Household appliance function recommendation method, system and device and storage medium

Abstract

The invention discloses a household appliance function recommendation method, system and device and a storage medium, and relates to the field of smart home, and the method comprises the steps: obtaining the environment information of a target household appliance in response to a power-on instruction of the target household appliance; the environment information comprises geographical location information and equipment information; determining an operation mode recommendation list of the target household appliance according to the environment information; and providing an operation mode recommendation list of the target household appliance for a client associated with the target user. The operation mode most suitable for the current environment is recommended to the user by intelligently analyzing the geographic position information and the equipment information, and the intelligent level of the household appliances is improved.

Description

Technical Field

[0001] This invention relates to the field of smart homes, specifically to a method, system, device, and storage medium for recommending home appliance functions. Background Technology

[0002] In the fiercely competitive home appliance industry, manufacturers are constantly developing and integrating numerous innovative features to meet diverse consumer needs. However, this diversification of features also brings complexity to the user experience, often leaving users confused when faced with a multitude of options. To address this issue, feature recommendation algorithms have emerged, aiming to simplify the user's selection process in an intelligent way.

[0003] Currently, the function recommendation methods used in the home appliance industry mainly rely on user-inputted personal information, interactive Q&A, and other data for personalized recommendations. While these methods improve the user experience to some extent, they typically require users to actively provide data, increasing the user's burden. Summary of the Invention

[0004] The main objective of this invention is to provide a method, system, device, and storage medium for recommending home appliance functions. By intelligently analyzing geographic location information and device information, it recommends the most suitable operating mode for the current environment to users, thereby improving the intelligence level of home appliances.

[0005] To achieve the above objectives, the embodiments of this application provide the following technical solutions:

[0006] According to a first aspect of the embodiments of this application, a method for recommending home appliance functions is provided, the method comprising:

[0007] In response to a power-on command for a target home appliance, the environmental information of the target home appliance is acquired; the environmental information includes geographical location information and device information.

[0008] Based on the environmental information, a recommended list of operating modes for the target home appliances is determined.

[0009] Provide the target user's associated client with a list of recommended operating modes for the target home appliance.

[0010] Optionally, the environmental information further includes historical usage data of the target home appliance; the step of determining a recommended list of operating modes for the target home appliance based on the environmental information includes:

[0011] The most recently used operating mode from the historical usage data of the target home appliance is selected as the first item in the recommended operating mode list.

[0012] Based on the geographic location information and device information, determine the remaining items in the recommended operating mode list, excluding the first item.

[0013] Optionally, determining the recommended list of operating modes for the target home appliance based on the environmental information includes:

[0014] The associated devices are determined based on the geographic location information, and the associated devices include devices that are associated with the target home appliance.

[0015] The operating mode of the associated device is obtained from the historical usage data of the associated device;

[0016] The recommended list of operating modes is determined based on the operating modes of the associated devices and the optional operating modes of the target home appliances.

[0017] Optionally, determining the associated device based on the geographic location information includes:

[0018] The first home appliance whose distance from the target home appliance meets a set range is identified as the associated device, and the first home appliance is of the same type as the target home appliance.

[0019] Optionally, determining the associated device based on the geographic location information includes:

[0020] The second home appliance in the associated home appliance group is obtained based on the geographical location information and the historical usage data of the target home appliance. The second home appliance has a communication connection with the target home appliance.

[0021] The second home appliance is identified as the associated device.

[0022] Optionally, the environmental information further includes time information; the step of determining the recommended list of operating modes for the target home appliance based on the environmental information includes:

[0023] Based on the geographic location information and the time information, the habitual characteristics of the target area at the target time are obtained. The habitual characteristics are used to characterize the habits of the target area at the target time. The target area is the area corresponding to the geographic location information, and the target time is the time corresponding to the time information.

[0024] The selectable operating modes of the target home appliance are determined based on the device information;

[0025] Based on the aforementioned habitual characteristics and the selectable operating modes of the target home appliance, a recommended list of operating modes is determined.

[0026] Optionally, the habitual features include at least one of the following: regional climate information; user habit information.

[0027] Optionally, the environmental information also includes historical device usage data of other users in the target area; determining the recommended list of operating modes for the target home appliances based on the environmental information includes:

[0028] Extract user behavior characteristics from the device history usage data of other users in the target region;

[0029] Based on the user behavior characteristics, several categories of user groups are obtained;

[0030] A recommended list of operating modes for the target home appliances is determined based on the user group category and the corresponding historical device usage data.

