A processing method, apparatus, and device based on user intent recognition

Abstract

This invention provides a processing method, apparatus, and device based on user intent recognition. The method includes: acquiring energy usage data from multiple users in the current environment; determining the energy-saving intents of the multiple users based on the energy usage data; generating an overall energy-saving plan based on the energy-saving intents of the multiple users; and controlling devices in the current environment according to the overall energy-saving plan. This invention achieves improved energy utilization efficiency and helps reduce energy waste by acquiring energy usage data from multiple users in the current environment and formulating and implementing an overall energy-saving plan based on this data, thereby enhancing the user experience.

Description

Technical Field

[0001] This invention relates to the field of smart home technology, and in particular to a processing method, apparatus, device, medium, and product based on user intent recognition. Background Technology

[0002] In multi-user household environments, family members often exhibit significant differences in their energy usage habits and energy-saving awareness. These differences stem not only from personal characteristics such as age, gender, and occupation, but are also influenced by a variety of factors, including lifestyle habits.

[0003] Most existing energy-saving systems focus on technological optimization, such as improving equipment performance and increasing energy efficiency to achieve energy-saving goals. However, in practical applications, even if the equipment itself has high energy efficiency, the energy-saving effect will still be greatly reduced if the user has improper usage habits or lacks energy-saving awareness.

[0004] For example, some family members like to turn off the lights when leaving the room, while others like to lower the air conditioning temperature. Each family member may have different energy-saving behaviors in real life, which can lead to energy waste and even conflict in some cases. Summary of the Invention

[0005] In view of the above problems, a processing method, apparatus, device, medium, and product based on user intent recognition is proposed to overcome or at least partially solve the above problems, including:

[0006] A processing method based on user intent recognition, the method comprising:

[0007] Obtain energy usage data from multiple users in the current environment;

[0008] Based on the energy usage data, determine the energy-saving intentions of the multiple users;

[0009] Based on the energy-saving intentions of the multiple users, an overall energy-saving plan is generated;

[0010] According to the overall energy-saving plan, the equipment in the current environment is controlled.

[0011] Optionally, generating an overall energy-saving plan based on the energy-saving intentions of the multiple users includes:

[0012] Based on the energy usage data, determine the device usage pattern for each user;

[0013] Based on the energy-saving intentions of the multiple users, determine the overall energy-saving index;

[0014] Based on the overall energy-saving indicators, the device usage patterns for each user are adjusted;

[0015] Generate an overall energy-saving plan based on the adjusted equipment usage patterns.

[0016] Optionally, determining the overall energy-saving index based on the energy-saving intentions of the multiple users includes:

[0017] The energy-saving intentions of each user are quantified to obtain the user energy-saving index for each user;

[0018] The overall energy saving index is determined based on the energy saving indexes of the multiple users.

[0019] Optionally, adjusting the device usage pattern for each user based on the overall energy-saving index includes:

[0020] Based on the overall energy-saving index, the energy-saving index for each user is adjusted;

[0021] Based on the adjusted user energy-saving indicators, the equipment usage patterns for each user will be adjusted.

[0022] Optionally, the overall energy-saving plan includes adjusted device usage modes for each user, and controlling the devices in the current environment according to the overall energy-saving plan includes:

[0023] When a control command from a target user is detected, the devices in the current environment are controlled according to the adjusted device usage mode corresponding to the target user in the overall energy-saving plan.

[0024] Optionally, determining the energy-saving intentions of the multiple users based on the energy usage data includes:

[0025] Based on the energy usage data, generate user profile data for each user;

[0026] Based on the user profile data, the multiple users are clustered to obtain multiple energy-saving behavior groups;

[0027] Each user's energy-saving intentions are determined based on the energy-saving behavior group to which each user belongs.

[0028] Optionally, before controlling the equipment in the current environment according to the overall energy-saving plan, the method further includes:

[0029] The overall energy-saving plan is displayed to the multiple users;

[0030] Upon detecting the target user's confirmation of the overall energy-saving plan, the system executes the control of devices in the current environment according to the overall energy-saving plan.

[0031] Optionally, it also includes:

[0032] Obtain user feedback information;

[0033] The overall energy-saving plan will be adjusted based on the user feedback.

[0034] Optionally, the device is a smart home device.

[0035] A processing apparatus based on user intent recognition, the apparatus comprising:

[0036] The energy usage data acquisition module is used to acquire energy usage data from multiple users in the current environment.

[0037] An energy-saving intent determination module is used to determine the energy-saving intent of the multiple users based on the energy usage data.

[0038] An overall energy-saving plan generation module is used to generate an overall energy-saving plan based on the energy-saving intentions of the multiple users;

[0039] The overall energy-saving plan execution module is used to control the equipment in the current environment according to the overall energy-saving plan.

[0040] An electronic 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 described above.

[0041] A computer-readable storage medium on which a computer program is stored, wherein the computer program, when executed by a processor, implements the method described above.

[0042] A computer program product includes a computer program that, when executed by a processor, implements the method described above.

