Intelligent water cup atomization control method and system based on scene recognition

Abstract

The invention discloses an intelligent water cup atomization control method and system based on scene recognition, and relates to the technical field of intelligent water drinking equipment control, and the method comprises the steps: obtaining user use scene information, including water cup posture data, temperature data and thirst degree, and calculating an activity intensity score based on the water cup posture data; classifying scene information used by the user according to a scene classification rule and the activity intensity score, and identifying a scene type; setting and adjusting atomization control parameters based on the scene type, the temperature data and the thirst degree; and recording user satisfaction feedback data, establishing a scene atomization parameter association strategy, and adjusting the type of the identified scene. Precise atomization control adaptation is achieved by adjusting the scene recognition standard, especially for special group users such as heart failure patients, atomization parameters can be automatically adjusted according to the thirst degree, the thirst feeling of the heart failure patients is relieved, and meanwhile the liquid intake amount is reasonably limited.

Description

Technical Field

[0001] This invention relates to the field of intelligent drinking water equipment control technology, and in particular to an intelligent water cup atomization control method and system based on scene recognition. Background Technology

[0002] With the popularization of smart devices and the development of technology, smart water bottles, as a new type of health management tool, have gradually gained favor among consumers, especially attracting the attention of cardiovascular medical professionals. In recent years, smart water bottles, by integrating sensors, microcontrollers, and wireless communication modules, can monitor multiple data points such as water temperature, water intake, and usage frequency, providing users with personalized healthy drinking advice. At the same time, the atomization function of water bottles is also being gradually applied to enhance the drinking experience and alleviate thirst in patients with water restriction, especially in terms of water temperature regulation and humidification, which is particularly suitable for special groups such as athletes or patients with heart failure who are on water restriction. The atomization function can adjust the amount of water mist in the water bottle to improve comfort. However, the existing atomization control technology of smart water bottles is still in its early stages. Atomization control is often limited to fixed set parameters and does not fully consider the user's usage scenario, environmental factors, and physiological state. Traditional smart water bottles rely more on water temperature or simple timer control, while ignoring the need for adaptive adjustment under different intensities of activity and real-time response to the user's thirst status.

[0003] Existing smart water bottle atomization control technology suffers from significant shortcomings in precision and flexibility. On one hand, most smart water bottles operate solely based on water temperature data or simple sensor data, failing to intelligently optimize based on the user's actual usage scenario and physiological state. For instance, the requirements for atomization volume and frequency differ drastically between static and strenuous exercise scenarios, but most smart water bottles cannot adjust based on the intensity of user behavior or scenario type. Similarly, for users with varying degrees of thirst, especially special groups like heart failure patients who require strict water restriction but frequently experience thirst, current technology lacks the ability to adjust atomization parameters according to thirst levels. Furthermore… Existing technologies are slow to respond to environmental factors; when the temperature is too high or too low, the atomization control cannot be adjusted flexibly enough. On the other hand, the feedback mechanism for user experience is lacking. Most devices fail to optimize atomization control parameters based on user satisfaction, resulting in user feedback not being reflected in the device's operation strategy in a timely manner during long-term use, thus affecting the device's intelligence level. Therefore, a scene-recognition-based smart water cup atomization control method is particularly important. It can not only capture the user's usage scenario in real time, but also make fine adjustments based on the scenario type, environmental conditions, and the user's physiological state, thereby optimizing the user experience. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the problem to be solved by this invention is to provide a smart water cup atomization control method based on scene recognition. In view of the shortcomings of the prior art, this invention proposes an intelligent control strategy that integrates multi-dimensional information such as water cup posture data, activity intensity score, temperature data and thirst level. By classifying scenes and adjusting atomization control parameters, the atomization volume, atomization frequency and particle size can be adjusted according to different usage scenarios and the user's thirst level, thereby improving the accuracy and personalization of atomization control.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide a smart water cup atomization control method based on scene recognition, comprising: acquiring user usage scene information, including water cup posture data, temperature data, and thirst level; calculating an activity intensity score based on the water cup posture data; classifying the user usage scene information according to scene classification rules and the activity intensity score to identify scene types; setting and adjusting atomization control parameters based on the scene type, the temperature data, and the thirst level; recording user satisfaction feedback data and establishing a scene atomization parameter association strategy to adjust the identified scene type.

[0007] As a preferred embodiment of the scene recognition-based intelligent water cup atomization control method of the present invention, the water cup attitude data includes water cup tilt angle data obtained by a gyroscope sensor and water cup acceleration data obtained by an accelerometer sensor; the temperature data includes water cup internal temperature data and ambient temperature data obtained by a temperature sensor; the thirst level includes no thirst, mild thirst, moderate thirst, and severe thirst.

[0008] As a preferred embodiment of the scene recognition-based intelligent water cup atomization control method of the present invention, the activity intensity score is calculated based on the water cup posture data, including the following steps: calculating the rate of change of the water cup tilt angle according to the water cup tilt angle data; and calculating the activity intensity score using the rate of change of the water cup tilt angle and the water cup acceleration data.

