Intelligent screen control method and system for gas heating water heater

Abstract

The invention relates to the technical field of water boiler intelligent screen control, and provides a gas heating water heater intelligent screen control method and system, and the method comprises the steps: collecting operation behavior data and environment situation data of a user on an intelligent screen of a gas heating water heater in real time; according to the operation behavior data and the environment situation data, the instant intention and the situation of the user are judged; and according to the instant intention and the situation of the user, the interaction mode, the function presentation priority and the information pushing strategy of the intelligent screen are adjusted, so that intelligent screen control over the gas heating water heater is achieved. The gas heating water heater has the effect of improving the operation efficiency and the use experience of the gas heating water heater.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water stove wisdom screen control, in particular to a gas heating water stove wisdom screen control method and system. BACKGROUND

[0002] With the rapid development of smart home technology, as the core equipment of household heating and hot water supply, the control mode of gas heating water stove is gradually upgrading from traditional mechanical knobs or monochrome LCD screens to intelligent and visual direction. However, most of the gas heating water stove products on the market still use simple buttons or low-resolution display screens, with single operation interface and limited information display, which cannot meet the user's demand for intuitive perception of device status, multi-functional integration and remote interaction.

[0003] The existing gas heating water stove control technology has obvious limitations: first, the operation interface has poor interactivity, most products only support basic parameter display, and cannot realize graphical menu navigation or multimedia information prompt; second, the control function is single, lacking modern interactive capabilities such as high-definition video playback and touch sliding operation; third, the device is strongly isolated, and is not effectively combined with mobile Internet, so users cannot realize remote monitoring or software upgrade through wireless network. These problems make it difficult for users to intuitively grasp the running status of the device, and limit the functional expansion space of gas heating water stove in the smart home scene. Users generally reflect that when trying to adjust the heating temperature or hot water setting, they need to repeatedly press the keys or search layer by layer in the simple menu, which is inefficient. When the gas heating water stove device is abnormal, an abstract fault code is often displayed on the screen, and the user cannot intuitively understand the problem, nor can they obtain multimedia guidance for preliminary troubleshooting. In addition, due to the lack of remote connection capability, users cannot turn on the heating in advance when they are out, nor can they check the running status of the gas heating water stove device in real time, which greatly reduces the convenience experience of smart home. Especially in the modern residential environment, users expect the gas heating water stove device not only to run efficiently, but also to seamlessly integrate with the smart home system, and to improve the user experience through more humanized interaction mode.

[0004] In view of the above problems, the existing technology needs to be improved. SUMMARY

[0005] The present application discloses a gas heating water stove wisdom screen control method and system, which aims to solve the problems of poor interactivity of operation interface, single control function, strong isolation of device, difficulty in meeting the user's demand for intuitive perception of device status, multi-functional integration and remote interaction in the existing gas heating water stove control technology, and difficulty for users to intuitively grasp the running status of the device, which limits the functional expansion space of gas heating water stove in the smart home scene.

[0006] The technical solution of the present application is as follows: In a first aspect, the application discloses a gas heating water heater smart screen control method, comprising: Real-time collection of user operation behavior data and environmental context data on the smart screen of the gas heating water heater; According to the operation behavior data and the environmental context data, the user's user immediate intention and the situation are judged; According to the user's immediate intention and the situation, the interaction mode, the function presentation priority and the information push strategy of the smart screen are adjusted to realize the gas heating water heater smart screen control.

[0007] Through the technical scheme, the real-time perception and intelligent analysis of user operation behavior and environmental context can be realized, and then the interaction mode, the function presentation priority and the information push strategy of the smart screen are dynamically adjusted, so that the intelligent control level and the user experience of the gas heating water heater are significantly improved, and the problems of poor operation interface interaction, single control function and strong device isolation in the prior art are effectively solved.

[0008] Further, in some embodiments, the step of judging the user's user immediate intention and the situation according to the operation behavior data and the environmental context data comprises: Based on the operation behavior data and the environmental context data, it is judged whether there is a conflict or ambiguity situation, and if the judgment result is yes, the existing conflict or ambiguity situation is identified; Based on the existing conflict or ambiguity situation, the potential user intention is weighted and evaluated according to the preset priority rule and the current environmental situation, and the initial weight of the potential user intention is obtained; Combined with the historical operation habit data of the user, the initial weight of the potential user intention is adjusted to obtain the adjusted weight of the potential user intention; According to the adjusted weight of the potential user intention, the user's user immediate intention and the situation are judged; When the potential user intention has a conflict or ambiguity situation, an intention confirmation option is provided to the user; According to the feedback information of the user on the intention confirmation option, the user's immediate intention is determined.

[0009] Through the technical scheme, the user's immediate intention can be more accurately identified through multi-dimensional data analysis and conflict ambiguity processing mechanism, and the user experience is improved through the intention confirmation option, which effectively avoids misjudgment and operation errors, so that the control of the smart screen is more accurate and humanized.

[0010] Further, in some embodiments, the step of judging the user's user immediate intention and the situation according to the operation behavior data and the environmental context data comprises: Collecting physiological state data and activity demand data of a user, and integrating the physiological state data and the activity demand data into comprehensive state demand information; Integrating preset priority rules and a current environment scenario into state demand verification information; Identifying an inconsistency between the comprehensive state demand information and the state demand verification information; Generating a physiological activity-specific weight factor according to the physiological state data, the activity demand data, and the inconsistency; Evaluating the physiological activity-specific weight factor and the preset priority rules to obtain a weight evaluation result; Fusing the weight evaluation result and the physiological activity-specific weight factor to correct a weighted evaluation result of a potential user intention as an initial weight of the potential user intention.

[0011] Through the technical solution, the physiological state and the activity demand data are introduced, and multi-dimensional evaluation is performed in combination with the priority rules and the environment scenario, so that the weight evaluation of the potential user intention is more refined and personalized, thereby improving the accuracy and adaptability of intention judgment.

[0012] On the basis of the above, the present application further proposes that when the potential user intention has a conflict or ambiguity, the step of providing an intention confirmation option for the user includes: When the potential user intention has a conflict or ambiguity, displaying the intention confirmation option on a screen of the smart screen, and presenting the intention confirmation option in the form of dynamic flashing or gradual high-lighting; Adjusting the position of the intention confirmation option on the screen to move the intention confirmation option within the user's line of sight; Playing a voice prompt in a periodic and gradually increasing volume to guide the user to focus on the intention confirmation option on the screen; If the user does not perform screen touch or voice response within a preset time, pushing a notification containing the intention confirmation option to an associated user mobile terminal; Receiving feedback of the user on the intention confirmation option through the user mobile terminal, and determining an instant intention of the user.

[0013] Through the technical solution, the user can be effectively guided to focus on and confirm the potential intention through multi-modal prompting methods (vision, hearing, mobile terminal pushing) and dynamic interaction design, which significantly improves the operation convenience and accuracy of the user in a complex situation, and avoids misoperation caused by ambiguous intention.

[0014] As an optional solution, the present application further discloses that according to the user instant intention and the situation, adjusting the interaction mode, the function presentation priority, and the information pushing strategy of the smart screen to realize the step of controlling the gas heating water heater smart screen, which includes: Monitor the user's real-time intent and the context in which they are situated, and obtain the corresponding rate and magnitude of change for each. When the rate of change and the magnitude of change reach their respective preset upper limits, the currently activated interaction methods, function presentation priorities, and information push strategies are identified. Calculate new adjustment schemes based on the new user's immediate intent and context; Compare the differences between the new adjustment plan and the currently activated interaction methods, function presentation priorities, and information push strategies; When the difference exceeds a preset threshold, a transition animation or gradient effect is executed, and a prompt sound is played to smoothly switch to the new adjustment scheme. Maintain and adjust the cooldown time mechanism, and prioritize new adjustment plans during the cooldown period; When the number of potential user intents is greater than one, the new adjustment scheme corresponding to the potential user intent with higher priority is executed first.

[0015] This technical solution enables dynamic monitoring of intent and context changes, and introduces smooth switching and cooling-off time mechanisms to ensure a natural and smooth adjustment process for the smart screen, avoiding frequent or abrupt interface changes. At the same time, through a priority evaluation mechanism, it prioritizes key needs in multi-intent scenarios, significantly improving system stability and user experience.