[0043] The embodiments of the present invention have the following advantages:

[0044] In this embodiment of the invention, by acquiring energy usage data of multiple users in the current environment; determining the energy-saving intentions of multiple users based on the energy usage data; generating an overall energy-saving plan based on the energy-saving intentions of multiple users; and controlling the equipment in the current environment according to the overall energy-saving plan, it is realized that by acquiring energy usage data of multiple users in the current environment and formulating and implementing an overall energy-saving plan based on this data, not only is energy utilization efficiency improved, but energy waste is also reduced and user experience is enhanced. Attached Figure Description

[0045] 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.

[0046] Figure 1 This is a flowchart of a processing method based on user intent recognition provided in some embodiments of the present invention;

[0047] Figure 2 This is a flowchart illustrating a user intent recognition-based processing method provided in some embodiments of the present invention;

[0048] Figure 3 This is a flowchart of another processing method based on user intent recognition provided in some embodiments of the present invention;

[0049] Figure 4 This is a flowchart of another processing method based on user intent recognition provided in some embodiments of the present invention;

[0050] Figure 5 This is a structural block diagram of a processing device based on user intent recognition provided in some embodiments of the present invention. Detailed Implementation

[0051] 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.

[0052] Reference Figure 1 The diagram illustrates a flowchart of a user intent recognition-based processing method according to some embodiments of the present invention, which may specifically include the following steps:

[0053] Step 101: Obtain energy usage data from multiple users in the current environment.

[0054] The current environment can be a specific place or area that requires energy-saving control, such as an office, living room, or bedroom.

[0055] As examples, smart home systems can collect energy usage data from users in the current environment. These systems can connect various smart home devices (such as lighting, appliances, security, and environmental monitoring) in the home via wired or wireless means to form an interconnected network, enabling intelligent management and control of these smart home devices.

[0056] For example, a smart home system can connect to devices such as smart meters, water meters, gas meters, sensors, and monitoring equipment. By deploying sensors and smart meters in the current environment, users' energy usage, such as the consumption data of electricity, natural gas, and water resources, can be monitored in real time.

[0057] In some examples, multiple users in the current environment can be identified through monitoring devices, and a profile can be created for each user to record their user behavior data. This user behavior data can include user actions on devices in the current environment. By utilizing energy usage data over a certain period (e.g., one day) and combining it with user behavior data generated during that period, smart home systems can analyze the energy usage data for multiple users in the current environment. By acquiring the energy usage data of multiple users in the current environment, the energy-saving intentions of these users can be analyzed.

[0058] Step 102: Determine the energy-saving intentions of the multiple users based on the energy usage data.

[0059] Among them, energy-saving intent can indicate whether a user is willing to take measures to reduce energy consumption in order to achieve the goal of energy saving. This intent can be determined by the user's operating behavior on the device in the current environment. Each user's energy-saving intent is different; for example, energy-saving intent can be stingy, generous, or general. Users with stingy energy-saving intent will like to avoid using the device as much as possible to reduce energy consumption; generous users will not turn off the device even if they no longer need it; general users will only turn on the device when needed and will turn it off immediately after use, and the time they use the device is relatively short.

[0060] By acquiring energy usage data for multiple users in the current environment, it is possible to determine each user's energy-saving intentions. For example, a father might like to turn off the lights when leaving a room, while a mother might prefer to lower the air conditioning temperature when leaving a room.

[0061] In some examples, smart home systems can analyze energy usage data to infer or determine whether a user intends to conserve energy.

[0062] In some embodiments of the present invention, determining the energy-saving intentions of the multiple users based on the energy usage data includes: generating user profile data for each user based on the energy usage data; clustering the multiple users based on the user profile data to obtain multiple energy-saving behavior groups; and determining the energy-saving intentions of each user based on the energy-saving behavior group to which each user belongs.

[0063] In some examples, a user profile can be created for each user based on the collected energy usage data (such as electricity consumption, water consumption, gas consumption, etc.) of each user, and user profile data for each user can be determined by combining the user behavior data of each user; the user profile data can include various characteristics and behavioral patterns of the user.

[0064] Before generating user profile data for each user, energy usage data and user behavior data can be preprocessed, including but not limited to data cleaning, removal of outliers and missing values, and feature extraction to extract features that are helpful in identifying energy-saving intentions, thus determining user profile data for each user.

[0065] After generating user profile data for each user, cluster analysis and other techniques can be used to group user profiles with similar energy-saving behavior characteristics into one category to form different energy-saving behavior groups. These energy-saving behavior groups can include stingy groups, generous groups, and general groups. Based on the energy-saving behavior group to which a user belongs, the user's energy-saving intention can be inferred. Since users in the same group have similar energy-saving behavior characteristics, they can be considered to have similar energy-saving intentions.

[0066] As examples, machine learning algorithms can be used to analyze users' usage habits and identify each user's energy-saving intentions. For instance, cluster analysis can be used to distinguish different users' energy-saving behavior patterns, and then unsupervised learning algorithms, such as K-means clustering, can be used to divide users into different energy-saving behavior groups, each of which can represent a specific energy-saving intention or behavior pattern.

[0067] Step 103: Generate an overall energy-saving plan based on the energy-saving intentions of the multiple users.

[0068] The overall energy-saving plan can include energy-saving actions that each user needs to take.