[0009] As a preferred embodiment of the scene recognition-based intelligent water cup atomization control method of the present invention, wherein: the scene types include static scenes, light exercise scenes, and vigorous exercise scenes; the step of classifying user usage scene information and identifying scene types according to scene classification rules and activity intensity scores includes the following steps: obtaining activity intensity scores... And perform scenario judgment, if the activity intensity score If the score is less than the first threshold, the current scene type is initially determined to be a static scene, and the next step is executed; the activity intensity score is continuously obtained within Q1 seconds. A second judgment is then made, and the activity intensity score within Q1 seconds is determined. If all scores are less than the first threshold, the current scene type is determined to be a static scene; otherwise, the current scene type remains unchanged, and the activity intensity score is re-acquired. And perform scenario judgment; if the activity intensity score If the score is greater than or equal to the first threshold and less than or equal to the second threshold, the current scene type is initially determined to be a light-motion scene, and the next step is executed; the activity intensity score is continuously obtained within Q2 seconds. A second judgment is then made, and the activity intensity score is determined within a consecutive Q2 seconds. If all scores are greater than or equal to the first threshold and less than or equal to the second threshold, the current scene type is determined to be a light exercise scene; otherwise, the current scene type remains unchanged, and the activity intensity score is obtained again. And perform scenario judgment; if the activity intensity score If the score exceeds the second threshold, the current scene type is preliminarily determined to be a vigorous exercise scene, and the next step is executed; the activity intensity score is continuously obtained within Q3 seconds. A second judgment is then made, and the activity intensity score is determined within a consecutive Q3 seconds. If all scores are greater than the second threshold, the current scene type is determined to be a vigorous exercise scene; otherwise, the current scene type remains unchanged, and the activity intensity score is obtained again. And perform scene judgment.

[0010] As a preferred embodiment of the scene recognition-based intelligent water cup atomization control method of the present invention, the atomization control parameters include single atomization volume, atomization frequency, and atomized particle size; the atomization control parameters are set as follows: when the scene type is a static scene, the atomization control parameters are set to low, i.e., low single atomization volume, low atomization frequency, and small atomized particle size; when the scene type is a light exercise scene, the atomization control parameters are set to medium, i.e., medium single atomization volume, medium atomization frequency, and medium atomized particle size; when the scene type is a vigorous exercise scene, the atomization control parameters are set to high, i.e., high single atomization volume, high atomization frequency, and high atomized particle size.

[0011] As a preferred embodiment of the scene recognition-based smart water cup atomization control method of the present invention, the atomization control parameters set and adjusted based on the scene type and the temperature data include the following steps: acquiring water cup tilt angle data, water cup internal temperature data, and ambient temperature data; performing atomization control judgment on the water cup tilt angle data; if the water cup tilt angle data is greater than the tilt angle threshold, then implementing a tipping protection measure, i.e., stopping the atomization operation and closing the smart water cup's spout; if the water cup tilt angle data is greater than the tilt angle threshold, then keeping the current atomization control parameters unchanged; performing atomization control judgment on the water cup internal temperature data; if the water cup internal temperature data is greater than a first temperature threshold, then indicating that the temperature is too high, issuing a corresponding prompt to the user, reducing the single atomization volume to M1% of the original, and increasing the atomized particle size to M% of the original. 2%; If the water temperature inside the cup is lower than the second temperature threshold, it indicates that the temperature is too low, and a corresponding prompt is issued to the user. The atomization frequency is increased to the original M3%, and the atomized particle size is reduced to the original M4. If the water temperature inside the cup is greater than or equal to the second temperature threshold and less than or equal to the first temperature threshold, it indicates that the temperature is normal, and the current atomization control parameters remain unchanged. Atomization control is judged based on the ambient temperature data. If the ambient temperature data is greater than the third temperature threshold, it is determined that the ambient temperature is too high, and the atomization frequency is increased to the original M5. If the ambient temperature data is less than the fourth temperature threshold, it is determined that the ambient temperature is too low, and the atomized particle size is increased to the original M6. If the ambient temperature data is greater than or equal to the fourth temperature threshold and less than or equal to the third temperature threshold, it is determined that the ambient temperature is normal, and the current atomization control parameters remain unchanged.

[0012] As a preferred embodiment of the scene recognition-based intelligent water cup atomization control method described in this invention, the atomization control parameters set and adjusted based on thirst level include the following steps: when thirst is not present, the atomization function is not activated; when thirst is mild, the basic atomization control parameters are used; when thirst is moderate, the single atomization volume and atomization frequency are increased; when thirst is severe, the single atomization volume and atomization frequency are increased, and the atomized particle size is reduced; the user type is determined, and if the user belongs to the normal type, the original atomization control parameters remain unchanged; if the user belongs to a special group, the atomization control parameters are adjusted according to the corresponding water intake limit.

[0013] Secondly, to further address the safety issues existing in the control of intelligent drinking water devices, the present invention provides an intelligent water cup atomization control system based on scene recognition, comprising: a data acquisition module for acquiring water cup posture data, temperature data, and thirst level, and calculating an activity intensity score based on the water cup posture data; a scene recognition module for classifying user usage scene information according to scene classification rules and activity intensity score, and identifying scene types; an atomization control module for setting and adjusting the single atomization volume, atomization frequency, and atomization particle size based on scene type, temperature data, and thirst level; and a feedback adjustment module for recording user satisfaction feedback data and establishing a scene atomization parameter association strategy to adjust the identified scene type.