[0016] In one implementation, when the difference exceeds a preset threshold, the steps of executing a transition animation or gradient effect and playing a prompt sound to smoothly switch to the new adjustment scheme include: Collect ambient light intensity data and user visual impairment information; Adjust the brightness, contrast, and duration of transition animations or gradient effects based on ambient light intensity data; Adjust the color saturation, element size, and motion trajectory of transition animations or gradient effects based on the user's visual impairment information; In low-light environments or when users have visual impairments, increase the visual contrast of transition animations or gradient effects and extend the duration of transition animations or gradient effects.

[0017] This technical solution can adaptively adjust the visual parameters of transition animations and gradient effects based on ambient lighting and user visual impairment information, significantly improving the readability and accessibility of smart screens under different lighting conditions and for different user groups, and enhancing the inclusiveness of the user experience.

[0018] In another implementation, when the difference exceeds a preset threshold, the steps of performing a transition animation or gradient effect and playing a prompt sound to smoothly switch to the new adjustment scheme include: Collect environmental noise data; Based on the ambient noise data, adjust the volume of the prompt sound so that the volume of the prompt sound is higher than the preset decibel value of the ambient noise data; Collect the user's defined level of hearing impairment; Adjust the frequency range of the prompt tone according to the level of hearing loss, so that the frequency range of the prompt tone avoids the frequency bands where the user's hearing sensitivity is reduced; Increase the duration of the alert sound.

[0019] This technical solution can adaptively adjust the volume, frequency, and duration of the prompt tone according to the ambient noise and the user's level of hearing impairment, significantly improving the audibility and recognizability of the prompt tone in noisy environments or for users with hearing impairment, and ensuring the effective delivery of key information.

[0020] As a further improvement, when the difference exceeds a preset threshold, a transition animation or gradient effect is executed, and a prompt sound is played to smoothly switch to the new adjustment scheme. The steps include: Collect user behavior data and environmental context data; Based on user behavior data and environmental context data, determine whether the user is in a multitasking state and obtain the processing status judgment result; If the processing status judgment result indicates that the user is in a multitasking state, then reduce the visual intensity of the transition animation or gradient effect. If the processing status judgment result indicates that the user is in a multitasking state, then increase the recognizability of the prompt sound; If the processing status judgment result indicates that the user is in a multitasking state, then adjust the display area of ​​the transition animation or gradient effect.

[0021] This technical solution can intelligently adjust the visual intensity of transition animations, the recognizability of prompt sounds, and the display area based on whether the user is in a multitasking state, effectively reducing interference with the user's attention and improving the user's operating efficiency and experience in multitasking scenarios.

[0022] To enhance functionality, if the processing status determination result indicates that the user is in a multitasking state, the steps to increase the recognizability of the prompt sound include: Continuously monitor the user's head orientation and gaze direction; Adjust the playback direction and volume distribution of the prompt tone according to the direction of the head's orientation and line of sight.

[0023] This technical solution can dynamically adjust the playback direction and volume distribution of prompt sounds by monitoring the user's head orientation and gaze direction, making the prompt sounds more accurately attract the user's attention. Especially when the user is multitasking, it significantly improves the recognition and effectiveness of the prompt sounds.

[0024] Secondly, this application also discloses a smart screen control system for a gas-fired heating and hot water boiler, used to perform smart screen control of the gas-fired heating and hot water boiler, including: The real-time data acquisition module is used to collect user operation behavior data and environmental context data on the smart screen of the gas-fired heating and hot water boiler in real time. The data analysis and judgment module is used to determine the user's immediate intent and current situation based on operational behavior data and environmental context data. The smart screen control module is used to adjust the smart screen's interaction method, function presentation priority, and information push strategy according to the user's real-time intentions and the current situation, so as to realize the smart screen control of the gas heating hot water boiler.

[0025] This technical solution provides a system-level solution for intelligent screen control of gas-fired heating and hot water boilers. Through modular design, the functions of data acquisition, intent judgment, and intelligent screen control are clearly defined, ensuring efficient operation and scalability of the system, thereby effectively improving the intelligence level and user experience of gas-fired heating and hot water boilers.

[0026] Beneficial Effects: The smart screen control method for gas-fired heating and hot water boilers disclosed in this application collects real-time user operation behavior data and environmental context data on the smart screen. Based on this data, it determines the user's immediate intention and current situation, and then dynamically adjusts the smart screen's interaction method, function presentation priority, and information push strategy. This method effectively solves the problems of poor user interface interactivity, limited control functions, and strong device isolation in existing gas-fired heating and hot water boiler control technologies. Specifically, through intelligent analysis of user operation behavior and environmental context, the system can more accurately understand user needs and provide a personalized interactive experience, avoiding the cumbersome button operations and information searches of traditional control methods. Simultaneously, dynamically adjusting the function presentation priority and information push strategy enables users to intuitively and efficiently obtain the information they need and achieve convenient control of the equipment, significantly improving the user's intuitive perception of equipment status and multi-functional integrated experience. Furthermore, this method provides a technical foundation for the seamless integration of gas-fired heating and hot water boilers with smart home systems through intelligent control, overcoming the limitations of strong equipment isolation in existing technologies. This greatly enhances the convenience of smart home experiences, enabling gas-fired heating and hot water boilers to not only operate efficiently but also improve the overall user experience through more user-friendly interaction. Attached Figure Description

[0027] Figure 1 This is a flowchart of a smart screen control method for a gas-fired heating and hot water boiler according to one embodiment of the present invention; Figure 2 This is a flowchart of a smart screen control method for a gas-fired heating hot water boiler according to another embodiment of the present invention; Figure 3 This is a system block diagram of a smart screen control system for a gas-fired heating and hot water boiler according to another embodiment of the present invention; Explanation of reference numerals in the attached figures: 1. Smart screen control system for gas-fired heating and hot water boilers; 11. Real-time data acquisition module; 12. Data analysis and judgment module; 13. Smart screen control module. Detailed Implementation

[0028] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0029] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0030] Traditional gas-fired heating and hot water boilers typically use mechanical knobs or monochrome LCD screens for control, resulting in a limited user interface and information display. This fails to meet users' needs for intuitive device status monitoring, multi-functional integration, and remote interaction. Consequently, adjusting heating or hot water settings is inefficient, and users struggle to understand problems or obtain multimedia guidance when equipment malfunctions. Furthermore, the lack of remote connectivity significantly reduces the convenience of smart home experiences.

[0031] In response, this application proposes a smart screen control method for gas-fired heating and hot water boilers, combining... Figure 1 As shown, it includes: S1 collects real-time user operation behavior data and environmental context data on the smart screen of the gas-fired heating and hot water boiler; S2, based on operational behavior data and environmental context data, determines the user's immediate intent and current situation; S3 adjusts the interaction method, function presentation priority, and information push strategy of the smart screen according to the user's real-time intention and the situation, so as to realize the smart screen control of the gas heating and hot water boiler.

[0032] To make the technical solution of this application easier and clearer to understand, the key terms involved will be explained first.

[0033] "Smart screen" refers to an intelligent control terminal that integrates a display screen and interactive functions. It can display device status, provide an operating interface, and support multiple interaction methods, such as touch and voice.

[0034] "Operational behavior data" refers to all operations recorded by the user on the smart screen, including but not limited to touch, swipe, button, and voice commands.

[0035] "Environmental context data" refers to real-time information about the environment in which the gas-fired heating and hot water boiler is located, such as indoor temperature, humidity, light intensity, outdoor temperature, and weather conditions.

[0036] "User's immediate intent" refers to the operation or state that the user currently wants the gas-fired heating and hot water boiler to perform, such as adjusting the temperature, switching modes, or querying information.

[0037] "Context" refers to the user's current environment and state, such as being at home, out and about, sleeping, or exercising.

[0038] "Interaction method" refers to the way smart screens exchange information and receive commands from users, such as graphical interface, voice interaction, gesture control, etc.

[0039] "Function presentation priority" refers to the display order and prominence of various functional modules on the smart screen, such as prioritizing the display of frequently used functions and highlighting emergency notifications.

[0040] "Information push strategy" refers to the methods and content by which smart screens send notifications, reminders, or suggestions to users, such as pop-up prompts, voice broadcasts, and message lists.

[0041] The implementation environment of this application is typically a home or commercial premises. The gas-fired heating and hot water boiler is connected to the smart screen via a network. The smart screen obtains environmental context data through sensors or external data sources and obtains operational behavior data through user operations.

