Scheme recommendation method and device, electronic equipment, storage medium and program product

Abstract

The invention provides a scheme recommendation method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of computers. The method comprises the following steps: acquiring target information; the target information is used for indicating at least one service demand satisfied by a target space expected by a target user; performing intelligent analysis based on the target information and the intelligent device in the target space to obtain an intelligent analysis result; based on the intelligent analysis result, determining a target device which needs to be configured and meets the service demand, and generating a corresponding intelligent recommendation scheme; the intelligent recommendation scheme is used for recommending the target equipment which needs to be configured and meets the service requirement to the target user. The problem that it is difficult for a user to select a proper intelligent device in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of Internet of Things technology. Specifically, the present application relates to a solution recommendation method, device, electronic device, storage medium and program product. Background Art

[0002] With the continuous advancement of technology and people's pursuit of convenience in life, the application of smart devices has gradually become popular. Smart devices cover a variety of types, such as smart lighting, smart security, smart appliances, etc., and have rich functions and networking capabilities.

[0003] However, with the increasing variety of smart devices and the increasing complexity of individual device functions, users face a higher barrier to entry when choosing the right smart device. Furthermore, vendors must demonstrate a high level of expertise when providing device recommendations to users. They must understand users' specific needs and provide satisfactory products and services.

[0004] From the above, we can see that it is difficult for users to choose suitable smart devices, which has become an urgent problem that needs to be solved. Summary of the Invention

[0005] This application provides a solution recommendation method, device, electronic device, and storage medium, which can solve the problem in related technologies that users have difficulty in selecting suitable smart devices. The technical solution is as follows:

[0006] According to one aspect of the present application, a solution recommendation method includes: obtaining target information; the target information is used to indicate at least one service requirement that a target user expects a target space to meet; performing intelligent analysis based on the target information and the smart devices under the target space to obtain an intelligent analysis result; determining the target device that needs to be configured to meet the service requirement based on the intelligent analysis result, and generating a corresponding intelligent recommendation solution; the intelligent recommendation solution is used to recommend the target device that needs to be configured to meet the service requirement to the target user.

[0007] According to one aspect of the present application, a solution recommendation method includes: displaying a recommendation page; the recommendation page is used to display the intelligent analysis results of the intelligent analysis of the target space; the intelligent analysis is based on target information and the intelligent devices under the target space; the target information is used to indicate at least one service requirement that the target user expects the target space to meet; displaying an intelligent recommendation solution on the recommendation page; the intelligent recommendation solution is used to recommend to the target user a target device that needs to be configured to meet the service requirement; the target device is a device determined based on the intelligent analysis result and needs to be configured to meet the service requirement

[0008] According to one aspect of the present application, a solution recommendation device includes: an information acquisition module for acquiring target information; the target information is used to indicate at least one service requirement that the target user expects the target space to meet; an intelligent analysis module for performing intelligent analysis based on the target information and the intelligent devices under the target space to obtain an intelligent analysis result; a solution generation module for determining the target device that needs to be configured to meet the service requirement based on the intelligent analysis result, and generating a corresponding intelligent recommendation solution; the intelligent recommendation solution is used to recommend the target device that needs to be configured to meet the service requirement to the target user.

[0009] In an exemplary embodiment, the target information includes user input information; the information acquisition module is also used to obtain the user input information; the user input information is used to determine the service requirements that the target user expects the target space to meet; based on the user input information, the service requirements that the target user expects the target space to meet are determined to obtain the target information.

[0010] In an exemplary embodiment, the target information includes a user tag; the information acquisition module is further used to obtain at least one of the user tags, where the user tag is used to indicate user characteristics; the user characteristics are used to reflect the service requirements that the target user expects the target space to meet; based on the user tag, the target space is matched with corresponding service requirements according to matching rules, and the target information is obtained based on the matched service requirements.

[0011] In an exemplary embodiment, the target information includes user behavior information; the information acquisition module is also used to obtain the user behavior information; the user behavior information is analyzed regarding behavioral habits to obtain habit information; the habit information is used to indicate the behavioral habits of the target user; based on the behavioral habits indicated by the habit information, the service requirements that the user expects the target space to meet are determined, and the corresponding target information is obtained.

[0012] In an exemplary embodiment, the target information includes demand auxiliary information, and the demand auxiliary information includes one or more of the energy consumption information of the target space and the spatial environment information of the target space; the demand auxiliary information user indicates the spatial status of the target space; the energy consumption information is used to indicate the energy consumption of the target space, and the spatial environment information is used to indicate the environmental status of the target space; the information acquisition module is also used to obtain the demand auxiliary information corresponding to the target space; the target space is evaluated based on the demand auxiliary information to determine the spatial status of the target space to be optimized; based on the spatial status to be optimized, the service requirements expected to be met by the target space are determined, and the corresponding target information is obtained.

[0013] In an exemplary embodiment, the intelligent analysis result includes an intelligent score, which is used to reflect the intelligence level of the target space; the intelligent analysis module is also used to determine the target device functions required to meet the service requirements in the target space based on the service requirements indicated by the target information; and calculate based on the target device functions and the device functions of the smart devices under the target space to obtain the corresponding intelligent score of the target space.

[0014] In an exemplary embodiment, the solution generation module is also used to determine at least one candidate device required to meet the service requirements in the target space based on the target device functions and the device functions of the smart devices in the target space; determine the recommendation level of each candidate device for the intelligent score based on the impact of each candidate device being configured in the target space on the intelligent score; based on the corresponding recommendation level of each candidate device, screen the target device from each candidate device, and obtain the intelligent recommendation solution based on the determined target device.

[0015] In an exemplary embodiment, the intelligent analysis module is also used to obtain priority information for each service demand based on user preference information if the target information indicates that the target user has multiple service demands for the target space; the priority information is used to indicate the corresponding priority level of satisfying each service demand; and the target space is intelligently analyzed in combination with the corresponding priority level of each service demand indicated by the priority information to obtain the corresponding intelligent analysis result of the target space.

[0016] In an exemplary embodiment, the intelligent analysis module is also used to determine the corresponding spatial level of each subspace if there is at least one subspace in the target space; assign a corresponding weight to each subspace based on the corresponding spatial level of each subspace; and perform an intelligent analysis on the target space in combination with the corresponding weight of each subspace to obtain the corresponding intelligent analysis result of the target space.

[0017] In an exemplary embodiment, the solution generation module is also used to determine the importance of each target device in meeting the service needs if the intelligent recommendation solution includes multiple target devices; determine the recommendation order according to the corresponding importance of each target device; and recommend each target device in the intelligent recommendation solution according to the recommendation order.

[0018] In an exemplary embodiment, the solution recommendation device is also used to, if it is detected that the smart device in the target space has changed, re-perform intelligent analysis based on the changed smart device to obtain an updated intelligent analysis result; and regenerate a corresponding intelligent recommendation solution based on the updated analysis result.

[0019] According to one aspect of the present application, a solution recommendation device includes: a page display module for displaying a recommendation page; the recommendation page is used to display the intelligent analysis results of the intelligent analysis of the target space; the intelligent analysis is based on the target information and the intelligent devices under the target space; the target information is used to indicate at least one service requirement that the target user expects the target space to meet; a solution display module is used to display an intelligent recommendation solution on the recommendation page; the intelligent recommendation solution is used to recommend to the target user the target device that needs to be configured to meet the service requirement; the target device is determined based on the intelligent analysis result and needs to be configured to meet the service requirement.

[0020] In an exemplary embodiment, the solution display module is also used to display a purchase page corresponding to the target device in response to a purchase operation of the target device recommended by the intelligent recommendation solution, and the purchase page is used to provide the user with a purchase entry for the target device.

[0021] In an exemplary embodiment, the solution display module is further configured to recommend the target device in the intelligent recommendation solution if it is detected that the target device does not exist in the target space.

[0022] In an exemplary embodiment, the solution recommendation method is also used to obtain an updated intelligent analysis result if a change is detected in the smart device under the target space; the updated intelligent analysis result is obtained by re-intelligent analysis of the changed smart device; the updated intelligent analysis result is displayed on the recommendation page, and a regenerated intelligent recommendation solution is obtained, and the regenerated intelligent recommendation solution is displayed on the recommendation page.

[0023] According to one aspect of the present application, an electronic device includes at least one processor and at least one memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the solution recommendation method described above is implemented.

[0024] According to one aspect of the present application, a storage medium stores a computer program thereon, and when the computer program is executed by one or more processors, the solution recommendation method described above is implemented.

[0025] According to one aspect of the present application, a computer program product includes a computer program, and when the computer program is executed by one or more processors, the computer program implements the solution recommendation method described above.

[0026] The beneficial effects of the technical solution provided by this application are:

[0027] In the above technical solution, this solution is based on target information, can determine the target user's service needs for the target space, and perform intelligent analysis based on the target information and the various smart devices under the target space, so as to determine how to configure and manage smart devices to optimize the intelligence level of the target space, generate corresponding intelligent solutions, recommend target devices to users, and meet the target user's service needs through the target devices, thereby reducing the difficulty for users to configure smart devices for the target space. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for describing the embodiments of the present application. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without inventive efforts.

[0029] Figure 1 It is a schematic diagram of the implementation environment involved in this application;

[0030] Figure 2 is a hardware structure diagram of an electronic device according to an exemplary embodiment;

[0031] Figure 3 is a flowchart of a solution recommendation method according to an exemplary embodiment;

[0032] Figure 4 yes Figure 2 A flowchart of step 330 in one embodiment corresponding to the embodiment;

[0033] Figure 5 yes Figure 2 A flowchart of an embodiment corresponding to step 350 in an embodiment;

[0034] Figure 6 is a flow chart showing another solution recommendation method according to an exemplary embodiment;

[0035] Figure 6a yes Figure 6 A schematic diagram of a specific implementation of the recommendation page involved in the corresponding embodiment;

[0036] Figure 7 This is a schematic diagram of a specific implementation of a solution recommendation method in an application scenario;

[0037] Figure 8 is a structural block diagram of a solution recommendation device according to an exemplary embodiment;

[0038] Figure 9 is a structural block diagram of a solution recommendation device according to another exemplary embodiment;

[0039] Figure 10 The figure is a structural block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0040] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and are not to be construed as limiting the present application.