[0031] According to a second aspect of the embodiments of this application, a method for recommending home appliance functions is provided, including:

[0032] In response to the power-on operation of the target user, the environmental information of the target home appliance is sent to the server so that the server can determine a recommended list of operating modes for the target home appliance based on the environmental information. The environmental information includes geographical location information and device information.

[0033] Receive the recommended list of operating modes for the target home appliance returned by the server, and display the recommended list of operating modes.

[0034] Optionally, the method further includes:

[0035] Obtain the target user's modification operations on the control parameters of the running modes in the running mode recommendation list;

[0036] A custom operating mode for the target home appliance is generated based on the modified control parameters.

[0037] According to a third aspect of the embodiments of this application, a home appliance function recommendation system is provided, the system comprising:

[0038] The information acquisition module is used to acquire environmental information of the target home appliance in response to a power-on command; the environmental information includes geographical location information and device information.

[0039] The recommendation list determination module is used to determine a recommendation list of operating modes for the target home appliances based on the environmental information.

[0040] The recommendation module is used to provide a list of recommended operating modes of the target home appliances to the clients associated with the target user.

[0041] According to a fourth aspect of the embodiments of this application, a home appliance function recommendation system is provided, comprising:

[0042] The sending module is used to send the environmental information of the target home appliance to the server in response to the power-on operation of the target user, so that the server can determine the recommended list of operating modes of the target home appliance based on the environmental information. The environmental information includes geographical location information and device information.

[0043] The display module is used to receive the recommended list of operating modes of the target home appliance returned by the server and display the recommended list of operating modes.

[0044] According to a fifth aspect of the present application, an electronic device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the methods described in the first and second aspects above.

[0045] According to a sixth aspect of the embodiments of this application, a computer-readable storage medium is provided, on which computer-readable instructions are stored, which can be executed by a processor to implement the methods described in the first and second aspects above.

[0046] In summary, this application provides a method, system, device, and storage medium for recommending home appliance functions. By responding to a power-on command for a target home appliance, it acquires the environmental information of the target home appliance; the environmental information includes geographical location information and device information; it determines a recommended list of operating modes for the target home appliance based on the environmental information; and it provides the recommended list of operating modes to a client associated with the target user. Through intelligent analysis of geographical location information and device information, it recommends the most suitable operating mode for the current environment to the user, thereby improving the intelligence level of home appliances. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0048] The structures, proportions, sizes, etc. illustrated in this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed herein, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0049] Figure 1 A flowchart of a method for recommending home appliance functions provided in this application embodiment;

[0050] Figure 2 Flowchart of another method for recommending home appliance functions provided in this application embodiment;

[0051] Figure 3 This is a schematic diagram of the client interface provided in an embodiment of this application;

[0052] Figure 4 This is a schematic diagram of a home appliance function recommendation system provided in an embodiment of this application;

[0053] Figure 5 This is a schematic diagram of another home appliance function recommendation system provided in an embodiment of this application;

[0054] Figure 6 This paper shows a structural diagram of an electronic device provided in an embodiment of this application;

[0055] Figure 7 A diagram of a computer-readable storage medium provided in an embodiment of this application is shown.

[0056] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0058] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0059] Furthermore, in this invention, descriptions involving "first," "second," etc., are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0060] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0061] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are feasible for those skilled in the art. If the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0062] Figure 1 This application illustrates a method for recommending home appliance functions, the method comprising:

[0063] Step 101: In response to the power-on command for the target home appliance, obtain the environmental information of the target home appliance; the environmental information includes geographical location information and device information;

[0064] Step 102: Determine a recommended list of operating modes for the target home appliance based on the environmental information;

[0065] Step 103: Provide the target user's associated client with a list of recommended operating modes for the target home appliance.

[0066] In one possible implementation, the environmental information further includes historical usage data of the target home appliance; in step 102, determining the recommended list of operating modes for the target home appliance based on the environmental information includes: taking the most recently used operating mode from the historical usage data of the target home appliance as the first item in the recommended list of operating modes; and determining the remaining items in the recommended list of operating modes other than the first item based on the geographical location information and the device information.

[0067] To provide an intelligent home appliance function recommendation system, the system automatically recommends the most suitable operating mode to the user based on the target home appliance's environmental information (including geographical location information, device information, and historical usage data).