[0042] The core of the smart screen control method for gas-fired heating and hot water boilers in this application lies in the intelligent perception and response to user intentions and situations.

[0043] Firstly, various methods can be employed to collect real-time user operation behavior data and environmental context data on the smart screen of the gas-fired heating and hot water boiler. For example, the smart screen can have built-in touch sensors and microphones to record the user's touch trajectory, click locations, and voice commands in real time as operation behavior data. Simultaneously, the smart screen can integrate temperature, humidity, and light sensors and connect to an external meteorological service interface to obtain environmental context data such as indoor temperature, humidity, light intensity, and outdoor weather. Another approach is for the smart screen to connect to the user's mobile terminal via Bluetooth or Wi-Fi to obtain the user's operation records and location information, combining this with the operating status sensor data from the gas-fired heating and hot water boiler itself to form both operation behavior data and environmental context data.

[0044] Secondly, in determining a user's immediate intent and current situation based on operational behavior data and environmental context data, the following methods can be used. For example, the system can preset a series of rules. When a user clicks the "heat up" button three times consecutively on the smart screen, and the environmental context data shows that the room temperature is lower than the set temperature, the system determines that the user's immediate intent is "to increase the heating temperature." When the environmental context data shows nighttime and the user has not performed any operation for a long time, the system determines that the user's current situation is "sleep mode." Another approach is that the system can utilize machine learning models. By training on a large amount of historical operational behavior data and environmental context data, the system can learn the correlation between user behavior patterns and intent / context. When receiving new operational behavior data and environmental context data, the model can predict the user's immediate intent and current situation. For example, when a user frequently checks the hot water temperature within a specific time period, and the environmental context data shows shower time, the model may determine that the user's intent is "preparing to take a shower," and the current situation is "taking a shower at home."

[0045] Finally, regarding adjusting the smart screen's interaction methods, function presentation priorities, and information push strategies based on the user's immediate intent and the context, the following specific implementations can be made. For example, when the system determines that the user's immediate intent is "to increase the heating temperature" and the context is "at home," the smart screen's interaction method can be adjusted to highlight the temperature adjustment slider, the function presentation priority should place the heating temperature adjustment function first, and the information push strategy can display a prompt such as "The current room temperature is low; it is recommended to increase the heating temperature." Another implementation is that when the system determines that the user's immediate intent is "to query fault information" and the context is "equipment malfunction," the smart screen's interaction method can be switched to voice interaction, guiding the user to speak the fault code, the function presentation priority should place fault diagnosis and solutions in the most prominent position, and the information push strategy can push multimedia information including fault code explanations, troubleshooting steps for common problems, and contact after-sales service.

[0046] Optional, combinedFigure 2 As shown, the steps S2 takes to determine the user's immediate intent and current situation based on operational behavior data and environmental context data include: S21. Based on operational behavior data and environmental context data, determine whether there is a conflict or ambiguity. If the determination result is yes, then identify the existing conflict or ambiguity. S22, based on existing conflicts or ambiguities, and according to preset priority rules and the current environmental context, the potential user intent is weighted and evaluated to obtain the initial weight of the potential user intent; S23, combine the user's historical operation habit data to adjust the initial weight of potential user intent, and obtain the adjusted potential user intent weight; S24, Based on the adjusted potential user intent weights, determine the user's immediate intent and current context; S25, When there is a conflict or ambiguity in the intent of a potential user, provide the user with an intent confirmation option; S26, determine the user's immediate intent based on the user's feedback on the intent confirmation option.

[0047] Specifically, when determining a user's immediate intent and context, the system first conducts a preliminary analysis of potential user intents based on real-time collected operational behavior data and environmental context data. Based on this, the system determines whether these potential intents are conflicting or ambiguous. For example, if a user performs two seemingly contradictory actions consecutively within a short period (such as first raising the heating temperature and then immediately lowering it), or if an action has multiple reasonable interpretations within the current context, it is identified as conflicting or ambiguous. After identifying conflicts or ambiguities, the system does not immediately make a judgment. Instead, it uses these conflicts or ambiguities, combined with preset priority rules and the current specific environmental context, to perform a weighted evaluation of all potential user intents, thereby obtaining an initial weight for each potential user intent. The preset priority rules can be set according to principles such as product design, user safety, or energy conservation. For example, in cold weather, heating-related intents may have higher priority; and the current environmental context may include factors such as outdoor temperature, indoor humidity, and time of day.

[0048] Furthermore, to improve the personalization and accuracy of intent judgment, the system also incorporates users' historical operation habit data to adjust the initial weights of the potential user intents obtained above, thus obtaining adjusted potential user intent weights. For example, if a user typically performs a hot shower operation within a specific time period, the system will increase the weight of the intent "hot shower" based on historical habits, even if the current operation is somewhat ambiguous. Ultimately, the system will determine the user's immediate intent and the context based on the adjusted potential user intent weights.

[0049] It is worth noting that after the aforementioned weighted evaluation and historical data adjustment, if potential user intentions still exhibit conflict or ambiguity—that is, if no single intention has a significantly higher weight than others, or if the weights of multiple intentions are very close—the system will proactively offer the user an intention confirmation option. These options aim to clarify the user's true intention and prevent the system from making incorrect judgments. After receiving feedback from the user regarding the intention confirmation option, the system can ultimately determine the user's immediate intention.

[0050] It should be noted that ambiguity refers to a situation where, when determining a user's immediate intent, the system, based on collected operational behavior data and environmental context data, cannot clearly identify a single, definite user intent, or multiple potential intents with similar probabilities exist, making it difficult for the system to make a unique decision. In this state, the boundaries of the user's intent are unclear, or there is overlap or conflict between different intents.

[0051] Ambiguity arises when, based on operational behavior data and environmental context data, the user's immediate intent might simultaneously refer to both "taking a bath" and "doing laundry." This step addresses the problem in traditional home control systems where inaccurate user intent identification or inability to distinguish complex situations is a common issue. When the system identifies ambiguity, it takes step-by-step or branching actions to avoid directly determining the user's intent, which could lead to erroneous operations. The purpose of identifying ambiguity is to trigger a subsequent intent confirmation mechanism. Through steps such as historical evaluation, integration of historical operational habit data, and providing the user with intent confirmation options, this uncertainty is eliminated. This ensures that the system can accurately determine the user's immediate intent and the surrounding context, avoiding misoperations and improving control precision and user experience.

[0052] For example, in a home water heater usage scenario, a user operates the system in a high-temperature environment. The real-time data acquisition module captures user behavior data, such as the user clicking the "gentle warmth" and "hot water" icons consecutively within a short period. Simultaneously, environmental context data (e.g., an indoor temperature sensor showing a room temperature of 20°C, and an outdoor temperature sensor showing a temperature of 5°C) is also collected. When processing this data, the data analysis and judgment module may identify ambiguities. For instance, a user quickly clicking "gentle warmth" might indicate an intention to turn on the heating, but immediately clicking "hot water" might indicate an intention to use hot water. Both intentions are plausible in the current context but conflict with each other, making it impossible for the system to directly determine the user's true intention. In this case, the system will determine that ambiguity exists and initiate a subsequent intention confirmation process.

[0053] Optionally, based on existing conflicts or ambiguities, the steps to obtain the initial weights of potential user intentions by weighting them according to preset priority rules and the current environmental context include: Collect users' physiological status data and activity demand data, and integrate them into comprehensive status demand information; The preset priority rules and the current environment scenario are integrated into state requirement verification information; Identify inconsistencies between the comprehensive state requirement information and the state requirement verification information; Based on physiological state data, activity demand data, and inconsistencies, physiological activity-specific weighting factors are generated. The physiological activity-specific weighting factors are evaluated against the preset priority rules to obtain the weighting evaluation results; By integrating the weighted evaluation results with physiological activity-specific weighting factors, a weighted evaluation result of potential user intent is obtained and used as the initial weight of potential user intent.

[0054] Specifically, physiological state data can be understood as real-time or historical data reflecting a user's physical condition, such as heart rate, body temperature, respiratory rate, sleep patterns, and fatigue level. Activity demand data refers to the environmental demands generated by a user's current or anticipated activities, such as exercise, rest, cooking, and reading. Once collected, this data can be integrated into comprehensive state demand information to fully reflect the user's current physiological and activity status. For example, when a user's heart rate and body temperature rise, it may indicate that the user is engaged in physical activity or feels hot.

