Water purification equipment control method and device, water purification equipment and storage medium

Abstract

The invention discloses a water purification equipment control method and device, electronic equipment and a storage medium, and relates to the technical field of smart home, and the method comprises the following steps: obtaining historical water use event data of target water purification equipment, and carrying out multi-stage preprocessing on the historical water use event data to obtain standardized water use behavior data of a user; on the basis of the standardized water consumption behavior data, predicting a future water consumption time point of the user under the condition of judging that the user has a water consumption habit in a future target time period; generating a control instruction of the target water purification equipment according to the future water consumption time point; wherein the control instruction is used for indicating the target water purification equipment to start a pure water backflow program at a preset advance time before the future water use time point. According to the method provided by the invention, the passive, fixed or delayed control mode of the traditional water purification equipment is fundamentally changed, so that the invalid backflow action is avoided to the greatest extent under the fundamental goal of ensuring that the water used by a user every time is fresh water.

Description

Technical Field

[0001] This application relates to the field of smart home technology, and in particular to a water purification equipment control method, device, water purification equipment and storage medium. Background Technology

[0002] In the field of reverse osmosis water purification equipment, the poor quality of the "first cup of water" caused by long-term shutdown is a core pain point in user experience.

[0003] Currently, mainstream technical solutions to this problem, such as fixed-interval pure water recirculation or delayed recirculation based on a single shutdown event, can maintain pipeline water quality to some extent, but their control logic is essentially passive and blind. These solutions either cause significant waste of water and electricity and equipment wear and tear due to mechanical timed recirculation when users do not need water for extended periods, or they fail to learn and adapt to individual users' long-term water usage habits, leading to an irreconcilable contradiction between insufficient water quality assurance and resource consumption. Therefore, a solution to address these problems is urgently needed. Summary of the Invention

[0004] This application provides a water purification equipment control method, device, water purification equipment, and storage medium to address the deficiencies in the prior art.

[0005] This application provides a water purification equipment control method, including the following steps: Historical water usage event data of the target water purification device is acquired, and the historical water usage event data is preprocessed in multiple stages to obtain standardized water usage behavior data of the user. Based on the standardized water usage behavior data, if it is determined that the user has water usage habits in the future target time period, the future water usage time point of the user is predicted. Based on the future water usage time, a control command is generated for the target water purification device; wherein, the control command is used to instruct the target water purification device to start the pure water reflux program at a preset advance time before the future water usage time.

[0006] According to the water purification equipment control method provided in this application, the step of performing multi-stage preprocessing on the historical water use event data to obtain standardized water use behavior data of users includes: The historical water usage event data is cleaned to obtain initial cleaned data; wherein, the cleaning includes: filtering out water usage events with equipment alarms, water usage events without complete start and end times, and water usage events with a single water usage duration of less than a first preset duration; Based on a preset merging time threshold, two water use events in the initial cleaning data with an adjacent time interval less than the merging time threshold are merged into a single water use session, and water use sessions with a session duration exceeding a second preset duration are filtered out to obtain the standardized water use behavior data.

[0007] According to the water purification equipment control method provided in this application, the step of determining the user's water usage habits within a future target time period based on the standardized water usage behavior data includes: Based on the date type and daytime period category of the future target period, determine the corresponding water usage pattern judgment rules; Based on the water usage pattern judgment rules, the user's historical water usage records in the standardized water usage behavior data are verified, and a verification result is generated. If the verification result indicates that the user has a water usage habit in the future target time period, the user is determined to have a water usage habit if the result meets the regularity conditions defined in the water usage pattern judgment rules.

[0008] According to a water purification equipment control method provided in this application, the date type includes weekdays and non-weekdays, and the daytime period category includes high-frequency periods and low-frequency periods; The rule for determining the corresponding water usage pattern based on the date type and daytime period category of the future target time period includes: When the future target period falls within a high-frequency period of a workday, a first judgment rule is adopted; wherein, the regularity condition defined by the first judgment rule is: in the most recent N historical workdays, the number of days with water usage records within the same time period is not less than M days, where N and M are a first set of preset positive integers; If the future target period falls within a non-high-frequency period of a working day or a non-working day, a second judgment rule is adopted; wherein, the regularity condition defined by the second judgment rule is: in the most recent P historical dates of the same type, the number of days with water usage records within the same time period is not less than Q days, where P and Q are the second set of preset positive integers, and P is greater than N.

[0009] According to a water purification equipment control method provided in this application, the step of predicting the user's future water usage time points, based on determining whether the user has water usage habits within a future target time period, includes: The future target time period is divided into multiple consecutive subdivided time units; For each segmented time unit, predictive features are extracted based on the standardized water use behavior data; wherein, the predictive features include at least user habit representations derived from the water use pattern judgment rules; The predicted features of each subdivided time unit are input into a pre-trained prediction model, which outputs the predicted water usage probability of the user in each subdivided time unit; wherein, the prediction model is a classification model trained based on the user's historical water usage behavior data, used to output the water usage probability in future subdivided time units; The subdivided time units where the predicted probability of water use exceeds a preset probability threshold are determined as the future water use time points.

[0010] According to the water purification equipment control method provided in this application, the step of generating control instructions for the target water purification equipment based on the future water usage time includes: The start time of the pure water recirculation process is calculated based on the future water usage time and the preset lead time. Based on the start time of the pure water reflux program, control instructions for the target water purification device are generated.

