An energy-saving suggestion generation method and device for a household appliance, equipment, and medium

Abstract

The embodiment of the application provides a kind of energy-saving suggestion generation method and device of household appliance, equipment, medium, the method comprises: constructing the energy-saving suggestion rule for target household appliance, the energy-saving suggestion rule includes the energy-saving suggestion information associated with energy-saving influencing factor;One or more target energy-saving influencing factors of the target household appliance are acquired;In the energy-saving suggestion rule, the energy-saving suggestion information matched with the one or more target energy-saving influencing factors is determined.Through the embodiment of the application, the matched energy-saving suggestion information is generated based on the acquired energy-saving influencing factor, so as to provide effective suggestion for user using household appliance, improve household energy efficiency, also can effectively guide user to form good energy-saving habit.

Description

Technical Field

[0001] This invention relates to the field of home appliance control technology, and in particular to a method, apparatus, device, and medium for generating energy-saving suggestions for home appliances. Background Technology

[0002] In modern households, with the popularization of smart devices, the types and number of home appliances are increasing day by day. At the same time, the energy consumption of various home appliances is becoming increasingly prominent.

[0003] In daily life, household appliances such as air conditioners, lighting, and other appliances account for a significant portion of energy consumption. At the same time, users often lack sufficient awareness and practice regarding effective energy conservation, resulting in high household electricity consumption, high appliance operating costs, and energy waste. Summary of the Invention

[0004] In view of the above problems, a method, apparatus, equipment, and medium for generating energy-saving recommendations for household appliances are proposed to provide solutions to these problems or at least partially resolve them, including:

[0005] A method for generating energy-saving suggestions for home appliances, the method comprising:

[0006] Construct energy-saving recommendation rules for target home appliances, wherein the energy-saving recommendation rules include energy-saving recommendation information associated with energy-saving influencing factors;

[0007] Obtain one or more target energy-saving influencing factors of the target home appliance;

[0008] The energy-saving recommendation rules identify energy-saving recommendation information that matches the one or more target energy-saving influencing factors.

[0009] Optionally, determining the energy-saving recommendation information that matches the one or more target energy-saving influencing factors in the energy-saving recommendation rule includes:

[0010] The one or more target energy-saving influencing factors are input into a preset energy-saving suggestion generation model for home appliances to generate energy-saving suggestion information that matches the target energy-saving influencing factors. The energy-saving suggestion generation model for home appliances is a model that learns the relationship between energy-saving influencing factors and energy-saving suggestion information based on the energy-saving suggestion rules.

[0011] Optionally, the target energy-saving influencing factors include user intent categories, and obtaining one or more target energy-saving influencing factors of the target home appliance includes:

[0012] In response to an input operation on the input interface of the home appliance energy-saving suggestion generation system for the target home appliance, determine the input data corresponding to the input operation;

[0013] Determine the initial text information corresponding to the input data;

[0014] Keywords are identified in the initial text information;

[0015] The user intent category is determined based on the keywords, and the user intent category is used to characterize the user's energy-saving needs for the target home appliance.

[0016] Optionally, determining the initial text information corresponding to the input data includes:

[0017] When the input data is voice data, a preset voice recognition model is invoked to convert the voice data into text information.

[0018] Optionally, determining keywords in the initial text information includes:

[0019] Obtain the context information and / or user preference information of the input data;

[0020] The initial text data is segmented based on the context information and / or the user preference information to obtain segmentation information.

[0021] Keywords are determined from the word segmentation information.

[0022] Optionally, the target energy-saving influencing factors include environmental information, and obtaining one or more target energy-saving influencing factors of the target home appliance includes:

[0023] Identify one or more target sensors associated with the target home appliance;

[0024] Obtain sensor data corresponding to the one or more target sensors, and use the sensor data to determine the environmental information of the target home appliance.

[0025] Optionally, the target energy-saving influencing factors include equipment status information, and obtaining one or more target energy-saving influencing factors of the target home appliance includes:

[0026] Call the API interface of the target home appliance to obtain the device status of the target home appliance through the API interface.

[0027] Optionally, it also includes:

[0028] Obtain feedback information regarding the energy-saving recommendations;

[0029] The energy-saving recommendation rules are adjusted based on the feedback information.

[0030] Optionally, obtaining feedback information regarding the energy-saving suggestion information includes:

[0031] Obtain first energy consumption information of the target home appliance before applying the energy-saving suggestion information and second energy consumption information after applying the energy-saving suggestion information;

[0032] The implementation effect information of the energy-saving suggestion information is determined by combining the first energy consumption information and the second energy consumption message;

[0033] Obtain user satisfaction information of the target users regarding the energy-saving suggestions;

[0034] The implementation effect information and / or the user satisfaction information will be used as feedback information for the energy-saving suggestion information.

[0035] Optionally, it also includes:

[0036] Generate visual dynamic charts based on the energy-saving recommendations;

[0037] The visualized dynamic chart is sent to the target user for display.