[0055] The preset priority rules can include user-defined preference settings, system default comfort parameters, or general rules derived from big data analysis. The current environmental context includes room temperature, humidity, lighting, and air quality. This information is integrated into state requirement verification information, which is used to compare it with the user's comprehensive state requirement information.

[0056] In practical applications, identifying inconsistencies between comprehensive state requirement information and state requirement verification information refers to the difference between the user's actual physiological activity state and the state inferred by the system based on the environment and preset rules. For example, if the ambient temperature is low, but the user's physiological state data shows that they are exercising vigorously and sweating, this is an inconsistency.

[0057] Based on physiological state data, activity demand data, and inconsistencies, a physiological activity-specific weighting factor can be generated. This weighting factor aims to quantify the degree to which a user's individualized physiological and activity demands influence the judgment of potential intentions. For example, when a user is asleep, their sensitivity to temperature changes may be higher, and the physiological activity-specific weighting factor related to sleep would be increased.

[0058] Furthermore, the physiological activity-specific weighting factors are evaluated against preset priority rules to obtain weight evaluation results. This evaluation process can employ methods such as machine learning models, fuzzy logic, or expert systems to determine how the physiological activity-specific weighting factors should correct the influence of the preset priority rules in the current context.

[0059] Finally, by integrating the weighted evaluation results with physiological activity-specific weighting factors, a weighted evaluation result of potential user intent is obtained and used as the initial weight of potential user intent. This means that, based on the traditional weighted evaluation based on environment and preset rules, a more refined consideration of individualized user physiological and activity states is introduced, making the determination of the initial weight more closely aligned with the user's actual needs.

[0060] In some preferred embodiments, a specific example is given below. Suppose a user returns home on a winter evening when the room temperature is low. The smart screen might initially determine, based on environmental context data, that the user needs to turn on the heating function. However, with the solution of this application, the system further collects the user's physiological state data (e.g., a higher heart rate and slightly higher than normal body temperature detected by wearable devices) and activity demand data (e.g., the user is engaged in indoor fitness activities). At this point, the comprehensive status demand information indicates that the user is in an exercise state, while the status demand verification information (based on the need for heating due to low room temperature) is inconsistent. Based on these inconsistencies, the system generates a physiological activity-specific weighting factor of "not suitable for overheating during exercise." This weighting factor is evaluated and integrated with preset heating priority rules, so that the initial weight of the potential user's intention is no longer simply inclined towards "turning on the heating," but may be adjusted to "keeping ventilation," "weak heating," or even "turning on the cooling," thereby more accurately reflecting the user's true needs during exercise, avoiding blindly turning on the heating due to low ambient temperature, and improving the comfort and intelligence level of the user experience.

[0061] Optionally, when there are conflicting or ambiguous intentions among potential users, the step of providing the user with an intention confirmation option includes: When there are conflicting or ambiguous intentions of potential users, an intention confirmation option is displayed on the smart screen, and the intention confirmation option is presented in the form of dynamic flashing or gradual highlighting. Adjust the position of the intent confirmation option on the screen so that it moves within the user's field of vision; Play voice prompts periodically with progressively increasing volume to guide user attention to intent confirmation options on the screen; If the user does not perform screen touch or voice response within a preset time, a notification containing an intent confirmation option will be pushed to the associated user's mobile terminal. Receive feedback from the user via their mobile device regarding the intent confirmation option and determine the user's immediate intent.

[0062] Specifically, when the system determines that a potential user's intent is conflicting or ambiguous, an intent confirmation option will be displayed on the smart screen to ensure that the user can promptly notice and understand these intents requiring confirmation. To enhance its visual prominence, the intent confirmation option can be presented through dynamic flashing or gradual highlighting. Dynamic flashing refers to the intent confirmation option periodically switching between being displayed and hidden at a certain frequency, or rapidly changing between different brightness and colors to attract the user's attention. Gradual highlighting refers to the intent confirmation option's brightness, color, or background gradually increasing in a smooth transition, making it stand out from surrounding elements and guiding the user's visual focus.

[0063] Furthermore, to ensure that the intent confirmation option remains within the user's field of vision to the greatest extent possible, its position on the screen can be dynamically adjusted. For example, the intent confirmation option can move slowly along a preset path on the screen, or its display position can be intelligently adjusted based on the user's head posture, eye-tracking data, and other information, so that it is always located near the area currently being focused on by the user, thereby increasing the probability of the user discovering and responding.

[0064] In addition, to provide multimodal cues, voice prompts are played periodically with progressively increasing volume to guide user attention to the intent confirmation options on the screen. Periodic playback means that the voice prompts are repeated at regular intervals to prevent users from missing them due to brief distractions. Progressively increasing volume means that the volume of the prompt gradually increases with each repetition until it reaches a preset maximum volume. This method gently attracts the user's attention, avoids sudden loud noises that could startle them, and ensures that the user can hear it under different ambient noise levels.

[0065] As a backup and important interaction mechanism, if the user does not interact with the screen or respond via voice within a preset time, the system will determine that the user may not have noticed the prompt on the smart screen or may be temporarily unable to interact. In this case, the system will push a notification containing an intent confirmation option to the associated user's mobile device. This notification can be presented as a pop-up message, vibration, or ringtone, ensuring that the user receives the confirmation request even when not in front of the smart screen.

[0066] Ultimately, the system receives feedback from the user via their mobile device regarding the intent confirmation option. The user can then select the corresponding option on their mobile device to confirm or modify their intent. Based on this feedback, the system can accurately determine the user's immediate intent, thereby avoiding erroneous operations caused by conflicting or ambiguous intents.

[0067] In some preferred embodiments, a specific example is given below. Suppose a user operates the smart screen of a gas-fired heating and hot water boiler. Based on the user's behavior data and environmental context data, the system determines that the user may have two conflicting intentions: one is to set the indoor temperature to 25°C, and the other is to activate the energy-saving mode. Because these two intentions conflict, the system requires user confirmation.

[0068] Specifically, the smart screen first displays an intent confirmation option in the center of the screen, such as "Do you want to set the temperature to 25℃ or activate energy-saving mode?". To attract the user's attention, this option is presented with a soft, gradient highlight effect and slowly moves from left to right on the screen. If the user does not touch the screen or respond with voice within 5 seconds, the system will play a voice prompt at a low volume: "Please confirm your operation intent." If the user still does not respond after another 5 seconds, the volume of the voice prompt will be slightly increased and played again. If the user still does not interact with the smart screen within the preset 15-second timeframe, the system will immediately push a notification to the user's associated mobile terminal (such as the user's smartphone) with the message: "Gas-fired heating and hot water boiler intent conflict, please confirm: Set to 25℃ / Activate energy-saving mode." The user can click the corresponding option on their phone to confirm. For example, if the user selects "Set to 25℃" on their phone, the system will receive this feedback and determine that the user's immediate intent is to set the temperature to 25℃, after which the gas-fired heating and hot water boiler will be controlled according to this intent. This multi-layered, multi-modal interaction method ensures accurate identification of user intent and stable system operation.

[0069] Optionally, the steps for adjusting the smart screen's interaction methods, function presentation priorities, and information push strategies based on the user's immediate intent and the context to achieve smart screen control of the gas-fired heating and hot water boiler include: Monitor the user's real-time intent and the context in which they are situated, and obtain the corresponding rate and magnitude of change for each. When the rate of change and the magnitude of change reach their respective preset upper limits, the currently activated interaction methods, function presentation priorities, and information push strategies are identified. Calculate new adjustment schemes based on the new user's immediate intent and context; Compare the differences between the new adjustment plan and the currently activated interaction methods, function presentation priorities, and information push strategies; When the difference exceeds a preset threshold, a transition animation or gradient effect is executed, and a prompt sound is played to smoothly switch to the new adjustment scheme. Maintain and adjust the cooldown time mechanism, and prioritize new adjustment plans during the cooldown period; When the number of potential user intents is greater than one, the new adjustment scheme corresponding to the potential user intent with higher priority is executed first.