[0014] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the computer program, when executed by the processor, implements any step of the scene recognition-based intelligent water cup atomization control method described in the first aspect of the present invention.

[0015] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the scene recognition-based intelligent water cup atomization control method as described in the first aspect of the present invention.

[0016] The beneficial effects of this invention are as follows: By collecting data on the tilt angle, acceleration, and water temperature of the water cup, this invention can accurately assess the user's activity intensity, providing reliable quantitative indicators for subsequent scenario type determination and ensuring that the water cup can be adjusted under different usage scenarios. By adjusting the scenario recognition criteria, it can quickly respond to changes in user activity intensity, achieving precise atomization control adaptation. Especially for special user groups, such as patients with heart failure, it can automatically adjust atomization parameters according to the degree of thirst, alleviating the thirst of patients with heart failure while reasonably limiting fluid intake and effectively avoiding the health risks that may be caused by excessive water consumption. In addition, the user feedback optimization mechanism of this invention can continuously optimize the control strategy according to the specific needs of different user groups, providing personalized drinking solutions. By intelligently adjusting atomization parameters, it not only optimizes the atomization effect but also effectively reduces resource waste, while improving user comfort under various environmental conditions and physiological states, providing a safe, comfortable, and precise assisted drinking experience for special groups. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is an overall flowchart of the scene recognition-based smart water cup atomization control method in Example 1.

[0019] Figure 2 This is a flowchart of the scene recognition process in Example 1.

[0020] Figure 3 This is a flowchart of the atomization control parameter adjustment process based on scene type and temperature data in Example 1.

[0021] Figure 4 This is a flowchart of the atomization control parameter adjustment based on thirst level in Example 1.

[0022] Figure 5 This is a schematic diagram of the computer device in Example 3. Detailed Implementation

[0023] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0024] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0025] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0026] Example 1 Reference Figures 1-4 This is the first embodiment of the present invention, which provides a smart water cup atomization control method based on scene recognition.

[0027] Existing smart water bottle atomization control methods suffer from the following main problems: Firstly, most smart water bottles operate solely based on water temperature data or simple sensor data, without intelligent optimization considering the user's actual usage scenarios and physiological state. For example, the requirements for atomization volume and frequency differ drastically between static and strenuous exercise scenarios, but most smart water bottles cannot adjust based on the intensity of user behavior or scenario type. Similarly, for users with varying degrees of thirst, especially special groups like heart failure patients who require strict water restriction but frequently experience thirst, existing technologies lack the ability to adjust atomization parameters according to thirst levels. Furthermore, existing technologies are slow to respond to environmental factors; when temperatures are too high or too low, the atomization control response is not sufficiently flexible. Secondly, user experience feedback mechanisms are lacking. Most devices fail to optimize atomization control parameters based on user satisfaction, resulting in user feedback not being reflected in the device's operating strategy in a timely manner during long-term use, thus affecting the device's intelligence level.

[0028] This application provides a method that can effectively solve the problems mentioned above. The following will describe in detail how to implement the scene recognition-based smart water cup atomization control method with reference to several embodiments.

[0029] Figure 1 The overall flowchart of the smart water cup atomization control method based on scene recognition is shown, including: S1: Obtain user usage scenario information, including water cup posture data, temperature data, and thirst level, and calculate the activity intensity score based on the water cup posture data.

[0030] Preferably, the cup attitude data includes the cup tilt angle data obtained by the gyroscope sensor and the cup acceleration data obtained by the accelerometer sensor, wherein the sampling frequency of both the gyroscope sensor and the accelerometer sensor is 50Hz.

[0031] Preferably, the temperature data includes the water temperature inside the cup and the ambient temperature data obtained through a temperature sensor.

[0032] Preferably, the degree of thirst includes no thirst, mild thirst, moderate thirst, and severe thirst.

[0033] Furthermore, the activity intensity score is calculated based on the water cup posture data, including the following steps: calculating the rate of change of the water cup tilt angle based on the water cup tilt angle data. The specific formula is as follows: ; in, For the first The rate of change of the angle of tilt of the water cup at any given time; For the first Data on the tilt angle of the water cup at any given time; For the first Data on the tilt angle of the water cup at any given time; For time intervals.

[0034] The activity intensity score is calculated using the rate of change of the water cup's tilt angle and the water cup's acceleration data. The specific formula is as follows: ; in, Score the activity intensity; and These are weighting coefficients used to control the rate of change of the cup's tilt angle and the degree of influence of the cup's acceleration data. , ; For the first The rate of change of the angle of tilt of the water cup at any given time; For the first Acceleration data of the water cup at any given time.

[0035] Ideally, the cup's attitude data is acquired through a gyroscope and an accelerometer, while the temperature information inside and outside the cup is obtained through a temperature sensor. This provides precise data support for subsequent intelligent decision-making. In particular, by combining the rate of change of tilt angle and acceleration data, the user's action state can be accurately captured with high precision. This precise data acquisition method not only allows for a better understanding of user behavior but also provides a scientific basis for judgments in different scenarios, ensuring the accuracy and response speed of the atomization control strategy.

[0036] S2: Classify user scenario information based on scenario classification rules and activity intensity scores to identify scenario types.