[0069] In some examples, an overall energy-saving plan can be developed based on the energy-saving intentions of multiple users, such as through linear programming or dynamic programming, to balance the energy-saving needs and preferences of different members; incentive mechanisms, such as points rewards or competitions, can also be designed to encourage multiple members to control equipment in accordance with the coordinated overall energy-saving plan.

[0070] For example, in a family environment, if the parents are more frugal and the children are more generous (or the children need a brighter environment), the lights will be dimmed when they need to turn them on in the morning, turned off during the day, and automatically dimmed when only the parents are home at night. The lights will be brighter when the children are home, and only the living room lights will be turned on if the children are in the living room.

[0071] In some embodiments of the present invention, generating an overall energy-saving plan based on the energy-saving intentions of the multiple users includes: determining the device usage mode of each user based on the energy usage data; determining an overall energy-saving index based on the energy-saving intentions of the multiple users; adjusting the device usage mode of each user based on the overall energy-saving index; and generating an overall energy-saving plan based on the adjusted device usage mode.

[0072] In some embodiments of the present invention, the device is a smart home device.

[0073] The device usage pattern can include the device usage time, the number of times the device is used, etc.

[0074] In some examples, by collecting and analyzing each user's energy usage data, such as the amount of electricity, natural gas, or water consumed, and how these consumptions change over time, it is possible to identify each user's device usage patterns, such as which devices are used during which time periods, and the frequency and intensity of use.

[0075] After determining the device usage patterns of each user, the energy-saving intentions of multiple users can be summarized and analyzed to formulate overall energy-saving targets. Then, the device usage patterns of each user can be adjusted to meet the overall energy-saving targets. Adjusting the device usage patterns of each user may include, but is not limited to, changing the usage time of the device or reducing the power of the device.

[0076] After adjusting each user's device usage patterns, an overall energy-saving plan can be developed based on these adjusted patterns. This plan can include information describing how each user should adjust their device usage patterns and how these adjustments will work together to achieve the overall energy-saving goals.

[0077] For example, an energy-saving intention coordination algorithm can be used to combine the device usage patterns of multiple users (such as the usage time of operations like turning off lights and water, and the frequency of switching on and off) to comprehensively coordinate an overall energy-saving plan that meets the habits of each member as much as possible.

[0078] In some embodiments of the present invention, determining the overall energy-saving index based on the energy-saving intentions of the multiple users includes: quantifying the energy-saving intentions of each user to obtain the user energy-saving index of each user; and determining the overall energy-saving index based on the user energy-saving indexes of the multiple users.

[0079] In some examples, each user's energy-saving intentions can be quantified, such as by converting the user's energy-saving intentions into specific, measurable values ​​or indicators (such as scores from 0 to 100).

[0080] By statistically analyzing the energy-saving indicators of these individual users, an overall indicator reflecting the energy-saving behavior of the entire group can be obtained. This overall energy-saving indicator can be the average, sum, median, or other statistical measure of the energy-saving indicators of all users.

[0081] As examples, an energy-saving intent model can be designed, which uses a supervised learning algorithm to transform the user's energy-saving intent into a quantifiable intent representation, such as an energy-saving level or energy-saving score. For the same type of lamp, the higher the energy-saving level, the lower the brightness can be set.

[0082] In some embodiments of the present invention, adjusting the device usage mode of each user according to the overall energy saving index includes: adjusting the user energy saving index of each user according to the overall energy saving index; and adjusting the device usage mode of each user according to the adjusted user energy saving index.

[0083] After obtaining the overall energy-saving index, if some users' energy-saving indexes fail to meet the overall energy-saving index (i.e., the average level of the group or the expected target), in order to promote the improvement of the overall energy-saving effect, the smart home system can adjust the energy-saving indexes of each user accordingly based on the requirements of the overall energy-saving index.

[0084] Among these, there can be a correlation between device usage modes and energy-saving indicators. In order for users to meet the adjusted energy-saving indicators, the smart home system can suggest that users adjust their device usage modes or automatically adjust the device usage modes. For example, the smart home system can automatically adjust the operating mode and power of appliances according to the new energy-saving indicators; it can also suggest that users make adjustments themselves, such as reducing unnecessary device use or choosing more energy-efficient devices.

[0085] For example, if the current cooling temperature of the air conditioner is 20 degrees Celsius and the energy-saving index is 40 points, and the adjusted index is 80 points, then the air conditioner cooling temperature can be adjusted to 26 degrees Celsius according to the adjusted index.

[0086] Step 104: Control the equipment in the current environment according to the overall energy-saving plan.

[0087] Once the overall energy-saving plan is determined, these devices can be adjusted or managed based on the relevant information described in the overall energy-saving plan in order to achieve the energy-saving goal.

[0088] In some embodiments of the present invention, the overall energy-saving plan includes an adjusted device usage mode corresponding to each user, and controlling the devices in the current environment according to the overall energy-saving plan includes: when a control command from a target user is detected, controlling the devices in the current environment according to the adjusted device usage mode corresponding to the target user in the overall energy-saving plan.