[0070] Specifically, monitoring user intent and context means that the system continuously tracks changes in user intent and environmental context, and quantifies the speed (rate of change) and extent (amplitude of change) of these changes. For example, the rate of change can be measured by the number of times user intent or context state switches per unit time, and the amplitude of change can be represented by the distance or difference between intent or context state on a predefined dimension. Its purpose is to capture the dynamic characteristics of user needs and environmental changes. The preset upper limit can be understood as a sensitivity parameter for the system to determine whether adjustments are needed. Only when changes in user intent or context reach or exceed these preset upper limits does the system deem it necessary to initiate an adjustment process, avoiding overreaction to minor or transient changes.

[0071] In practical applications, identifying the currently activated interaction methods, function presentation priorities, and information push strategies means that the system acquires the various configurations currently used by the smart screen as a benchmark for subsequent adjustments. Furthermore, calculating new adjustment schemes based on new user intent and context means that the system generates an optimal set of interaction methods, function presentation priorities, and information push strategies based on the latest user intent and environmental context, using preset rules, algorithms, or machine learning models. Comparing the new adjustment scheme with the currently activated interaction methods, function presentation priorities, and information push strategies means that the system evaluates the degree of deviation between the old and new schemes. For example, the differences can be quantified by calculating the Euclidean distance or similarity index between different strategy parameters.

[0072] When the difference exceeds a preset threshold, a transition animation or gradient effect is executed, along with a prompt sound, to smoothly switch to the new adjustment scheme. This aims to provide a user-friendly transition experience and avoid abrupt interface changes. Transition animations can include element translation, scaling, fade-in / fade-out, etc., while gradient effects can be smooth transitions in color, brightness, and transparency. The prompt sound serves as an auditory aid. Furthermore, a maintenance adjustment cooldown mechanism ensures that after an adjustment is completed, the system will not immediately implement new large-scale adjustments for a certain period to prevent frequent switching. During the cooldown period, the system can prioritize potential new adjustment schemes, ensuring that only more important or urgent intentions break the cooldown. When the number of potential user intentions is greater than one, the new adjustment scheme corresponding to the higher-priority potential user intention is executed first. This means the system has the ability to handle multiple intentions and can intelligently select the scheme that best meets the user's current core needs based on preset priority rules.

[0073] In some preferred embodiments, a specific example is given below. Suppose a user is setting the hot water temperature using the smart screen of a gas-fired heating and hot water boiler. Initially, the user may set the temperature to 40 degrees Celsius. At this time, the system detects that the user's immediate intention is "hot water temperature 40°C", and the current situation is "the user is setting the hot water temperature".

[0074] Subsequently, the user suddenly and rapidly adjusts the temperature from 40 degrees Celsius to 55 degrees Celsius, and environmental context data (e.g., the indoor temperature sensor detects a sudden drop in room temperature) also shows that the current situation changes from "the user is setting hot water" to "the user needs to heat up quickly." At this point, the system will detect that both the user's immediate intention and the rate and magnitude of change in the current situation exceed preset upper limits.

[0075] The system identifies the current smart screen's interaction method (e.g., temperature slider display), function presentation priority (e.g., temperature adjustment function highlighted), and information push strategy (e.g., no additional information push).

[0076] Based on the new user's immediate intent ("hot water temperature 55℃") and the new context ("user needs rapid heating"), the system calculates a new adjustment scheme, such as adjusting the temperature slider to 55 degrees Celsius, displaying a "rapid heating mode activated" prompt on the screen, and possibly adjusting the information push strategy to display energy-saving suggestions.

[0077] The system compared the new adjustment scheme with the currently activated scheme and found that the temperature settings were significantly different, and the function prompts and information push strategies had also changed. This difference exceeded the preset threshold.

[0078] Instead of abruptly switching interfaces, the system executes a smooth transition animation. For example, the temperature slider smoothly slides from 40 degrees Celsius to 55 degrees Celsius, while the "Rapid Heating Mode Activated" message appears with a gradual highlight and a gentle notification sound. This allows the user to clearly perceive that the system is responding to their new intention, and the transition is natural and comfortable.

[0079] After completing this adjustment, the system will initiate a cooldown period mechanism, for example, set to 5 seconds. During these 5 seconds, even if the user makes minor actions or the context changes slightly, the system will not immediately perform a new large-scale adjustment. Instead, it will prioritize potential adjustment options. For example, if the user attempts to adjust the temperature back to 40 degrees Celsius during the cooldown period, the system will assess the priority of this new intention. If the system determines that the current intention of "rapid heating" has a higher priority (e.g., based on the user's historical habits or the current environmental context), it will maintain the 55-degree Celsius setting, avoiding frequent switching back and forth, thereby ensuring system stability and a consistent user experience.

[0080] Optionally, when the difference exceeds a preset threshold, the steps of performing a transition animation or gradient effect and playing a prompt sound to smoothly switch to the new adjustment scheme include: Collect ambient light intensity data and user visual impairment information; Adjust the brightness, contrast, and duration of transition animations or gradient effects based on ambient light intensity data; Adjust the color saturation, element size, and motion trajectory of transition animations or gradient effects based on the user's visual impairment information; In low-light environments or when users have visual impairments, increase the visual contrast of transition animations or gradient effects and extend the duration of transition animations or gradient effects.

[0081] Specifically, ambient light intensity data refers to the brightness information of the current environment obtained in real time through the light sensor built into the smart screen of the gas-fired heating and hot water boiler or external environmental sensors. User visual impairment information can be understood as the visual assistance preferences preset by the user in the system settings, such as whether they suffer from color blindness, amblyopia, etc., or potential visual impairment inferred by analyzing the user's historical operating behavior patterns (such as frequently adjusting screen brightness, enlarging fonts, etc.).

[0082] Adjusting the brightness, contrast, and duration of transition animations or gradient effects based on ambient light intensity data means that when the ambient light intensity is high, the brightness of the transition animations or gradient effects can be appropriately reduced to avoid visual stimulation or glare for the user; when the ambient light intensity is low, the brightness can be appropriately increased and the contrast can be increased to ensure clear visibility in dim environments. Simultaneously, the duration of transition animations or gradient effects can also be fine-tuned according to light intensity. For example, the transition speed can be accelerated in bright light, while it can be appropriately prolonged in low light, giving users more time to perceive changes in the screen content.

[0083] In practical applications, the color saturation, element size, and motion trajectory of transition animations or gradient effects can be adjusted based on the user's visual impairment information. For example, for colorblind users, color saturation can be adjusted, and high-contrast color combinations can be selected to avoid using easily confused color pairs. For users with low vision, the size of key elements in the transition animation can be increased to make them easier to identify. For users with motion perception impairment, the motion trajectory can be adjusted to make it smoother or more visually guiding to reduce the difficulty of their perception.

[0084] Furthermore, in low-light environments or when users have visual impairments, the visual contrast of transition animations or gradient effects is increased, and their duration is extended. This means the system will adaptively adjust based on the actual situation. For example, at night or in a dimly lit room, the colors of transition animations will be more vivid, the contrast between the background and foreground will be higher, and the animation playback time will be longer to ensure that users can fully perceive the change in screen content. Similarly, when the system detects that a user has a visual impairment, similar enhancements will be taken to provide a more user-friendly and easily perceptible interactive experience.

[0085] In some preferred embodiments, a specific example is given below. Suppose a user enters the kitchen at night, and the light sensor built into the smart screen of the gas-fired heating and water heater detects extremely low ambient light intensity, for example, below 50 lux. Simultaneously, the system, through user settings or historical behavior analysis, identifies that the user has mild color blindness. When the smart screen of the gas-fired heating and water heater needs to switch from "standby mode" to "heating mode," according to the above scheme, the system will perform the following adjustments: First, due to the low ambient light intensity, the brightness of transition animations or gradient effects will be appropriately increased, and the contrast will also be enhanced to ensure clear visibility of screen content switching in dim environments. For example, the background color will gradually change from dark gray to light blue, and the colors of text and icons will be chosen as highly saturated white or bright yellow to create a sharp contrast.

[0086] Secondly, considering that some users have mild color blindness, the color saturation of the transition animations will be further adjusted to avoid using easily confused red and green tones, and instead adopt blue and yellow tones or high-contrast monochrome gradients. At the same time, the size of key function icons in the transition animations (such as the "heating mode" icon) will be slightly enlarged, and their movement trajectory will be designed to be smoother and clearer, for example, slowly enlarging from the center of the screen with a fade-in effect, rather than rapid flashing or complex rotation.