[0011] According to the water purification equipment control method provided in this application, after generating the control command for the target water purification equipment based on the start time of the pure water reflux program, the method further includes: The control command of the target water purification device is sent to the service queue or database associated with the target water purification device, so that the local control system of the target water purification device can obtain and execute the control command.

[0012] This application also provides a water purification equipment control device, including the following modules: The processing module is used to acquire historical water use event data of the target water purification equipment and perform multi-stage preprocessing on the historical water use event data to obtain standardized water use behavior data of the user. The prediction module is used to predict the user's future water usage time based on the standardized water usage behavior data, assuming the user has water usage habits in a future target time period. The control module is used to generate control instructions for the target water purification device based on the future water usage time point; wherein the control instructions are used to instruct the target water purification device to start the pure water reflux program at a preset advance time before the future water usage time point.

[0013] This application also provides a water purification device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the water purification device control method described above.

[0014] This application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the water purification device control method as described above.

[0015] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the water purification equipment control method described above.

[0016] This application provides a water purification equipment control method, device, water purification equipment, and storage medium. It acquires historical water usage event data of the target water purification equipment and performs multi-stage preprocessing on the historical water usage event data to obtain standardized water usage behavior data of the user. Based on the standardized water usage behavior data, it determines whether the user has a water usage habit within a future target time period and predicts the user's future water usage time point. According to the future water usage time point, it generates a control instruction for the target water purification equipment. The control instruction is used to instruct the target water purification equipment to start a pure water reflux program at a preset advance time before the future water usage time point. Therefore, this application obtains and processes users' historical water usage data to form a standardized behavioral profile, and then judges their future water usage habits and predicts the precise time of water usage based on this profile. Finally, it generates control commands to drive the water purification equipment to start the recirculation program in advance. This fundamentally changes the passive, fixed, or delayed control mode of traditional water purification equipment. It can actively learn and adapt to the individual water usage patterns of different users, and only perform necessary pure water recirculation before the time when the user is most likely to use water. Thus, while ensuring that the user uses fresh water every time, it avoids ineffective recirculation actions to the greatest extent, achieving the effects of energy saving, water saving, and reducing unnecessary wear and tear on the equipment. Attached Figure Description

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

[0018] Figure 1 This is a schematic diagram of the hardware environment for an interaction method of a smart device according to an embodiment of this application.

[0019] Figure 2 This is a schematic diagram comparing the principles of osmosis and reverse osmosis provided in this application.

[0020] Figure 3 This is a flowchart illustrating the water purification equipment control method provided in this application.

[0021] Figure 4 This is a complete flowchart of the water purification equipment control method provided in this application.

[0022] Figure 5This is a schematic diagram of the structure of the water purification equipment control device provided in this application.

[0023] Figure 6 This is a schematic diagram of the structure of the electronic device provided in this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] According to one aspect of the embodiments of this application, a water purification device control method is provided. This water purification device control method is widely used in whole-house intelligent digital control application scenarios such as smart homes, smart home ecosystems, and intelligence house ecosystems. Optionally, in this embodiment, the above-mentioned water purification device control method can be applied to, for example... Figure 1 The hardware environment shown consists of terminal device 102 and server 104. For example... Figure 1 As shown, server 104 is connected to terminal device 102 via a network and can be used to provide services (such as application services) to the terminal or clients installed on the terminal. A database can be set up on the server or independently of the server to provide data storage services for server 104. Cloud computing and / or edge computing services can be configured on the server or independently of the server to provide data processing services for server 104.

[0027] The aforementioned network may include, but is not limited to, at least one of the following: wired network, wireless network. The aforementioned wired network may include, but is not limited to, at least one of the following: wide area network, metropolitan area network, local area network. The aforementioned wireless network may include, but is not limited to, at least one of the following: Wi-Fi (Wireless Fidelity), Bluetooth. The terminal device 102 may not be limited to PC, mobile phone, tablet computer, smart air conditioner, smart range hood, smart refrigerator, smart oven, smart stove, smart washing machine, smart water heater, smart washing equipment, smart dishwasher, smart projector, smart TV, smart clothes rack, smart curtains, smart audio-visual equipment, smart socket, smart speaker, smart speaker box, smart fresh air equipment, smart kitchen and bathroom equipment, smart bathroom equipment, smart robot vacuum cleaner, smart window cleaning robot, smart mopping robot, smart air purifier, smart steam oven, smart microwave oven, smart water heater, smart air purifier, smart water dispenser, smart door lock, etc.

[0028] Figure 2 This is a schematic diagram comparing the principles of osmosis and reverse osmosis provided in this application, such as... Figure 2 As shown, the left and right comparisons visually demonstrate the movement principles of liquids on both sides of a semipermeable membrane under natural conditions and driven by external forces. The left side shows the osmosis process: initially, the two sides of the semipermeable membrane are pure water and saline water (i.e., water containing solutes); due to the concentration difference, water molecules in the pure water spontaneously migrate through the semipermeable membrane to the saline water side. This process is osmosis, ultimately leading to a difference in liquid level on both sides, reaching a dynamic equilibrium. The right side shows the reverse osmosis process: an external pressure (indicated by the arrow) greater than its natural osmotic pressure is applied to the saline water side. This pressure overcomes the direction of natural osmosis, forcing water molecules in the saline water to pass through the semipermeable membrane in the opposite direction to enter the pure water side, thus separating pure water from the saline water. This is the core physical principle of reverse osmosis (RO) water purification technology. When the water purifier is shut down for a period of time (e.g., 1 hour or longer), this reverse osmosis causes a significant increase in the TDS (Total Dissolved Solids) value of the water stored in the pure water pipes, forming so-called "stale water" or "overnight water."