[0041] It will be understood by those skilled in the art that, unless expressly stated otherwise, the singular forms "a", "an", "said" and "the" used herein may also include the plural forms. It should be further understood that the term "comprising" used in the specification of the present disclosure refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, "connected" or "coupled" as used herein may include wireless connections or wireless couplings. The term "and / or" used herein includes all or any units and all combinations of one or more associated listed items.

[0042] As mentioned earlier, with the increase in the categories of smart devices and the increasing complexity of the functions of single devices, users face a higher threshold when choosing suitable smart devices.

[0043] Specifically, with the vast number of smart devices on the market, it can be difficult for users to determine which one best suits their needs. Furthermore, some smart device features require users to have a certain level of technical expertise to fully utilize their potential, and the compatibility issues between different brands and devices can lead users to be more cautious in their selection. Furthermore, the interconnectivity between smart devices complicates configuration, forcing users to consider not only the functionality of a single smart device but also how it works together with other smart devices. This is especially true when multiple smart devices need to work together in a home or office, and improper selection can lead to unsatisfactory results.

[0044] Furthermore, users have diverse service needs: some want improved comfort, others focus on safety or energy efficiency optimization, and the configuration of smart devices must match these needs. Users may find it difficult to make decisions without a full understanding of the device's functions.

[0045] As can be seen from the above, the related technology still has the defect that it is difficult for users to choose a suitable smart device.

[0046] To this end, the solution recommendation method provided in this application can effectively reduce the difficulty for users to select smart devices. Accordingly, the solution recommendation method is applicable to a solution recommendation device, which can be deployed on an electronic device. The electronic device can be a computer device configured with a von Neumann architecture, for example, the computer device includes a desktop computer, a laptop computer, a server, etc.; the electronic device can also be an electronic device with a central control function, for example, the electronic device includes a gateway, etc.; the electronic device can also refer to a portable and mobile electronic device, for example, the electronic device includes a smart phone, a tablet computer, etc.

[0047] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0048] Figure 1 This is a schematic diagram of an implementation environment involved in a solution recommendation method. The implementation environment at least includes a user terminal 110, a smart device 130, a server 170, and a network device. Figure 1 In the embodiment, the network devices include a gateway 150 and a router 190, which is not specifically limited here.

[0049] Among them, the user terminal 110, which can also be considered as a user end or terminal, can deploy (also understood as install) the client associated with the smart device 130. This user terminal 110 can be an electronic device such as a smart phone, tablet computer, laptop computer, desktop computer, smart control panel, other devices with display and control functions, etc., which are not limited here.

[0050] Among them, the client is associated with the smart device 130. In essence, the user registers an account in the client and configures the smart device 130 in the client. For example, the configuration includes adding a device identifier to the smart device 130, so that when the client is run in the user terminal 110, it can provide the user with device display, device control and other functions about the smart device 130. This client can be in the form of an application or a web page. Accordingly, the interface for device display on the client can be in the form of a program window or a web page, which is not limited here.

[0051] The smart device 130 is deployed in the gateway 150, and communicates with the gateway 150 through its own configured communication module, and is thereby controlled by the gateway 150. It should be understood that the smart device 130 generally refers to one of a plurality of smart devices 130, and the embodiment of the present application only takes the smart device 130 as an example, that is, the embodiment of the present application does not limit the number and device types of smart devices deployed in the gateway 150. In an application scenario, the smart device 130 accesses the gateway 150 through a local area network, and is thereby deployed in the gateway 150. The process of the smart device 130 accessing the gateway 150 through the local area network includes: the gateway 150 first establishes a local area network, and the smart device 130 joins the local area network established by the gateway 150 by connecting to the gateway 150. This local area network includes but is not limited to: ZIGBEE or Bluetooth. Among them, the smart device 130 can be a smart printer, a smart fax machine, a smart camera, a smart air conditioner, a smart door lock, a smart light, or a human body sensor equipped with a communication module, a door and window sensor, a temperature and humidity sensor, a water immersion sensor, a natural gas alarm, a smoke alarm, a wall switch, a wall socket, a wireless switch, a wireless wall sticker switch, a Rubik's Cube controller, a curtain motor, a millimeter wave radar, etc.

[0052] The interaction between the user terminal 110 and the smart device 130 can be achieved through a local area network or a wide area network. In one application scenario, the user terminal 110 establishes a communication connection between the router 190 and the gateway 150 by means of a wired or wireless method. For example, the wired or wireless method includes but is not limited to WIFI, so that the user terminal 110 and the gateway 150 are deployed in the same local area network, thereby enabling the user terminal 110 to interact with the smart device 130 through the local area network path. In another application scenario, the user terminal 110 establishes a communication connection between the server 170 and the gateway 150 by means of a wired or wireless method. For example, the wired or wireless method includes but is not limited to 2G, 3G, 4G, 5G, WIFI, etc., so that the user terminal 110 and the gateway 150 are deployed in the same wide area network, thereby enabling the user terminal 110 to interact with the smart device 130 through the wide area network path.

[0053] The server side 170 can also be considered as a cloud, cloud platform, platform side, service side, etc. The server side 170 can be a single server, a server cluster composed of multiple servers, or a cloud computing center composed of multiple servers, so as to better provide backend services to a large number of user terminals 110. For example, the backend services include solution recommendation services.

[0054] In an application scenario, the server side 170 obtains target information, which can indicate the service requirements that the target user expects the target space to meet, and thus performs intelligent analysis based on the target information and the smart device 130 under the target space to obtain an intelligent analysis result; then, based on the intelligent analysis result, the target device that needs to be configured to meet the service requirements is determined, and a corresponding intelligent recommendation plan is generated, and the intelligent recommendation plan is used to recommend the target device that needs to be configured to meet the service requirements to the target user.

[0055] Of course, in other application scenarios, the above-mentioned solution recommendation process completed by the user terminal 110 can also be implemented by the user terminal 110. At this time, after the server side 170 generates an intelligent recommendation solution for the target scenario, the intelligent recommendation solution is sent to the user terminal 110 through the wide area network path, so that the user terminal 110 can provide more effective services to the user based on the intelligent recommendation solution.

[0056] See also Figure 2 , Figure 2 This is a hardware structure diagram of a server according to an exemplary embodiment. Figure 1 A server 170 is shown in an implementation environment.

[0057] It should be noted that the server is only an example adapted for this application and cannot be considered to provide any limitation on the scope of use of this application. The server cannot be interpreted as needing to rely on or must have Figure 2 One or more components of exemplary server 200 are shown.

[0058] The hardware structure of the server 200 may vary greatly due to different configurations or performances, such as Figure 2 As shown, the server 200 includes a power supply 210 , an interface 230 , at least one memory 250 , and at least one central processing unit (CPU) 270 .

[0059] Specifically, the power supply 210 is used to provide operating voltage for each hardware device on the server 200 .

[0060] The interface 230 includes at least one wired or wireless network interface 231 for interacting with external devices. Figure 1 The interaction between the user terminal 110 and the server 170 in the implementation environment is shown.

[0061] Of course, in other examples adapted by this application, the interface 230 may further include at least one serial-to-parallel conversion interface 233, at least one input-output interface 235, and at least one USB interface 237, etc. Figure 2As shown, this does not constitute a specific limitation.

[0062] The memory 250 serves as a carrier for resource storage and can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon include an operating system 251, application 253 and data 255, etc. The storage method can be temporary storage or permanent storage.

[0063] Among them, the operating system 251 is used to manage and control the hardware devices and application programs 253 on the server 200 to enable the central processing unit 270 to calculate and process the massive data 255 in the memory 250. It can be WindowsServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.

[0064] The application 253 is a computer program formed by computer-readable instructions based on the operating system 251 to perform at least one specific task, and may include at least one module ( Figure 2 Each module may include corresponding computer-readable instructions. For example, the solution recommendation device may be considered as an application 253 deployed on the server 200.

[0065] The data 255 may be photos, pictures, etc. stored in a disk, or may be intelligent recommendation solutions, etc. stored in the memory 250 .

[0066] The central processing unit 270 may include one or more processors and is configured to communicate with the memory 250 via at least one communication bus to read the computer program stored in the memory 250, thereby performing operations and processing on the massive data 255 in the memory 250. For example, the solution recommendation method may be implemented by the central processing unit 270 reading the application program 253 stored in the memory 250.

[0067] In addition, the present application can also be implemented through hardware circuits or hardware circuits combined with software. Therefore, the implementation of the present application is not limited to any specific hardware circuits, software, or a combination of the two.

[0068] See also Figure 3 , the embodiment of the present application provides a solution recommendation method, which is applicable to electronic devices, for example, the electronic device can be Figure 1 The server 170 in the implementation environment shown may also be a user terminal 110, a gateway 150, etc. The hardware structure of the electronic device may be as follows: Figure 2 shown.

[0069] In the following method embodiments, for ease of description, the execution subject of each step of the method is taken as an electronic device as an example for illustration, but this does not constitute a specific limitation.

[0070] like Figure 3 As shown, the method may include the following steps:

[0071] Step 310: Obtain target information.

[0072] Among them, the target information is the basis for intelligent analysis, and is used to indicate at least one service requirement that the target user expects the target space to meet. For example, the target information may include the functions that the target user expects the target space to achieve; if the user expects to manage the living room through various smart devices, then the living room is regarded as the target space; the service requirement is the goal that the user expects to achieve in the target control, and the service requirement may include environmental adjustment (such as temperature, humidity), safety assurance (such as security monitoring), lighting management, energy optimization, etc., which are not limited here.

