Water purifier intelligent water temperature adjusting system based on voiceprint recognition and self-learning algorithm

Abstract

The invention discloses a water purifier intelligent water temperature adjusting system based on voiceprint recognition and a self-learning algorithm, which comprises a water purifier and a water purifier control system, and is characterized in that the water purifier control system comprises an intelligent interaction and data acquisition module, a cloud collaboration module and a water taking execution module; the intelligent interaction and data acquisition module comprises a water purifier-based information acquisition system, a water purifier use environment data acquisition system, a user preference acquisition system, a self-learning algorithm module and a data communication system, and the cloud collaboration module comprises a cloud server and a cloud big data learning module. The water taking execution module comprises a water purifier heating control system and a mixed water adjusting system, and the water purifier heating control system is connected with the cloud collaboration module through the data communication system. The water outlet temperature can be automatically adjusted according to factors such as gender, age, current temperature and humidity and personal preference, and water outlet can be controlled through voice.

Description

Technical Field

[0001] The present invention relates to the technical field of water purifier equipment, and specifically to an intelligent water temperature regulation system for a water purifier based on voiceprint recognition and a self-learning algorithm. Background Art

[0002] As people's living standards improve, they demand higher and higher levels of drinking water quality and convenience. Integrated water purifiers combine water purification and heating functions, providing users with a convenient and fast hot water supply. However, most integrated water purifiers currently on the market offer limited water temperature adjustment options, typically offering only a few fixed temperature settings, failing to meet the personalized water temperature needs of different users in different scenarios.

[0003] Users of different genders and ages have different preferences for water temperature. For example, older adults may prefer warmer water for making tea, while younger people may prefer moderately hot water for drinking. Furthermore, ambient temperature and humidity also affect users' perception of water temperature. In hot and humid weather, users may prefer cooler water, while in cold and dry seasons, they prefer warmer water. Furthermore, each user has their own unique drinking water preferences; some prefer lukewarm water, while others prefer hot water.

[0004] Existing water purifiers are unable to comprehensively consider these factors to dynamically adjust the water outlet temperature, resulting in a poor user experience and an inability to truly meet the user's personalized drinking water needs; at the same time, the existing water extraction operation is also relatively complicated. It is usually necessary to select the water temperature and water volume on the water purifier before water can be extracted. The water temperature adjustment mode is mechanized and mostly fixed-gear adjustment, which cannot be dynamically adapted according to individual user differences and environmental changes; the operating process is cumbersome and complicated, and traditional products require multiple button presses to set parameters such as temperature and water volume, which is not convenient to use; the interaction method lacks intelligence, lacks natural language interaction, user identity recognition and other functions, and it is difficult to meet users' needs for an intelligent water use experience, and is not friendly enough to the elderly and children. Summary of the Invention

[0005] In order to solve the problem that existing water purifiers are not user-friendly enough in use, the present invention provides an intelligent water temperature regulation system for water purifiers based on voiceprint recognition and self-learning algorithm, which can automatically adjust the water outlet temperature according to factors such as gender, age, current temperature and humidity, personal preferences, etc., and can control the water outlet by voice.

[0006] To this end, the present invention provides the following technical solutions: The intelligent water temperature regulation system of a water purifier based on voiceprint recognition and self-learning algorithm includes a water purifier and a water purifier control system. The water purifier control system includes an intelligent interaction and data acquisition module, a cloud collaboration module, and a water extraction execution module; the intelligent interaction and data acquisition module includes an information acquisition system based on a water purifier, a water purifier usage environment data acquisition system, a user preference acquisition system, a self-learning algorithm module, and a data communication system. The cloud collaboration module includes a cloud server and a cloud big data learning module. The water extraction execution module includes a water purifier heating control system and a mixed water adjustment system. The water purifier control system is connected to the cloud collaboration module through a data communication system; the information acquisition system includes a voice module with voiceprint recognition function. The information acquisition system collects user identity data and generates The user identity is bound to the voiceprint, and the information collection system collects user instruction data and determines the user identity based on voiceprint recognition. The water outlet temperature of the water purifier is determined based on the user instruction, the ambient temperature and humidity information collected by the water purifier usage environment data collection system, the self-learning algorithm module, and the calculation results of the cloud-based big data learning module. The water purifier includes a hot water bucket. The water purifier heating control system determines whether the hot water heats the hot water in the hot water bucket based on the outlet water temperature, and determines the water output of the hot water bucket and the water output of normal temperature water. The mixed water regulation system controls the water outlet valve switch to provide the set water output of hot water and normal temperature water. After completing a water outlet, the user preference collection system collects user information, water outlet information, and user feedback information, and transmits them to the self-learning algorithm module and the cloud-based big data learning module for optimization and big data analysis.