[0038] An energy-saving suggestion generation device for home appliances, the device comprising:

[0039] The rule building module is used to build energy-saving suggestion rules for target home appliances, wherein the energy-saving suggestion rules include energy-saving suggestion information associated with energy-saving influencing factors;

[0040] An energy-saving influencing factor acquisition module is used to acquire one or more target energy-saving influencing factors of the target home appliance;

[0041] The energy-saving recommendation information determination module is used to determine energy-saving recommendation information that matches the one or more target energy-saving influencing factors in the energy-saving recommendation rules.

[0042] An electronic device includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when executed by the processor, the computer program implements the energy-saving suggestion generation method for home appliances as described above.

[0043] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the energy-saving suggestion generation method for home appliances as described above.

[0044] The embodiments of the present invention have the following advantages:

[0045] In this embodiment of the invention, energy-saving suggestion rules for target home appliances can be constructed. The energy-saving suggestion rules include energy-saving suggestion information associated with energy-saving influencing factors. One or more target energy-saving influencing factors of the target home appliances are obtained. Then, energy-saving suggestion information matching the one or more target energy-saving influencing factors can be determined in the energy-saving suggestion rules. This enables the rapid generation of matching energy-saving suggestion information based on the obtained energy-saving influencing factors, so as to provide effective suggestions for users to use home appliances, improve household energy efficiency, and effectively guide users to develop good energy-saving habits. Attached Figure Description

[0046] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description of the present invention will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a flowchart illustrating the steps of a method for generating energy-saving suggestions for home appliances according to an embodiment of the present invention;

[0048] Figure 2 This is a flowchart of the steps of another method for generating energy-saving suggestions for home appliances provided in an embodiment of the present invention;

[0049] Figure 3 This is a flowchart of the steps of another method for generating energy-saving suggestions for home appliances provided in an embodiment of the present invention;

[0050] Figure 4 This is a flowchart of the steps of another method for generating energy-saving suggestions for home appliances provided in an embodiment of the present invention;

[0051] Figure 5 This is a schematic diagram of an interactive energy-saving suggestion generation system provided in an embodiment of the present invention;

[0052] Figure 6 This is a schematic diagram of the structure of an energy-saving suggestion generation device for home appliances provided in an embodiment of the present invention. Detailed Implementation

[0053] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0054] Reference Figure 1 The diagram illustrates a flowchart of a method for generating energy-saving suggestions for home appliances according to an embodiment of the present invention, which may specifically include the following steps:

[0055] Step 101: Construct energy-saving recommendation rules for the target home appliances, wherein the energy-saving recommendation rules include energy-saving recommendation information associated with energy-saving influencing factors;

[0056] In practical applications, to achieve energy-saving management of home appliances, energy-saving suggestion rules for target appliances can be preset. These rules can include energy-saving suggestion information associated with energy-saving influencing factors. Specifically, the energy-saving suggestion information can include energy-saving controls to be implemented for specific appliance types. For example, it can be set to turn off the air conditioner or adjust its temperature to the preset temperature when the indoor temperature is higher than a preset temperature. Indoor temperature is considered an energy-saving influencing factor, and the energy-saving measure is turning off the air conditioner or adjusting its temperature to the preset temperature.

[0057] Step 102: Obtain one or more target energy-saving influencing factors of the target home appliance;

[0058] In this embodiment of the invention, some energy-saving influencing factors related to energy saving of home appliances can be preset, wherein the target energy-saving influencing factors may include any one or more of the following:

[0059] User intent category, environmental information, device status information, user preference information, and contextual information.

[0060] User intent categories characterize a user's energy-saving needs for a target home appliance; for example, a user might pre-set their bedroom air conditioner to turn off in 30 minutes. Environmental information describes the environment surrounding the target home appliance, such as temperature, humidity, and brightness. Device status information may include, but is not limited to, real-time energy consumption and operating status of the target home appliance. User preference information can be user-defined appliance usage preferences or user preference information derived from analysis of past appliance usage. Contextual information can be scenarios set by the user for different appliance usage needs, or specific scenarios, such as different scenario modes for weekdays, weekends, and holidays. Within each scenario mode, energy-saving suggestions can be set for each appliance based on the specific needs of that scenario.

[0061] In one embodiment of the present invention, the target energy-saving influencing factors include environmental information, and the step of obtaining one or more target energy-saving influencing factors of the target home appliance includes:

[0062] Identify one or more target sensors associated with the target home appliance; acquire sensor data corresponding to the one or more target sensors, and use the sensor data to determine the environmental information of the target home appliance.

[0063] In practical applications, the location of home appliances can be determined, and multiple associated target sensors in the indoor space where the appliance is located can be determined based on the location of the appliance. For example, the associated sensors for the air conditioner in the bedroom may include a temperature sensor for detecting the bedroom temperature, a humidity sensor for detecting the bedroom humidity, and a light sensor for detecting the bedroom light.