[0029] This issue manifests directly at the user end as poor water quality in the "first glass": after a long period of inactivity (such as the first use of water in the morning or after returning home from get off work), the first few glasses of water drawn from the tap have a higher TDS value and a poorer taste. This has become one of the core pain points affecting the user experience of RO water purifiers, essentially a problem of the stability and reliability of the output water quality.

[0030] To address the "first cup of water" problem, "pure water reflux" technology is commonly used. Its core physical principle is to balance the osmotic pressure on both sides of the RO membrane through pure water reflux. Specifically, after the equipment is shut down, an additional reflux device (such as an electric valve or a small-flow reflux valve) guides a portion of the pure water from the pressure storage tank or downstream pipeline back to the RO membrane's inlet (raw water side), thereby diluting the concentration on the concentrate side, effectively inhibiting natural osmosis, and maintaining the stability of the pure water quality. This manifests as follows: 1. Fixed-interval reflow: Perform a reflow once every fixed time interval (e.g., 4 hours).

[0031] Existing defects: Severe resource waste: This is the most prominent problem with this solution. When users do not use water for extended periods (e.g., 8 hours of sleep at night and 10 hours of work during the day), the system mechanically performs two or three useless backflow cycles. Each backflow requires starting the water pump, consuming electricity and generating wastewater, resulting in a huge waste of water and electricity resources.

[0032] Component lifespan reduction: The lifespan of core components such as RO membranes, water pumps, and solenoid valves is closely related to their operating cycle. Frequent and unnecessary start-ups, shutdowns, and operations will accelerate the aging and damage of these components.

[0033] Poor user experience: While the issue of stagnant water is resolved, users may worry about its high operating costs and potential failure rate. This "clumsy" intelligence fails to truly understand user needs.

[0034] 2. Fixed Delay Backflow: After the equipment stops, a backflow is performed after a fixed delay (e.g., 20 minutes).

[0035] Existing defects: Poor adaptability and inability to handle complex habits: This solution only reacts to "single" outage events, completely ignoring users' long-term, macro-level water usage patterns. For example, if a user collects water at 10 PM, the system will perform a backflow at 10:20 PM. However, this is ineffective in ensuring water quality at 7 AM the next morning, because nearly 9 hours have passed from the end of the backflow until the following morning, and the problem of stagnant water will reappear.

[0036] Limitations of the customization feature: Although customization is provided, ordinary users lack the professional knowledge and patience to accurately set up complex backflow plans. Setting them too frequently is wasteful, while setting them too sparsely cannot guarantee water quality, resulting in a high user experience cost and often unsatisfactory results.

[0037] Lack of predictive capability: This scheme is essentially a "post-hoc" and passive control logic. It can only respond to "downtime" events that have already occurred, and has no ability to predict "water usage" events that will occur in the future.

[0038] The fundamental flaw in these solutions lies in the "blindness" of their control logic, which fails to achieve an intelligent balance between "ensuring water quality" and "conserving resources." Therefore, zero-stagnant-water technology faces a dilemma: ensuring optimal water quality at all times necessitates incurring extremely high costs associated with wasted water and electricity; conserving resources inevitably requires sacrificing water quality at certain times.

[0039] Based on this, this application proposes a water purification equipment control method to solve at least one of the above problems.

[0040] The following is combined Figures 3-6 This application describes a water purification equipment control method, apparatus, electronic device, and storage medium.

[0041] Figure 3 This is a flowchart illustrating the water purification equipment control method provided in this application, such as... Figure 3 As shown, the method includes the following: Step 100: Obtain historical water usage event data for the target water purification equipment, and perform multi-stage preprocessing on the historical water usage event data to obtain standardized water usage behavior data of the user.

[0042] Specifically, for the target water purification device, such as a specific water purifier in a user's home, historical water usage event data is obtained. This data typically includes the start time, end time, and duration of each water usage event. To eliminate interference and restore the true user behavior, this raw data needs to undergo multi-stage preprocessing. For example, invalid data generated when the device malfunctions (such as events that report "timeoutAlarm") and extremely short-duration trial water usage (such as turning the faucet on and off for less than 6 seconds) are first filtered out. Then, multiple water usages with close intervals (such as within 10 minutes) are merged into a single continuous water usage session, ultimately obtaining standardized water usage behavior data that accurately reflects the user's water usage patterns and has consistent quality.

[0043] Step 200: Based on standardized water use behavior data, determine the user's future water use time points if the user has existing water use habits in the future target time period.

[0044] Specifically, based on this high-quality behavioral data, it is analyzed whether users have stable water usage habits during a future target period (e.g., a certain time period the next morning) (e.g., frequently using water between 7 and 8 am on weekdays). If the existence of this habit is determined, a prediction algorithm is further used to predict a more accurate future water usage time, for example, predicting that water will be used around 7:15 am the next morning.

[0045] Step 300: Generate control instructions for the target water purification equipment based on the future water usage time; wherein, the control instructions are used to instruct the target water purification equipment to start the pure water reflux program at a preset advance time before the future water usage time.