[0007] The purpose of this solution is to overcome the defects of existing integrated water purifiers for heat and water, such as mechanized water temperature regulation, complex operation, and non-intelligent interaction. By building a fully intelligent ecosystem with deep collaboration between "user-device-cloud", it can realize intelligent innovation of the entire process from water collection interaction to water temperature adaptation. Specifically, by using advanced voice interaction, voiceprint recognition, self-learning algorithms, big data analysis and other technologies, the water purifier can accurately identify the user's identity, automatically match the user's personalized water temperature needs, and continuously optimize the adjustment strategy through voice feedback, ultimately bringing users an extremely convenient, highly personalized and scientifically accurate water use experience, filling the market's technological gap in the field of intelligent integrated water purifiers for heat and water.

[0008] The intelligent interaction and data acquisition module is the basis for realizing personalized water temperature adjustment, which covers a variety of advanced technologies. The voice interaction module (such as iFlytek's voice module) is deeply integrated with the high-precision voiceprint recognition technology. It not only gives the water purifier the ability to "understand" the user's natural language and "identify" the user's identity, but also supports diversified command operations. Users can issue routine commands such as "get me a cup of hot water" or shout out specific scene commands such as "make tea", "make milk", and "make coffee". When the user issues a scene command, the voiceprint recognition technology locks the user's identity while the built-in temperature and humidity sensor collects environmental data in real time and integrates it with the user preference information pre-stored locally and in the cloud. The self-learning algorithm is based on these multi-dimensional data and the scenario-based water temperature recommendation strategy provided by the cloud big data model to quickly calculate the water temperature and water volume suitable for the user in a specific scenario. In addition, the voice feedback function after the user takes water is also critical. When the user says "the water temperature is too high" or "the water temperature is just right", The built-in voice recognition system can capture the evaluation in time, provide a basis for the self-learning algorithm to optimize the subsequent water temperature adjustment strategy, realize the dynamic collection of data and the continuous evolution of the algorithm, and further improve the accuracy of scenario-based water temperature recommendations.

[0009] The cloud-based collaboration module's cloud server serves as the system's "intelligent brain," carrying out core tasks for data processing and policy optimization. It aggregates massive amounts of multi-dimensional data uploaded from various devices, including user voiceprints, voice commands, real-time environmental data, and user voice feedback. Leveraging cutting-edge big data analytics technologies (based on existing general-purpose big models) and artificial intelligence models, it conducts in-depth mining of this data. Firstly, it analyzes the water usage patterns and common preferences of different user groups across various scenarios. For example, it analyzes the water temperature preferences of users from different regions, ages, and genders for scenarios like "tea brewing," "milk brewing," and "coffee brewing" under specific temperature and humidity conditions. Secondly, based on these mining results, it constructs and continuously optimizes a big data model for scenario-based water temperature recommendations, generating both universal and personalized water temperature recommendation strategies, which are then fed back to the water purifier. Building on its existing self-learning algorithm, the auxiliary water purifier further enhances the scientific and precise nature of water temperature regulation by incorporating user identity and specific scenarios, achieving comprehensive optimization from individual to group, and from general needs to scenario-based needs.