[0064] Once the target sensor is identified, its data can be acquired. In a real home network, wireless protocols (such as Zigbee or Wi-Fi) can be used to transmit the sensor data of the target sensor to the central control system in order to acquire the sensor data of the target sensor.

[0065] In one embodiment of the present invention, the target energy-saving influencing factors include equipment status information, and obtaining one or more target energy-saving influencing factors of the target home appliance includes: calling the API interface of the target home appliance, and obtaining the equipment status of the target home appliance through the API interface.

[0066] In practical applications, an API interface for communicating with one or more home appliances can be pre-set in the interactive energy-saving suggestion generation system that applies the energy-saving suggestion generation method for home appliances in the embodiments of the present invention, so that the device status of the target home appliance can be obtained through the API interface.

[0067] Step 103: Determine energy-saving recommendation information that matches the one or more target energy-saving influencing factors in the energy-saving recommendation rules.

[0068] After obtaining one or more target energy-saving influencing factors, a comprehensive analysis can be conducted based on one or more target node influencing factors to determine matching energy-saving recommendation information from the constructed energy-saving recommendation rules. Then, based on the determined energy-saving recommendation information, energy-saving control of home appliances can be implemented to improve household energy efficiency and effectively guide users to develop good energy-saving habits.

[0069] In one embodiment of the present invention, the method further includes: generating a visual dynamic chart based on the energy-saving suggestion information; and sending the visual dynamic chart to the target user for display.

[0070] In practical applications, the generated energy-saving suggestions can be displayed in a preset manner. For example, users can use the visualization function on the interactive energy-saving suggestion generation system's interface to generate dynamic icons based on the energy-saving suggestion information. These dynamic charts can then be sent to relevant target users for display.

[0071] In this embodiment of the invention, energy-saving suggestion rules for target home appliances can be constructed. The energy-saving suggestion rules include energy-saving suggestion information associated with energy-saving influencing factors. One or more target energy-saving influencing factors of the target home appliances are obtained. Then, energy-saving suggestion information matching the one or more target energy-saving influencing factors can be determined in the energy-saving suggestion rules. This enables the rapid generation of matching energy-saving suggestion information based on the obtained energy-saving influencing factors, so as to provide effective suggestions for users to use home appliances, improve household energy efficiency, and effectively guide users to develop good energy-saving habits.

[0072] Reference Figure 2 The diagram illustrates a flowchart of another method for generating energy-saving suggestions for home appliances according to an embodiment of the present invention, which may specifically include the following steps:

[0073] Step S201: Construct energy-saving recommendation rules for the target home appliances, wherein the energy-saving recommendation rules include energy-saving recommendation information associated with energy-saving influencing factors;

[0074] In practical applications, to achieve energy-saving management of home appliances, energy-saving suggestion rules for target appliances can be preset. These rules can include energy-saving suggestion information associated with energy-saving influencing factors. Specifically, the energy-saving suggestion information can include energy-saving controls to be implemented for specific appliance types. For example, it can be set to turn off the air conditioner or adjust its temperature to the preset temperature when the indoor temperature is higher than a preset temperature. Indoor temperature is considered an energy-saving influencing factor, and the energy-saving measure is turning off the air conditioner or adjusting its temperature to the preset temperature.

[0075] Step S202: Obtain one or more target energy-saving influencing factors of the target home appliance;

[0076] In this embodiment of the invention, some energy-saving influencing factors related to energy saving of home appliances can be preset, wherein the target energy-saving influencing factors may include any one or more of the following:

[0077] User intent category, environmental information, device status information, user preference information, and contextual information.

[0078] User intent categories characterize a user's energy-saving needs for a target home appliance; for example, a user might pre-set their bedroom air conditioner to turn off in 30 minutes. Environmental information describes the environment surrounding the target home appliance, such as temperature, humidity, and brightness. Device status information may include, but is not limited to, real-time energy consumption and operating status of the target home appliance. User preference information can be user-defined appliance usage preferences or user preference information derived from analysis of past appliance usage. Contextual information can be scenarios set by the user for different appliance usage needs, or specific scenarios, such as different scenario modes for weekdays, weekends, and holidays. Within each scenario mode, energy-saving suggestions can be set for each appliance based on the specific needs of that scenario.

[0079] Step S203: Input the one or more target energy-saving influencing factors into a preset energy-saving suggestion generation model for home appliances, and generate energy-saving suggestion information that matches the target energy-saving influencing factors. The energy-saving suggestion generation model for home appliances is a model that learns the relationship between energy-saving influencing factors and energy-saving suggestion information based on the energy-saving suggestion rules.

[0080] In practical applications, an energy-saving suggestion generation model can be pre-trained. This model can learn the relationship between energy-saving influencing factors and energy-saving suggestion information through energy-saving suggestion rules, and thus output matching energy-saving suggestion information for the input target energy-saving influencing factors.