[0089] As examples, target users can be users with user profiles who control smart home devices; control commands can be any form of user input, such as commands sent through touchscreens, buttons, remote controls, voice commands, or mobile applications in smart home devices.

[0090] In some examples, smart home devices can receive input or commands from target users. Since the overall energy-saving plan has already adjusted the user energy-saving indicators and device usage patterns of each user in advance based on the overall energy-saving indicators, the adjusted device usage patterns for the target users can be determined from the overall energy-saving plan to control the devices in the current environment.

[0091] In some embodiments of the present invention, before controlling the devices in the current environment according to the overall energy-saving plan, the method further includes: displaying the overall energy-saving plan to the plurality of users; and upon detecting a confirmation operation by the target user regarding the overall energy-saving plan, executing the control of the devices in the current environment according to the overall energy-saving plan.

[0092] As examples, an interactive interface can be pre-designed to display the overall energy-saving plan on the client interface or the screen of a smart home device, allowing users to easily access and implement the overall energy-saving plan.

[0093] After the overall energy-saving plan is displayed, users can confirm the relevant information described in the plan to control the equipment in the current environment according to the plan. Confirmation can be done by clicking a button, selecting an option, or other means to express acceptance and agreement to the information described in the overall energy-saving plan.

[0094] In some embodiments of the present invention, the method further includes: obtaining user feedback information; and adjusting the overall energy-saving plan based on the user feedback information.

[0095] After presenting the overall energy-saving plan to multiple users, the system can collect or receive user feedback, suggestions, satisfaction ratings, and adjustment requests regarding the overall energy-saving plan. This information can then be analyzed to identify areas for improvement or optimization within the overall energy-saving plan, and the plan can be automatically adjusted, or adjusted based on adjustment information from user feedback.

[0096] In some examples, users can adjust their energy-saving intentions within the interactive interface, such as setting personalized energy-saving goals.

[0097] In this embodiment of the invention, by acquiring energy usage data of multiple users in the current environment; determining the energy-saving intentions of multiple users based on the energy usage data; generating an overall energy-saving plan based on the energy-saving intentions of multiple users; and controlling the equipment in the current environment according to the overall energy-saving plan, it is realized that by acquiring energy usage data of multiple users in the current environment and formulating and implementing an overall energy-saving plan based on this data, not only is energy utilization efficiency improved, but energy waste is also reduced and user experience is enhanced.

[0098] The following is in conjunction with the appendix Figure 2 The present invention will be described by way of example:

[0099] Step 201: Start the smart home system.

[0100] Step 202: Collect energy usage data.

[0101] In practical applications, smart home systems can collect energy usage data from family members. For example, they can collect detailed user behavior data, such as the time, frequency, and duration of appliance use, as well as environmental data, such as indoor and outdoor temperature and humidity, as these factors may affect users' energy-saving behavior.

[0102] Next, energy usage data undergoes data preprocessing, which may include data cleaning, removal of outliers and missing values, and feature extraction to identify features that help identify energy-saving intentions. For example, a user's electricity consumption behavior during peak electricity pricing periods may indicate their energy-saving awareness.

[0103] Step 203: Analyze the user's energy-saving intentions.

[0104] In practical applications, machine learning algorithms (such as random forests, support vector machines, or neural networks) can be used to analyze users' usage habits and identify energy-saving intentions.

[0105] For example, cluster analysis can be used to distinguish the energy-saving behavior patterns of different users. Unsupervised learning algorithms, such as K-means clustering, can be used to divide users into different energy-saving behavior groups, each of which can represent a specific energy-saving intention or behavior pattern.

[0106] Clustering algorithms (such as K-means) can be used to group users to identify groups of users with similar energy-saving behavior patterns.

[0107] Step 204: Design an energy-saving intent model.

[0108] In practical applications, an energy-saving intent model can be designed, based on supervised learning algorithms, to transform the user's energy-saving intent into a quantifiable representation, such as an energy-saving level or an energy-saving score.

[0109] In practice, the model can be trained based on historical energy data, and its performance can be evaluated through methods such as cross-validation. The model can be optimized by adjusting its parameters to improve recognition accuracy, and the model can be updated periodically with new user energy data to adapt to changes in user behavior.

[0110] For example, if a user reduces their electricity consumption during peak hours, the model can identify them as a user with energy-saving intentions.

[0111] Step 205: Develop an energy-saving intent coordination algorithm.

[0112] In practical applications, energy-saving intention coordination algorithms can be developed to formulate an overall energy-saving plan based on the energy-saving intentions of multiple users. For example, linear programming or dynamic programming optimization algorithms can be used to balance the energy-saving needs and preferences of different members, and incentive mechanisms, such as points rewards or competitions, can be designed to encourage multiple members to control equipment according to the coordinated overall energy-saving plan.

[0113] Step 206: The interactive interface displays the overall energy-saving plan.

[0114] In practical applications, user-friendly interactive interfaces can be designed to display the overall energy-saving plan, enabling users to easily access and execute energy-saving operations; and feedback mechanisms can be provided to allow users to adjust their energy-saving intentions, such as setting personalized energy-saving goals.

[0115] Step 207: Multiple users execute the overall energy-saving plan.