[0046] Specifically, based on this predicted time point and combined with a preset advance time (e.g., 10 minutes), the specific start time (i.e., 7:05) is calculated, and a control command containing this time is generated. This command will eventually be issued, and its core function is to instruct the target water purification equipment to actively start the pure water recirculation program before the predicted water usage time (i.e., 7:05). By guiding the pure water back to the front end of the reverse osmosis membrane to balance the osmotic pressure, it ensures that when the user turns on the tap at the predicted water usage time (7:15), they can immediately obtain a "first glass of water" with a low TDS value and fresh taste.

[0047] The above describes the steps of the water purification equipment control method provided in this application. As can be seen from the above description, according to the water purification equipment control method provided in this application, historical water usage event data of the target water purification equipment is acquired, and multi-stage preprocessing is performed on the historical water usage event data to obtain standardized water usage behavior data of the user; based on the standardized water usage behavior data, if it is determined that the user has a water usage habit in the future target time period, the user's future water usage time point is predicted; based on the future water usage time point, a control command for the target water purification equipment is generated; wherein, the control command is used to instruct the target water purification equipment to start the pure water reflux program at a preset advance time before the future water usage time point. Therefore, this application obtains and processes users' historical water usage data to form a standardized behavioral profile, and then judges their future water usage habits and predicts the precise time of water usage based on this profile. Finally, it generates control commands to drive the water purification equipment to start the recirculation program in advance. This fundamentally changes the passive, fixed, or delayed control mode of traditional water purification equipment. It can actively learn and adapt to the individual water usage patterns of different users, and only perform necessary pure water recirculation before the time when the user is most likely to use water. Thus, while ensuring that the user uses fresh water every time, it avoids ineffective recirculation actions to the greatest extent, achieving the effects of energy saving, water saving, and reducing unnecessary wear and tear on the equipment.

[0048] Based on the above embodiments, in this embodiment, step 100 performs multi-stage preprocessing on historical water use event data to obtain standardized water use behavior data of users, including: Step 110: Clean the historical water usage event data to obtain initial cleaned data; wherein, the cleaning includes: filtering out water usage events with equipment alarms, water usage events without complete start and end times, and water usage events with a single water usage duration of less than a first preset duration.

[0049] Step 120: Based on the preset merging time threshold, merge two water use events in the initial cleaning data with an adjacent time interval less than the merging time threshold into one water use session, and filter out water use sessions with a session duration exceeding the second preset duration to obtain standardized water use behavior data.

[0050] Specifically, historical water usage event data refers to each water usage information recorded from the water purification equipment controller or cloud platform, which usually includes the start time stamp and end time stamp of water usage.

[0051] The first step is to perform a cleaning process to remove unreliable and unintended data: filtering out water usage events with device alarms (such as communication timeout alarms), as these data may be distorted due to hardware or communication failures; filtering out events without complete start and end times to ensure the integrity of the time series analysis; and filtering out events where the duration of a single water usage is less than a first preset duration (e.g., 6 seconds), which effectively excludes unintentional non-water-connecting behaviors such as users accidentally touching the faucet or testing the water temperature, thus obtaining relatively pure initial cleaning data.

[0052] Subsequently, based on the understanding of users' continuous water usage behavior, a reconstruction step is performed: a merging time threshold is set (e.g., 10 minutes), and events in the initial cleaning data where the time interval between two adjacent water usage events is less than this threshold are merged into a single water usage session. This better reflects the continuous water usage logic in actual user scenarios, such as continuously drawing water, making tea, or cooking. Finally, to ensure the rationality of the data, water usage sessions whose merged session duration exceeds a second preset duration (e.g., 1 hour) need to be filtered out to exclude extreme anomalies such as users forgetting to turn off the water. Through the above two-stage processing, the final output standardized water usage behavior data is a series of clear, complete behavioral units that represent users' real water usage scenarios, providing a reliable foundation for model learning.

[0053] The water purification equipment control method provided in this embodiment constructs high-quality, standardized user water behavior data by progressively cleaning, merging, and filtering the original water usage event data, thus laying a solid data foundation for subsequent intelligent prediction.

[0054] Based on the above embodiments, in this embodiment, step 200, which determines the user's water usage habits within a future target time period based on standardized water usage behavior data, includes: Step 210: Determine the corresponding water usage pattern judgment rules based on the date type and daytime period category of the future target time period.

[0055] Step 220: Based on the rules for judging water usage patterns, verify the historical water usage records of users in the standardized water usage behavior data and generate verification results.

[0056] Step 230: If the verification result indicates that the regularity conditions are met as defined in the rules for judging water usage patterns, determine whether the user has water usage habits in the future target time period.

[0057] It should be noted that date types include weekdays and non-weekdays, and daytime time categories include high-frequency time periods and low-frequency time periods.

[0058] Specifically, the target time period (e.g., "7:00 to 8:00 AM tomorrow") is first analyzed and broken down into two key dimensions: one is the date type, which distinguishes between weekdays (Monday to Friday) and non-weekdays (Saturday, Sunday, and public holidays), because users' routines are often quite different on these two dates; the other is the daytime time category, which is further divided into high-frequency periods (e.g., 05:00-09:00 AM and 16:00-20:00 PM on weekdays, corresponding to the peak water usage before and after get off work) and low-frequency periods (other times) based on the social activity patterns at different times of the day.