[0068] Assume a user owns a smart air conditioner equipped with the aforementioned appliance function recommendation method. When the user turns on the smart air conditioner, the system automatically obtains the air conditioner's environmental information, including the user's geographical location (e.g., Beijing), device information (e.g., air conditioner model, installation location), and historical usage data (e.g., the user typically turns on the air conditioner at night and prefers the 26°C cooling mode). Based on this information, the system determines a recommended list of air conditioner operating modes. First, the system uses the user's most recently used operating mode (26°C cooling mode) as the first item in the recommendation list. Then, based on Beijing's current climate (e.g., cold winters) and device information (e.g., the air conditioner is installed in the bedroom), the system recommends the heating mode as the second item and may recommend the energy-saving mode as the third item. The system sends this recommendation list to the user's mobile client, where the user can directly select a mode from the list or have the system automatically select the first item (26°C cooling mode). In this way, the user does not need to manually set the air conditioner mode each time; the system can automatically provide the most suitable recommendation based on environmental changes and user habits, thereby achieving intelligent and personalized appliance control.

[0069] In one possible implementation, step 102, determining the recommended list of operating modes for the target home appliance based on the environmental information, includes:

[0070] Based on the geographic location information, associated devices are determined, including devices that are associated with the target home appliance; the operating modes of the associated devices are obtained from the historical usage data of the associated devices; and a recommended list of operating modes is determined based on the operating modes of the associated devices and the selectable operating modes of the target home appliance.

[0071] In one possible implementation, determining the associated device based on the geographic location information includes: identifying a first home appliance whose distance from the target home appliance meets a set range as the associated device, wherein the first home appliance is of the same type as the target home appliance.

[0072] The home appliance function recommendation method provided in this application utilizes geographic location information to identify associated devices of the same type as the target home appliance, and recommends the operating mode of the target home appliance based on the historical usage data of these associated devices. This improves the accuracy and practicality of the recommendation system by considering the usage patterns of similar devices in similar environments.

[0073] Assuming a user owns a smart washing machine equipped with the aforementioned appliance function recommendation method, when the user turns on the washing machine, the system automatically obtains the washing machine's environmental information, including the user's geographical location (e.g., Shanghai) and device information (e.g., washing machine model, installation location). Based on the geographical location information, the system identifies associated devices of the same type as the target washing machine, located in Shanghai and within a set distance from the user's washing machine. The system retrieves the operating modes of these associated devices from their historical usage data; for example, in winter, most associated devices select a heated washing mode to improve cleaning performance. Then, based on the operating modes of these associated devices and the target washing machine's available operating modes, the system generates a recommendation list, which may include heated washing, water-saving modes, and quick washes. The system sends this recommendation list to the user's mobile client, allowing the user to directly select a mode from the list or have the system automatically select the first item in the recommendation list. In this way, users can choose the most suitable operating mode based on their preferences and environmental conditions, while the system provides an intelligent recommendation based on geographical location and similar device usage data, making appliance use more intelligent and personalized.

[0074] In one possible implementation, determining the associated device based on the geographic location information includes: obtaining a second home appliance in the associated home appliance group based on the geographic location information and the historical usage data of the target home appliance, wherein the second home appliance has a communication connection with the target home appliance; and determining the second home appliance as the associated device.

[0075] The home appliance function recommendation method provided in this application achieves more intelligent and collaborative home appliance operation mode recommendations through communication connections between smart home appliances. This method utilizes the interconnectivity between devices in a smart home system to improve the accuracy and personalization of home appliance operation mode recommendations.

[0076] Assuming a user owns a smart refrigerator equipped with the aforementioned appliance function recommendation method, when the user turns on the smart refrigerator, the system automatically acquires the refrigerator's environmental information, including the user's geographical location and device information. Based on the geographical location information and the refrigerator's historical usage data, the system identifies other smart refrigerators in the associated appliance group that have a communication connection with the user's refrigerator. The system obtains the operating modes of these associated refrigerators from their historical usage data; for example, in summer, most associated refrigerators select energy-saving mode to reduce energy consumption. Then, based on the operating modes of these associated refrigerators and the target refrigerator's available operating modes, the system determines a recommendation list, which may include energy-saving mode, rapid cooling mode, and intelligent preservation mode. The system sends the recommendation list to the user's mobile client, where the user can directly select a mode from the list or have the system automatically select the first item in the recommendation list. In this way, the user's smart refrigerator can intelligently recommend the most suitable operating mode for the current environment and user habits based on the usage modes of other similar refrigerators and its own available modes, achieving intelligent and personalized appliance control.