[0087] Finally, the duration of transition animations or gradient effects will be extended, for example, from the default 0.5 seconds to 1.2 seconds, giving users more time to perceive and understand the switching of screen content. Through these adaptive adjustments, even in low-light environments and when users have visual impairments, users can clearly and comfortably perceive the smooth switching of smart screen modes, thereby improving the overall user experience and system usability.

[0088] Optionally, when the difference exceeds a preset threshold, the steps of performing a transition animation or gradient effect and playing a prompt sound to smoothly switch to the new adjustment scheme include: Collect environmental noise data; Based on the ambient noise data, adjust the volume of the prompt sound so that the volume of the prompt sound is higher than the preset decibel value of the ambient noise data; Collect the user's defined level of hearing impairment; Adjust the frequency range of the prompt tone according to the level of hearing loss, so that the frequency range of the prompt tone avoids the frequency bands where the user's hearing sensitivity is reduced; Increase the duration of the alert sound.

[0089] Specifically, environmental noise data refers to the background noise intensity and spectral distribution information in the environment where the smart screen is located. This data can be collected in real time through microphone arrays integrated inside or outside the smart screen. The microphone array can continuously monitor the acoustic characteristics of the surrounding environment and process the collected raw audio signals, such as analyzing their frequency components and energy distribution through Fourier transform, thereby quantifying the level of environmental noise. The purpose is to provide an accurate reference for adjusting the volume of subsequent prompts.

[0090] The adjustment of the alert tone volume based on ambient noise data, ensuring the volume is higher than a preset decibel value, means the system dynamically calculates an appropriate alert tone playback volume after acquiring ambient noise data. For example, if the ambient noise is 60 decibels and the preset decibel value is set to 10 decibels, the alert tone playback volume will be adjusted to 70 decibels. The preset decibel value can be configured according to the actual application scenario and user preferences to ensure the alert tone has sufficient loudness to penetrate background noise without causing user discomfort. The goal is to ensure the alert tone can still be clearly heard by the user in noisy environments.

[0091] In practical applications, the hearing loss level set by the user can be understood as the user's pre-configured personal hearing health information on the smart screen or associated mobile terminal, such as mild, moderate, or severe hearing loss, or specific audiogram data (i.e., hearing thresholds at different frequencies). This information can be manually entered by the user or obtained through data synchronization with professional hearing devices. Its purpose is to provide a personalized basis for adjusting the frequency of the prompts.

[0092] Furthermore, adjusting the frequency range of the prompts based on the level of hearing loss to avoid frequency bands where the user's hearing sensitivity is reduced means that the system intelligently selects or generates the frequency components of the prompts based on the user's hearing loss level information. For example, if a user has hearing loss in the high-frequency range, the system will select or synthesize prompts mainly concentrated in the mid-to-low frequency range, or adjust the fundamental frequency and overtones of the prompts to a frequency band where the user's hearing sensitivity is higher. The purpose is to ensure that the frequency of the prompts can be effectively transmitted to the user's auditory system, improving the perception efficiency for users with hearing loss.

[0093] In addition, increasing the duration of the alert tone means extending its playback time to a preset duration that is longer than the regular alert tone. For example, a regular alert tone might last 0.5 seconds, while the extended duration might be 1 second or longer. The purpose is to provide users with a longer perception window, especially when users are distracted or have slow reaction times, increasing the likelihood that they will notice the alert tone.

[0094] In some preferred embodiments, it is assumed that Mr. Zhang, the user, is an elderly person with slightly impaired hearing, and his hearing sensitivity is reduced in the frequency range above 5000Hz. Mr. Zhang has preset his hearing loss level in the smart screen. When Mr. Zhang is cooking in the kitchen, approximately 70 decibels of noise is generated (e.g., the range hood is operating). At this time, the control scheme of the gas heating and hot water boiler smart screen needs to switch from "energy-saving mode" to "fast hot water mode," triggering the playback of a prompt tone. The solution of this application will first collect the 70-decibel ambient noise data in the kitchen. Based on the preset 10-decibel value, the volume of the prompt tone will be adjusted to 80 decibels. At the same time, the system will read Mr. Zhang's hearing loss level, identify his high-frequency hearing loss characteristics, and therefore the frequency range of the prompt tone will be adjusted to between 200Hz and 3000Hz, avoiding the high-frequency range in which he is not sensitive. In addition, the duration of the prompt tone will also be increased from the default 0.5 seconds to 1.5 seconds. With these adjustments, even in a noisy kitchen environment, and given Mr. Zhang's hearing loss, he can clearly and promptly hear the prompts, thus recognizing the switch to the smart screen mode and avoiding missing important information due to unclear prompts.

[0095] Optionally, when the difference exceeds a preset threshold, the steps of performing a transition animation or gradient effect and playing a prompt sound to smoothly switch to the new adjustment scheme include: Collect user behavior data and environmental context data; Based on user behavior data and environmental context data, determine whether the user is in a multitasking state and obtain the processing status judgment result; If the processing status judgment result indicates that the user is in a multitasking state, then reduce the visual intensity of the transition animation or gradient effect. If the processing status judgment result indicates that the user is in a multitasking state, then increase the recognizability of the prompt sound; If the processing status judgment result indicates that the user is in a multitasking state, then adjust the display area of ​​the transition animation or gradient effect.

[0096] The collection of user behavior data and environmental context data refers to the system continuously acquiring user operation records on the smart screen, such as touch frequency, swipe trajectory, voice commands, and application switching frequency, as well as environmental information around the smart screen, such as ambient noise level, ambient light intensity, indoor temperature, and humidity. This data is used to comprehensively analyze the user's current state.

[0097] Furthermore, based on user behavior data and environmental context data, the system determines whether the user is in a multitasking state and obtains a processing state judgment result. Specifically, the system analyzes the user's operation mode on the smart screen (such as quickly switching between different functions, frequently checking the time or messages), the complexity of voice interaction, and the level of environmental noise (such as kitchen cooking sounds, TV playback sounds), and combines preset judgment models or machine learning algorithms to assess whether the user is currently processing multiple tasks simultaneously, thereby obtaining a judgment result on whether the user is in a multitasking state.

[0098] When the processing status indicates that the user is in a multitasking state, the visual intensity of transition animations or gradient effects is reduced. Specifically, the system will reduce the complexity of transition animations, shorten their duration, reduce color saturation, and weaken the flicker frequency or transparency to make them less visually striking, so as to avoid excessively distracting the user's already scattered attention.

[0099] Meanwhile, if the processing status judgment result indicates that the user is in a multitasking state, the recognition of the prompt sound will be increased. Specifically, the system will adjust the volume, frequency, timbre or playback mode of the prompt sound to make it easier for the user to perceive and recognize it in the background noise. For example, it can use a more penetrating frequency, a shorter but clearer sound effect, or adjust the volume adaptively to ensure that it is higher than the preset decibel value of the ambient noise.

[0100] In addition, if the processing status judgment result indicates that the user is in a multitasking state, the display area of ​​the transition animation or gradient effect will be adjusted. Specifically, the system will limit the display range of the transition animation or gradient effect to a specific area of ​​the screen, such as near the control that the user is currently operating, or move it to the edge of the screen where the user's line of sight may be more easily reached, so as to avoid interfering with the core display area of ​​other tasks that the user is performing.

[0101] In some preferred embodiments, a specific example is given below. Assume a user is cooking in the kitchen while simultaneously setting the timer function of a gas-fired heating and hot water boiler via a smart screen. At this time, the system determines that the user is currently in a multitasking state by monitoring user behavior data (e.g., frequent touches on different areas of the screen, rapid switching between the cooking timer and the boiler settings interface) and environmental context data (e.g., noticeable cooking noise in the kitchen). When the gas-fired heating and hot water boiler needs to switch its operating mode from "heating" to "hot water," conventionally, a full-screen, long-lasting mode-switching animation might appear, accompanied by a loud prompt sound. However, according to the optimized solution of this application, the system will recognize that the user is in a multitasking state and take the following adjustments: First, reduce the visual intensity of transition animations or gradient effects. For example, mode switching animations are no longer full-screen, but appear as a smaller, softer icon gradient in the corner of the screen, or only in the relevant functional area with rapid, low-saturation color changes, and their duration is shortened accordingly to reduce visual interference for the user.

[0102] Secondly, the system enhances the recognizability of the notification sounds. It intelligently adjusts the volume of the notification sounds based on the kitchen's noise level, making them slightly louder than the ambient noise. It may also select a short, clear sound effect with a specific frequency to ensure that users can clearly hear the mode-switching notification sounds even during busy cooking sessions, without being drowned out by other noises.