[0081] In this embodiment of the invention, energy-saving suggestion rules for target home appliances can be constructed. These rules include energy-saving suggestion information associated with energy-saving influencing factors. One or more target energy-saving influencing factors for the target home appliance are obtained. These factors are then input into a preset energy-saving suggestion generation model for the home appliance to generate energy-saving suggestion information matching the target energy-saving influencing factors. This enables the rapid generation of matching energy-saving suggestion information based on the obtained energy-saving influencing factors, providing effective suggestions for users' use of home appliances, improving household energy efficiency, and effectively guiding users to develop good energy-saving habits. Introducing an energy-saving suggestion generation model allows for more accurate determination of energy-saving suggestion information matching the target energy-saving influencing factors.

[0082] Reference Figure 3 The diagram illustrates a flowchart of another method for generating energy-saving suggestions for home appliances according to an embodiment of the present invention, which may specifically include the following steps:

[0083] Step S301: Construct energy-saving recommendation rules for the target home appliances, wherein the energy-saving recommendation rules include energy-saving recommendation information associated with energy-saving influencing factors;

[0084] In practical applications, to achieve energy-saving management of home appliances, energy-saving suggestion rules for target appliances can be preset. These rules can include energy-saving suggestion information associated with energy-saving influencing factors. Specifically, the energy-saving suggestion information can include energy-saving controls to be implemented for specific appliance types. For example, it can be set to turn off the air conditioner or adjust its temperature to the preset temperature when the indoor temperature is higher than a preset temperature. Indoor temperature is considered an energy-saving influencing factor, and the energy-saving measure is turning off the air conditioner or adjusting its temperature to the preset temperature.

[0085] Step S302: In response to the input operation on the input interface of the home appliance energy-saving suggestion generation system for the target home appliance, determine the input data corresponding to the input operation;

[0086] In practical applications, user input operations can include voice input operations, with the corresponding input data being voice data, and user input operations can also include text input operations, with the corresponding input data being text data.

[0087] Step S303: Determine the initial text information corresponding to the input data;

[0088] After receiving the input data, the initial text information is obtained directly for text data. If the input data is not text data, a text-to-text conversion operation is required to obtain the initial text information.

[0089] In one embodiment of the present invention, determining the initial text information corresponding to the input data includes: when the input data is voice data, calling a preset voice recognition model to convert the voice data into text information.

[0090] For example, speech recognition technology (such as Google Speech-to-Text) can be used to convert speech into text to ensure the accuracy of the text.

[0091] Step S304: Determine keywords from the initial text information;

[0092] In one embodiment of the present invention, determining keywords in the initial text information includes:

[0093] Obtain contextual information and / or user preference information from the input data; perform word segmentation on the initial text data based on the contextual information and / or the user preference information to obtain word segmentation information, and determine keywords from the word segmentation information. For example, use a Named Entity Recognition (NER) algorithm to identify keywords (such as "air conditioner" and "lights").

[0094] In practical applications, a context management module can be set up to store context information and / or user preference information of the input data. This context information and / or user preference information can then be combined for word segmentation processing to obtain accurate word segmentation data. Keywords can then be extracted based on the word segmentation information.

[0095] Step S305: Determine the user intent category based on the keyword. The user intent category is used to characterize the user's energy-saving needs for the target home appliance.

[0096] Step S306: Determine energy-saving suggestion information that matches the user intent category in the energy-saving suggestion rule.

[0097] In this embodiment of the invention, an energy-saving suggestion rule is constructed for a target home appliance. The energy-saving suggestion rule includes energy-saving suggestion information associated with energy-saving influencing factors. In response to an input operation on the input interface of the energy-saving suggestion generation system for the target home appliance, input data corresponding to the input operation is determined. Initial text information corresponding to the input data is determined. Keywords are determined in the initial text information. User intent category is determined based on the keywords. Energy-saving suggestion information matching the user intent category is determined in the energy-saving suggestion rule. This realizes the determination of user intent based on user input, and then the generation of corresponding energy-saving suggestion information based on user intent, achieving personalized recommendations, improving household energy efficiency, and effectively guiding users to develop good energy-saving habits.

[0098] Reference Figure 4 The diagram illustrates a flowchart of another method for generating energy-saving suggestions for home appliances according to an embodiment of the present invention, which may specifically include the following steps:

[0099] Step S401: Construct energy-saving recommendation rules for the target home appliances, wherein the energy-saving recommendation rules include energy-saving recommendation information associated with energy-saving influencing factors;

[0100] In practical applications, to achieve energy-saving management of home appliances, energy-saving suggestion rules for target appliances can be preset. These rules can include energy-saving suggestion information associated with energy-saving influencing factors. Specifically, the energy-saving suggestion information can include energy-saving controls to be implemented for specific appliance types. For example, it can be set to turn off the air conditioner or adjust its temperature to the preset temperature when the indoor temperature is higher than a preset temperature. Indoor temperature is considered an energy-saving influencing factor, and the energy-saving measure is turning off the air conditioner or adjusting its temperature to the preset temperature.