[0077] In one possible implementation, the environmental information further includes time information; in step 102, determining the recommended list of operating modes for the target home appliance based on the environmental information includes:

[0078] Based on the geographic location information and the time information, the habitual characteristics of the target region at the target time are obtained. The habitual characteristics are used to characterize the habits of the target region at the target time. The target region is the region corresponding to the geographic location information, and the target time is the time corresponding to the time information. Based on the device information, the optional operating modes of the target home appliance are determined. Based on the habitual characteristics and the optional operating modes of the target home appliance, a recommended list of operating modes is determined.

[0079] The home appliance function recommendation method provided in this application uses time information and geographical location information to obtain climate information of the target area, and combines the selectable operating modes of the target home appliance to intelligently recommend the operating mode most suitable for the current climate conditions.

[0080] Assuming a user owns a smart air conditioner equipped with the aforementioned appliance function recommendation method, when the user turns on the smart air conditioner, the system automatically obtains the air conditioner's environmental information, including the user's geographical location (e.g., Beijing) and time information (e.g., 3 PM in summer). Based on the geographical location and time information, the system obtains the climate information for Beijing at 3 PM in summer, such as temperature and humidity. Then, the system determines the air conditioner's available operating modes based on the device information, such as cooling mode, dehumidification mode, and energy-saving mode. Combining the climate information and available operating modes, the system generates a recommendation list, possibly recommending cooling mode as the first choice due to the hot weather. The system sends the recommendation list to the user's mobile client, where the user can directly select a mode from the list or have the system automatically select the first item in the recommendation list. The user's smart air conditioner can intelligently recommend the most suitable operating mode based on the current climate conditions and its available modes, achieving intelligent and personalized appliance control. This method not only improves user comfort but also contributes to energy conservation and emission reduction, aligning with the development trend of smart homes.

[0081] In one possible implementation, the habitual features include at least one of the following: regional climate information; user habit information.

[0082] The home appliance function recommendation method provided in this application combines geographical location information, time information, and user habit information to achieve more accurate and personalized home appliance operation mode recommendations. By combining geographical location and time information, the system can take into account environmental factors such as climate and weather in different regions and time periods, and recommend the home appliance operation mode most suitable for the current environmental conditions.

[0083] Assume a user owns a smart air conditioner equipped with the aforementioned appliance function recommendation method. When the user turns on the smart air conditioner, the system automatically obtains the air conditioner's environmental information, including the user's geographical location (e.g., Shanghai) and time information (e.g., 3 PM in summer). Based on the geographical location and time information, the system obtains user habit information for Shanghai at 3 PM in summer, such as most users preferring lower indoor temperatures. Then, the system determines the air conditioner's available operating modes based on the device information, such as cooling mode, dehumidification mode, and energy-saving mode. Combining user habit information and available operating modes, the system generates a recommendation list, potentially recommending cooling mode as the first choice to meet the user's need for a cool indoor environment. The system sends this recommendation list to the user's mobile client, where the user can directly select a mode from the list or have the system automatically select the first item in the recommendation list. The user's smart air conditioner can intelligently recommend the most suitable operating mode based on current environmental conditions and the user's personal habits, achieving intelligent and personalized appliance control.

[0084] In one possible implementation, the environmental information further includes historical device usage data of other users in the target area; in step 102, determining the recommended list of operating modes for the target home appliance based on the environmental information includes: extracting user behavior characteristics from the historical device usage data of other users in the target area; classifying the user behavior characteristics to obtain several categories of user groups; and determining the recommended list of operating modes for the target home appliance based on the categories of the user groups and the corresponding historical device usage data.

[0085] The home appliance function recommendation method provided in this application analyzes the historical usage data of other users' devices in the target area, extracts user behavior characteristics, and classifies users based on these characteristics, thereby providing more accurate home appliance operation mode recommendations for specific user groups.

[0086] Assume a user owns a smart refrigerator equipped with the aforementioned appliance function recommendation method. When the user turns on the smart refrigerator, the system automatically acquires the refrigerator's environmental information, including the user's geographical location and time. Based on the geographical location and time information, the system extracts user behavior characteristics from the historical usage data of other users' smart refrigerators in the target area. Then, the system categorizes users based on these characteristics, identifying several user groups, such as frequent shoppers and infrequent shoppers. The system determines a recommendation list based on these user group categories and corresponding device historical usage data. For example, for frequent shoppers, the recommendation list might include "energy-saving mode" and "rapid cooling mode," while for infrequent shoppers, it might include "holiday mode" and "intelligent preservation mode." The system sends the recommendation list to the user's mobile client, allowing the user to directly select a mode from the list or have the system automatically select the first item in the list. In this way, the user's smart refrigerator can intelligently recommend the most suitable operating mode based on the usage habits of other users in the target area and its own available modes, achieving intelligent and personalized appliance control. This method not only improves user comfort but also contributes to energy conservation and emission reduction, aligning with the development trend of smart homes.