[0116] In practical applications, the recognition results can be applied to smart home systems to automatically adjust device operation to achieve energy savings.

[0117] Step 208: The system monitors the energy-saving effect.

[0118] In practical applications, smart home systems can analyze the overall energy-saving plan in real time to monitor its implementation effectiveness.

[0119] Step 209: Collect user feedback.

[0120] In practical applications, user feedback is collected to evaluate energy-saving effects and user satisfaction. Based on the feedback, the coordination algorithm is adjusted to optimize the overall energy-saving plan.

[0121] Step 210: Optimize the coordination algorithm.

[0122] In real-world applications, the coordination algorithm can be integrated into existing smart home systems, such as by communicating with smart home devices via APIs, to conduct system testing, including functional testing, performance testing, and user satisfaction testing, ensuring the effectiveness of the coordination mechanism and user satisfaction.

[0123] For example, in a family with multiple members, each with different energy-saving habits, a smart home system collects data and identifies each member's energy-saving intentions. For instance, the father prefers to turn off the lights when leaving a room, while the mother tends to lower the air conditioning temperature. The system uses a coordination algorithm to combine these intentions and create an overall energy-saving plan, such as automatically reducing the brightness of living room lights at night and automatically turning off the air conditioning when family members leave the room. Through the user interface, family members can see energy-saving suggestions and overall energy-saving goals and provide feedback. Based on this feedback, the system continuously optimizes the overall energy-saving plan, improving the family's energy efficiency.

[0124] In this embodiment of the invention, the multi-user family energy-saving intention coordination mechanism can effectively coordinate the energy-saving behavior of family members, improve the efficiency of family energy use, and at the same time take into account individual comfort and living habits to achieve overall optimization of family energy saving. This mechanism not only improves energy utilization efficiency, but also helps to reduce energy waste, enhance family harmony, and provide customized energy-saving suggestions for different family members.

[0125] Reference Figure 3 The diagram illustrates a flowchart of another user intent recognition-based processing method provided by some embodiments of the present invention, which may specifically include the following steps:

[0126] Step 301: Obtain energy usage data from multiple users in the current environment.

[0127] The current environment can be a specific place or area that requires energy-saving control, such as an office, living room, or bedroom.

[0128] As examples, smart home systems can collect energy usage data from users in the current environment. These systems can connect various smart home devices (such as lighting, appliances, security, and environmental monitoring) in the home via wired or wireless means to form an interconnected network, enabling intelligent management and control of these smart home devices.

[0129] For example, a smart home system can connect to devices such as smart meters, water meters, gas meters, sensors, and monitoring equipment. By deploying sensors and smart meters in the current environment, users' energy usage, such as the consumption data of electricity, natural gas, and water resources, can be monitored in real time.

[0130] In some examples, multiple users in the current environment can be identified through monitoring devices, and a profile can be created for each user to record their user behavior data. This user behavior data can include user actions on devices in the current environment. By utilizing energy usage data over a certain period (e.g., one day) and combining it with user behavior data generated during that period, smart home systems can analyze the energy usage data for multiple users in the current environment. By acquiring the energy usage data of multiple users in the current environment, the energy-saving intentions of these users can be analyzed.

[0131] Step 302: Determine the energy-saving intentions of the multiple users based on the energy usage data.

[0132] Among them, energy-saving intent can indicate whether a user is willing to take measures to reduce energy consumption in order to achieve the goal of energy saving. This intent can be determined by the user's operating behavior on the device in the current environment. Each user's energy-saving intent is different; for example, energy-saving intent can be stingy, generous, or general. Users with stingy energy-saving intent will like to avoid using the device as much as possible to reduce energy consumption; generous users will not turn off the device even if they no longer need it; general users will only turn on the device when needed and will turn it off immediately after use, and the time they use the device is relatively short.

[0133] By acquiring energy usage data for multiple users in the current environment, it is possible to determine each user's energy-saving intentions. For example, a father might like to turn off the lights when leaving a room, while a mother might prefer to lower the air conditioning temperature when leaving a room.

[0134] In some examples, smart home systems can analyze energy usage data to infer or determine whether a user intends to conserve energy.

[0135] Step 303: Determine the device usage pattern for each user based on the energy usage data.

[0136] Step 304: Determine the overall energy saving index based on the energy saving intentions of the multiple users.

[0137] Step 305: Adjust the device usage mode for each user based on the overall energy saving index.

[0138] In some embodiments of the present invention, the device is a smart home device.

[0139] The device usage pattern can include the device usage time, the number of times the device is used, etc.

[0140] In some examples, by collecting and analyzing each user's energy usage data, such as the amount of electricity, natural gas, or water consumed, and how these consumptions change over time, it is possible to identify each user's device usage patterns, such as which devices are used during which time periods, and the frequency and intensity of use.

[0141] After determining the device usage patterns of each user, the energy-saving intentions of multiple users can be summarized and analyzed to formulate overall energy-saving targets. Then, the device usage patterns of each user can be adjusted to meet the overall energy-saving targets. Adjusting the device usage patterns of each user may include, but is not limited to, changing the usage time of the device or reducing the power of the device.