[0059] Based on the combination of these two dimensions, the corresponding rules for judging water usage patterns are determined. For example, for "weekdays + high-frequency periods", a high-sensitivity rule is adopted (such as "using water during this period for 3 out of the last 5 weekdays" is considered to be a habit). For "weekdays + low-frequency periods" or "non-weekdays", a rule with broader coverage and slightly lower sensitivity is adopted (such as "using water for 5 out of the last 10 days of the same type").

[0060] Next, based on the selected rules, the user's historical water usage data is validated in the standardized water usage behavior data, that is, their water usage in the same historical period (e.g., the mornings of the past 5 working days) is statistically calculated. Finally, if the validation result (e.g., "water usage on 4 out of 5 days") meets the regularity condition defined by the rules, it is determined that the user has stable water usage habits in the future target period, thus providing a reliable decision-making basis for initiating subsequent refined time-point predictions.

[0061] The water purification equipment control method provided in this embodiment proposes a differentiated habit judgment method based on date type and daytime time, which realizes the scenario-based and refined identification of users' water use behavior, thereby significantly improving the accuracy and adaptability of the intelligent prediction system.

[0062] Based on the above embodiments, in this embodiment, step 210 determines the corresponding water usage pattern judgment rule according to the date type and daytime period category of the future target time period, including: Step 211: If the target time period in the future falls within a high-frequency period of a workday, the first judgment rule shall be adopted; wherein, the regularity condition defined by the first judgment rule is: in the most recent N historical workdays, the number of days with water usage records within the same time period is not less than M days, where N and M are the first set of preset positive integers.

[0063] Step 212: If the target period in the future falls within a non-high-frequency period of a working day or falls within a non-working day, the second judgment rule shall be adopted. The regularity condition defined by the second judgment rule is: in the most recent P historical dates of the same type, the number of days with water usage records within the same time period is not less than Q days, where P and Q are the second set of preset positive integers, and P is greater than N.

[0064] Specifically, when the target time period falls within a high-frequency period of the workday (e.g., 7:00-8:00 AM on a workday), user behavior (such as getting up, washing, and preparing breakfast) is usually highly regular and constrained by daily routines. Therefore, a highly sensitive first judgment rule is adopted: that is, examining the regularity within a relatively short period of time. The regularity condition is quantified as "in the most recent N historical workdays (e.g., N=5), the number of days with water usage records within the same time period is not less than M days (e.g., M=3)". This means that as long as the user has used water on a significant number of workday mornings in the past week (e.g., more than half), the system considers them to have a stable habit. Conversely, when the target time period falls during a non-high-frequency period on a weekday (such as 2:00 PM to 3:00 PM on a weekday afternoon) or the entire non-working day, user behavior may be more random and scattered (such as significant differences in wake-up times on weekends). Therefore, a second judgment rule with a longer coverage period and wider tolerance is adopted: its regularity condition is quantified as "in the most recent P similar historical dates (e.g., P=10), the number of days with water usage records within the same time period is not less than Q days (e.g., Q=5)".

[0065] The reason for specifically setting "P greater than N" (e.g., examining 10 days instead of 5 days) is that in periods of high irregularity, a longer observation window is needed to confirm a relatively stable pattern.

[0066] The water purification equipment control method provided in this embodiment uses two sets of parameters (N, M) and (P, Q) to perceive user habits in different life scenarios with different levels of strictness. This prevents missed judgments during periods of strong regularity and avoids misjudgments during periods of weak regularity, thus making habit judgment both accurate and robust.

[0067] Based on the above embodiments, in this embodiment, step 200, determining whether the user has a water usage habit within a future target time period and predicting the user's future water usage time points, includes: Step 240: Divide the future target time period into multiple consecutive subdivided time units.

[0068] Step 250: For each segmented time unit, extract predictive features based on standardized water use behavior data; wherein, the predictive features include at least user habit representations derived from water use pattern judgment rules.

[0069] Step 260: Input the predicted features of each subdivided time unit into the pre-trained prediction model and output the predicted water usage probability of the user in each subdivided time unit; wherein, the prediction model is: a classification model trained based on the user's historical water usage behavior data, used to output the water usage probability in future subdivided time units.

[0070] Step 270: Determine the subdivided time units where the predicted probability of water use exceeds the preset probability threshold as future water use time points.

[0071] Specifically, the target time period (e.g., "from 6 a.m. to 9 a.m. tomorrow") is divided into multiple consecutive subdivided time units (e.g., if each unit is 5 minutes, then the time period is divided into 36 units), thereby achieving granular refinement from time period to point in time, providing a time benchmark for precise control.

[0072] Next, for each segmented time unit (such as "7:00-7:05 tomorrow morning"), predictive features are extracted from standardized water usage behavior data. These features include not only conventional statistics (such as the user's historical average water usage duration during this time period and the number of historical water usage days), but more importantly, user habit representations derived from the aforementioned water usage pattern judgment rules. For example, if the system has determined that a user has a habit of using water on weekday mornings, this representation can be an identifier or a weight. This is equivalent to injecting prior knowledge into the model, enhancing the specificity of the prediction. Then, this set of features for each unit is input into a pre-trained predictive model. This model is a classification model trained on massive amounts of historical user water usage behavior data (e.g., using the XGBoost algorithm). Its function is to learn the complex mapping relationship between user behavior and time units and output a predicted water usage probability between 0 and 1, representing the model's belief that the user is likely to use water within that specific 5-minute unit.

[0073] Finally, a preset probability threshold (e.g., 60%) is set, and all subdivided time units where the predicted water usage probability exceeds this threshold, such as the two units "7:10-7:15" and "7:20-7:25" with predicted probabilities of 85% and 70% respectively, are determined as the final future water usage time points.