[0103] Finally, adjust the display area of ​​transition animations or gradient effects. For example, mode switching prompts and animations can be displayed near the cooking timer or water heater settings interface that the user is currently using, rather than in the center of the screen, to avoid interfering with the core task the user is focusing on.

[0104] Through the above adjustments, users can still perceive the mode switching of the gas-fired heating and hot water boiler in an undisturbed and efficient manner while multitasking, thereby improving the overall user experience and control efficiency.

[0105] Optionally, if the processing status determination result indicates that the user is in a multitasking state, the steps to increase the recognizability of the prompt sound include: Continuously monitor the user's head orientation and gaze direction; Adjust the playback direction and volume distribution of the prompt tone according to the direction of the head's orientation and line of sight.

[0106] Specifically, continuous monitoring of the user's head orientation and gaze direction refers to acquiring real-time spatial posture information of the user's head and gaze point information through sensors integrated into the smart screen or its surrounding environment (e.g., cameras, infrared sensors, eye-tracking devices). Head orientation can be understood as the rotation angle and direction of the user's head in three-dimensional space, while gaze direction refers to the specific area or object the user's eyes are looking at. This data is continuously collected and analyzed to determine the user's current focus of attention. Adjusting the playback direction and volume distribution of the prompt tone based on the head orientation and gaze direction can be understood as using spatial audio technology or a multi-channel speaker array to directionally send the prompt tone to the area the user is currently focusing on. For example, when the system detects that the user's head orientation or gaze direction deviates from the smart screen and turns to a specific direction, the playback direction of the prompt tone will be adjusted to that specific direction. Simultaneously, the volume in that direction can be appropriately increased, while the volume in other directions can be correspondingly decreased, thus forming a directional sound field. The purpose is to ensure that the prompt tone can be transmitted more directly and effectively to the user's auditory perception area, and can be clearly perceived even when the user is not directly facing the smart screen.

[0107] In some preferred embodiments, a specific example is given below. Suppose a user is cooking in the kitchen, and the smart screen of the gas-fired water heater displays an important status update (e.g., the water temperature has reached the set value or an abnormality warning has appeared). At this time, the user may be looking down at the recipe or focused on chopping vegetables, and their head and gaze are not directly directed at the smart screen. The control method of this application continuously monitors the user's head orientation and gaze direction. For example, using the smart screen's built-in wide-angle camera and eye-tracking algorithm, the system detects that the user's head is facing the work surface and their gaze is focused on the recipe. Based on this judgment, the system immediately adjusts the playback direction and volume distribution of the notification sound. Specifically, if the smart screen is equipped with multiple speakers or supports beamforming technology, the system focuses and directs the sound beam of the notification sound towards the direction the user's head is facing, while appropriately increasing the volume in that direction and maintaining a lower volume in other directions. For example, the notification sound may be played at a slightly higher volume from the right speaker of the smart screen, creating a sound field directed towards the user's head. In this way, even if users are not directly looking at the smart screen, they can clearly hear and perceive the prompts, thus obtaining important information about the gas-fired heating and hot water boiler in a timely manner and avoiding missing key operations or safety prompts due to distraction. This directional prompt not only improves the effective transmission of information but also avoids the interference that may be caused to users or the surrounding environment by raising the volume globally.

[0108] This application proposes a smart screen control system for a gas-fired heating and hot water boiler, used to execute smart screen control of the gas-fired heating and hot water boiler, combined with... Figure 3As shown, the intelligent control system 1 for gas-fired heating and hot water boilers includes: The real-time data acquisition module 11 is used to collect user operation behavior data and environmental context data on the smart screen of the gas heating hot water boiler in real time. The data analysis and judgment module 12 is used to determine the user's immediate intent and current situation based on operational behavior data and environmental context data. The smart screen control module 13 is used to adjust the interaction mode, function presentation priority and information push strategy of the smart screen according to the user's real-time intention and the situation, so as to realize the smart screen control of the gas heating hot water boiler.

[0109] To make the technical solution of this application easier and clearer to understand, the key terms involved will be explained first.

[0110] "Smart screen" refers to an intelligent control terminal that integrates a display screen and interactive functions. It can display device status, provide an operating interface, and support multiple interaction methods, such as touch and voice.

[0111] "Operational behavior data" refers to all operations recorded by the user on the smart screen, including but not limited to touch, swipe, button, and voice commands.

[0112] "Environmental context data" refers to real-time information about the environment in which the gas-fired heating and hot water boiler is located, such as indoor temperature, humidity, light intensity, outdoor temperature, and weather conditions.

[0113] "User's immediate intent" refers to the operation or state that the user currently wants the gas-fired heating and hot water boiler to perform, such as adjusting the temperature, switching modes, or querying information.

[0114] "Context" refers to the user's current environment and state, such as being at home, out and about, sleeping, or exercising.

[0115] "Interaction method" refers to the way smart screens exchange information and receive commands from users, such as graphical interface, voice interaction, gesture control, etc.

[0116] "Function presentation priority" refers to the display order and prominence of various functional modules on the smart screen, such as prioritizing the display of frequently used functions and highlighting emergency notifications.

[0117] "Information push strategy" refers to the methods and content by which smart screens send notifications, reminders, or suggestions to users, such as pop-up prompts, voice broadcasts, and message lists.

[0118] The implementation environment of this application is typically a home or commercial premises. The gas-fired heating and hot water boiler is connected to the smart screen via a network. The smart screen obtains environmental context data through sensors or external data sources and obtains operational behavior data through user operations.

[0119] The core of the smart screen control system for gas-fired heating and hot water boilers in this application lies in the systematic realization of intelligent perception and response to user intentions and contexts. The specific methods for real-time collection of user operation behavior data and environmental context data, judgment of the user's immediate intentions and current situation, and adjustment of the smart screen's interaction methods, function presentation priorities, and information push strategies have already been described in the above embodiments, and will not be repeated here. It is important to emphasize that the smart screen control system for gas-fired heating and hot water boilers in this application, through modular design, materializes the above functions to achieve more efficient and stable operation.

[0120] Specifically, the real-time data acquisition module can be understood as a collection of hardware sensors and software interfaces, designed to continuously and accurately acquire user actions on the smart screen and environmental information about the gas-fired heating and hot water boiler. For example, this module may include touch sensors, microphones, and cameras integrated within the smart screen to capture user actions such as touch, swipes, voice commands, and gestures. Simultaneously, the module can also acquire environmental context data such as indoor and outdoor temperature, humidity, light intensity, and weather conditions through built-in temperature sensors, humidity sensors, and light sensors, or by communicating with external smart home gateways and weather service interfaces. As a preferred implementation, the real-time data acquisition module can employ a polling mechanism or an event-driven mechanism to ensure the real-time nature and effectiveness of the data.

[0121] The data analysis and judgment module can be understood as the core processing unit of the system. Its purpose is to perform in-depth analysis of the data acquired by the real-time data acquisition module, thereby accurately identifying the user's immediate intent and context. Specifically, this module can have a built-in preset rule engine to directly determine the user's intent based on specific operation sequences and environmental conditions. For example, when it detects that a user clicks the "heat up" button multiple times within a specific time period and the ambient temperature is low, the rule engine can determine that the user's intent is "to increase the heating temperature." In addition, the data analysis and judgment module can also integrate machine learning models. By training on historical operation behavior data and environmental context data, it can learn and predict the user's complex intents and contexts. For example, the model can analyze the user's operating habits in different time periods and environments, thereby more accurately determining whether the user is preparing to take a bath, sleep, or go out. The output of this module, namely the user's immediate intent and context, will serve as the basis for the smart screen control module's decision-making.

[0122] Furthermore, the smart screen control module can be understood as an execution unit responsible for dynamically adjusting the smart screen's display and interaction logic based on the output of the data analysis and judgment module. Its purpose is to provide the most suitable interactive experience based on the user's immediate intent and the context. For example, when the data analysis and judgment module identifies the user's intent as "increasing the heating temperature" and the context as "at home," the smart screen control module can immediately adjust the smart screen's display interface, placing the temperature adjustment slider or button in the most prominent position, and may guide the user through operation via voice prompts. In addition, this module can adjust the priority of function presentation; for example, when the user is preparing to sleep, it can prioritize displaying sleep-related heating modes (such as silent mode or low-power mode). Simultaneously, information push strategies are also dynamically adjusted; for example, when the user is away, it can push the operating status of the gas-fired heating boiler or energy-saving suggestions. Through the coordinated adjustment of interaction methods, function presentation priorities, and information push strategies, the smart screen control module ensures that the smart screen can provide highly personalized and context-aware control services.