[0101] Step S402: Obtain one or more target energy-saving influencing factors of the target home appliance;

[0102] In this embodiment of the invention, some energy-saving influencing factors related to energy saving of home appliances can be preset, wherein the target energy-saving influencing factors may include any one or more of the following:

[0103] User intent category, environmental information, device status information, user preference information, and contextual information.

[0104] User intent categories characterize a user's energy-saving needs for a target home appliance; for example, a user might pre-set their bedroom air conditioner to turn off in 30 minutes. Environmental information describes the environment surrounding the target home appliance, such as temperature, humidity, and brightness. Device status information may include, but is not limited to, real-time energy consumption and operating status of the target home appliance. User preference information can be user-defined appliance usage preferences or user preference information derived from analysis of past appliance usage. Contextual information can be scenarios set by the user for different appliance usage needs, or specific scenarios, such as different scenario modes for weekdays, weekends, and holidays. Within each scenario mode, energy-saving suggestions can be set for each appliance based on the specific needs of that scenario.

[0105] Step S403: Determine energy-saving recommendation information that matches the one or more target energy-saving influencing factors in the energy-saving recommendation rules.

[0106] Step S404: Obtain feedback information regarding the energy-saving suggestion information;

[0107] Step S405: Adjust the energy-saving recommendation rule based on the feedback information.

[0108] After receiving feedback, the existing energy-saving recommendation rules can be optimized to meet user needs, creating personalized energy-saving recommendation rules and improving user satisfaction.

[0109] In one embodiment of the present invention, obtaining feedback information regarding the energy-saving suggestion information includes:

[0110] Obtain first energy consumption information of the target home appliance before applying the energy-saving suggestion information and second energy consumption information after applying the energy-saving suggestion information;

[0111] The implementation effect information of the energy-saving suggestion information is determined by combining the first energy consumption information and the second energy consumption message;

[0112] Obtain user satisfaction information of the target users regarding the energy-saving suggestions;

[0113] The user satisfaction information and / or the implementation effect information will be used as feedback information for the energy-saving suggestion information.

[0114] In this embodiment of the invention, an energy-saving suggestion rule is constructed for a target home appliance. The energy-saving suggestion rule includes energy-saving suggestion information associated with energy-saving influencing factors. One or more target energy-saving influencing factors of the target home appliance are obtained. Energy-saving suggestion information matching the one or more target energy-saving influencing factors is determined in the energy-saving suggestion rule, and feedback information on the energy-saving suggestion information is obtained. The energy-saving suggestion rule is adjusted based on the feedback information, so that it can be continuously optimized based on the feedback information to make the generated suggestions meet user expectations.

[0115] Reference Figure 5 This diagram illustrates an interactive energy-saving suggestion generation system according to an embodiment of the present invention. The interactive energy-saving suggestion generation system in this embodiment may include modules such as intent recognition and semantic analysis, environmental and equipment status monitoring, personalized suggestion generation, user interaction design, dynamic adjustment and learning, and experimentation and evaluation. The combined effect of these modules results in a highly efficient interactive energy-saving suggestion generation system that not only improves household energy efficiency but also effectively guides users to develop good energy-saving habits.

[0116] The following is a detailed description of the functions of each module in the interactive energy-saving suggestion generation system:

[0117] (1) Intent recognition and semantic analysis:

[0118] A user interface allows users to input energy-saving related questions via voice or text. Speech recognition technology (such as Google Speech-to-Text) is used to convert speech to text, ensuring accuracy. NLP techniques are employed for word segmentation and text analysis to build an intent recognition model and extract the user's energy-saving intent.

[0119] Specifically, Named Entity Recognition (NER) algorithms can be used to identify keywords (such as "air conditioner" and "lights") and map them to specific intent categories. For example, if the system recognizes the intent related to the living room lights and the action of turning them on, then the relevant home appliances can be controlled.

[0120] In the process of intent recognition and semantic analysis, a context management module can also be designed to store the user's historical dialogues and preference information.

[0121] During word segmentation, the context management module can be invoked to combine the user's historical dialogue and preference information for word segmentation. By improving the accuracy of word segmentation recognition based on context information, the accuracy of intent recognition can be improved, ensuring that the system can understand complex user requests.

[0122] (ii) Environmental and equipment condition monitoring

[0123] Environmental and equipment status monitoring refers to sensor integration, deploying sensors such as temperature, humidity, and light to monitor the home environment in real time. Wireless protocols (such as Zigbee or Wi-Fi) are used to transmit sensor data to a central control system. APIs for smart home devices are integrated to obtain real-time data on device energy consumption and operating status.