[0073] In one possible implementation, the target information may include user input information, which may be information generated by service requirements input by the user, such as the user's functional requirements for the target space, requirements for smart devices, preference settings, personalized options, etc.

[0074] The target user refers to the user who has service needs for the target space. The target space is the physical space that the target user hopes to manage and serve through smart devices, and can be a space where multiple smart devices are configured.

[0075] In one possible implementation, the target information may include information about the target space, such as the name, purpose, area, location, etc. of the target space, and may also include device information, such as the name, model, brand, function, etc. of the installed smart devices in the target space.

[0076] Specifically, the service requirement can be determined based on at least one of user input information, matching at least one identified user tag, habit information obtained through analysis of user behavior information, or a spatial state to be optimized based on evaluation of auxiliary demand information. The electronic device can then obtain target information based on the service requirement.

[0077] Step 330 , performing intelligent analysis based on the target information and the intelligent devices in the target space to obtain intelligent analysis results.

[0078] Among them, intelligent analysis refers to the analysis process of evaluating how to meet the user's service needs based on target information and existing smart devices in the target space, thereby optimizing the configuration and operation of smart devices.

[0079] In one possible implementation, intelligent analysis can be implemented using machine learning, data mining, deep learning, and other methods, which are not specifically limited herein. The intelligent analysis results refer to the conclusions reached through intelligent analysis. In one possible implementation, the intelligent analysis results may include one or more of the following: optimal intelligent device configurations that meet service requirements, system optimization recommendations, or intelligent scoring.

[0080] It can be understood that target information can provide the service needs of target users, and smart devices are tools for executing intelligent analysis results to meet the service needs specified in the target information. Then, intelligent analysis can generate intelligent analysis results by integrating target information with existing or candidate smart devices, thereby deciding how to configure and manage the smart devices in the target space to achieve the purpose of optimizing the intelligence level of the target space.

[0081] For example, assuming a target user wants to improve the comfort of the bedroom, the target information can be obtained to indicate the service needs of the target user; the bedroom is already equipped with a smart air conditioner, a humidifier and smart lamps; further, the server can perform intelligent analysis based on the target information and the smart devices in the bedroom to determine the optimal adjustment parameters of the equipment, such as lowering the temperature and maintaining the humidity at 40% at 10 pm, and gradually brightening the lights starting at 7 am; then, based on the above intelligent analysis, intelligent analysis results can be obtained, for example, it is recommended to set the smart air conditioner to automatic mode, automatically adjust according to the ambient temperature, automatically start the humidifier when the humidity is lower than the set value, set the lighting system to wake-up mode according to the user's work and rest time, and regularly increase the light brightness every morning, etc.

[0082] It should be noted that before intelligent analysis is performed, the target information and the data obtained from the collection of intelligent devices in the target space can also be processed. In the data processing process, extracting and filtering useful information usually requires the following steps:

[0083] Data collection: Collect data, including target information, device information of smart devices in the target space, etc.; Data cleaning: Clean and pre-process the collected data, including removing invalid data, processing missing values, correcting outliers, etc., to ensure the accuracy and completeness of the data; Data conversion: Convert and organize the original data to meet the needs of analysis and information extraction. For example, store the data in a specific format, convert it into different data types, etc.; Feature extraction: Analyze the cleaned and converted data to extract features related to the target. Features can be numerical, textual, categorical, etc., representing some useful information or characteristics in the data;

[0084] Data modeling and analysis: Utilize the extracted features for data modeling and analysis, and use statistical methods, machine learning algorithms, etc. to conduct data mining to discover useful information hidden in the data. The so-called useful information depends on the specific application and analysis objectives, and certain data analysis determination and verification are required in actual implementation. For example, in the process of intelligent scoring, useful information may include the intelligence score of the target space, user demand preferences, the functions and performance of smart devices, etc. It can be understood that the above information is of great significance for evaluating the level of intelligence, making smart device recommendations and personalized services. In general, useful information is information that is closely related to the analysis objectives (for example, meeting service needs) and can provide insights and decision support. By screening out useful information through data processing and analysis, a basis and basis can be provided for system optimization and the provision of personalized intelligent services.

[0085] Step 350: Determine the target device that needs to be configured to meet the service requirements based on the intelligent analysis results, and generate a corresponding intelligent recommendation solution.

[0086] The intelligent recommendation solution recommends target devices to meet the target user's service needs. Target devices are smart devices that can meet the service needs. For example, if the target user wants to improve bedroom comfort in the summer, the intelligent recommendation solution might include smart air conditioners, which are target devices that can meet the target user's service needs.

[0087] First of all, it should be noted that the goal of intelligent analysis is to meet the service needs of target users for the target space, and the realization of service needs depends on the various smart devices deployed in the target space. It is understandable that the smart devices in the target space may just meet the service needs of the target users for the target space, but it is also possible that they cannot meet them. Based on this, before generating an intelligent recommendation plan, it is necessary to determine whether the existing smart devices in the target space can meet the service needs. For example, if a user wants to improve the air quality in his home, the intelligent analysis will detect the current air quality data and whether the existing equipment (such as air purifiers or humidifiers) can meet the service needs.

[0088] It should be noted that there are many types of smart devices on the market, including smart lighting, smart thermostats, smart appliances, and security cameras, and different brands and models have different functions. It is difficult for users to clearly understand which devices can best meet their specific needs. Furthermore, the linkage functions between different smart devices are complex, especially when users want multiple devices to work together, such as linking smart lighting with security systems, or temperature control with curtains. These linkages require complex setup and may involve different protocols, standards, or platforms. In other words, the installation, configuration, and linkage of smart devices often require technical knowledge, especially when the devices need to connect to the home network, other smart devices, or specific application platforms. For non-technical users, completing these steps can be difficult.

[0089] Based on this, this solution can obtain intelligent analysis results based on target information and smart devices in the target space through intelligent analysis, and issue intelligent recommendation solutions based on the intelligent analysis results, recommending suitable smart device combinations and simplifying the user selection process.

[0090] Specifically, if it's determined that the existing smart devices in the target space can't meet the user's service needs, an intelligent recommendation plan can be generated based on the intelligent analysis results. This intelligent recommendation plan not only includes optimization suggestions for existing smart devices, but also lists recommended smart devices and their contribution to improving the intelligence of the target space. The target user can then view the intelligent recommendation plan and purchase and install the recommended target devices based on the intelligent recommendation plan to meet their service needs for the target space.

[0091] Through the above process, based on the target information, the target user's service needs for the target space can be determined, and intelligent analysis can be performed based on the target information and the various smart devices under the target space, so as to determine how to configure and manage smart devices to optimize the intelligence level of the target space, generate corresponding intelligent solutions, recommend target devices to users, and meet the target user's service needs through the target devices, thereby reducing the difficulty for users to configure smart devices for the target space.

[0092] In an exemplary embodiment, step 310 may further include the following steps: obtaining user input information, and determining, based on the user input information, service requirements that the target user desires the target space to satisfy, thereby obtaining target information. The target information includes the user input information, which is information input by the user and used to determine the service requirements that the target user desires the target space to satisfy.

[0093] For example, users input their service requirements for the target space through the page provided by the user terminal, such as: "I hope the bedroom maintains a constant temperature", "I want the kitchen lights to be automatically adjusted according to the time", "I need to improve the security of the living room", etc., where the input can be completed through a text input box, an option list or a voice command. It can be understood that the information input by the user reflects the specific functions or services they expect to achieve in the target space.

[0094] In one possible implementation, an input control can be provided for the user to obtain user input information. The target user can use the input control to set different service requirements. For example, the input control is a slider component, and the user can set the comfort level of the room according to his or her own settings. The position of the slider is the user's choice; the input control is an energy-saving setting radio button, which provides several options for the user to choose from, such as "intelligent energy saving", "standard energy saving", "no energy saving requirements", etc.; the input control is a security setting check box: several check boxes are provided for the user to choose, such as "security monitoring", "anti-theft alarm", etc., and the user can check one or more of them according to his or her needs.

[0095] In another possible implementation, user input information can be obtained through a questionnaire survey. For example, the questionnaire survey can include the following questions: · How often do you use smart devices? (Options: frequent use, occasional use, rare use); · What are your main needs for smart devices? (Options: safety, comfort, energy saving, entertainment experience, health management, etc.); · Which control method do you prefer for smart devices? (Options: mobile phone application, voice control, touch panel, automatic sensor trigger, etc.); · Do you hope that smart devices can be interconnected and operated in conjunction? (Options: yes, no); · Which aspect of smart services do you value more? (Options: convenience, safety, comfort, user personalization, etc.); · What are your requirements for the price range of the device? (Options: affordable, mid-priced, high-end products); · Are you willing to accept the system's intelligent improvement suggestions to enhance your intelligent service experience? (Options: yes, no); · What concerns do you have about the security and privacy protection of smart devices? (Options: very concerned, somewhat concerned, not concerned).

[0096] Furthermore, the system can parse and analyze the user input to identify the service requirements for the target space. For example, if the user inputs "The bedroom needs to maintain a constant temperature," the system will determine that the user's service requirement is "temperature control." By combining the user input and the parsed service requirements, the corresponding target information can be obtained. For example, if the user input is "Maintain the bedroom temperature at around 22 degrees Celsius," the service requirement determined to be "temperature control" constitutes the target information.

[0097] Under the influence of the above-mentioned embodiments, the target user can describe the service requirements that he or she expects to achieve in the target space through text, options or voice input. Then, the user does not need to have a technical background, and the system can identify the service requirements based on his or her simple input and obtain the corresponding user input information; further, by analyzing the user input information, the service requirements can be accurately parsed, thereby providing the target user with a tailored intelligent recommendation plan, reducing the complexity of device selection, configuration and linkage operations.