[0010] The water extraction execution module focuses on the automation of the water extraction process and the accuracy of water temperature control. The heating system adopts high-precision heating elements and temperature sensors, and an outlet water pump (boosting pump) to ensure that the water is heated quickly and accurately; the mixed water adjustment device is equipped with an intelligent valve, which can finely adjust the mixing ratio of hot and cold water at the millisecond level, and control the outlet water temperature error to an extremely small range. Whether it is the coolness of direct drinking water, the suitability of warm water for brewing, or the precise temperature of hot water for making tea, it can accurately meet user needs and provide users with a high-quality water use experience; normal temperature water can be stored by setting up a normal temperature water bucket, or it can be directly obtained by connecting to the water purifier's water supply pipeline.

[0011] As a preferred embodiment of the present invention, the information collection system is connected to the user's mobile phone, and the user provides personal information data through the mobile phone, including personal temperature preference, gender, and age. In this solution, the mobile phone can be directly connected to the water purifier, or personal information and preferences can be transmitted to the water purifier through a pre-configured mobile phone app.

[0012] As a preferred embodiment of the present invention, the water purifier usage environment data acquisition system includes a water purifier external environment temperature sensor and humidity sensor, as well as a hot water bucket temperature sensor, a normal temperature water bucket temperature sensor, and a water outlet temperature sensor. The temperature and humidity of the water purifier's external environment, when used in conjunction with the temperature required by the customer, can better meet the customer's actual water outlet temperature requirements; the water temperature of the hot water bucket and the normal temperature water bucket are important parameters for determining the water outlet solution, and the water outlet temperature can be compared with the preset water outlet temperature to detect whether the water outlet temperature meets the customer's requirements; in addition, the hot water bucket can be equipped with multiple heating devices, such as electric heating devices, rapid heating bodies, etc., which can increase the outlet temperature and speed of hot water, and the temperature range of mixed water is also more accurate.

[0013] As a preferred solution of the present invention, the self-learning algorithm module calculates the water temperature that meets the user experience based on the user information preset before use and the real-time ambient temperature and humidity. At the same time, if the user has feedback on the water temperature each time, the self-learning algorithm will collect the feedback data, continuously learn and adjust, and achieve precise matching of personalized water temperature.

[0014] As a preferred embodiment of the present invention, the data communication system includes one or both of a Bluetooth-WiFi Combo module and a WiFi communication module. The water purifier in this embodiment is equipped with a built-in Bluetooth-WiFi Combo module or WiFi communication module. After network configuration via a mobile phone app, it can connect to a cloud server and report every user's water withdrawal event to the cloud for data analysis.

[0015] As a preferred solution of the present invention, the cloud-based big data learning module performs data analysis based on a general large model. After data collection and data cleaning, it analyzes user groups with the same conditions, continuously mines such data, calculates the common preferences for water temperature, and feeds the results back to the self-learning algorithm to adjust the algorithm parameters. After continuous optimization, subsequent new users, as long as the user information is preset, can get a water temperature that is more in line with the user experience.

[0016] As a preferred embodiment of the present invention, the water dispensing module also includes an infrared sensor module. This module monitors the water level in the water receiving container in real time. By accurately sensing water level changes, it quickly triggers an automatic water shut-off function when the container is nearing overflow, eliminating the need for manual user operation. This solution achieves fully automated, contactless water dispensing with a "water collection - full stop" system, ensuring safety and convenience.

[0017] As a preferred solution of the present invention, the mixed water regulating system controls the intelligent valve to perform millisecond-level fine regulation on the mixing ratio of hot and cold water, thereby reducing the error in the outlet water temperature.

[0018] As a preferred embodiment of the present invention, the method comprises the following steps: Use the mobile phone APP to configure the network for the water purifier so that it can connect to the cloud server; Bind the user to the user's voiceprint and preset the user's information, age, gender, and personal preferences; The water purifier receives voice commands; After the water purifier identifies the user based on the voiceprint, it uses the self-learning algorithm module and the cloud-based big data learning module to analyze big data to determine the outlet water temperature; Water is discharged through the water purifier heating control system and mixed water regulation system, and the infrared sensing module is used to stop the water when the cup is full. The user preference collection system collects user feedback and optimizes the self-learning algorithm module; The data of water withdrawal events and bound user information feedback are reported to the cloud server and cloud big data learning module for big data analysis.