[0124] Ensure the accuracy and timeliness of device status data, supporting the system in generating recommendations based on device status. Data processing and analysis: Process collected data using stream processing frameworks (such as Apache Kafka or Flink). Generate real-time device and environment status reports for subsequent analysis and recommendation generation. Personalized recommendation generation refers to building a flexible rule base to define various energy-saving recommendation rules.

[0125] Dynamically generate energy-saving suggestions based on user input and environmental data using a rule engine (such as Drools). Recommendation algorithm implementation steps: Apply machine learning models to analyze user history and generate personalized suggestions. Use collaborative filtering or content-based recommendation algorithms to provide suggestions based on user device usage habits and energy-saving goals. Context-aware recommendation: Set suggestion strategies for different contextual patterns (e.g., weekdays, weekends, holidays). Generate context-appropriate energy-saving suggestions based on environmental data and user habits.

[0126] In practical applications, some energy-saving influencing factors related to the energy efficiency of home appliances can be preset. The target energy-saving influencing factors may include any one or more of the following:

[0127] User intent category, environmental information, device status information, user preference information, and contextual information.

[0128] User intent categories characterize a user's energy-saving needs for a target home appliance; for example, a user might pre-set their bedroom air conditioner to turn off in 30 minutes. Environmental information describes the environment surrounding the target home appliance, such as temperature, humidity, and brightness. Device status information may include, but is not limited to, real-time energy consumption and operating status of the target home appliance. User preference information can be user-defined appliance usage preferences or user preference information derived from analysis of past appliance usage. Contextual information can be scenarios set by the user for different appliance usage needs, or specific scenarios, such as different scenario modes for weekdays, weekends, and holidays. Within each scenario mode, energy-saving suggestions can be set for each appliance based on the specific needs of that scenario.

[0129] In practical applications, the three algorithms mentioned above are generated based on different influencing factors, and can therefore be integrated into rule engines (such as Drools) to build an energy-saving suggestion generation model. The influencing factors of the energy-saving suggestion generation model can be adjusted based on the three influencing factors mentioned above.

[0130] (III) User Interaction Design

[0131] In practical applications, a user-friendly interface, with a simple and intuitive design, ensures that users can easily access input and suggestion functions. In this embodiment of the invention, UI design principles can be adopted to improve the user experience.

[0132] To enhance user experience, multimodal interactions can be implemented, and applications supporting voice, touch, and graphical interfaces can be developed. This ensures users can interact with the system across different devices, such as smartphones, tablets, and smart speakers.

[0133] In addition, visual feedback can be set up, using data visualization tools (such as D3.js) to design dynamic charts that demonstrate energy consumption trends and the effectiveness of energy-saving recommendations. An intuitive feedback interface is provided so that users can clearly understand the value of the energy-saving recommendations.

[0134] (iv) Dynamic adjustment and learning

[0135] In practical applications, feedback options (such as "accept" and "disaccept") can be set in the user interface to record user feedback on suggestions. This feedback data can then be used to optimize and adjust subsequent suggestions.

[0136] Adaptive Learning Algorithm: Employing reinforcement learning algorithms, the system dynamically adjusts its suggestion generation strategy based on user feedback and energy consumption data. This ensures the system can continuously learn and adapt to changes in user behavior, improving the relevance of suggestions. Regular Evaluation and Optimization: Evaluation metrics (such as energy-saving effect and user satisfaction) are set to regularly assess system performance. Based on the evaluation results, the algorithm and strategies are adjusted to ensure continuous system optimization.

[0137] Experimentation and Evaluation: User testing and feedback collection. Conduct user testing to evaluate the system's effectiveness and user acceptance. Use A / B testing to compare the effects of different suggestion generation strategies and collect and analyze user feedback.

[0138] The interactive energy-saving suggestion generation system can also utilize data analysis tools (such as Python's Pandas) to analyze user behavior and energy consumption data. Regular reports can be generated to evaluate the effectiveness of the suggestions and user satisfaction. A continuous improvement cycle is established: a feedback loop for continuous improvement is created, and user feedback and system performance are reviewed regularly.

[0139] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0140] Reference Figure 6 The diagram shows a structural schematic of an energy-saving suggestion generation device for home appliances according to an embodiment of the present invention, which may specifically include the following modules:

[0141] The rule building module 601 is used to build energy-saving suggestion rules for target home appliances, wherein the energy-saving suggestion rules include energy-saving suggestion information associated with energy-saving influencing factors;

[0142] The energy-saving influencing factor acquisition module 602 is used to acquire one or more target energy-saving influencing factors of the target home appliance;

[0143] The energy-saving suggestion information determination module 603 is used to determine energy-saving suggestion information that matches the one or more target energy-saving influencing factors in the energy-saving suggestion rules.