[0098] In another exemplary embodiment, step 310 may further include the following steps: acquiring at least one user tag; matching corresponding service requirements for the target space according to the user tag and matching rules, and obtaining target information based on the matched service requirements.

[0099] Among them, the target information includes user tags. User tags are data that describe user characteristics and are used to indicate user characteristics. User characteristics are used to reflect the service requirements that the target user expects the target space to meet. User tags can reflect the target user's lifestyle, needs or preferences.

[0100] In one possible implementation, user tags can be determined by creating a user profile for the target user. A user profile is a comprehensive description of a user's basic information, behavioral characteristics, preferences, and service needs. It can include information such as the target user's age, gender, occupation, usage preferences, location, and lifestyle. Specifically, the target user's user information and historical behavior information can be analyzed and processed to determine the user profile corresponding to the target user, and then determine the user tag corresponding to the target user.

[0101] In another possible implementation, a tag setting option is provided on a page provided by the user terminal, allowing the user to select or set a tag that applies to him or her. For example, in the tag setting related to family groups, the user can choose whether to belong to a family group with a baby.

[0102] Matching rules refer to the standards and logic used to automatically match service requests based on user tags, target spaces, smart devices, usage scenarios, and other information. For example, if a family group tag for a baby is used, service requests related to baby care can be matched based on that user tag. If the user tag identifies the target user's lifestyle as "no one at home during the daytime on weekdays," service requests such as "security monitoring," "energy-saving device control," and "automatic door locking" can be matched.

[0103] Under the influence of the above-mentioned embodiments, through user tags, the system can quickly and accurately match user needs, avoid users from making complex configurations themselves, and reduce the burden of manual input and device selection for users. Furthermore, through reasonable matching rules, the system can effectively establish an association between user tags and service needs, providing users with a smarter and more convenient service experience, thereby meeting users' personalized needs.

[0104] In another exemplary embodiment, step 310 may further include the following steps: obtaining user behavior information; analyzing the user behavior information regarding behavioral habits to obtain habit information; and determining, based on the behavioral habits indicated by the habit information, the service requirements that the user expects the target space to meet, and obtaining corresponding target information. The target information includes the user behavior information, and the habit information indicates the behavioral habits of the target user.

[0105] First, it should be noted that user behavior information of the target user within the target space can be collected through monitoring applications of sensors, smart devices, and / or user terminals within the target space. For example, smart lighting can detect that the target user has a habit of turning on the bedroom light at 9 pm every night and turning it off at 7 am. Specifically, user behavior information may include the user's daily schedule, frequency of use of home devices, device preferences within specific time periods, and other information, without limitation here.

[0106] Regarding behavioral habit analysis, user behavioral information is analyzed to extract behavioral patterns and habits. The analysis process may include behavioral time pattern recognition, device usage frequency statistics, and abnormal behavior detection. For example, by analyzing the target user's sleep and rest schedule over a week, it can be identified that the target user typically uses bedroom lights during specific time periods (such as 9 pm to 7 am) and turns off smart appliances in the living room when leaving home. The analysis process can be implemented through machine learning methods, data mining, and other methods, which are not limited here.

[0107] Furthermore, based on behavioral habit analysis, habit information can be generated. This behavior habit analysis provides an overview of the target user's daily behavior patterns, including their behavioral habits and preferences. For example, habit information may include "the user tends to turn on the bedroom light at 9 pm and off at 7 am." Based on the behavioral habits indicated by this habit information, the target user's desired service requirements within the target space can be inferred. For example, if the target user is detected to automatically turn on the lights at 9 pm every day, it can be inferred that the target user requires "intelligent lighting timing control" as a service requirement.

[0108] It should be noted that based on the user behavior information obtained from long-term tracking, the intelligent recommendation plan can be continuously learned and adjusted, so that the intelligent recommendation plan can become more accurate over time.

[0109] Under the influence of the above-mentioned embodiments, by analyzing user behavior information and generating habit information, it is possible to accurately identify and infer the service needs that users expect in the target space, reduce the user's manual operations, and determine the service needs based on the behavioral habits of the target user. Users can obtain target information without configuring complex parameters, so that they can subsequently obtain intelligent recommendation solutions that are more in line with the user's lifestyle based on the target information.

[0110] In another exemplary embodiment, step 310 may also include the following steps: obtaining demand auxiliary information corresponding to the target space; performing a state evaluation on the target space based on the demand auxiliary information to determine the spatial state of the target space to be optimized; based on the spatial state to be optimized, determining the service requirements that the target space is expected to meet, and obtaining corresponding target information.

[0111] Among them, the target information includes demand auxiliary information, which is information that assists in determining service needs and is used to indicate the spatial state of the target space. The spatial state is a comprehensive description of the current environmental conditions and / or equipment operation status of the target space.

[0112] Furthermore, the demand auxiliary information includes one or more of energy consumption information of the target space and spatial environment information of the target space. Specifically, the energy consumption information is used to indicate the energy consumption of the target space, and the spatial environment information is used to indicate the environmental conditions of the target space.

[0113] It should be noted that auxiliary information related to the target space's needs can be obtained through smart devices deployed in the target space. Specifically, smart sensors and / or smart devices within the target space can be used to obtain energy consumption information such as electricity and gas usage, as well as spatial environmental information such as temperature, humidity, air quality, and lighting brightness.

[0114] Based on the collected auxiliary demand information, the current state of the target space can be evaluated to determine whether any areas of the target space require optimization or adjustment, thereby determining the target space's state for optimization. This state evaluation can be performed by comparing and analyzing preset standards or benchmarks, which are not limited here. For example, if energy consumption information indicates that a room's air conditioner is operating at high energy consumption for extended periods of time, and spatial environment information indicates that the room's air quality is poor, then it can be determined that the target space's air conditioner equipment management and air purification require optimization.

[0115] As you can understand, by acquiring energy consumption information and spatial environment information, we can comprehensively assess the spatial state of the target space and determine which spatial states require optimization. Based on the spatial states to be optimized, the system automatically infers the user's desired service needs, thereby obtaining the corresponding target information. Using the aforementioned example, if the space state has high air conditioning energy consumption, we can infer that the target user needs to achieve energy conservation, and if the air quality is poor, we can infer that the target user needs air purification.

[0116] Through the above process, based on the evaluation of the space status, service requirements can be automatically analyzed and generated without the user actively proposing specific optimization requirements. For example, the target user may not be aware of the energy consumption problem of the target space. The system automatically analyzes and recommends energy-saving smart devices, thereby improving the proactive service capabilities of the intelligent recommendation plan; further, it can also adjust and optimize the intelligent recommendation plan in real time based on the space status, thereby ensuring that the target space is always in an efficient and comfortable state.

[0117] In an exemplary embodiment, step 330 may also include the following steps: if the target information indicates that the target user has multiple service requirements for the target space, then obtaining priority information for each service requirement based on the user preference information; combining the corresponding priority levels of each service requirement indicated by the priority information, performing an intelligent analysis of the target space to obtain the corresponding intelligent analysis results of the target space.

[0118] First, it should be noted that a target user may have multiple service requirements for the target space simultaneously, such as temperature adjustment, air quality control, and device energy saving. However, due to resource limitations, device performance, or conflicts between service requirements, it may not be possible to meet all service requirements simultaneously in actual application scenarios. In this case, it is necessary to determine which service requirements should be met first to optimize the overall state of the target space.

[0119] For example, temperature regulation and energy saving requirements may conflict. The target user wants to achieve a comfortable temperature, but at the same time wants to reduce the energy consumption of smart devices. It is understandable that both goals may not be achieved at the same time. Therefore, priority can be given to meeting the temperature regulation needs and switching to energy saving mode after reaching the set temperature.

[0120] User preference information refers to the target user's personal preferences for different service requirements within the target space. This information can be obtained through the target user's historical behavior, personalized settings, or direct input, and can reflect the user's emphasis on different smart devices or service requirements. For example, if a user directly indicates a higher weight for energy conservation through personalized preference settings, energy conservation-related service requirements can be given a higher priority.

[0121] Priority information indicates the priority level for satisfying each service requirement. Priority information specifies the priority level for each service requirement within the target space. Priority refers to the relative position of a specific service requirement within the priority information, quantifying the urgency or importance of satisfying different service requirements. As you can see, a higher priority level indicates a higher priority level. For example, if the user preference information set by the target user indicates that comfort is more important than energy conservation, then the comfort-related service requirement will be assigned a higher priority, while energy conservation will be assigned a lower priority.

[0122] Then, it is possible to combine priority information to clarify which service needs need to be met first. Through intelligent analysis based on the priority of service needs, it is possible to balance different service needs and ensure that the most important service needs are given priority when all needs cannot be met at the same time. This not only improves the flexibility of intelligent analysis, but also provides users with the best service experience, while optimizing equipment operation when resources are limited.

[0123] Of course, we conduct personalized learning based on users' long-term usage behavior and feedback, and continuously optimize their preferences and priorities for service needs. For example, if a user has been using a certain service for a long time, similar services will be given a higher priority to better meet the user's actual needs.

[0124] In the above process, by combining user preference information, we can accurately identify the target user's emphasis on different service needs, thereby obtaining priority information, and sorting each service need according to the priority information to avoid processing too many tasks at the same time and dispersing resources, ensuring that the service needs that the target user cares about most are met first, making the intelligent recommendation plan more personalized and in line with the user's lifestyle.

[0125] See also Figure 4 In another exemplary embodiment, step 330 may further include the following steps:

[0126] Step 331: If there is at least one subspace in the target space, determine the corresponding space level of each subspace.

[0127] First of all, it should be noted that the target space can include multiple subspaces. For example, the target space can include subspaces such as the living room, kitchen, bedroom, study, and storage room. The space level refers to the relative importance of the subspace in the entire target space.