[0019] As a preferred solution of the present invention, the water extraction execution module adopts the following steps when determining the water output of the hot water bucket and the water output of the normal temperature water: Step 1: Obtain the required hot water flow rate and normal temperature water flow rate under the set temperature through the preliminary test data; Step 2: After mixing the water, detect the temperature difference at the water outlet. If it is less than 3°C, continue to discharge water until the end. If it is greater than 3°C, proceed to the next step. Step 3: Look up the table based on the positive and negative values of the temperature difference and change only the flow rate of the hot water first; Step 4: Detect the temperature difference at the water outlet. If it is less than 3°C, continue to discharge water until the end. If it is greater than 10°C, return to step 3. If it is greater than 3°C but less than 10°C, perform PID adjustment. Step 5: Perform PID adjustment. If the temperature difference can be adjusted to less than 3°C, continue to discharge water until the end. If it cannot be achieved, adjust the flow rate of normal temperature water through the flow control pump. Step 6: Adjust the flow rate of normal temperature water through the flow control pump until the temperature difference is less than 3°C.

[0020] The PID regulating method in this scheme is a basic regulating method of the control system in classical control theory. It is a linear regulating law with proportional, integral and differential effects.

[0021] Compared with the prior art, the present invention has the following beneficial effects: Highly personalized: By comprehensively collecting user information, environmental data, and personal preferences, this system can tailor water temperatures to each user. Regardless of age or gender, and in varying temperature and humidity environments, users can all receive water temperatures that meet their needs, significantly enhancing the user's drinking experience in a variety of scenarios.

[0022] Intelligent Learning Optimization: A self-learning algorithm, combined with user feedback, continuously adapts and optimizes water temperature adjustment strategies. With increasing usage, the water purifier will increasingly accurately grasp the user's true needs, and the water temperature provided will increasingly meet user expectations. Furthermore, the cloud-based big data learning module analyzes extensive user data to further optimize water temperature recommendations based on user commonalities, ensuring both accuracy and rationality in water temperature adjustment.

[0023] Convenient and Efficient: Users only need to complete their personal information and preferences once on the app. The water purifier will then automatically adjust the water temperature based on various factors, eliminating the need for frequent manual adjustments. This intelligent operation greatly simplifies the user experience and meets the demand for convenient and efficient smart home products in today's fast-paced lives. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of a process of the present invention.

[0025] Figure 2 It is a schematic diagram of a water discharge step of the present invention. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0027] See also Figure 1-Figure 2 , an intelligent water temperature regulation system for water purifiers based on voiceprint recognition and self-learning algorithm, including a water purifier and a water purifier control system. The water purifier control system includes an intelligent interaction and data acquisition module, a cloud collaboration module, and a water extraction execution module; the intelligent interaction and data acquisition module includes an information acquisition system based on the water purifier, a water purifier usage environment data acquisition system, a user preference acquisition system, a self-learning algorithm module, and a data communication system. The cloud collaboration module includes a cloud server and a cloud big data learning module. The water extraction execution module includes a water purifier heating control system, a mixed water adjustment system, and the water purifier control system is connected to the cloud collaboration module through a data communication system; the information collection system includes a voice module with voiceprint recognition function. The information collection system collects user identity data and uses voiceprint binding The information collection system collects user instruction data and determines the user identity based on voiceprint recognition. The water outlet temperature of the water purifier is determined based on the user instruction, the ambient temperature and humidity information collected by the water purifier usage environment data collection system, the self-learning algorithm module, and the calculation results of the cloud-based big data learning module. The water purifier includes a hot water bucket and a normal temperature water bucket. The water purifier heating control system determines whether the hot water heats the hot water in the hot water bucket based on the outlet water temperature, and determines the water output of the hot water bucket and the water output of the normal temperature water bucket. The mixed water adjustment system controls the outlet valve switch to provide the set hot water and normal temperature water output. After completing a water outlet, the user preference collection system collects user information, water outlet information, and user feedback information, and passes them to the self-learning algorithm module and the cloud-based big data learning module for optimization and big data analysis.

[0028] The information collection system is connected to the user's mobile phone, and the user provides personal information data through the mobile phone. The personal information data includes personal temperature preference, gender, and age.