[0144] In one embodiment of the present invention, the energy-saving suggestion information determination module 603, when determining energy-saving suggestion information that matches the one or more target energy-saving influencing factors in the energy-saving suggestion rules, can specifically be used for:

[0145] The one or more target energy-saving influencing factors are input into a preset energy-saving suggestion generation model for home appliances to generate energy-saving suggestion information that matches the target energy-saving influencing factors. The energy-saving suggestion generation model for home appliances is a model that learns the relationship between energy-saving influencing factors and energy-saving suggestion information based on the energy-saving suggestion rules.

[0146] In one embodiment of the present invention, the target energy-saving influencing factors include user intent categories, and the energy-saving influencing factor acquisition module 602 may include the following sub-modules:

[0147] The input data determination submodule is used to determine the input data corresponding to the input operation in response to the input operation for the target home appliance on the input interface of the home appliance energy-saving suggestion generation system.

[0148] The text information determination submodule is used to determine the initial text information corresponding to the input data;

[0149] The keyword determination submodule is used to determine keywords from the initial text information;

[0150] The user intent category determination submodule is used to determine the user intent category based on the keyword. The user intent category is used to characterize the user's energy-saving needs for the target home appliance.

[0151] In one embodiment of the present invention, the text information determination submodule may include the following sub-units:

[0152] The speech-to-text conversion unit is used to call a preset speech recognition model to convert the speech data into text information when the input data is speech data.

[0153] In one embodiment of the present invention, the keyword determination submodule may include the following units:

[0154] The association information acquisition unit is used to acquire context information and / or user preference information of the input data;

[0155] The word processing unit is used to perform word segmentation on the initial text data based on the context information and / or the user preference information to obtain word segmentation information;

[0156] The keyword determination module is used to determine keywords from the word segmentation information.

[0157] In one embodiment of the present invention, the target energy-saving influencing factors include environmental information, and the energy-saving influencing factor acquisition module 602 may include the following sub-modules:

[0158] The associated sensor determination submodule is used to determine one or more target sensors associated with the target home appliance;

[0159] The environmental information acquisition submodule is used to acquire sensor data corresponding to the one or more target sensors and use the sensor data to determine the environmental information of the target home appliance.

[0160] In one embodiment of the present invention, the target energy-saving influencing factors include equipment status information, and the energy-saving influencing factor acquisition module 602 may include the following sub-modules:

[0161] The device status acquisition submodule is used to call the API interface of the target home appliance and obtain the device status of the target home appliance through the API interface.

[0162] In one embodiment of the present invention, the device further includes:

[0163] The feedback information acquisition module is used to acquire feedback information regarding the energy-saving suggestion information;

[0164] The energy-saving suggestion rule adjustment module is used to adjust the energy-saving suggestion rule based on the feedback information.

[0165] In one embodiment of the present invention, the feedback information acquisition module may include the following sub-modules:

[0166] An energy consumption acquisition submodule is used to acquire first energy consumption information of the target home appliance before applying the energy-saving suggestion information and second energy consumption information after applying the energy-saving suggestion information.

[0167] The implementation effect information determination submodule is used to combine the first energy consumption information and the second energy consumption message to determine the implementation effect information of the energy-saving suggestion information;

[0168] The user satisfaction information determination submodule is used to obtain the target user's user satisfaction information with the energy-saving suggestion information;

[0169] The feedback information determination submodule is used to use the user satisfaction information and / or the implementation effect information as feedback information for the energy-saving suggestion information.

[0170] In one embodiment of the present invention, the device may further include the following sub-modules:

[0171] A visualization dynamic chart determination module is used to generate a visualization dynamic chart based on the energy-saving suggestion information;

[0172] The chart display module is used to send the visual dynamic chart to the target user for display.

[0173] In this embodiment of the invention, energy-saving suggestion rules for target home appliances can be constructed. The energy-saving suggestion rules include energy-saving suggestion information associated with energy-saving influencing factors. One or more target energy-saving influencing factors of the target home appliances are obtained. Then, energy-saving suggestion information matching the one or more target energy-saving influencing factors can be determined in the energy-saving suggestion rules. This enables the rapid generation of matching energy-saving suggestion information based on the obtained energy-saving influencing factors, so as to provide effective suggestions for users to use home appliances, improve household energy efficiency, and effectively guide users to develop good energy-saving habits.

[0174] An embodiment of the present invention also provides an electronic device, which may include a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, it implements a method for generating energy-saving suggestions for home appliances as follows:

[0175] Construct energy-saving recommendation rules for target home appliances, wherein the energy-saving recommendation rules include energy-saving recommendation information associated with energy-saving influencing factors;

[0176] Obtain one or more target energy-saving influencing factors of the target home appliance;

[0177] The energy-saving recommendation rules identify energy-saving recommendation information that matches the one or more target energy-saving influencing factors.

[0178] An embodiment of the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements a method for generating energy-saving suggestions for home appliances as follows:

[0179] Construct energy-saving recommendation rules for target home appliances, wherein the energy-saving recommendation rules include energy-saving recommendation information associated with energy-saving influencing factors;

[0180] Obtain one or more target energy-saving influencing factors of the target home appliance;

[0181] The energy-saving recommendation rules identify energy-saving recommendation information that matches the one or more target energy-saving influencing factors.