[0087] Figure 2 A method for recommending home appliance functions is shown, applied to a client, the method comprising:

[0088] Step 201: In response to the target user's power-on operation, send the environmental information of the target home appliance to the server so that the server can determine the recommended list of operating modes of the target home appliance based on the environmental information. The environmental information includes geographical location information and device information.

[0089] Step 202: Receive the recommended list of operating modes for the target home appliance returned by the server, and display the recommended list of operating modes.

[0090] In one possible implementation, the method further includes: obtaining the target user's modification operation of the control parameters in the operating mode recommendation list; and generating a custom operating mode for the target home appliance based on the modified control parameters.

[0091] In one possible implementation, the method further includes: setting the custom operating mode as the first item in the recommended operating mode list of the target home appliance, and determining the remaining items in the recommended operating mode list of the target home appliance other than the first item based on the geographical location information and device information.

[0092] The home appliance function recommendation method provided in this application allows users to modify the control parameters of the operating mode according to their own needs and preferences, generating a custom operating mode and improving the personalization of home appliance use. The system can learn user preferences based on their modifications to the operating modes in the recommended list and consider these preferences in future recommendations.

[0093] Assume a user owns a smart air conditioner with the aforementioned appliance function recommendation method. When the user turns on the smart air conditioner, the system automatically obtains the air conditioner's environmental information, including the user's geographical location and device information. Based on this environmental information, the system determines a recommended list of air conditioner operating modes. First, the system uses the user's previously created custom operating mode (e.g., 26°C cooling mode with medium fan speed) as the first item in the recommendation list. Then, based on the geographical location and device information, the system determines the other items in the recommendation list besides the custom mode, such as energy-saving mode and dehumidification mode. The system then sends this recommendation list to the user's mobile client.

[0094] Users can choose a custom mode or select other recommended modes based on their current environment and needs, or modify the control parameters (such as temperature and fan speed) in the recommended modes. If a user modifies the control parameters in a recommended mode, for example, adjusting the temperature from 26℃ to 24℃, the system generates a new custom operating mode based on the user's changes. This new custom mode can then be used as the first item in the recommendation list in future use. In this way, the user's smart air conditioner can intelligently recommend the most suitable operating mode based on the user's personalized needs and environmental conditions, while allowing the user to adjust it according to their preferences, achieving intelligent and personalized home appliance control. This method not only improves user comfort but also helps improve energy efficiency and reduce emissions.

[0095] The method for recommending home appliance functions provided in the embodiments of this application will be described in detail below.

[0096] Phase 1: In response to the power-on command of the target home appliance, obtain the environmental information of the target home appliance; the environmental information includes geographical location information, device information, historical usage data of the target home appliance, time information, and historical usage data of other users' devices in the target area.

[0097] Geographic location information: The system first collects the geographic location information of home appliances, which typically includes the latitude and longitude coordinates of the devices. This information is crucial for cloud servers, as they can use these coordinates to determine the city or region where the devices are located. This helps the servers obtain local climate data, environmental standards, and potential energy use policies, thereby providing more accurate operating mode recommendations for home appliances.

[0098] Device Information: The system also collects model information for home appliances. This model information allows the cloud server to identify the brand and model of the device, and then query all the operating modes and functions supported by that device. This is crucial for providing customized services and ensuring that devices operate at their optimal condition.

[0099] Historical Usage Data: To better understand user habits and preferences, the system also collects historical usage data for the target home appliances. This data includes the user's past selected modes, temperature settings, and usage frequency. This data helps the system learn user preferences and provide more personalized recommendations in the future.

[0100] Time information: Time information is also part of environmental information, including the current date and time. This information is crucial for determining a user's potential needs; for example, a user's needs for home appliances may vary at different times of day or in different seasons.

[0101] Historical usage data from other users: To further enhance the accuracy of recommendations, the system also collects historical usage data of home appliances from other users in the same region. By analyzing this data, the system can identify common or trending usage patterns, which can be used as part of the recommendation algorithm to provide operating patterns that are more in line with local habits.

[0102] Phase Two: The cloud server will process the collected environmental information and, based on this data, recommend the most suitable operating mode for home appliances to the user. The following is a detailed explanation of the solution:

[0103] The first option: Recommendation based on recent usage patterns.

[0104] The most recently used operating mode from the historical usage data of the target home appliance is selected as the first item in the recommended operating mode list; the remaining items in the recommended operating mode list, excluding the first item, are determined based on the geographical location information and device information.