[0037] Preferably, the scene types include static scenes, light exercise scenes, and vigorous exercise scenes.

[0038] Furthermore, such as Figure 2 The diagram shows the scene recognition flowchart. Based on scene classification rules and activity intensity scores, user scenario information is categorized to identify scene types. This includes the following steps: obtaining activity intensity scores... And perform scenario judgment, if the activity intensity score If the value is less than the first threshold, the current scene type is initially determined to be a static scene, and the next step is executed.

[0039] Continuously obtain the activity intensity score within Q1 seconds. A second judgment is then made, and the activity intensity score within Q1 seconds is determined. If all values ​​are less than the first threshold, then the current scene type is determined to be a static scene.

[0040] Conversely, if the scenario type remains unchanged, the activity intensity score will be re-acquired. And perform scene judgment.

[0041] If the activity intensity score If the value is greater than or equal to the first threshold and less than or equal to the second threshold, the current scene type is initially determined to be a light motion scene, and the next step is executed.

[0042] Continuously obtain the activity intensity score within Q2 seconds. A second judgment is then made, and the activity intensity score is determined within a consecutive Q2 seconds. If all values ​​are greater than or equal to the first threshold and less than or equal to the second threshold, then the current scene type is determined to be a light motion scene.

[0043] Conversely, if the scenario type remains unchanged, the activity intensity score will be re-acquired. And perform scene judgment.

[0044] If the activity intensity score If the value exceeds the second threshold, the current scene type is preliminarily determined to be a violent motion scene, and the next step is executed.

[0045] Continuously obtain the activity intensity score within Q3 seconds. A second judgment is then made, and the activity intensity score is determined within a consecutive Q3 seconds. If all values ​​are greater than the second threshold, then the current scene type is determined to be a violent motion scene.

[0046] Conversely, if the scenario type remains unchanged, the activity intensity score will be re-acquired. And perform scene judgment.

[0047] For example, in this invention, the smart water bottle collects user data in real time through a built-in gyroscope and accelerometer, with a sampling frequency of 50Hz; assuming a first threshold of 15, a second threshold of 30, and time windows Q1, Q2, and Q3 are all 3 seconds, the weighting coefficients are... =0.6、 =0.4; In a typical usage scenario, the user's behavior pattern changes as follows: First, the user drinks water while sitting quietly in the office. The rate of change of the tilt angle of the water cup is approximately 0.8° / s, and the acceleration value remains around 0.2g. The calculated activity intensity score is 8.2, which is less than the first threshold of 15. Monitoring continues for 3 seconds (Q1 time window). During this period, the activity intensity scores are 8.2, 7.9, and 8.5, all less than the first threshold, therefore the scenario is classified as a static scenario. Subsequently, the user gets up and walks to the meeting room. The rate of change of the tilt angle of the water cup increases to 2.5° / s, and the acceleration value rises to 0.6g. The calculated activity intensity score is 22.4, which is between the first and second thresholds. Continuous monitoring within the Q2 time window (3 seconds) records activity intensity scores of 22.4, 20.8, and 21.6, all between 15 and 30. Therefore, the scenario type is updated to a light exercise scenario. Subsequently, the user participated in an outdoor sports activity organized by the company. During brisk running, the rate of change of tilt angle recorded by the water cup increased dramatically to 5.8° / s, and the acceleration value reached 1.2g. The calculated activity intensity score was 45.6, significantly exceeding the second threshold of 30. Continuous monitoring within the Q3 time window (3 seconds) recorded activity intensity scores of 45.6, 42.8, and 44.3, respectively, consistently remaining above the second threshold. Therefore, the scenario type was determined to be a vigorous exercise scenario.

[0048] It should be noted that common methods for determining the thresholds for scene recognition, namely the first threshold and the second threshold, include empirical methods based on physiological research, statistical analysis methods based on wearable device data, machine learning classification methods, or fuzzy logic control methods. This invention uses a data-driven approach to determine these two thresholds. First, test subjects of different ages are recruited, and daily drinking scenarios are simulated in a laboratory environment. Activity intensity data is collected over several consecutive hours. The data is then divided into three clusters using the K-means clustering algorithm, corresponding to static, light exercise, and vigorous exercise scenarios, respectively. By analyzing the probability distribution of the inter-class boundaries, the first threshold and the second threshold are determined. The thresholds for scene recognition can be determined based on the specific scene classification technology used; this embodiment does not impose specific limitations on this.

[0049] Ideally, by setting different thresholds based on activity intensity scores and making secondary judgments on continuous data, scenarios can be intelligently classified into static, light exercise, and vigorous exercise types, which can effectively avoid misjudging scenario types. For example, the threshold for static scenarios is lower, while the threshold for vigorous exercise scenarios is higher, ensuring that the smart water bottle responds accurately to users in different scenarios. This scenario classification method provides adaptive control response, making the atomization control of the water bottle more flexible and precise in different usage scenarios.

[0050] S3: Set and adjust the atomization control parameters based on scene type, temperature data, and thirst level.

[0051] Preferably, the atomization control parameters include single atomization volume, atomization frequency, and atomized particle size.

[0052] Specifically, the atomization control parameters include: when the scene type is a static scene, the atomization control parameters are set to low, that is, low single atomization volume, low atomization frequency, and small atomization particle size.