[0142] After adjusting each user's device usage patterns, an overall energy-saving plan can be developed based on these adjusted patterns. This plan can include information describing how each user should adjust their device usage patterns and how these adjustments will work together to achieve the overall energy-saving goals.

[0143] For example, an energy-saving intention coordination algorithm can be used to combine the device usage patterns of multiple users (such as the usage time of operations like turning off lights and water, and the frequency of switching on and off) to comprehensively coordinate an overall energy-saving plan that meets the habits of each member as much as possible.

[0144] In some embodiments of the present invention, determining the overall energy-saving index based on the energy-saving intentions of the multiple users includes: quantifying the energy-saving intentions of each user to obtain the user energy-saving index of each user; and determining the overall energy-saving index based on the user energy-saving indexes of the multiple users.

[0145] In some examples, each user's energy-saving intentions can be quantified, such as by converting the user's energy-saving intentions into specific, measurable values ​​or indicators (such as scores from 0 to 100).

[0146] By statistically analyzing the energy-saving indicators of these individual users, an overall indicator reflecting the energy-saving behavior of the entire group can be obtained. This overall energy-saving indicator can be the average, sum, median, or other statistical measure of the energy-saving indicators of all users.

[0147] As examples, an energy-saving intent model can be designed, which uses a supervised learning algorithm to transform the user's energy-saving intent into a quantifiable intent representation, such as an energy-saving level or energy-saving score. For the same type of lamp, the higher the energy-saving level, the lower the brightness can be set.

[0148] In some embodiments of the present invention, adjusting the device usage mode of each user according to the overall energy saving index includes: adjusting the user energy saving index of each user according to the overall energy saving index; and adjusting the device usage mode of each user according to the adjusted user energy saving index.

[0149] After obtaining the overall energy-saving index, if some users' energy-saving indexes fail to meet the overall energy-saving index (i.e., the average level of the group or the expected target), in order to promote the improvement of the overall energy-saving effect, the smart home system can adjust the energy-saving indexes of each user accordingly based on the requirements of the overall energy-saving index.

[0150] Among these, there can be a correlation between device usage modes and energy-saving indicators. In order for users to meet the adjusted energy-saving indicators, the smart home system can suggest that users adjust their device usage modes or automatically adjust the device usage modes. For example, the smart home system can automatically adjust the operating mode and power of appliances according to the new energy-saving indicators; it can also suggest that users make adjustments themselves, such as reducing unnecessary device use or choosing more energy-efficient devices.

[0151] For example, if the current cooling temperature of the air conditioner is 20 degrees Celsius and the energy-saving index is 40 points, and the adjusted index is 80 points, then the air conditioner cooling temperature can be adjusted to 26 degrees Celsius according to the adjusted index.

[0152] Step 306: Generate an overall energy-saving plan based on the adjusted equipment usage pattern.

[0153] The overall energy-saving plan can include energy-saving actions that each user needs to take.

[0154] In some examples, an overall energy-saving plan can be developed based on the energy-saving intentions of multiple users, such as through linear programming or dynamic programming, to balance the energy-saving needs and preferences of different members; incentive mechanisms, such as points rewards or competitions, can also be designed to encourage multiple members to control equipment in accordance with the coordinated overall energy-saving plan.

[0155] For example, in a family environment, if the parents are more frugal and the children are more generous (or the children need a brighter environment), the lights will be dimmed when they need to turn them on in the morning, turned off during the day, and automatically dimmed when only the parents are home at night. The lights will be brighter when the children are home, and only the living room lights will be turned on if the children are in the living room.

[0156] Step 307: Control the equipment in the current environment according to the overall energy-saving plan.

[0157] Once the overall energy-saving plan is determined, these devices can be adjusted or managed based on the relevant information described in the overall energy-saving plan in order to achieve the energy-saving goal.

[0158] In some embodiments of the present invention, the overall energy-saving plan includes an adjusted device usage mode corresponding to each user, and controlling the devices in the current environment according to the overall energy-saving plan includes: when a control command from a target user is detected, controlling the devices in the current environment according to the adjusted device usage mode corresponding to the target user in the overall energy-saving plan.

[0159] As examples, target users can be users with user profiles who control smart home devices; control commands can be any form of user input, such as commands sent through touchscreens, buttons, remote controls, voice commands, or mobile applications in smart home devices.

[0160] In some examples, smart home devices can receive input or commands from target users. Since the overall energy-saving plan has already adjusted the user energy-saving indicators and device usage patterns of each user in advance based on the overall energy-saving indicators, the adjusted device usage patterns for the target users can be determined from the overall energy-saving plan to control the devices in the current environment.

[0161] In some embodiments of the present invention, before controlling the devices in the current environment according to the overall energy-saving plan, the method further includes: displaying the overall energy-saving plan to the plurality of users; and upon detecting a confirmation operation by the target user regarding the overall energy-saving plan, executing the control of the devices in the current environment according to the overall energy-saving plan.

[0162] As examples, an interactive interface can be pre-designed to display the overall energy-saving plan on the client interface or the screen of a smart home device, allowing users to easily access and implement the overall energy-saving plan.