[0074] The water purification equipment control method provided in this embodiment is based on precise time point prediction using subdivided time units and prediction models. It elevates intelligent control from macroscopic time period perception to microscopic moment-based decision-making, thereby achieving ultimate optimization and high automation of on-demand backflow control.

[0075] Based on the above embodiments, in this embodiment, step 300 generates control instructions for the target water purification device according to future water usage times, including: Step 310: Calculate the start time of the pure water recirculation program based on the future water usage time and the preset lead time.

[0076] Step 320: Based on the start time of the pure water reflux program, generate control instructions for the target water purification equipment.

[0077] Furthermore, after step 320, the method also includes: Step 330: Send the control command of the target water purification device to the service queue or database associated with the target water purification device so that the local control system of the target water purification device can obtain and execute the control command.

[0078] Specifically, based on the predicted future water usage time (e.g., determined to be "7:15 tomorrow morning"), combined with a preset lead time (e.g., 10 minutes), the start time of the pure water recirculation process (i.e., 7:05) is calculated. This lead time is a key parameter to ensure water quality, allowing sufficient time for recirculation purification and water system renewal.

[0079] Subsequently, based on this startup time, a control command for the target water purifier is generated. This command is essentially a digital command containing the precise execution time (7:05) and the action type (starting reflux). To enable the device located in the user's home to receive and execute this command, the control command is sent out. Sending out the command here refers to pushing the command to a central scheduling system, such as a service queue or database associated with the target water purifier. Each device has its unique identifier and associated data channel (a dedicated area in the service queue or database) in the cloud. After the command is sent out, the local control system of the water purifier (i.e., the microcontroller or processor built into the device) retrieves the command from its associated cloud queue or database through periodic queries or long-term connection monitoring, and finally automatically executes the command when the local clock reaches the startup time specified by the command (7:05), that is, drives the water pump, valves, and other components to start the pure water reflux program.

[0080] The water purification equipment control method provided in this embodiment constructs a reliable, efficient, and scalable intelligent control execution system through a complete closed-loop process from predicting the time point to generating, issuing, and finally executing control commands. This ensures that the results of the aforementioned intelligent prediction can be accurately and timely transformed into the physical actions of the water purification equipment.

[0081] Figure 4 This is a complete flowchart of the water purification equipment control method provided in this application. The following is a summary of the process. Figure 4 This application provides a complete description of the control method for the water purification equipment.

[0082] like Figure 4 As shown, an intelligent prediction and backflow control decision-making process based on water usage events is demonstrated.

[0083] The process begins with a water usage event. The system first determines whether the event occurred on a weekday. If so, it enters the first phase of the 24-hour prediction model (this model does not operate during the nighttime period from 23:00 to 4:59 the next day). Next, the system determines whether the water usage falls within a preset high-frequency period (i.e., 05:00-9:00 or 16:00-20:00). If it falls within a high-frequency period, the system further verifies the user's habits to determine if they meet the regularity condition of "using water on 3 out of the last 5 days". If this condition is not met, or if the water usage does not fall within a high-frequency period, the system does not make a prediction and instead uses a conservative local backflow logic as a fallback. If the regularity condition is met, the system generates water usage habits based on this and confirms that the user's high-frequency period exists.

[0084] Subsequently, the system will predict the next day's water usage time based on high-frequency periods and ultimately issue an AI backflow logic command to drive the device to perform precise backflow before the predicted time. If the system determines that the user does not have a high-frequency period, it will still perform local backflow. The core of this process is to dynamically decide whether to enable AI prediction based on habit learning or revert to general rules by analyzing the time attributes and historical patterns of a single water usage event, thereby achieving a balance between intelligence and reliability.

[0085] The water purification equipment control method provided in this application addresses the resource waste caused by the "fixed-time reflux mode." It uses a machine learning model to perform fine-grained probability prediction of the user's water usage behavior over the next 24 hours and sets trigger thresholds to ensure that the reflux action is only initiated when water usage is highly likely. This "prediction-driven" mode fundamentally eliminates unnecessary cycles during periods when water usage is not needed, such as when the user is sleeping or away from home, thus directly achieving the technical effects of energy saving, water saving, and extending equipment lifespan. Secondly, addressing the pain point of "poor adaptability of simple custom modes and inability to cope with complex habits," a hybrid architecture of "preliminary rule screening + accurate prediction by machine learning models" is adopted. This architecture combines the ability to quickly identify stable habits with a powerful learning ability for complex and non-linear patterns. This design enables the system to not only distinguish between macro-level patterns of weekdays and non-weekdays but also to perceive micro-level scenarios such as "the first glass of water in the morning," thereby achieving truly personalized and adaptive services that fit individual user habits, fundamentally improving the user experience and achieving the invention's objective of "precise preservation."

[0086] The control device for the water purification equipment provided in this application is described below. The control device for the water purification equipment described below can be referred to in correspondence with the control method for the water purification equipment described above.

[0087] Figure 5 This is a schematic diagram of the structure of the water purification equipment control device provided in this application, such as... Figure 5 As shown, the water purification equipment control device provided in this application includes: The processing module 501 is used to acquire historical water use event data of the target water purification equipment and perform multi-stage preprocessing on the historical water use event data to obtain standardized water use behavior data of the user. Prediction module 502 is used to predict the user's future water usage time based on standardized water use behavior data, assuming the user has water use habits in the future target period. The control module 503 is used to generate control instructions for the target water purification equipment based on the future water usage time. The control instructions are used to instruct the target water purification equipment to start the pure water reflux program at a preset advance time before the future water usage time.