[0128] Regarding the spatial grade, it can be based on a comprehensive evaluation of the function, importance or usage frequency of each subspace in the target space. For example, the spatial grade of the living room and bedroom may be higher because they are the main places for daily activities or rest, while the spatial grade of the storage room is lower.

[0129] In summary, we can first divide the target space and identify the various subspaces (such as living room, kitchen, bedroom, etc.). Based on factors such as the function of each subspace, the frequency of user activities in the space, and the equipment configuration, we can determine a corresponding space level for each subspace.

[0130] Step 333: assign corresponding weights to the subspaces based on the corresponding spatial levels of the subspaces.

[0131] First of all, it should be noted that the weight is a numerical value assigned according to the spatial level of the subspace. Subspaces with higher spatial levels may receive higher weights and thus be given priority in intelligent analysis.

[0132] Specifically, the weight can be used to indicate the importance of each subspace to the overall target space in the intelligent analysis. The higher the weight, the greater the influence of the subspace on the overall intelligent analysis.

[0133] Step 335 , combining the corresponding weights of each subspace, and performing intelligent analysis on the target space to obtain the corresponding intelligent analysis results of the target space.

[0134] Specifically, the weight of each subspace is combined to conduct an intelligent analysis of the overall target space. This intelligent analysis considers the weight of each subspace and its impact on the overall space, focusing on the equipment operation and environmental conditions in high-weighted subspaces. This allows resources and optimization strategies to be concentrated in high-priority spaces, avoiding unnecessary resource waste. For example, if the living room has a high weight, the intelligent analysis will prioritize its temperature, air quality, and equipment operation, while the lower-weighted storage room will be treated as a secondary analysis target.

[0135] It can be understood that since different subspaces have different weights in the entire target space, the weighted analysis method can be used to more efficiently handle multiple service demands in complex spaces, focusing on analyzing high-weight areas, thereby improving the accuracy and efficiency of the analysis.

[0136] Through the above process, intelligent analysis based on spatial levels and weights can provide personalized optimization solutions for different subspaces, flexibly respond to the service needs of multiple subspaces, reasonably allocate resources, and improve the overall intelligent experience. At the same time, it avoids excessive intervention in unimportant subspaces and ensures efficient resource utilization.

[0137] In another exemplary embodiment, step 330 may include the following steps: based on the service requirements indicated by the target information, determining the target device functions required to meet the service requirements in the target space; calculating based on the target device functions and the device functions of the smart devices in the target space to obtain the corresponding intelligent score of the target space.

[0138] The intelligent analysis results include an intelligent score, which reflects the target space's intelligence level. Specifically, the intelligent score is a quantitative indicator that measures the target space's intelligence level in meeting user service needs. The intelligent score is calculated by comprehensively evaluating the target device's functionality, interoperability between devices, device automation, and energy efficiency.

[0139] The intelligence level can refer to the overall performance of the target space in terms of intelligent functions, equipment integration, automated processing capabilities and service demand satisfaction capabilities. It can be understood that the higher the intelligence score, the higher the intelligence level of the target space, and the better it can meet the user's service needs.

[0140] It should be noted that the target device function is the device function that can meet the service requirements. Specifically, based on the service requirements indicated by the target information, the target device functions required to meet these service requirements can be identified. For example, if the user expects to increase the temperature of the room, the target device functions may include temperature control adjustment function, remote temperature control function and timed temperature control function, etc.

[0141] Then, after clarifying the target device functions, the device functions corresponding to the existing smart devices in the target space can be calculated to determine the intelligence score of the target space. Specifically, if the smart devices in the target space can support the target device functions, the intelligence score will be improved accordingly.

[0142] In one possible implementation, intelligent scoring can match target device capabilities with those of existing smart devices, calculate the degree of match for each device capability, and assign a corresponding score, which is the intelligent score. As can be understood, the higher the score, the higher the intelligent score. For example, a score range and level (e.g., from 0 to 5) can be set based on the target device capabilities corresponding to the service requirements and a predefined scoring system, and the intelligent score can be calculated based on whether the target device capabilities are present.

[0143] In another possible implementation, the service scores of each subspace can be combined to set a score range and level for each core subspace (high weight) and non-core subspace (low weight) according to the service score of each subspace, for example, from 0 to 100. The home's intelligence score can be calculated based on the weights of different core subspaces and non-core subspaces. Specifically, the weighted average or other calculation methods can be used to integrate the intelligence scores of different rooms.

[0144] It should be noted that since the performance of smart devices that can realize the same device functions may vary, even if there are smart devices with the target device functions in the current target space, there may be a situation where the service requirements cannot be met due to insufficient performance.

[0145] To avoid this situation, one possible implementation approach is to recommend a smart device that complements the target device's functionality if a smart device with the target device's functionality already exists within the target space, but that device is insufficient to meet the service requirement. For example, if the service requirement is for smart temperature control, and the existing smart device is a smart thermostat with limited control range, a smart fan or humidifier could be recommended as an additional feature to improve air circulation and comfort, thus comprehensively meeting the user's service needs.

[0146] In the above process, the intelligence level of the target space is reflected by calculating the intelligence score, which provides a method for quantitatively evaluating the intelligence level of the target space, allowing users to clearly understand the intelligence level of their home environment. Users can choose which smart devices to optimize by comparing the intelligence scores, thereby improving the overall intelligence level of the target space.

[0147] See also Figure 5 In an exemplary embodiment, step 350 may further include the following steps: Step 351, based on the target device function and the device functions of the smart devices in the target space, determine at least one candidate device required to meet the service requirements in the target space.

[0148] Specifically, the target device capabilities can be matched with the device capabilities of current smart devices to analyze whether the current smart devices can provide the service requirements required by the user. If the target device capabilities of existing smart devices are found to be insufficient, the target device capabilities are determined to be missing or in need of optimization. Based on these missing or in need of optimization, candidate devices are identified. Candidate devices are smart devices that can complement or enhance the target device capabilities.

[0149] For example, if a user wants to adjust the indoor temperature and there is already a smart thermostat in the target space, its adjustment capabilities and sensor accuracy will be evaluated to determine whether the smart thermostat can meet the service requirements. If the remote temperature control function of the smart thermostat is insufficient, the system will search for smart devices with remote temperature control functions to obtain corresponding candidate devices.

[0150] Step 353 : Determine the recommendation degree of each candidate device for the intelligent score based on the impact of each candidate device being configured in the target space on the intelligent score.

[0151] As mentioned previously, the intelligent analysis results include an intelligent score, which reflects the intelligence level of the target space. As you can imagine, candidate devices that better meet service requirements are more likely to have a higher intelligent score. Based on this, we can analyze the impact of each candidate device on the intelligent score after being deployed in the target space. Based on the candidate device's impact on the intelligent score, the system calculates a recommendation level for each candidate device. The recommendation level measures the candidate device's potential to improve the intelligent score; in other words, a higher recommendation level indicates a greater potential for improving the intelligent score.

[0152] Of course, the recommendation degree of each candidate device for the intelligent score can also be determined by combining the device functions of the candidate device with the priority of the service demand. For example, in a service demand that prioritizes air quality, the candidate device with a higher score for air filtration function will be recommended first, rather than the candidate device with the lowest price.

[0153] Step 355 : Based on the recommendation level of each candidate device, a target device is obtained from the candidate devices, and an intelligent recommendation solution is obtained based on the determined target device.

[0154] Specifically, based on the recommendation level of the candidate devices, the candidate devices with high recommendation levels can be screened out from all candidate devices as target devices. Of course, the screening process not only considers the recommendation level, but also takes into account practical factors such as the price, ease of installation, and compatibility of the candidate devices. For example, among multiple air quality control devices, a candidate device with high cost-effectiveness, comprehensive functions, and easy integration is selected as the final recommended target device. After the target device is determined, an intelligent recommendation plan will be generated. This intelligent recommendation plan can list in detail the configuration list that meets the user's service needs. The configuration list can explain the functions and configuration advantages of each target device and guide the user on how to achieve optimization.

[0155] Through the cooperation of the above embodiments, by analyzing the different impacts of candidate devices on intelligent scores, highly personalized device recommendations can be provided to target users, while ensuring that the recommended target devices can meet the user's service needs, while maximizing the intelligence level of the space; it can not only help users accurately select suitable target devices, but also provide a clear optimization path through quantified intelligent scores and recommendation levels, thereby achieving continuous optimization and improvement of the intelligence level of the target space.

[0156] In another exemplary embodiment, step 350 may also include the following steps: if the intelligent recommendation scheme includes multiple target devices, determine the importance of each target device in meeting the service needs; determine the recommendation order according to the corresponding importance of each target device, and recommend each target device in the intelligent recommendation scheme according to the recommendation order.

[0157] First of all, it should be noted that the degree of importance refers to the relative size of the contribution and influence of each target device on the realization of the service demand in the process of meeting the service demand. The degree of importance can reflect the necessity of each target device in the overall intelligent recommendation plan.

[0158] Specifically, the importance can be comprehensively considered in combination with functional matching (for example, the matching between the device functions of the target device and the target device functions required by the service requirements), scope of influence (for example, the degree of influence of the target device on the overall intelligence level), device performance (for example, the superior the target performance, the higher its importance), and synergy effect (for example, the ability of smart devices to work together), and no specific limitation is given here.

[0159] Based on the importance of each target device, a recommendation order can be assigned to each target device. Specifically, this can be achieved through a sorting algorithm that prioritizes more important target devices. Alternatively, a weighted scoring method can be used, which is not limited here. After determining the recommendation order for each target device, the intelligent recommendation solution will list each target device according to this recommendation order, ensuring that the target user prioritizes the most important target devices when viewing the intelligent recommendation solution.