[0182] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0183] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0184] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, embodiments of the present invention can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0185] Embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0186] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0187] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0188] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0189] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0190] The above provides a detailed description of a method, apparatus, equipment, and medium for generating energy-saving suggestions for home appliances. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for generating energy-saving suggestions for household appliances, characterized in that, The method includes: Construct energy-saving recommendation rules for target home appliances, wherein the energy-saving recommendation rules include energy-saving recommendation information associated with energy-saving influencing factors; Obtain one or more target energy-saving influencing factors of the target home appliance; The energy-saving recommendation rules identify energy-saving recommendation information that matches the one or more target energy-saving influencing factors; The target energy-saving influencing factors include user intent categories, and the acquisition of one or more target energy-saving influencing factors of the target home appliance includes: In response to an input operation on the input interface of the home appliance energy-saving suggestion generation system for the target home appliance, determine the input data corresponding to the input operation; Determine the initial text information corresponding to the input data; Keywords are identified in the initial text information; The user intent category is determined based on the keywords, and the user intent category is used to characterize the user's energy-saving needs for the target home appliance.

2. The method according to claim 1, characterized in that, The step of determining energy-saving recommendation information that matches the one or more target energy-saving influencing factors in the energy-saving recommendation rule includes: The one or more target energy-saving influencing factors are input into a preset energy-saving suggestion generation model for home appliances to generate energy-saving suggestion information that matches the target energy-saving influencing factors. The energy-saving suggestion generation model for home appliances is a model that learns the relationship between energy-saving influencing factors and energy-saving suggestion information based on the energy-saving suggestion rules.

3. The method according to claim 1, characterized in that, Determining the initial text information corresponding to the input data includes: When the input data is voice data, a preset voice recognition model is invoked to convert the voice data into text information.

4. The method according to claim 1, characterized in that, The step of determining keywords in the initial text information includes: Obtain the context information and / or user preference information of the input data; The initial text information is segmented based on the context information and / or the user preference information to obtain segmented information. Keywords are determined from the word segmentation information.

5. The method according to claim 1, characterized in that, The target energy-saving influencing factors include environmental information, and obtaining one or more target energy-saving influencing factors of the target home appliance includes: Identify one or more target sensors associated with the target home appliance; Acquire sensor data corresponding to the one or more target sensors, and determine the environmental information of the target home appliance based on the sensor data.

6. The method according to claim 1, characterized in that, The target energy-saving influencing factors include equipment status information, and obtaining one or more target energy-saving influencing factors of the target home appliance includes: Call the API interface of the target home appliance to obtain the device status of the target home appliance through the API interface.

7. The method according to claim 1, characterized in that, Also includes: Obtain feedback information regarding the energy-saving recommendations; The energy-saving recommendation rules are adjusted based on the feedback information.

8. The method according to claim 7, characterized in that, The step of obtaining feedback information regarding the energy-saving recommendations includes: Obtain first energy consumption information of the target home appliance before applying the energy-saving suggestion information and second energy consumption information after applying the energy-saving suggestion information; The implementation effect information of the energy-saving suggestion information is determined by combining the first energy consumption information and the second energy consumption information; Obtain user satisfaction information of the target users regarding the energy-saving suggestions; The user satisfaction information and / or the implementation effect information will be used as feedback information for the energy-saving suggestion information.

9. The method according to claim 1, characterized in that, Also includes: Generate visual dynamic charts based on the energy-saving recommendations; The visualized dynamic charts are sent to the target users for display.

10. An energy-saving suggestion generation device for household appliances, characterized in that, The device includes: The rule building module is used to build energy-saving suggestion rules for target home appliances, wherein the energy-saving suggestion rules include energy-saving suggestion information associated with energy-saving influencing factors; An energy-saving influencing factor acquisition module is used to acquire one or more target energy-saving influencing factors of the target home appliance; An energy-saving suggestion information determination module is used to determine energy-saving suggestion information that matches the one or more target energy-saving influencing factors in the energy-saving suggestion rules; The target energy-saving influencing factors include user intent categories, and the energy-saving influencing factor acquisition module includes the following sub-modules: The input data determination submodule is used to determine the input data corresponding to the input operation in response to the input operation for the target home appliance on the input interface of the home appliance energy-saving suggestion generation system. The text information determination submodule is used to determine the initial text information corresponding to the input data; The keyword determination submodule is used to determine keywords from the initial text information; The user intent category determination submodule is used to determine the user intent category based on the keyword. The user intent category is used to characterize the user's energy-saving needs for the target home appliance.

11. An electronic device, characterized in that, The device includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method for generating energy-saving recommendations for the home appliance as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the method for generating energy-saving recommendations for home appliances as described in any one of claims 1 to 9.

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