[0053] When the scene type is a light motion scene, set the atomization control parameters to medium, that is, medium single atomization volume, medium atomization frequency, and medium atomization particle size.

[0054] When the scene type is a high-intensity motion scene, set the atomization control parameters to high, that is, high single atomization volume, high atomization frequency, and high atomization particle size.

[0055] Furthermore, such as Figure 3 The diagram shows the flowchart for adjusting atomization control parameters based on scene type and temperature data. Setting and adjusting atomization control parameters based on scene type and temperature data includes the following steps: obtaining water cup tilt angle data, water temperature data inside the water cup, and ambient temperature data; performing atomization control judgment on the water cup tilt angle data; if the water cup tilt angle data is greater than the tilt angle threshold, then implementing tilt protection measures, i.e., stopping the atomization operation and closing the water outlet of the smart water cup.

[0056] If the cup tilt angle data is greater than the tilt angle threshold, the current atomization control parameters remain unchanged.

[0057] The system uses the water temperature data inside the cup to control the atomization process. If the water temperature data is higher than the first temperature threshold, it indicates that the temperature is too high. The system will issue a corresponding prompt to the user, reduce the single atomization volume to M1% of the original value, and increase the atomized particle size to M2% of the original value to protect the user's safety.

[0058] If the water temperature inside the cup is lower than the second temperature threshold, it indicates that the temperature is too low. The system will issue a corresponding prompt to the user, increase the atomization frequency to M3% of the original value, and reduce the atomized particle size to M4% of the original value to improve the user experience.

[0059] If the water temperature inside the cup is greater than or equal to the second temperature threshold and less than or equal to the first temperature threshold, it indicates that the temperature is normal, and the current atomization control parameters should remain unchanged.

[0060] The system performs atomization control judgment based on ambient temperature data. If the ambient temperature data is greater than the third temperature threshold, it is determined that the ambient temperature is too high, and the atomization frequency is increased to the original M5.

[0061] If the ambient temperature data is less than the fourth temperature threshold, it is determined that the ambient temperature is too low, and the atomized particle size is increased to the original M6.

[0062] If the ambient temperature data is greater than or equal to the fourth temperature threshold and less than or equal to the third temperature threshold, the ambient temperature is determined to be normal, and the current atomization control parameters remain unchanged.

[0063] For example, in this invention, it is assumed that the following parameter thresholds are set: the tilt angle threshold is 45°, the first temperature threshold for water temperature is 65°C, the second temperature threshold is 10°C, the third temperature threshold for ambient temperature is 35°C, and the fourth temperature threshold is 5°C. The parameter adjustment coefficients M1-M6 are 60%, 120%, 130%, 80%, 125%, and 115%, respectively. Below is a complete usage scenario example: When a user is jogging in the morning, the system first detects a strenuous exercise scenario and initially sets high-level atomization parameters: a single atomization volume of 0.8ml, atomization frequency of 6 times per minute, and atomized particle size of 5 micrometers. At this time, the water cup contains room temperature water (25℃), the ambient temperature is 22℃, and all parameters are within the normal range, maintaining the initial high-level atomization parameters. Subsequently, the user runs uphill, and the water cup's tilt angle suddenly increases to 50° (exceeding the 45° threshold). Immediately, tilt protection measures are activated, pausing the atomization function and closing the water outlet to prevent splashing and affecting the user's exercise experience. Once the tilt angle returns to a safe range, the atomization function restarts. Next, the user arrives at an open sports field, where the ambient temperature rises to 37℃. (Exceeding the environmental overheating threshold of 35℃), the system automatically increases the nebulization frequency to 7.5 times per minute (125% of the original 6 times) to increase hydration and help the user better cope with the high temperature environment. At the same time, due to the increased body temperature caused by strenuous exercise, the user added ice water to the water cup, causing the water temperature to drop to 8℃ (below the supercooling threshold of 10℃). The system then makes adjustments: increasing the nebulization frequency to 9.75 times per minute (an additional 130% increase) and reducing the atomized particle size to 4 micrometers (reduced to 80% of the original) to avoid discomfort to the respiratory tract caused by excessively cold water mist. Finally, the user returns indoors to rest, the scene type changes to a static scene, and the system automatically switches to low-level nebulization parameters: the single nebulization volume is reduced to 0.3ml, the nebulization frequency is reduced to 2 times per minute, and the atomized particle size is adjusted to 3 micrometers. The indoor air conditioning temperature is 26℃ (normal range), and the water temperature also returns to normal (22℃), maintaining the low-level parameter configuration.

[0064] It should be noted that the first, second, third, and fourth temperature thresholds mentioned above can be calculated using various methods, such as physiological safety threshold methods based on medical research, environmental comfort analysis methods, beverage temperature preference statistics methods, or heat transfer kinetic analysis methods. This invention uses a multi-dimensional experimental analysis method to determine these thresholds. By recruiting test subjects of different ages to conduct drinking water temperature tests, and combining thermal imaging analysis and oral temperature sensor data, the first, second, third, and fourth temperature thresholds are determined. These thresholds can also be adjusted according to actual conditions to obtain more accurate values; this embodiment does not specifically limit this. Secondly, regarding the aforementioned M1%~M6%, this invention uses an iterative optimization experimental method to analyze multiple sets of user feedback data, ultimately determining the optimal parameter combination, thereby ensuring good stability and fast convergence speed in practical applications.