[0029] The water purifier usage environment data acquisition system includes the water purifier's external environment temperature sensor and humidity sensor, as well as a hot water bucket temperature sensor, a normal temperature water bucket temperature sensor, and a water outlet temperature sensor.

[0030] The self-learning algorithm module calculates the water temperature that meets the user experience based on the user information preset before use and the real-time ambient temperature and humidity. At the same time, if the user has feedback on the water temperature each time, the self-learning algorithm will collect the feedback data and continuously learn and adjust to achieve accurate matching of personalized water temperature.

[0031] The data communication system includes one or both of a Bluetooth-WiFi Combo module and a WiFi communication module.

[0032] The cloud-based big data learning module performs data analysis based on a general large model. After data collection and cleaning, it analyzes user groups with the same conditions, continuously mines this type of data, calculates the common preferences for water temperature, and feeds the results back to the self-learning algorithm to adjust the algorithm parameters. After continuous optimization, subsequent new users, as long as the user information is preset, will be able to get a water temperature that is more in line with the user experience.

[0033] The water extraction execution module also includes an infrared sensing module, which monitors the water level of the water receiving container in real time. By accurately sensing the water level changes, it quickly triggers the automatic water shut-off function when the container is close to overflowing, without the need for manual operation by the user.

[0034] The mixed water regulation system controls the intelligent valve to fine-tune the mixing ratio of hot and cold water in milliseconds, reducing the error in the outlet water temperature.

[0035] The working principle and use process of the present invention include the following steps: Use the mobile phone APP to configure the network for the water purifier so that it can connect to the cloud server; Bind the user to the user's voiceprint and preset the user's information, age, gender, and personal preferences; The water purifier receives voice commands; After the water purifier identifies the user based on the voiceprint, it uses the self-learning algorithm module and the cloud-based big data learning module to analyze big data to determine the outlet water temperature; Water is discharged through the water purifier heating control system and mixed water regulation system, and the infrared sensing module is used to stop the water when the cup is full. The user preference collection system collects user feedback and optimizes the self-learning algorithm module; The data of water withdrawal events and bound user information feedback are reported to the cloud server and cloud big data learning module for big data analysis.

[0036] When the water extraction execution module determines the water output of the hot water bucket and the normal temperature water output, the following steps are adopted: Step 1: Obtain the required hot water flow rate and normal temperature water flow rate under the set temperature through the preliminary test data; Step 2: After mixing the water, detect the temperature difference at the water outlet. If it is less than 3°C, continue to discharge water until the end. If it is greater than 3°C, proceed to the next step. Step 3: Look up the table based on the positive and negative values of the temperature difference and change only the flow rate of the hot water first; Step 4: Detect the temperature difference at the water outlet. If it is less than 3°C, continue to discharge water until the end. If it is greater than 10°C, return to step 3. If it is greater than 3°C but less than 10°C, perform PID adjustment. Step 5: Perform PID adjustment. If the temperature difference can be adjusted to less than 3°C, continue to discharge water until the end. If it cannot be achieved, adjust the flow rate of normal temperature water through the flow control pump. Step 6: Adjust the flow rate of normal temperature water through the flow control pump until the temperature difference is less than 3°C.

[0037] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent water temperature regulation system for a water purifier based on voiceprint recognition and self-learning algorithm, comprising a water purifier and a water purifier control system, characterized in that: The water purifier control system includes an intelligent interaction and data acquisition module, a cloud collaboration module, and a water extraction execution module; The intelligent interaction and data acquisition module includes a water purifier-based information acquisition system, a water purifier usage environment data acquisition system, a user preference acquisition system, a self-learning algorithm module, and a data communication system. The cloud collaboration module includes a cloud server and a cloud big data learning module. The water extraction execution module includes a water purifier heating control system and a mixed water adjustment system. The water purifier control system is connected to the cloud collaboration module via a data communication system. The information collection system includes a voice module with voiceprint recognition function, the information collection system collects user identity data and uses voiceprint to bind the user identity, the information collection system collects user instruction data and determines the user identity based on voiceprint recognition, and determines the water outlet temperature of the water purifier based on user instructions, ambient temperature and humidity information collected by the water purifier usage environment data collection system, the self-learning algorithm module, and the calculation results of the cloud big data learning module; The water purifier includes a hot water barrel, and the water purifier heating control system determines whether the hot water is heated in the hot water barrel according to the outlet water temperature, and determines the water output of the hot water barrel and the water output of normal temperature water. The mixed water regulating system controls the water outlet valve switch to provide the set water output of hot water and normal temperature water; After completing a water discharge, the user preference collection system collects user information, water discharge information, and user feedback information, and transmits them to the self-learning algorithm module and the cloud big data learning module for optimization and big data analysis.