[0160] Through the above process, the intelligent recommendation solution recommends target devices in a clear order. Target users can quickly identify the most important target devices, reducing decision-making time and improving user experience. This allows users to more effectively purchase and configure devices based on the intelligent recommendation solution.

[0161] In an exemplary embodiment, after step 330, the method may further include the following steps: if a change is detected in the smart device in the target space, re-performing intelligent analysis based on the changed smart device to obtain an updated intelligent analysis result; and regenerating a corresponding intelligent recommendation plan based on the updated analysis result.

[0162] First of all, it should be noted that the status of smart devices in the target space needs to be continuously monitored, including the addition of new devices, removal of devices, device failures or function updates. It can be understood that if the smart devices in the target space change, for example, existing smart devices are dismantled or fail, it may change the service requirements that can be achieved by the target space. For example, the device functions of smart devices in the target space are reconfigured or adjusted, which may make it impossible to achieve the target device functions required for the service requirements.

[0163] Furthermore, intelligent analysis needs to be re-performed for the changed smart devices. Specifically, when a change in a smart device is detected, the specific change content is recorded and identified, so as to re-perform intelligent analysis based on the smart devices in the target space after the change, including evaluating the device functions, compatibility and impact on the overall intelligent score of the current smart device, etc. After re-analysis, an updated intelligent analysis result is generated, which includes a new intelligent score, the functional matching degree of each smart device, and the degree of satisfaction of user service needs.

[0164] Of course, if new target information is collected or user behavior changes, intelligent analysis and updated recommendations will be necessary. Furthermore, based on user feedback, intelligent analysis methods can be improved and optimized. For example, more precise algorithms can be introduced, and more business constraints and trade-offs can be considered to further enhance the quality of intelligent recommendations.

[0165] Then, after the updated intelligent analysis results, an updated intelligent recommendation plan can be generated. The intelligent recommendation plan will adjust the combination of target devices and the recommendation order of each intelligent device according to the new intelligent analysis results to ensure that the user's service needs for the target space are still met.

[0166] Through the above process, through real-time monitoring and analysis, it is possible to dynamically adapt to changes in the target space, ensure that the intelligent recommendation plan always conforms to the current target space, and improve the user experience; moreover, the intelligent recommendation plan obtained after re-analysis can continuously optimize the intelligence level of the target space, ensuring that user service needs are effectively met; in addition, the automatic update process reduces the need for manual intervention by users, and users can more easily enjoy the convenience of the smart home system without having to worry about configuration problems caused by device changes.

[0167] See also Figure 6 , the embodiment of the present application provides a solution recommendation method, which is applicable to electronic devices, for example, the electronic device can be Figure 1 The user terminal 110 in the implementation environment shown can also be a smart device 130 with a display function. The hardware structure of the electronic device can be as follows Figure 2 shown.

[0168] In the following method embodiments, for ease of description, the execution subject of each step of the method is taken as an electronic device as an example for illustration, but this does not constitute a specific limitation.

[0169] like Figure 6 As shown, the method may include the following steps:

[0170] Step 410: Display the recommendation page.

[0171] Among them, the recommendation page is a page that provides intelligent analysis for target users and is used to display the intelligent analysis results of the target space; the intelligent analysis is based on the target information and the smart devices under the target space; the target information is the basis of the intelligent analysis and is used to indicate at least one service requirement that the target user expects the target space to meet.

[0172] Regarding service requirements, they are the goals that users expect to achieve in the target control. Service requirements may include environmental adjustment (such as temperature and humidity), safety assurance (such as security monitoring), lighting management, energy optimization, etc., which are not limited here.

[0173] Regarding target users, they refer to users who have service needs for the target space. The target space is the physical space that the target user hopes to manage and serve through smart devices. It can be a space where multiple smart devices are configured.

[0174] Step 430: Display the intelligent recommendation solution on the recommendation page.

[0175] The intelligent recommendation solution is used to recommend target devices to target users to meet service requirements. Target devices are determined based on intelligent analysis results and are required to meet service requirements. The intelligent recommendation solution is generated by intelligently analyzing target information and the smart devices in the target space, and then determining the target devices required to meet service requirements based on the intelligent analysis results.

[0176] Figure 6a A specific implementation diagram of a recommendation page is shown, such as Figure 6a As shown, Figure 6 a1 is the intelligent analysis result page of the target space, such as Figure 6 As shown in a1, the bedroom's intelligence score of 231 points, the specific smart device details of the target space, and the trigger entrance 6a2 of the intelligent recommendation plan are displayed; click the trigger entrance of the intelligent trigger plan to enter the intelligent recommendation plan page 6a3, on which the target devices required to meet the service needs of the target user are displayed, including the G3 camera, smart thermostat, and Knight switch Q1. In addition, the degree of influence of each target device on the bedroom's intelligence score can also be viewed.

[0177] Through the above process, the recommendation page can provide the target user with a visual intelligent analysis display page, on which the target user can view the intelligent analysis results of the target space, the intelligent devices in the target space and their satisfaction with service needs. Users can understand the intelligence level of the target space more quickly and accurately, thereby enhancing the effectiveness of information communication.

[0178] In an exemplary embodiment, step 430 may further include the following steps: in response to a purchase operation of the target device recommended by the intelligent recommendation solution, displaying a purchase page corresponding to the target device, the purchase page being used to provide the user with a purchase entry for the target device.

[0179] The purchase operation is used to purchase the target device. If the user desires to purchase the target device, the user can trigger the purchase operation on the target device, enter the purchase page corresponding to the target device, and purchase the target device.

[0180] Regarding the purchase entrance, it may refer to a purchase channel link for purchasing the target device, such as a direct purchase link from the device manufacturer, an authorized e-commerce platform link, or other channel link, which is not limited here.

[0181] Please refer to Figure 6a ,like Figure 6 As shown in a1, the knight switch Q1 and the purchase entrance 6a4 are displayed in the intelligent recommendation solution page 6a3. If the user selects the knight switch Q1 and clicks the purchase entrance 6a4, he can jump to the corresponding purchase channel link.

[0182] Through the above process, users can jump directly from the recommendation page to the purchase page, providing users with a convenient purchasing experience without the need for additional search, improving user decision-making efficiency, and effectively shortening the purchase path. In addition, the smooth connection between intelligent recommendation plans and purchase operations provides users with a one-stop intelligent configuration and purchase service experience.

[0183] In an exemplary embodiment, step 430 may further include the following steps: if it is detected that the target device does not exist in the target space, recommending the target device in the intelligent recommendation scheme.

[0184] It can be understood that the target device is a device that can meet the user's service needs for the target space. If the target device is not in the target space, the missing target device can be automatically recommended to help the user ensure that the intelligent configuration of its target space is more comprehensive and meets service needs.

[0185] Please refer to Figure 6a ,like Figure 6 As shown in a1, the intelligent recommendation solution page 6a3 shows the target devices that need to be configured to meet the service requirements for the target user, including the G3 camera, the smart thermostat, and the Knight switch Q1. In addition, the influence of each target device on the intelligent score of the bedroom can also be viewed.

[0186] Through the above process, users can receive timely reminders when the target device is missing, reducing the time cost of information retrieval and decision-making.

[0187] In an exemplary embodiment, after step 430, the method may further include the following steps: if a change is detected in the smart device in the target space, obtaining an updated intelligent analysis result; the updated intelligent analysis result is obtained by re-intelligent analysis based on the changed smart device; displaying the updated intelligent analysis result on the recommendation page, and obtaining a regenerated intelligent recommendation plan, and displaying the regenerated intelligent recommendation plan on the recommendation page.

[0188] First of all, it should be noted that the smart devices configured in the target space can be monitored regularly or in real time, including the addition of new devices, removal of devices, device failures or function updates. It can be understood that if the smart devices in the target space change, for example, existing smart devices are dismantled or fail, it may change the service requirements that can be achieved by the target space. For example, the device functions of the smart devices in the target space are reconfigured or adjusted, which may make it impossible to achieve the target device functions required for the service requirements.

[0189] Furthermore, intelligent analysis needs to be re-performed for the changed smart devices. Specifically, when a change in a smart device is detected, the specific change content is recorded and identified, so as to re-perform intelligent analysis based on the smart devices in the target space after the change, including evaluating the device functions, compatibility and impact on the overall intelligent score of the current smart device, etc. After re-analysis, an updated intelligent analysis result is generated, which includes a new intelligent score, the functional matching degree of each smart device, and the degree of satisfaction of user service needs.

[0190] Then, the updated intelligent analysis results can be displayed on the recommendation page to ensure that users can clearly understand the current status and changes of the target space. Based on the updated intelligent analysis results, the system will generate a new intelligent recommendation plan and display the intelligent recommendation plan on the recommendation page.

[0191] Through the above process, the recommendation page is automatically adjusted according to the updated intelligent analysis results, so that users can intuitively view the changes in the smart devices on the target page and obtain new intelligent recommendation solutions in a timely manner.

[0192] Figure 7 This is a schematic diagram of a specific implementation of a solution recommendation method in an application scenario. The application scenario can be a smart home scenario. Figure 1In the implementation environment shown. Among them. The target information can be obtained through the smart device 130, the gateway 150 or the server 170. The target information can indicate the service requirements that the target user expects the target space to meet, thereby performing intelligent analysis based on the target information and the smart device 130 under the target space to obtain an intelligent analysis result; and then determining the target device that needs to be configured to meet the service requirements based on the intelligent analysis result, and generating a corresponding intelligent recommendation solution. Furthermore, a recommendation page can be displayed through the user terminal 110 or the smart device 130 with a display function. The recommendation page is used to display the intelligent analysis results of the intelligent analysis of the target space, and then the intelligent recommendation solution is displayed on the recommendation page. The intelligent recommendation solution is used to recommend the target device that needs to be configured to meet the service requirements to the target user.

[0193] Specifically, through step 801, the target information input by the target user is obtained.