[0163] After the overall energy-saving plan is displayed, users can confirm the relevant information described in the plan to control the equipment in the current environment according to the plan. Confirmation can be done by clicking a button, selecting an option, or other means to express acceptance and agreement to the information described in the overall energy-saving plan.

[0164] In some embodiments of the present invention, the method further includes: obtaining user feedback information; and adjusting the overall energy-saving plan based on the user feedback information.

[0165] After presenting the overall energy-saving plan to multiple users, the system can collect or receive user feedback, suggestions, satisfaction ratings, and adjustment requests regarding the overall energy-saving plan. This information can then be analyzed to identify areas for improvement or optimization within the overall energy-saving plan, and the plan can be automatically adjusted, or adjusted based on adjustment information from user feedback.

[0166] In some examples, users can adjust their energy-saving intentions within the interactive interface, such as setting personalized energy-saving goals.

[0167] In this embodiment of the invention, by acquiring energy usage data from multiple users in the current environment; determining the energy-saving intentions of multiple users based on the energy usage data; determining the device usage mode of each user based on the energy usage data; determining the overall energy-saving index based on the energy-saving intentions of multiple users; adjusting the device usage mode of each user based on the overall energy-saving index; generating an overall energy-saving plan based on the adjusted device usage mode; and controlling the devices in the current environment according to the overall energy-saving plan, this invention not only improves energy utilization efficiency but also helps reduce energy waste and enhances user experience by acquiring energy usage data from multiple users in the current environment and formulating and implementing an overall energy-saving plan based on this data.

[0168] Reference Figure 4 The diagram illustrates a flowchart of another user intent recognition-based processing method provided by some embodiments of the present invention, which may specifically include the following steps:

[0169] Step 401: Obtain energy usage data from multiple users in the current environment.

[0170] Step 402: Determine the energy-saving intentions of the multiple users based on the energy usage data.

[0171] Step 403: Generate an overall energy-saving plan based on the energy-saving intentions of the multiple users.

[0172] Step 404: Present the overall energy-saving plan to the multiple users.

[0173] Step 405: Upon detecting the target user's confirmation operation for the overall energy-saving plan, control the devices in the current environment according to the overall energy-saving plan.

[0174] In this embodiment of the invention, by acquiring energy usage data from multiple users in the current environment; determining the energy-saving intentions of multiple users based on the energy usage data; generating an overall energy-saving plan based on the energy-saving intentions of multiple users; displaying the overall energy-saving plan to multiple users; and controlling the devices in the current environment according to the overall energy-saving plan upon detecting confirmation operations from multiple users for the overall energy-saving plan, the invention achieves the goal of improving energy utilization efficiency, reducing energy waste, and enhancing user experience by acquiring energy usage data from multiple users in the current environment and formulating and implementing an overall energy-saving plan based on this data.

[0175] It should be noted that, for the sake of simplicity, the method embodiments are all 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.

[0176] Reference Figure 5 The diagram illustrates a structural schematic of a user intent recognition-based processing device according to some embodiments of the present invention, which may specifically include the following modules:

[0177] The energy usage data acquisition module 501 is used to acquire energy usage data of multiple users in the current environment.

[0178] The energy-saving intent determination module 502 is used to determine the energy-saving intent of the multiple users based on the energy usage data;

[0179] The overall energy-saving plan generation module 503 is used to generate an overall energy-saving plan based on the energy-saving intentions of the multiple users;

[0180] The overall energy-saving plan execution module 504 is used to control the equipment in the current environment according to the overall energy-saving plan.

[0181] In some embodiments of the present invention, the overall energy-saving plan generation module 503 includes:

[0182] The device usage mode determination submodule is used to determine the device usage mode for each user based on the energy usage data.

[0183] The overall energy saving index determination submodule is used to determine the overall energy saving index based on the energy saving intentions of the multiple users;

[0184] The device usage mode adjustment submodule is used to adjust the device usage mode for each user based on the overall energy saving index.

[0185] The energy-saving plan generation submodule is used to generate an overall energy-saving plan based on the adjusted equipment usage patterns.

[0186] In some embodiments of the present invention, the overall energy-saving index determination submodule includes:

[0187] The energy-saving intent quantification unit is used to quantify the energy-saving intent of each user and obtain the user's energy-saving index.

[0188] The energy-saving index determination unit is used to determine the overall energy-saving index based on the user energy-saving indexes of the multiple users.

[0189] In some embodiments of the present invention, the device uses a mode adjustment submodule, including:

[0190] An energy-saving index adjustment unit is used to adjust the user's energy-saving index for each user based on the overall energy-saving index.

[0191] The equipment usage mode adjustment unit is used to adjust the equipment usage mode for each user based on the adjusted user energy-saving index.

[0192] In some embodiments of the present invention, the overall energy-saving plan includes an adjusted device usage mode for each user, and the overall energy-saving plan execution module 504 includes:

[0193] The device control submodule is used to control the devices in the current environment according to the adjusted device usage mode corresponding to the target user in the overall energy-saving plan when a control command from the target user is detected.

[0194] In some embodiments of the present invention, the energy-saving intention determination module 502 includes:

[0195] The user profile data generation submodule is used to generate user profile data for each user based on the energy usage data.