[0088] The water purification equipment control device provided in this application acquires historical water usage event data of the target water purification equipment and performs multi-stage preprocessing on the historical water usage event data to obtain standardized water usage behavior data of the user. Based on the standardized water usage behavior data, it determines whether the user has water usage habits in the future target time period and predicts the user's future water usage time. According to the future water usage time, it generates control instructions for the target water purification equipment. The control instructions are used to instruct the target water purification equipment to start the pure water reflux program at a preset advance time before the future water usage time. Thus, this application acquires and processes historical water usage data of users to form a standardized behavioral profile, and then determines their future water usage habits and predicts the precise water usage time based on this profile. Finally, it generates control instructions to drive the water purification equipment to start the reflux program in advance. This fundamentally changes the passive, fixed, or delayed control mode of traditional water purification equipment. It can actively learn and adapt to the individualized water usage patterns of different users, and only perform necessary pure water reflux before the time when the user is most likely to use water. Therefore, while ensuring that the user uses fresh water every time, it minimizes ineffective reflux actions, achieving the effects of energy saving, water saving, and reducing unnecessary wear and tear on the equipment.

[0089] Based on the above embodiments, in this embodiment, the processing module 501 is specifically used for: Historical water usage event data is cleaned to obtain initial cleaned data; the cleaning process includes: filtering out water usage events with equipment alarms, water usage events without complete start and end times, and water usage events with a single water usage duration of less than a first preset duration. Based on a preset merging time threshold, two water use events with an adjacent time interval less than the merging time threshold in the initial cleaning data are merged into one water use session, and water use sessions with a session duration exceeding a second preset duration are filtered out to obtain standardized water use behavior data.

[0090] Based on the above embodiments, in this embodiment, the prediction module 502 is specifically used for: Based on the date type and daytime period category of the future target period, determine the corresponding water usage pattern judgment rules; Based on water usage pattern judgment rules, the historical water usage records of users in standardized water usage behavior data are verified, and verification results are generated. If the verification results indicate that the user's water usage habits meet the regularity conditions defined in the rules for judging water usage patterns, it is determined that the user has water usage habits in the future target time period.

[0091] Based on the above embodiments, in this embodiment, the date type includes weekdays and non-working days, and the daytime period category includes high-frequency periods and low-frequency periods; The device also includes a determining module, specifically used for: If the target period in the future falls within a high-frequency period of a workday, the first judgment rule shall be adopted; wherein, the regularity condition defined by the first judgment rule is: in the most recent N historical workdays, the number of days with water usage records within the same time period is not less than M days, where N and M are the first set of preset positive integers; If the target period in the future falls within a non-high-frequency period of a working day or falls on a non-working day, the second judgment rule shall be adopted. The regularity condition defined by the second judgment rule is: in the most recent P historical dates of the same type, the number of days with water usage records within the same time period is not less than Q days, where P and Q are the second set of preset positive integers, and P is greater than N.

[0092] Based on the above embodiments, in this embodiment, the prediction module 502 is further used for: Divide the future target period into multiple consecutive subdivided time units; For each segmented time unit, predictive features are extracted based on standardized water use behavior data; wherein, the predictive features include at least user habit representations derived from rules based on water use patterns. The predicted features of each subdivided time unit are input into a pre-trained prediction model, which outputs the predicted water usage probability of the user in each subdivided time unit. The prediction model is a classification model trained based on the user's historical water usage behavior data, used to output the water usage probability in future subdivided time units. The subdivided time units where the predicted probability of water use exceeds a preset probability threshold are identified as future water use time points.

[0093] Based on the above embodiments, in this embodiment, the control module 503 is specifically used for: The start time of the pure water recirculation program is calculated based on the future water usage time and the preset lead time. Based on the start time of the pure water reflux program, control instructions for the target water purification equipment are generated.

[0094] Based on the above embodiments, in this embodiment, the device further includes a sending module, specifically used for: Based on the start time of the pure water reflux program, after generating the control commands for the target water purification equipment, The control commands for the target water purification equipment are sent to the service queue or database associated with the target water purification equipment, so that the local control system of the target water purification equipment can obtain and execute the control commands.

[0095] Figure 6 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 6 As shown, the electronic device can be a robot or other electronic device. This electronic device may include: a processor 610, a communication interface 620, a memory 630, and a communication bus 640. The processor 610, communication interface 620, and memory 630 communicate with each other via the communication bus 640. The processor 610 can call logical instructions from the memory 630 to execute water purification device control methods, including: Historical water usage event data of the target water purification device is acquired, and the historical water usage event data is preprocessed in multiple stages to obtain standardized water usage behavior data of the user. Based on the standardized water usage behavior data, if it is determined that the user has water usage habits in the future target time period, the future water usage time point of the user is predicted. Based on the future water usage time, a control command is generated for the target water purification device; wherein, the control command is used to instruct the target water purification device to start the pure water reflux program at a preset advance time before the future water usage time.

[0096] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, 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, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. 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.