[0194] Target information may include: Room information: room name, purpose, area, location, etc. Device information: name, model, brand, function, etc. of installed devices. User input data: user requirements, preferences, and personalized options for smart devices. User behavior data: user operation behavior on installed devices, device usage status, device interaction, etc. Environmental data: room temperature, humidity, lighting, and other environmental information. Energy data: device energy consumption, electricity usage, and other related data.

[0195] In step 803, an intelligent score is calculated based on the target information and the intelligent devices in the target room to obtain an intelligent score.

[0196] Through step 805, an intelligent recommendation solution is generated according to the intelligent scoring, and the intelligent recommendation solution includes at least one target device.

[0197] Through step 807, the intelligent recommendation solution is displayed on the recommendation interface provided by the user terminal.

[0198] Through step 809, the user views the intelligent recommendation plan through the user terminal and selects the target device.

[0199] Through step 811, the target device is installed and configured in the target space.

[0200] Through step 813, the intelligent score calculation is re-performed to obtain an updated intelligent score.

[0201] Recalculating the intelligent scoring is typically necessary in the following situations: Data update: When the system collects new data or the target user's behavior changes, the scoring needs to be recalculated and the device recommendation results updated to reflect the latest situation. User demand changes: When the target user's service needs change, the intelligent scoring and intelligent recommendation solutions need to be re-optimized based on the new service needs to meet the target user's new service needs. Improved algorithms and models: The accuracy and effectiveness of the scoring and device recommendation results can be further improved by improving the scoring algorithm, updating the data processing method, or introducing new optimization methods.

[0202] Through step 815, the updated intelligent recommendation solution is displayed on the recommendation page.

[0203] Specifically, based on the updated intelligent scores and the target user's service needs, the intelligent recommendation plan will be adjusted based on the recalculated intelligent scores. The order of target devices recommended in the intelligent recommendation plan can be optimized based on the new intelligent scores and evaluation metrics. Regarding the user interface display: The recommendation page will be updated to ensure that users can intuitively understand the updated information and easily select and operate the target device.

[0204] For example, consider a family who wishes to create a smart living room. The user enters the living room's size and functional requirements through the user terminal. The system then performs an intelligent analysis and automatically calculates the living room's intelligence score. Assuming the living room's intelligence score is high, the system recommends devices such as smart lights, smart speakers, and smart thermostats for a better lighting, audio, and temperature control experience. Users can view the recommended devices through the terminal and purchase them directly through the links provided on the recommendation page or through the shopping cart. After device installation, the server updates the intelligence score based on user actions and usage to further enhance the smart experience and satisfaction.

[0205] It should be noted that this solution recommendation method is not only applicable to smart home scenarios. It can also provide users with targeted, personalized scenario-based services such as smart fitness solutions and smart entertainment solutions based on their interests and preferences, combined with intelligent scoring. Some configuration options are even provided to the user end, allowing users to flexibly adjust the weights of different dimensions of the evaluation system according to their needs, adapting to the personalized preferences of different users and optimizing the accuracy of recommendations.

[0206] In this application scenario, first, by combining intelligent scoring with user needs, users are provided with personalized, precise smart device recommendations. This ensures users can choose the most appropriate smart device based on their needs and preferences, avoiding the purchase of unnecessary or incompatible devices. Second, users can use these recommendations to implement scenario-based smart layouts, improving their quality of life and convenience. By recommending suitable smart devices, users can expand and enrich their home's smart features, such as smart lighting, smart speakers, and smart security systems. This not only enhances the home's intelligence level but also enables interoperability between devices, creating a more complete smart home ecosystem. Third, through intelligent scoring and device recommendations, the solution simplifies the smart device purchasing process. Users no longer need to spend extensive time and effort researching different devices; instead, they can directly select the appropriate device based on the recommendations and purchase it. This saves users time and effort, while also reducing the burden of purchasing. Fourth, by providing personalized device recommendations and intelligent scoring services, the solution meets users' individual needs, enhancing their smart experience and satisfaction. Users can choose the appropriate smart device based on their life scenarios and preferences, implementing intelligent scenario-based services, improving their quality of life and comfort. Fifth, the recommendation page improves merchants' sales efficiency by providing precise, intelligent recommendations. Merchants can provide targeted product recommendations based on users' personalized needs and intelligent ratings, improving sales accuracy and success rates.

[0207] 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.

[0208] The following are embodiments of the device of the present application, which can be used to perform the solution recommendation method involved in the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the method embodiment of the solution recommendation method involved in the present application.

[0209] See also Figure 8 In an embodiment of the present application, a solution recommendation device 900 is provided, including but not limited to: an information acquisition module 910, an intelligent analysis module 930, and a solution generation module 950.

[0210] The information acquisition module 910 is used to acquire target information; the target information is used to indicate at least one service requirement that the target user expects the target space to satisfy.

[0211] The intelligent analysis module 930 is used to perform intelligent analysis based on the target information and the intelligent devices in the target space to obtain intelligent analysis results.

[0212] The solution generation module 950 is used to determine the target device that needs to be configured to meet the service requirements based on the intelligent analysis results, and generate a corresponding intelligent recommendation solution; the intelligent recommendation solution is used to recommend the target device that needs to be configured to meet the service requirements to the target user.

[0213] In an exemplary embodiment, the target information includes user input information; the information acquisition module 910 is also used to obtain user input information; the user input information is used to determine the service requirements that the target user expects the target space to meet; based on the user input information, the service requirements that the target user expects the target space to meet are determined to obtain the target information.

[0214] In an exemplary embodiment, the target information includes a user tag; the information acquisition module 910 is further used to obtain at least one user tag, and the user tag is used to indicate user characteristics; the user characteristics are used to reflect the service requirements that the target user expects the target space to meet; according to the user tag, the corresponding service requirements are matched for the target space according to the matching rules, and the target information is obtained based on the matched service requirements.

[0215] In an exemplary embodiment, the target information includes user behavior information; the information acquisition module 910 is also used to obtain user behavior information; the user behavior information is analyzed regarding behavioral habits to obtain habit information; the habit information is used to indicate the behavioral habits of the target user; based on the behavioral habits indicated by the habit information, the service requirements that the user expects the target space to meet are determined, and the corresponding target information is obtained.

[0216] In an exemplary embodiment, the target information includes demand auxiliary information, which includes one or more of the energy consumption information of the target space and the spatial environment information of the target space; the demand auxiliary information user indicates the spatial status of the target space; the energy consumption information is used to indicate the energy consumption of the target space, and the spatial environment information is used to indicate the environmental status of the target space; the information acquisition module 910 is also used to obtain the corresponding demand auxiliary information of the target space; based on the demand auxiliary information, the target space is evaluated to determine the spatial status of the target space to be optimized; based on the spatial status to be optimized, the service requirements that the target space is expected to meet are determined, and the corresponding target information is obtained.

[0217] In an exemplary embodiment, the intelligent analysis results include an intelligent score, which is used to reflect the intelligence level of the target space; the intelligent analysis module 910 is also used to determine the target device functions required to meet the service requirements in the target space based on the service requirements indicated by the target information; and calculate based on the target device functions and the device functions of the smart devices in the target space to obtain the corresponding intelligent score of the target space.

[0218] In an exemplary embodiment, the solution generation module 950 is also used to determine at least one candidate device required to meet the service requirements in the target space based on the target device functions and the device functions of the smart devices in the target space; determine the recommendation level of each candidate device for the intelligent score based on the impact of each candidate device being configured in the target space on the intelligent score; based on the corresponding recommendation level of each candidate device, filter out the target device from each candidate device, and obtain an intelligent recommendation solution based on the determined target device.

[0219] In an exemplary embodiment, the intelligent analysis module 930 is also used to obtain priority information for each service demand based on user preference information if the target information indicates that the target user has multiple service demands for the target space; the priority information is used to indicate the corresponding priority level of meeting each service demand; and the target space is intelligently analyzed in combination with the corresponding priority level of each service demand indicated by the priority information to obtain the corresponding intelligent analysis result of the target space.

[0220] In an exemplary embodiment, the intelligent analysis module 930 is also used to determine the corresponding spatial level of each subspace if there is at least one subspace in the target space; assign a corresponding weight to each subspace based on the corresponding spatial level of each subspace; and perform an intelligent analysis of the target space in combination with the corresponding weight of each subspace to obtain the corresponding intelligent analysis result of the target space.

[0221] In an exemplary embodiment, the solution generation module 950 is also used to determine the importance of each target device in meeting service requirements if the intelligent recommendation solution includes multiple target devices; determine the recommendation order based on the corresponding importance of each target device; and recommend each target device in the intelligent recommendation solution according to the recommendation order.

[0222] In an exemplary embodiment, the solution recommendation device 900 is also used to, if a change is detected in the smart device in the target space, re-perform intelligent analysis based on the changed smart device to obtain an updated intelligent analysis result; and regenerate a corresponding intelligent recommendation solution based on the updated analysis result.

[0223] See also Figure 8In an embodiment of the present application, a solution recommendation device 1000 is provided, including but not limited to: a page display module 1010 and a solution display module 1030 .

[0224] Among them, the page display module 1010 is used to display the recommendation page; the recommendation page is used to display the intelligent analysis results of the target space; the intelligent analysis is based on the target information and the smart devices under the target space; the target information is used to indicate at least one service requirement that the target user expects the target space to meet.

[0225] The solution display module 1030 is used to display the intelligent recommendation solution on the recommendation page; the intelligent recommendation solution is used to recommend the target device that needs to be configured to meet the service requirements for the target user; the target device is determined based on the intelligent analysis results and needs to be configured to meet the service requirements.

[0226] In an exemplary embodiment, the solution display module 1030 is further used to display a purchase page corresponding to the target device in response to a purchase operation of the target device recommended by the intelligent recommendation solution, and the purchase page is used to provide the user with a purchase entry for the target device.