[0065] Preferably, the atomization control in this invention adapts to the needs of different scenarios by intelligently adjusting the single atomization volume, atomization frequency, and atomized particle size, reflecting a high degree of attention to user experience. By adjusting the atomization parameters according to the scenario type, the user experience in various scenarios can be improved. Especially in scenarios involving vigorous exercise, increasing the atomization volume and frequency can effectively improve user comfort. In static scenarios, reducing the atomization volume and frequency not only saves energy but also avoids unnecessary atomization operations, thus improving the energy efficiency of the device.

[0066] In one optional embodiment, instead of setting atomization control parameters based on scene type and temperature data, a thirst sensing function can be introduced into the smart water cup to adjust the atomization volume, atomization frequency, and atomized particle size according to the patient's thirst level. For example, by placing an oral humidity sensor at the water outlet of the smart water cup, when the user drinks, the oral humidity sensor contacts the oral cavity and acquires oral humidity data to determine the user's thirst level; or the user can self-assess their thirst by inputting a thirst level score on the touchscreen of the smart water cup or the accompanying APP to obtain the user's thirst level; then, based on the user's thirst level, including no thirst, mild thirst, moderate thirst, and severe thirst, the single atomization volume, atomization frequency, and atomized particle size can be adjusted, making the smart water cup more in line with the user's usage habits, and in the medical field, it can also provide more precise hydration solutions for patients, especially special groups such as patients with heart failure who are restricted from drinking water.

[0067] In an optional embodiment, thirst assessment can also be achieved by integrating multiple physiological parameters. For example, the smart water bottle can also be equipped with a saliva flow detector to assess thirst by measuring changes in saliva secretion before and after drinking; or indirectly infer thirst by detecting the time interval between consecutive drinking sessions and the amount of water consumed each time; for special groups such as patients with heart failure who are restricting their fluid intake, personalized thirst prediction models can be established by combining multi-dimensional data such as medication time, daily activity intensity, and ambient temperature and humidity; the thresholds for these thirst assessment parameters can be determined by analyzing a large amount of user data and combining medical research findings, rather than using fixed values.

[0068] In an optional embodiment, the thirst sensing function can also be linked with the scene recognition function. For example, when the user is detected to be in a strenuous exercise scene, the thirst assessment trigger threshold is automatically lowered to remind the user to replenish fluids in advance. For special groups such as patients with heart failure and water restriction, a special reminder mechanism is activated when severe thirst is detected in a static scene, as this may be a signal of changes in the condition. The linkage threshold between thirst level and scene type can be determined by analyzing the distribution of normal thirst levels of users in different scenes. In addition, to ensure the safety of use for special groups such as patients with heart failure and water restriction, a daily maximum water intake limit function can be set. A daily upper limit for water intake can be set for patients according to medical advice. When the upper limit is approached, the nebulization parameters are automatically reduced to avoid increased cardiac burden due to excessive water intake. At the same time, it can be connected to the patient's blood pressure monitoring device via Bluetooth. When an abnormally high blood pressure is detected and the thirst level is severe, a warning is issued and the patient is advised to consult a doctor to distinguish whether the symptom changes are caused by disease progression.

[0069] Specifically, such as Figure 4 As shown, setting and adjusting the atomization control parameters based on the degree of thirst includes the following steps: when the degree of thirst is no, the atomization function is not activated.

[0070] When the thirst level is mild, the basic nebulization control parameters are used.

[0071] When the thirst level is moderate, increase the single nebulization volume and nebulization frequency.

[0072] When the thirst level is severe, increase the single nebulization volume and nebulization frequency, and reduce the nebulized particle size.

[0073] The system determines the user type. If the user is a normal user, the original atomization control parameters remain unchanged.

[0074] If the user belongs to a special group, the atomization control parameters will be adjusted according to the corresponding water intake restrictions.

[0075] It should be noted that adjusting the nebulization parameters based on the degree of thirst can be achieved by establishing a model of the relationship between thirst and nebulization parameters through machine learning methods, and then optimizing it based on the user's historical usage data and satisfaction feedback, thereby forming a personalized nebulization control strategy. This embodiment does not impose any specific limitations on this.

[0076] S4: Record user satisfaction feedback data and establish a scene fogging parameter association strategy to adjust the identification scene type.

[0077] Preferably, user satisfaction feedback data includes both satisfied and dissatisfied users.

[0078] Specifically, recording user satisfaction feedback data and establishing a scenario-based fogging parameter association strategy, and adjusting the identified scenario type, includes the following steps: obtaining user satisfaction feedback data and making a judgment; if the user satisfaction feedback data is satisfactory, then keeping the current fogging control parameters unchanged.

[0079] If the user satisfaction feedback data is unsatisfactory, the current scenario type is judged. If the current scenario type is a static scenario, the first threshold is reduced to N1% of the original value to reduce the scope of static scenario judgment.

[0080] If the current scene type is a light motion scene, the first threshold is increased to N2% of the original and the second threshold is decreased to N3% of the original to reduce the judgment range of light motion scene. The first threshold is less than or equal to the second threshold. When the first threshold is equal to the second threshold, the adjustment of the first threshold and the second threshold is stopped.