[0097] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the water purification equipment control method provided by the above methods, including: Historical water usage event data of the target water purification device is acquired, and the historical water usage event data is preprocessed in multiple stages to obtain standardized water usage behavior data of the user. Based on the standardized water usage behavior data, if it is determined that the user has water usage habits in the future target time period, the future water usage time point of the user is predicted. Based on the future water usage time, a control command is generated for the target water purification device; wherein, the control command is used to instruct the target water purification device to start the pure water reflux program at a preset advance time before the future water usage time.

[0098] In another aspect, this application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the water purification equipment control methods provided by the above methods, including: Historical water usage event data of the target water purification device is acquired, and the historical water usage event data is preprocessed in multiple stages to obtain standardized water usage behavior data of the user. Based on the standardized water usage behavior data, if it is determined that the user has water usage habits in the future target time period, the future water usage time point of the user is predicted. Based on the future water usage time, a control command is generated for the target water purification device; wherein, the control command is used to instruct the target water purification device to start the pure water reflux program at a preset advance time before the future water usage time.

[0099] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0100] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0101] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for controlling a water purification device, characterized in that, include: Historical water usage event data of the target water purification device is acquired, and the historical water usage event data is preprocessed in multiple stages to obtain standardized water usage behavior data of the user. Based on the standardized water usage behavior data, if it is determined that the user has water usage habits in the future target time period, the future water usage time point of the user is predicted. Based on the future water usage time, a control command is generated for the target water purification device; wherein, the control command is used to instruct the target water purification device to start the pure water reflux program at a preset advance time before the future water usage time.

2. The water purification equipment control method according to claim 1, characterized in that, The process of performing multi-stage preprocessing on the historical water usage event data to obtain standardized water usage behavior data for users includes: The historical water usage event data is cleaned to obtain initial cleaned data; wherein, the cleaning includes: filtering out water usage events with equipment alarms, water usage events without complete start and end times, and water usage events with a single water usage duration of less than a first preset duration; Based on a preset merging time threshold, two water use events in the initial cleaning data with an adjacent time interval less than the merging time threshold are merged into a single water use session, and water use sessions with a session duration exceeding a second preset duration are filtered out to obtain the standardized water use behavior data.

3. The water purification equipment control method according to claim 1, characterized in that, The determination of a user's water usage habits within a future target time period based on the standardized water usage behavior data includes: Based on the date type and daytime period category of the future target period, determine the corresponding water usage pattern judgment rules; Based on the water usage pattern judgment rules, the user's historical water usage records in the standardized water usage behavior data are verified, and a verification result is generated. If the verification result indicates that the user has a water usage habit in the future target time period, the user is determined to have a water usage habit if the result meets the regularity conditions defined in the water usage pattern judgment rules.

4. The water purification equipment control method according to claim 3, characterized in that, The date type includes weekdays and non-working days, and the daytime time category includes high-frequency time periods and low-frequency time periods; The rule for determining the corresponding water usage pattern based on the date type and daytime period category of the future target time period includes: When the future target period falls within a high-frequency period of a workday, a first judgment rule is adopted; wherein, the regularity condition defined by the first judgment rule is: in the most recent N historical workdays, the number of days with water usage records within the same time period is not less than M days, where N and M are a first set of preset positive integers; If the future target period falls within a non-high-frequency period of a working day or a non-working day, a second judgment rule is adopted; wherein, the regularity condition defined by the second judgment rule is: in the most recent P historical dates of the same type, the number of days with water usage records within the same time period is not less than Q days, where P and Q are the second set of preset positive integers, and P is greater than N.

5. The water purification equipment control method according to claim 3 or 4, characterized in that, The step of determining whether the user has water usage habits within a future target time period and predicting the user's future water usage time points includes: The future target time period is divided into multiple consecutive subdivided time units; For each segmented time unit, predictive features are extracted based on the standardized water use behavior data; wherein, the predictive features include at least user habit representations derived from the water use pattern judgment rules; The predicted features of each subdivided time unit are input into a pre-trained prediction model, which outputs the predicted water usage probability of the user in each subdivided time unit; wherein, the prediction model is a classification model trained based on the user's historical water usage behavior data, used to output the water usage probability in future subdivided time units; The subdivided time units where the predicted probability of water use exceeds a preset probability threshold are determined as the future water use time points.

6. The water purification equipment control method according to claim 1, characterized in that, The step of generating control instructions for the target water purification device based on the future water usage time points includes: The start time of the pure water recirculation process is calculated based on the future water usage time and the preset lead time. Based on the start time of the pure water reflux program, control instructions for the target water purification device are generated.

7. The water purification equipment control method according to claim 6, characterized in that, After generating control commands for the target water purification device based on the start time of the pure water reflux program, the method further includes: The control command of the target water purification device is sent to the service queue or database associated with the target water purification device, so that the local control system of the target water purification device can obtain and execute the control command.

8. A control device for a water purification equipment, characterized in that, include: The processing module is used to acquire historical water use event data of the target water purification equipment and perform multi-stage preprocessing on the historical water use event data to obtain standardized water use behavior data of the user. The prediction module is used to predict the user's future water usage time based on the standardized water usage behavior data, assuming the user has water usage habits in a future target time period. The control module is used to generate control instructions for the target water purification device based on the future water usage time point; wherein the control instructions are used to instruct the target water purification device to start the pure water reflux program at a preset advance time before the future water usage time point.

9. A water purification device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the front-end resource dynamic optimization method as described in any one of claims 1 to 7.

10. A non-transitory 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 front-end resource dynamic optimization method as described in any one of claims 1 to 7.

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