; Determining high-risk areas for demonstration in the virtual elderly care space based on the instruction parsing result; The target simulation model of the high-risk area is called, pre-set environmental factors are inserted into the target simulation model, and a virtual risk scenario is demonstrated in the high-risk area based on the environmental factors and the target simulation model.

6. The method for recommending elderly care service products according to claim 1, wherein: During the demonstration of the virtual risk scenario, collecting the user's behavior and generating a first interest value according to the behavior, includes: During the virtual risk scenario demonstration, the user's behavior and actions are collected in real time through visual sensors and auditory sensors, wherein the behavior and actions include voice movements, body movements, and facial movements; For the voice action, convert the voice action into voice text, extract voice keywords from the voice text and extract voice features of the voice action, and calculate the interest value based on the keywords and voice features to obtain a voice interest value; For the limb movement, skeleton tracking is performed on the limb movement to obtain key joint points, specific movements are identified based on the key joint points, and interest values ​​are calculated according to the specific movements to obtain limb interest values; For the facial action, facial emotion technology is used to extract features of the facial action to obtain facial features, the emotional state is identified based on the facial features, and the interest value is calculated based on the emotional state to obtain a facial interest value; The voice interest value, the body interest value, and the facial interest value are weightedly summed to obtain the first interest value.

7. The method for recommending elderly care service products according to claim 6, wherein: During the virtual risk scenario demonstration, the method further includes: Pre-configure the preset trigger conditions for the salesperson to intervene in the virtual risk scenario; Continuously detecting the status of the virtual risk scenario, and when the status meets the preset trigger condition, initiating an intervention reminder to the business through a preset communication interface, and granting the business operator access to the virtual risk scenario; Receive the explanation content entered by the salesperson in the virtual risk scenario, and synchronize the explanation content to the user's user terminal in real time.

8. A device for recommending elderly care service products, characterized in that: The device comprises: A space construction module is used to receive customer housing data uploaded by users, construct a virtual elderly care space based on the customer housing data, and mark high-risk areas in the virtual elderly care space; a first interest value calculation module, configured to receive an interaction instruction initiated by the user, demonstrate a virtual risk scenario in the high-risk area of ​​the virtual elderly care space according to the interaction instruction, collect the user's behavior during the demonstration of the virtual risk scenario, and generate a first interest value based on the behavior; A second interest value calculation module is used to record the user's residence time and visit frequency in each high-risk area in the virtual elderly care space, and calculate a second interest value based on the residence time and visit frequency; A product recommendation module is used to perform weighted summation of the first interest value and the second interest value based on each high-risk area to obtain a target interest value, determine a target recommended product according to the target interest value, and recommend the target elderly care service product to the user.

9. A computer device, characterized in that: The computer device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for recommending elderly care service products as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for recommending elderly care service products according to any one of claims 1 to 7 is implemented.

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