[0081] If the current scene type is a violent motion scene, the second threshold will be increased to N4% of the original threshold to reduce the scope of violent motion scene judgment.

[0082] For example, in this invention, assume the initial parameters are set as follows: the first threshold is 15, the second threshold is 30, and the adjustment coefficients are N1=85%, N2=115%, N3=90%, and N4=110%. The following is a complete user feedback and adjustment process: Assuming an office scenario, initially, a user uses a smart water bottle in the office, which is classified as a static scenario (activity intensity score of 12). However, the user frequently lifts the water bottle to drink, making the actual user experience closer to a light exercise scenario. After three consecutive instances of user dissatisfaction, the strategy is adjusted: First feedback: the first threshold is reduced from 15 to 12.75 (85%); Second feedback: it is further reduced to 10.84 (another reduction of 85%); Third feedback: it is finally reduced to 9.21. After the adjustment, the user's daily office drinking action is more easily classified as a light exercise scenario, resulting in a more suitable atomization parameter configuration, and the user subsequently provides satisfactory feedback.

[0083] It should be noted that, for the above-mentioned N1%~N4%, i.e. the adjustment of the threshold, the present invention adopts a closed-loop optimization method to determine it. First, an adaptive test is carried out in the test users. The smart water cup collects more than the user feedback data, and the specific value is finally determined by combining the scene recognition accuracy and user satisfaction as dual indicators. This set of parameters ensures stability while ensuring that it can converge to the user's personalized optimal setting in a shorter adjustment cycle.

[0084] Ideally, fine-tuning the threshold for scene determination based on user feedback can not only improve the adaptability of the water cup but also optimize the user experience in real time. This adaptive mechanism based on user feedback can adjust the atomization parameters of the water cup under different usage habits and preferences, avoiding the rigid limitation of fixed thresholds and ensuring the maximization of personalized use.

[0085] In summary, this invention, by collecting data on the tilt angle, acceleration, and water temperature of the water cup, can accurately assess the user's activity intensity, providing reliable quantitative indicators for subsequent scenario type determination and ensuring the water cup can be adjusted under different usage scenarios. By adjusting the scenario recognition criteria, it can quickly respond to changes in user activity intensity, achieving precise atomization control adaptation. Especially for special user groups, such as patients with heart failure, it can automatically adjust atomization parameters according to thirst levels, alleviating thirst while reasonably limiting fluid intake and effectively avoiding the health risks associated with excessive water consumption. Furthermore, the user feedback optimization mechanism of this invention can continuously optimize the control strategy according to the specific needs of different user groups, providing personalized drinking solutions. By intelligently adjusting atomization parameters, it not only optimizes the atomization effect but also effectively reduces resource waste, while improving user comfort under various environmental conditions and physiological states, providing a safe, comfortable, and precise assisted drinking experience for special groups.

[0086] Example 2, an embodiment of the present invention, provides a scene recognition-based intelligent water cup atomization control system, comprising: a data acquisition module for acquiring water cup posture data, temperature data, and thirst level, and calculating an activity intensity score based on the water cup posture data; a scene recognition module for classifying user usage scene information according to scene classification rules and activity intensity score, and identifying scene types; an atomization control module for setting and adjusting the single atomization volume, atomization frequency, and atomization particle size based on scene type, temperature data, and thirst level; and a feedback adjustment module for recording user satisfaction feedback data and establishing a scene atomization parameter association strategy to adjust the identified scene type.

[0087] Example 3 is an embodiment of the present invention, which differs from the previous embodiment in that: like Figure 5As shown, if the aforementioned function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0088] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0089] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0090] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0091] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A smart water cup atomization control method based on scene recognition, characterized in that, include: Obtain user usage scenario information, including water cup posture data, temperature data, and thirst level, and calculate an activity intensity score based on the water cup posture data; The user scenario information is classified according to the scenario classification rules and the activity intensity score to identify the scenario type; The atomization control parameters are set and adjusted based on the scene type, the temperature data, and the degree of thirst. Record user satisfaction feedback data and establish a scene fogging parameter association strategy to adjust the identified scene type.

2. The intelligent water cup atomization control method based on scene recognition as described in claim 1, characterized in that: The cup attitude data includes the cup tilt angle data obtained by the gyroscope sensor and the cup acceleration data obtained by the accelerometer sensor; The temperature data includes the water temperature inside the cup and the ambient temperature data obtained through a temperature sensor. The degree of thirst is categorized as no thirst, mild thirst, moderate thirst, and severe thirst.

3. The intelligent water cup atomization control method based on scene recognition as described in claim 2, characterized in that: The activity intensity score is calculated based on the water cup posture data, including the following steps: Calculate the rate of change of the water cup's tilt angle based on the water cup tilt angle data; The activity intensity score is calculated using the rate of change of the tilt angle of the water cup and the acceleration data of the water cup.