[0123] The system in this application achieves intelligent perception and dynamic response to user intentions and contexts through the collaborative work of a real-time data acquisition module, a data analysis and judgment module, and a smart screen control module. The real-time data acquisition module comprehensively acquires user operation and environmental information, providing a rich data foundation for subsequent intelligent decision-making. The data analysis and judgment module uses this data for deep learning or rule-based reasoning to accurately identify the user's immediate needs and environment. Based on this, the smart screen control module dynamically adjusts the smart screen's interaction methods, function presentation priorities, and information push strategies, thereby providing a highly personalized, context-aware control experience. For example, when the system determines that a user enters a room and approaches the smart screen in cold weather, the smart screen control module can proactively place the temperature adjustment function in a prominent position, or even directly display temperature adjustment suggestions, greatly improving the convenience and intuitiveness of user operation. This ability to proactively adapt to user needs and environmental changes is not present in traditional systems, significantly improving the intelligence level of gas-fired heating and hot water boilers and user satisfaction.

[0124] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A smart screen control method for a gas-fired heating and hot water boiler, characterized in that, include: Real-time data collection of user behavior and environmental context data on the smart screen of the gas-fired heating and hot water boiler; Based on the operational behavior data and the environmental context data, the user's immediate intent and current situation can be determined. Based on the user's immediate intent and the current situation, the interaction method, function presentation priority, and information push strategy of the smart screen are adjusted to achieve smart screen control of the gas-fired heating and hot water boiler.

2. The intelligent screen control method for a gas-fired heating and hot water boiler according to claim 1, characterized in that, The step of determining the user's immediate intent and current situation based on the operational behavior data and the environmental context data includes: Based on the operational behavior data and the environmental context data, it is determined whether there is a conflict or ambiguity. If the determination result is yes, the conflict or ambiguity is identified. Based on existing conflicts or ambiguities, and according to preset priority rules and the current environmental context, the potential user intentions are weighted and evaluated to obtain the initial weights of the potential user intentions. By combining users' historical operation habit data, the initial weight of potential user intent is adjusted to obtain the adjusted potential user intent weight; Based on the adjusted potential user intent weights, the user's immediate intent and the context in which they are situated can be determined. When there are conflicting or ambiguous intentions among potential users, provide users with an option to confirm their intentions; Determine the user's immediate intent based on the user's feedback on the intent confirmation option.

3. The intelligent screen control method for a gas-fired heating and hot water boiler according to claim 2, characterized in that, The step of weighting and evaluating potential user intentions based on existing conflicts or ambiguities, according to preset priority rules and the current environmental context, to obtain the initial weights of potential user intentions includes: Collect users' physiological status data and activity demand data, and integrate them into comprehensive status demand information; The preset priority rules and the current environment scenario are integrated into state requirement verification information; Identify any inconsistencies between the comprehensive state requirement information and the state requirement verification information; Based on the physiological state data, the activity demand data, and the inconsistencies, a physiological activity-specific weighting factor is generated. The physiological activity-specific weighting factor is evaluated against a preset priority rule to obtain the weighting evaluation result; By integrating the weighted evaluation results with the physiological activity-specific weighting factors, a weighted evaluation result of the potential user intent is obtained and used as the initial weight of the potential user intent.

4. The intelligent screen control method for a gas-fired heating and hot water boiler according to claim 2, characterized in that, The step of providing users with intent confirmation options when potential user intents are conflicting or ambiguous includes: When there are conflicting or ambiguous intentions of potential users, an intention confirmation option is displayed on the smart screen, and the intention confirmation option is presented in the form of dynamic flashing or gradual highlighting. Adjust the position of the intent confirmation option on the screen so that the intent confirmation option is within the user's line of sight; Play voice prompts periodically and with progressively increasing volume to guide the user’s attention to the intent confirmation option on the screen; If the user does not perform screen touch or voice response within a preset time, a notification containing the intent confirmation option will be pushed to the associated user mobile terminal. Receive feedback from the user via their mobile terminal regarding the intent confirmation option, and determine the user's immediate intent.

5. The intelligent screen control method for a gas-fired heating and hot water boiler according to claim 1, characterized in that, The steps of adjusting the interaction method, function presentation priority, and information push strategy of the smart screen according to the user's real-time intent and the current situation to achieve smart screen control of the gas-fired heating hot water boiler include: Monitor the user's real-time intent and the context in which they are situated, and obtain the corresponding rate and magnitude of change for each. When the rate of change and the magnitude of change reach their respective preset upper limits, the currently activated interaction methods, function presentation priorities, and information push strategies are identified. Calculate a new adjustment scheme based on the new user's immediate intent and the current context; Compare the differences between the new adjustment plan and the currently activated interaction methods, function presentation priorities, and information push strategies; When the difference exceeds a preset threshold, a transition animation or gradient effect is executed, and a prompt sound is played to smoothly switch to the new adjustment scheme. Maintain and adjust the cooldown time mechanism, and prioritize new adjustment plans during the cooldown period; When the number of potential user intents is greater than one, the new adjustment scheme corresponding to the potential user intent with higher priority is executed first.

6. The intelligent screen control method for a gas-fired heating and hot water boiler according to claim 5, characterized in that, The step of executing a transition animation or gradient effect and playing a prompt sound when the difference exceeds a preset threshold to smoothly switch to the new adjustment scheme includes: Collect ambient light intensity data and user visual impairment information; Based on the ambient light intensity data, adjust the brightness, contrast, and duration of the transition animation or gradient effect; Based on the user's visual impairment information, adjust the color saturation, element size, and motion trajectory of the transition animation or gradient effect; In low-light environments or when users have visual impairments, increase the visual contrast of transition animations or gradient effects and extend the duration of transition animations or gradient effects.

7. The intelligent screen control method for a gas-fired heating and hot water boiler according to claim 5, characterized in that, The step of executing a transition animation or gradient effect and playing a prompt sound when the difference exceeds a preset threshold to smoothly switch to the new adjustment scheme includes: Collect environmental noise data; Based on the ambient noise data, adjust the volume of the prompt sound so that the volume of the prompt sound is higher than the ambient noise data by a preset decibel value; Collect the user's defined level of hearing impairment; Based on the level of hearing loss, adjust the frequency range of the prompt tone to avoid the frequency bands where the user's hearing sensitivity decreases. Increase the duration of the alert sound.

8. The intelligent screen control method for a gas-fired heating and hot water boiler according to claim 5, characterized in that, The step of executing a transition animation or gradient effect and playing a prompt sound when the difference exceeds a preset threshold to smoothly switch to the new adjustment scheme includes: Collect user behavior data and environmental context data; Based on the user behavior data and the environmental context data, determine whether the user is in a multitasking state and obtain the processing state determination result; If the processing status judgment result indicates that the user is in a multitasking state, then reduce the visual intensity of the transition animation or gradient effect. If the processing status judgment result indicates that the user is in a multitasking state, then the recognizability of the prompt sound will be increased; If the processing status determination result indicates that the user is in a multitasking state, then adjust the display area of ​​the transition animation or gradient effect.

9. A smart screen control method for a gas-fired heating and hot water boiler according to claim 8, characterized in that, The step of increasing the recognizability of the prompt sound if the user is in a multitasking state includes: Continuously monitor the user's head orientation and gaze direction; Adjust the playback direction and volume distribution of the prompt sound according to the head orientation and the direction of the gaze.

10. A smart screen control system for a gas-fired heating and hot water boiler, used to execute smart screen control of the gas-fired heating and hot water boiler, characterized in that, include: The real-time data acquisition module is used to collect user operation behavior data and environmental context data on the smart screen of the gas-fired heating and hot water boiler in real time. The data analysis and judgment module is used to determine the user's real-time intention and current situation based on the operation behavior data and the environmental context data. The smart screen control module is used to adjust the interaction mode, function presentation priority and information push strategy of the smart screen according to the user's real-time intention and the current situation, so as to realize the smart screen control of the gas heating hot water boiler.

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