[0105] The cloud server uses the most recent operating mode from the target home appliance's historical usage data as the first item in the recommendation list. This method provides users with familiar choices based on their recent behavior.

[0106] The second option: Recommended associated device mode.

[0107] The associated device is determined based on the geographic location information. The associated device is of the same type as the target home appliance, and the distance between the associated device and the target home appliance meets a set range. The operating mode of the associated device is obtained from the historical usage data of the associated device. The recommended list of operating modes is determined based on the operating mode of the associated device and the selectable operating modes of the target home appliance.

[0108] The third option: Recommended appliance group with communication connectivity.

[0109] Based on the geographic location information and the historical usage data of the target home appliance, the home appliances in the associated home appliance group are obtained, and there is a communication connection between the home appliances in the associated home appliance group and the target home appliance; a recommended list of operating modes is determined based on the operating modes of the home appliances in the associated home appliance group and the selectable operating modes of the target home appliance.

[0110] The fourth scenario: climate information recommendation.

[0111] Based on the geographic location information and the time information, obtain the regional climate information of the target region at the target time, where the target region is the region corresponding to the geographic location information and the target time is the time corresponding to the time information; determine the optional operating modes of the target home appliance based on the device information; and determine the recommended list of operating modes based on the regional climate information and the optional operating modes of the target home appliance.

[0112] Climate data recommendation examples: Hot regions: We recommend an air conditioner mode with energy-saving mode and powerful cooling, as well as a refrigerator mode with rapid freezing and cooling functions. Cold regions: We recommend a heater mode with energy-saving and efficient heating functions, as well as a washing machine mode with heated washing function. Rainy regions: We recommend a dryer mode with enhanced drying function, as well as an air purifier mode with dehumidification function.

[0113] Based on geographical location information, combined with local climate data, dietary habits, lifestyles, and other factors, the cloud server analyzes and determines the most suitable home appliance function mode for the local environment.

[0114] The fifth scenario: Recommendations based on user habits.

[0115] Based on the geographic location information and the time information, obtain user habit information of the target area at the target time; determine the optional operating modes of the target home appliance based on the device information; and determine the recommended list of operating modes based on the user habit information and the optional operating modes of the target home appliance.

[0116] Recommended dietary habits (examples): Oven: Ovens with multiple cooking modes are recommended. Range hood: Powerful smoke extraction mode is recommended. Refrigerator: Refrigerator mode with intelligent healthy recipe recommendations and ingredient management functions is recommended. Rice cooker: Multiple healthy cooking modes are recommended.

[0117] Lifestyle recommendations examples: Fast-paced cities: We recommend coffee machines with quick brewing and preset automatic morning start modes, and washing machines with quick wash and dry modes. Leisure and entertainment areas: We recommend home theater modes with surround sound and HD video playback, and game modes that integrate with large-screen TVs. Environmentally conscious areas: We recommend energy-efficient appliances and lighting systems using LED bulbs and automatic sensor switches.

[0118] The sixth scenario: Extract user behavior characteristics from the historical device usage data of other users in the target area; classify the user behavior characteristics to obtain several categories of user groups; determine a recommended list of operating modes for the target home appliances based on the categories of the user groups and the corresponding historical device usage data.

[0119] Cloud servers learn and predict users' potential needs by analyzing the common patterns of other users in the same region, thereby making more accurate recommendations.

[0120] Based on the above solution, this application embodiment also provides a model function matching method. The cloud server parses the information in the home appliance model, such as capacity, cooling method, energy efficiency rating, etc., and combines it with the specific functions of the home appliance model to return the most suitable function mode recommendation to the user.

[0121] Model-Function Matching Examples: Refrigerator Model-Function Matching: Based on information such as effective volume, cooling method, and compressor type in the refrigerator model, recommend an intelligent storage mode or energy-saving mode suitable for the user's habits. Washing Machine Model-Function Matching: Based on information such as rated washing capacity, spin speed, and drying function in the washing machine model, recommend a washing program suitable for the user's clothing material and washing needs. Air Conditioner Model-Function Matching: Based on information such as rated cooling capacity, indoor unit structure classification, and inverter function in the air conditioner model, recommend an operating mode suitable for the room size and the user's temperature preferences.

[0122] Phase 3: Provide the target user's associated client with a list of recommended operating modes for the target home appliances.

[0123] Figure 3 The client-side user interface is shown. Home appliances will display recommended operating modes on their screens, allowing users to operate them directly on the device. This design simplifies user interaction, enabling users to quickly select or modify operating modes without needing other media. Considering potential language differences among users in different regions, the recommendation system should support multilingual interfaces to accommodate diverse user needs and ensure users can understand and operate the home appliances.