[0227] In an exemplary embodiment, the solution display module 1030 is further configured to recommend the target device in the intelligent recommendation solution if it is detected that the target device does not exist in the target space.

[0228] In an exemplary embodiment, the solution recommendation method 1000 is also used to obtain updated intelligent analysis results if a change is detected in the smart device in the target space; the updated intelligent analysis results are obtained by re-intelligent analysis based on the changed smart device; the updated intelligent analysis results are displayed on the recommendation page, and the regenerated intelligent recommendation solution is obtained, and the regenerated intelligent recommendation solution is displayed on the recommendation page.

[0229] It should be noted that the solution recommendation device provided in the above embodiment only uses the division of the above-mentioned functional modules as an example when making solution recommendations. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the solution recommendation device will be divided into different functional modules to complete all or part of the functions described above.

[0230] In addition, the solution recommendation device and solution recommendation method provided in the above embodiments belong to the same concept, wherein the specific manner in which each module performs operations has been described in detail in the method embodiment and will not be repeated here.

[0231] See also Figure 10In an embodiment of the present application, an electronic device 4000 is provided. The electronic device 4000 may include: a desktop computer, a laptop computer, a server, a gateway, etc.

[0232] exist Figure 10 In the embodiment, the electronic device 4000 includes at least one processor 4001 and at least one memory 4003.

[0233] Data exchange between the processor 4001 and the memory 4003 can be achieved via at least one communication bus 4002. The communication bus 4002 may include a path for transmitting data between the processor 4001 and the memory 4003. The communication bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, for example. The communication bus 4002 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is used in the figure, but this does not mean that there is only one bus or only one type of bus.

[0234] Optionally, the electronic device 4000 may further include a transceiver 4004, which may be used for data exchange between the electronic device and other electronic devices, such as data transmission and / or data reception. It should be noted that in actual applications, the number of transceivers 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present application.

[0235] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 4001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0236] The memory 4003 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store a computer program in the form of instructions or data structures and can be accessed by the electronic device 400, but is not limited to these.

[0237] The memory 4003 stores a computer program, and the processor 4001 can read the computer program stored in the memory 4003 through the communication bus 4002 .

[0238] The computer program is executed by one or more processors 4001 to implement the solution recommendation method in the above embodiments.

[0239] In addition, an embodiment of the present application provides a storage medium on which a computer program is stored. The computer program is executed by one or more processors to implement the solution recommendation method as described above.

[0240] In an embodiment of the present application, a computer program product is provided, including a computer program, which is executed by one or more processors to implement the solution recommendation method described above.

[0241] Compared with related technologies, this solution is based on target information and can determine the target user's service needs for the target space. It can also perform intelligent analysis based on the target information and the various smart devices in the target space, thereby determining how to configure and manage smart devices to optimize the intelligence level of the target space, generate corresponding intelligent solutions, recommend target devices to users, and meet the target user's service needs through the target devices, thereby reducing the difficulty for users to configure smart devices for the target space.

[0242] The above description is only part of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A solution recommendation method, characterized in that: include: Get target information; The target information is used to indicate at least one service requirement that the target user expects the target space to satisfy; Perform intelligent analysis based on the target information and the intelligent devices in the target space to obtain intelligent analysis results; Determine the target device that needs to be configured to meet the service requirements based on the intelligent analysis results, and generate a corresponding intelligent recommendation plan; The intelligent recommendation scheme is used to recommend the target device that needs to be configured to meet the service requirements to the target user.

2. The method according to claim 1, characterized in that The target information includes user input information; The obtaining of target information includes: Acquire the user input information; the user input information is used to determine the service requirements that the target user expects the target space to meet; According to the user input information, the service demand that the target user expects the target space to satisfy is determined to obtain the target information.

3. The method according to claim 1, characterized in that The target information includes a user tag; The obtaining of target information includes: Acquire at least one of the user tags, where the user tag is used to indicate a user feature; the user feature is used to reflect a service requirement that the target user expects the target space to satisfy; According to the user tag, the target space is matched with corresponding service requirements according to matching rules, and the target information is obtained based on the matched service requirements.

4. The method according to claim 1, characterized in that The target information includes user behavior information; The obtaining of target information includes: Obtaining the user behavior information; Analyzing the behavior habits of the user behavior information to obtain habit information; the habit information is used to indicate the behavior habits of the target user; Based on the behavior habit indicated by the habit information, the service demand that the user expects the target space to satisfy is determined, and corresponding target information is obtained.

5. The method according to claim 1, characterized in that The target information includes demand auxiliary information, and the demand auxiliary information includes one or more of energy consumption information of the target space and spatial environment information of the target space; the demand auxiliary information indicates the spatial state of the target space; the energy consumption information is used to indicate the energy consumption of the target space; The space environment information is used to indicate the environment condition of the target space; The obtaining of target information includes: Acquire the required auxiliary information corresponding to the target space; Performing a state evaluation on the target space based on the demand auxiliary information to determine a space state of the target space to be optimized; Based on the space state to be optimized, the service requirements that the target space is expected to meet are determined, and corresponding target information is obtained.

6. The method according to claim 1, characterized in that The intelligent analysis result includes an intelligent score, and the intelligent score is used to reflect the intelligence level of the target space; The intelligent analysis is performed based on the target information and the intelligent devices in the target space to obtain intelligent analysis results, including: Based on the service requirement indicated by the target information, determining a target device function required to meet the service requirement in the target space; A calculation is performed based on the target device function and the device function of the smart device in the target space to obtain a corresponding intelligent score of the target space.

7. The method according to claim 6, characterized in that Determining the target device that needs to be configured to meet the service requirements based on the intelligent analysis results, and generating a corresponding intelligent recommendation solution, includes: Determine, according to the target device function and the device function of the smart device in the target space, at least one candidate device required to meet the service requirement in the target space; Determining the degree of recommendation of each candidate device for the intelligent score according to the influence of each candidate device being configured in the target space on the intelligent score; Based on the corresponding recommendation degree of each candidate device, the target device is screened from the candidate devices, and the intelligent recommendation solution is obtained based on the determined target device.

8. The method according to claim 1, characterized in that The intelligent analysis is performed based on the target information and the intelligent devices in the target space to obtain intelligent analysis results, including: If the target information indicates that the target user has multiple service requirements for the target space, priority information for each of the service requirements is obtained according to the user preference information; the priority information is used to indicate the priority level of satisfying each of the service requirements; Combined with the corresponding priority levels of the service demands indicated by the priority information, the target space is intelligently analyzed to obtain the corresponding intelligent analysis results of the target space.

9. The method according to claim 1, characterized in that The intelligent analysis is performed based on the target information and the intelligent devices in the target space to obtain intelligent analysis results, including: If there is at least one subspace in the target space, determining the space level corresponding to each subspace; Based on the corresponding spatial level of each subspace, assigning a corresponding weight to each subspace; In combination with the corresponding weights of each of the subspaces, the target space is intelligently analyzed to obtain the corresponding intelligent analysis results of the target space.

10. The method according to any one of claims 1 to 9, characterized in that: Based on the intelligent analysis result, determining the target device that needs to be configured to meet the service demand, and generating a corresponding intelligent recommendation solution, includes: If the intelligent recommendation scheme includes multiple target devices, determining the importance of each of the target devices in satisfying the service demand; Determining a recommendation order according to the respective importance of each of the target devices; In the intelligent recommendation scheme, each of the target devices is recommended according to the recommendation order.

11. The method according to any one of claims 1 to 9, characterized in that: After performing intelligent analysis based on the target information and the intelligent devices in the target space to obtain the intelligent analysis results, the method further includes: If it is detected that the smart device in the target space has changed, re-performing intelligent analysis according to the changed smart device to obtain an updated intelligent analysis result; Based on the updated analysis results, a corresponding intelligent recommendation solution is regenerated.

12. A solution recommendation method, characterized in that: include: Display the recommended page; The recommendation page is used to display the intelligent analysis results of the intelligent analysis of the target space; The intelligent analysis is performed based on target information and intelligent devices in the target space; The target information is used to indicate at least one service requirement that the target user expects the target space to satisfy; Displaying intelligent recommendation solutions on the recommendation page; The intelligent recommendation scheme is used to recommend target devices that need to be configured to meet the service requirements to the target user; The target device is a device determined based on the intelligent analysis result and configured to meet the service requirements.

13. The method according to claim 12, characterized in that The intelligent recommendation solution is displayed on the recommendation page, including: In response to a purchase operation for a target device recommended by the intelligent recommendation solution, a purchase page corresponding to the target device is displayed, wherein the purchase page is used to provide the user with a purchase entry for the target device.

14. The method according to claim 13, characterized in that Before responding to the purchase operation of the target device recommended by the intelligent recommendation solution, the method further includes: If it is detected that the target device does not exist in the target space, the target device is recommended in the intelligent recommendation scheme.

15. The method according to any one of claims 12 to 14, characterized in that After the intelligent recommendation solution is displayed on the recommendation page, the method further includes: If it is detected that the smart device in the target space has changed, an updated intelligent analysis result is obtained; the updated intelligent analysis result is obtained by re-analyzing the smart device after the change; The updated intelligent analysis result is displayed on the recommendation page, and a regenerated intelligent recommendation plan is obtained, and the regenerated intelligent recommendation plan is displayed on the recommendation page.

16. An electronic device, characterized in that: include: at least one processor and at least one memory, wherein: The memory has computer-readable instructions stored thereon; The computer-readable instructions are executed by one or more of the processors so that the electronic device implements the solution recommendation method according to any one of claims 1 to 15.

17. A storage medium having computer-readable instructions stored thereon, characterized in that: The computer-readable instructions are executed by one or more processors to implement the solution recommendation method according to any one of claims 1 to 15.

18. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 15 are implemented.

Images