[0196] The energy-saving behavior group determination submodule is used to cluster the multiple users based on the user profile data to obtain multiple energy-saving behavior groups;

[0197] The user energy-saving intent determination submodule determines each user's energy-saving intent based on the energy-saving behavior group to which each user belongs.

[0198] In some embodiments of the present invention, the apparatus further includes:

[0199] The overall energy-saving plan display module is used to display the overall energy-saving plan to the multiple users;

[0200] The confirmation operation detection module is used to execute the control of the devices in the current environment according to the overall energy saving plan when the confirmation operation of the target user for the overall energy saving plan is detected.

[0201] In some embodiments of the present invention, the apparatus further includes:

[0202] The user feedback information acquisition module is used to acquire user feedback information.

[0203] The overall energy-saving plan adjustment module is used to adjust the overall energy-saving plan based on the user feedback information.

[0204] In some embodiments of the present invention, the device is a smart home device.

[0205] Some embodiments of the present invention also provide an electronic device, including 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 described above.

[0206] Some embodiments of the present invention also provide a computer-readable storage medium on which a computer program is stored, and which, when executed by a processor, implements the method described above.

[0207] Some embodiments of the present invention also provide a computer program product, including a computer program that, when executed by a processor, implements the method described above.

[0208] 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.

[0209] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0210] 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.

[0211] 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.

[0212] This invention is 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.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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 the aforementioned element.

[0217] The above provides a detailed description of a user intent recognition-based processing method, apparatus, device, medium, and product. 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 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 processing method based on user intent recognition, characterized in that, The method includes: Obtain energy usage data from multiple users in the current environment; Based on the energy usage data, determine the energy-saving intentions of the multiple users; Based on the energy-saving intentions of the multiple users, an overall energy-saving plan is generated; According to the overall energy-saving plan, the equipment in the current environment is controlled; The step of generating an overall energy-saving plan based on the energy-saving intentions of the multiple users includes: Based on the energy usage data, determine the device usage pattern for each user; Based on the energy-saving intentions of the multiple users, determine the overall energy-saving index; Based on the overall energy-saving indicators, the device usage patterns for each user are adjusted; Generate an overall energy-saving plan based on the adjusted equipment usage patterns.

2. The method according to claim 1, characterized in that, The step of determining the overall energy-saving index based on the energy-saving intentions of the multiple users includes: The energy-saving intentions of each user are quantified to obtain the user energy-saving index for each user; The overall energy saving index is determined based on the energy saving indexes of the multiple users.

3. The method according to claim 2, characterized in that, The adjustment of each user's device usage mode based on the overall energy-saving index includes: Based on the overall energy-saving index, the energy-saving index for each user is adjusted; Based on the adjusted user energy-saving indicators, the equipment usage patterns for each user will be adjusted.

4. The method according to any one of claims 1 to 3, characterized in that, The overall energy-saving plan includes adjusted device usage modes for each user, and controlling the devices in the current environment according to the overall energy-saving plan includes: When a control command from a target user is detected, the devices in the current environment are controlled according to the adjusted device usage mode corresponding to the target user in the overall energy-saving plan.

5. The method according to any one of claims 1 to 3, characterized in that, Determining the energy-saving intentions of the multiple users based on the energy usage data includes: Based on the energy usage data, generate user profile data for each user; Based on the user profile data, the multiple users are clustered to obtain multiple energy-saving behavior groups; Each user's energy-saving intentions are determined based on the energy-saving behavior group to which each user belongs.

6. The method according to any one of claims 1 to 3, characterized in that, Before controlling the equipment in the current environment according to the overall energy-saving plan, the method further includes: The overall energy-saving plan is displayed to the multiple users; Upon detecting a confirmation operation from the target user regarding the overall energy-saving plan, the process of controlling the devices in the current environment according to the overall energy-saving plan is executed.

7. The method according to any one of claims 1 to 3, characterized in that, Also includes: Obtain user feedback information; The overall energy-saving plan will be adjusted based on the user feedback.

8. The method according to claim 1, characterized in that, The device in question is a smart home device.

9. A processing apparatus based on user intent recognition, characterized in that, The device includes: The energy usage data acquisition module is used to acquire energy usage data from multiple users in the current environment. An energy-saving intent determination module is used to determine the energy-saving intent of the multiple users based on the energy usage data. An overall energy-saving plan generation module is used to generate an overall energy-saving plan based on the energy-saving intentions of the multiple users; An overall energy-saving plan execution module is used to control the equipment in the current environment according to the overall energy-saving plan; The overall energy-saving plan generation module includes: The device usage mode determination submodule is used to determine the device usage mode for each user based on the energy usage data. The overall energy saving index determination submodule is used to determine the overall energy saving index based on the energy saving intentions of the multiple users; The device usage mode adjustment submodule is used to adjust the device usage mode for each user based on the overall energy saving index. The energy-saving plan generation submodule is used to generate an overall energy-saving plan based on the adjusted equipment usage patterns.

10. An electronic device, characterized in that, It 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 as described in any one of claims 1 to 8.

11. 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 as described in any one of claims 1 to 8.

12. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 8.

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