[0124] In one possible implementation, data sharing and collaborative work between home appliances are permitted. For example, when multiple devices detect similar usage patterns, they can learn from each other and optimize recommendation algorithms. Cloud servers can statistically analyze the usage patterns of similar devices by city and use this data to refine recommendation algorithms for more accurate recommendations.

[0125] In one possible implementation, users can also modify the recommended function modes or select other modes via a mobile application. The mobile application provides a more intuitive user interface and more detailed control options, allowing users to more easily personalize their settings. If a user feels the recommended functions do not meet their needs, they can manually select their desired operating mode from all the device's functions. Specific available modes vary depending on the device and model.

[0126] Specifically, the system acquires the target user's modifications to the control parameters in the recommended operating mode list. Based on these modifications, it generates a custom operating mode for the target home appliance and places this user-created custom operating mode as the first item in the recommended list. The remaining items in the recommended list, excluding the custom mode, are determined based on geographic location and device information, ensuring that these other modes also match the user's geographic location and device characteristics.

[0127] This approach enables home appliances to not only provide intelligent recommendations based on environmental information but also allow users to personalize settings according to their needs, while simultaneously collecting user feedback to optimize the recommendation algorithm. This two-way interactive design enhances the user experience and makes home appliances more intelligent and personalized.

[0128] In summary, this application provides a method for recommending home appliance functions. In response to a power-on command for a target home appliance, the method acquires the environmental information of the target appliance, including geographic location information and device information. Based on the environmental information, it determines a recommended list of operating modes for the target appliance and provides this list to a client associated with the target user. By intelligently analyzing geographic location information and device information, the method recommends the most suitable operating mode for the current environment, thereby improving the intelligence level of home appliances.

[0129] Based on the same technical concept, embodiments of this application also provide a home appliance function recommendation system, such as... Figure 4 As shown, the system includes:

[0130] The information acquisition module 401 is used to acquire environmental information of the target home appliance in response to a power-on command for the target home appliance; the environmental information includes geographical location information and device information.

[0131] Recommendation list determination module 402 is used to determine a recommendation list of operating modes for the target home appliances based on the environmental information;

[0132] The recommendation module 403 is used to provide a list of recommended operating modes of the target home appliances to the client associated with the target user.

[0133] Based on the same technical concept, embodiments of this application also provide a home appliance function recommendation system, such as... Figure 5 As shown, it includes:

[0134] The sending module 501 is used to send the environmental information of the target home appliance to the server in response to the power-on operation of the target user, so that the server can determine the recommended list of operating modes of the target home appliance based on the environmental information. The environmental information includes geographical location information and device information.

[0135] The display module 502 is used to receive the recommended list of operating modes of the target home appliance returned by the server and display the recommended list of operating modes.

[0136] This application also provides an electronic device corresponding to the method provided in the foregoing embodiments. Please refer to... Figure 6The diagram illustrates an electronic device provided by some embodiments of this application. The electronic device 80 may include: a processor 800, a memory 801, a bus 802, and a communication interface 803, wherein the processor 800, the communication interface 803, and the memory 801 are connected via the bus 802; the memory 801 stores a computer program that can run on the processor 800, and when the processor 800 runs the computer program, it executes the method provided by any of the foregoing embodiments of this application.

[0137] The memory 801 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one physical port (which can be wired or wireless), such as the Internet, wide area network, local area network, or metropolitan area network.

[0138] Bus 802 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The memory 801 is used to store programs. After receiving an execution instruction, the processor 800 executes the program. The method disclosed in any of the foregoing embodiments of this application can be applied to the processor 800, or implemented by the processor 800.

[0139] The processor 800 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 800 or by instructions in software form. The processor 800 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules may reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 801. Processor 800 reads the information in memory 801 and, in conjunction with its hardware, completes the steps of the above method.

[0140] The electronic devices and methods provided in the embodiments of this application are based on the same inventive concept and have the same beneficial effects as the methods they employ, operate, or implement.

[0141] This application also provides a computer-readable storage medium corresponding to the method provided in the foregoing embodiments. Please refer to... Figure 7 The computer-readable storage medium shown is an optical disc 90, on which a computer program (i.e., a program product) is stored, which, when run by a processor, executes the methods provided in any of the foregoing embodiments.

[0142] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical and magnetic storage media, which will not be elaborated here.