4. The intelligent water cup atomization control method based on scene recognition as described in claim 3, characterized in that: The scene types include static scenes, light exercise scenes, and vigorous exercise scenes; The process of classifying user scenario information and identifying scenario types based on scenario classification rules and activity intensity scores includes the following steps: By obtaining activity intensity scores And perform scenario judgment, if the activity intensity score If the value is less than the first threshold, the current scene type is preliminarily determined to be a static scene, and the next step is executed; Continuously obtain the activity intensity score within Q1 seconds. A second judgment is then made, and the activity intensity score within Q1 seconds is determined. If all values ​​are less than the first threshold, then the current scene type is determined to be a static scene. Conversely, if the scenario type remains unchanged, the activity intensity score will be re-acquired. And perform scene judgment; If the activity intensity score If the value is greater than or equal to the first threshold and less than or equal to the second threshold, the current scene type is initially determined to be a light motion scene, and the next step is executed; Continuously obtain the activity intensity score within Q2 seconds. A second judgment is then made, and the activity intensity score is determined within a consecutive Q2 seconds. If all values ​​are greater than or equal to the first threshold and less than or equal to the second threshold, then the current scene type is determined to be a light motion scene. Conversely, if the scenario type remains unchanged, the activity intensity score will be re-acquired. And perform scene judgment; If the activity intensity score If the value exceeds the second threshold, the current scene type is preliminarily determined to be a violent motion scene, and the next step is executed; Continuously obtain the activity intensity score within Q3 seconds. A second judgment is then made, and the activity intensity score is determined within a consecutive Q3 seconds. If all values ​​are greater than the second threshold, the current scene type is determined to be a violent motion scene; Conversely, if the scenario type remains unchanged, the activity intensity score will be re-acquired. And perform scene judgment.

5. The intelligent water cup atomization control method based on scene recognition as described in claim 4, characterized in that: The atomization control parameters include single atomization volume, atomization frequency, and atomized particle size; The atomization control parameters include: When the scene type is a static scene, the atomization control parameters are set to low, that is, low single atomization volume, low atomization frequency and small atomization particle size; When the scene type is a light sports scene, set the atomization control parameters to medium, that is, medium single atomization amount, medium atomization frequency, and medium atomization particle size; When the scene type is a violent sports scene, the atomization control parameters are set to high, that is, high single atomization volume, high atomization frequency, and high atomization particle size.

6. The intelligent water cup atomization control method based on scene recognition as described in claim 5, characterized in that: Setting and adjusting atomization control parameters based on the scene type and temperature data includes the following steps: The system acquires data on the tilt angle of the water cup, the internal water temperature of the water cup, and the ambient temperature. It then performs atomization control judgment based on the tilt angle data. If the tilt angle data exceeds the tilt angle threshold, it executes a tipping protection measure, namely, stopping the atomization operation and closing the water outlet of the smart water cup. If the cup tilt angle data is greater than the tilt angle threshold, then keep the current atomization control parameters unchanged; The system performs atomization control based on the water temperature data inside the cup. If the water temperature data exceeds the first temperature threshold, it indicates that the temperature is too high. The system then issues a corresponding prompt to the user, reduces the single atomization volume to M1% of the original value, and increases the atomized particle size to M2% of the original value. If the water temperature inside the cup is lower than the second temperature threshold, it indicates that the temperature is too low. The system will then issue a corresponding warning to the user, increase the atomization frequency to M3% of the original value, and reduce the atomized particle size to M4% of the original value. If the water temperature inside the cup is greater than or equal to the second temperature threshold and less than or equal to the first temperature threshold, it indicates that the temperature is normal, and the current atomization control parameters should remain unchanged. The system performs atomization control based on ambient temperature data. If the ambient temperature exceeds a third temperature threshold, the system determines that the ambient temperature is too high and increases the atomization frequency to 5% of the original value. If the ambient temperature data is lower than the fourth temperature threshold, the ambient temperature is determined to be too low, and the atomized particle size is increased to 6% of the original size. If the ambient temperature data is greater than or equal to the fourth temperature threshold and less than or equal to the third temperature threshold, the ambient temperature is determined to be normal, and the current atomization control parameters remain unchanged.

7. The intelligent water cup atomization control method based on scene recognition as described in claim 6, characterized in that: Setting and adjusting the nebulization control parameters based on the degree of thirst includes the following steps: The nebulization function is not activated when the thirst level is not high. When the thirst level is mild, the basic nebulization control parameters are used; When the thirst level is moderate, increase the single nebulization volume and nebulization frequency; When the thirst level is severe, increase the single nebulization volume and nebulization frequency, and reduce the nebulized particle size; The system determines the user type. If the user is a normal user, the original atomization control parameters remain unchanged. If the user belongs to a special group, the atomization control parameters will be adjusted according to the corresponding water intake restrictions.

8. A scene-recognition-based intelligent water cup atomization control system, based on the scene-recognition-based intelligent water cup atomization control method according to any one of claims 1 to 7, characterized in that: include, The data acquisition module is used to acquire water cup posture data, temperature data, and thirst level, and calculate the activity intensity score based on the water cup posture data; The scene recognition module is used to classify user usage scene information and identify scene types based on scene classification rules and activity intensity scores; The atomization control module is used to set and adjust the single atomization volume, atomization frequency, and atomized particle size based on scene type, temperature data, and thirst level; The feedback adjustment module is used to record user satisfaction feedback data and establish a scene fogging parameter association strategy to adjust the identified scene type.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the scene recognition-based intelligent water cup atomization control method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the scene recognition-based intelligent water cup atomization control method as described in any one of claims 1 to 7.

Images