[0143] The computer-readable storage medium provided in the above embodiments of this application and the method provided in the embodiments of this application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application stored therein.

[0144] It should be noted that the above embodiments are illustrative of this application and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. This application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0145] The above description is merely a preferred embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0146] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made under the concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A method for recommending home appliance functions, characterized in that, The method includes: In response to a power-on command for a target home appliance, the environmental information of the target home appliance is acquired; the environmental information includes geographical location information and device information. Based on the environmental information, a recommended list of operating modes for the target home appliances is determined. Provide the target user's associated client with a list of recommended operating modes for the target home appliance.

2. The method as described in claim 1, characterized in that, The environmental information also includes historical usage data of the target home appliance; the step of determining a recommended list of operating modes for the target home appliance based on the environmental information includes: The most recently used operating mode from the historical usage data of the target home appliance is selected as the first item in the recommended operating mode list. Based on the geographic location information and device information, determine the remaining items in the recommended operating mode list, excluding the first item.

3. The method as described in claim 1, characterized in that, The step of determining the recommended list of operating modes for the target home appliances based on the environmental information includes: The associated devices are determined based on the geographic location information, and the associated devices include devices that have a relationship with the target home appliance. The operating mode of the associated device is obtained from the historical usage data of the associated device; The recommended list of operating modes is determined based on the operating modes of the associated devices and the optional operating modes of the target home appliances.

4. The method as described in claim 3, characterized in that, The step of determining the associated device based on the geographic location information includes: The first home appliance whose distance from the target home appliance meets a set range is identified as the associated device, and the first home appliance is of the same type as the target home appliance.

5. The method as described in claim 3, characterized in that, The step of determining the associated device based on the geographic location information includes: The second home appliance in the associated home appliance group is obtained based on the geographical location information and the historical usage data of the target home appliance. The second home appliance has a communication connection with the target home appliance. The second home appliance is identified as the associated device.

6. The method as described in claim 1, characterized in that, The environmental information also includes time information; the step of determining the recommended list of operating modes for the target home appliance based on the environmental information includes: Based on the geographic location information and the time information, the habitual characteristics of the target area at the target time are obtained. The habitual characteristics are used to characterize the habits of the target area at the target time. The target area is the area corresponding to the geographic location information, and the target time is the time corresponding to the time information. The selectable operating modes of the target home appliance are determined based on the device information; Based on the aforementioned habitual characteristics and the selectable operating modes of the target home appliance, a recommended list of operating modes is determined.

7. The method as described in claim 6, characterized in that, The customary features include at least one of the following: Regional climate information; User habit information.

8. The method as described in claim 1, characterized in that, The environmental information also includes historical device usage data from other users in the target area; the step of determining a recommended list of operating modes for the target home appliances based on the environmental information includes: Extract user behavior characteristics from the device history usage data of other users in the target region; Based on the user behavior characteristics, several categories of user groups are obtained; A recommended list of operating modes for the target home appliances is determined based on the user group category and the corresponding historical device usage data.

9. A method for recommending home appliance functions, characterized in that, include: In response to the power-on operation of the target user, the environmental information of the target home appliance is sent to the server so that the server can determine a recommended list of operating modes for the target home appliance based on the environmental information. The environmental information includes geographical location information and device information. Receive the recommended list of operating modes for the target home appliance returned by the server, and display the recommended list of operating modes.

10. The method as described in claim 9, characterized in that, The method further includes: Obtain the target user's modification operations on the control parameters of the running modes in the running mode recommendation list; A custom operating mode for the target home appliance is generated based on the modified control parameters.

11. A home appliance function recommendation system, characterized in that, The system includes: The information acquisition module is used to acquire environmental information of the target home appliance in response to a power-on command; the environmental information includes geographical location information and device information. The recommendation list determination module is used to determine a recommendation list of operating modes for the target home appliances based on the environmental information. The recommendation module is used to provide a list of recommended operating modes of the target home appliances to the clients associated with the target user.

12. A home appliance function recommendation system, characterized in that, The system includes: The sending module is used to send the environmental information of the target home appliance to the server in response to the power-on operation of the target user, so that the server can determine the recommended list of operating modes of the target home appliance based on the environmental information. The environmental information includes geographical location information and device information. The display module is used to receive the recommended list of operating modes of the target home appliance returned by the server and display the recommended list of operating modes.

13. An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor runs the computer program, it performs an action to implement the method as claimed in any one of claims 1-10.

14. A computer-readable storage medium, characterized in that, It stores computer-readable instructions that can be executed by a processor to implement the method as described in any one of claims 1-10.

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