2. The intelligent water temperature control system for water purifiers based on voiceprint recognition and self-learning algorithm according to claim 1 is characterized by: The information collection system is connected to the user's mobile phone, and the user provides personal information data through the mobile phone. The personal information data includes personal temperature preference, gender, and age.

3. The intelligent water temperature control system for water purifiers based on voiceprint recognition and self-learning algorithm according to claim 1 is characterized by: The water purifier usage environment data acquisition system includes a water purifier external environment temperature sensor and a humidity sensor, and also includes a hot water bucket temperature sensor, a normal temperature water bucket temperature sensor, and a water outlet temperature sensor.

4. The intelligent water temperature control system for water purifiers based on voiceprint recognition and self-learning algorithm according to claim 1 is characterized by: The self-learning algorithm module calculates the water temperature that meets the user experience based on the user information preset before use and the real-time ambient temperature and humidity. At the same time, if the user has feedback on the water temperature each time, the self-learning algorithm will collect the feedback data and continuously learn and adjust to achieve accurate matching of personalized water temperature.

5. The intelligent water temperature regulation system for water purifiers based on voiceprint recognition and self-learning algorithm according to claim 1 is characterized by: The data communication system includes one or both of a Bluetooth-WiFi Combo module and a WiFi communication module.

6. The intelligent water temperature control system for water purifiers based on voiceprint recognition and self-learning algorithm according to claim 1 is characterized by: The cloud-based big data learning module performs data analysis based on a general large model. After data collection and cleaning, it analyzes user groups with the same conditions, continuously mines this type of data, calculates the common preferences for water temperature, and feeds the results back to the self-learning algorithm to adjust the algorithm parameters. After continuous optimization, subsequent new users, as long as the user information is preset, can get a water temperature that is more in line with the user experience.

7. The intelligent water temperature control system for water purifiers based on voiceprint recognition and self-learning algorithm according to claim 1 is characterized by: The water extraction execution module also includes an infrared sensing module, which monitors the water level of the water receiving container in real time. By accurately sensing the water level changes, it quickly triggers the automatic water stop function when the container is close to overflowing, without the need for manual operation by the user.

8. The intelligent water temperature control system for water purifiers based on voiceprint recognition and self-learning algorithm according to claim 1 is characterized by: The mixed water regulating system controls the intelligent valve to finely regulate the mixing ratio of hot and cold water in milliseconds, thereby reducing the error in the outlet water temperature.

9. The intelligent water temperature control system for water purifiers based on voiceprint recognition and self-learning algorithm according to claim 1 is characterized by: The following usage steps are included: Use the mobile phone APP to configure the network for the water purifier so that it can connect to the cloud server; Bind the user to the user's voiceprint and preset the user's information, age, gender, and personal preferences; The water purifier receives voice commands; After the water purifier identifies the user based on the voiceprint, it uses the self-learning algorithm module and the cloud-based big data learning module to analyze big data to determine the outlet water temperature; Water is discharged through the water purifier heating control system and mixed water regulation system, and the infrared sensing module is used to stop the water when the cup is full. The user preference collection system collects user feedback and optimizes the self-learning algorithm module; The data of water withdrawal events and bound user information feedback are reported to the cloud server and cloud big data learning module for big data analysis.

10. The intelligent water temperature control system for water purifiers based on voiceprint recognition and self-learning algorithm according to claim 1 is characterized by: When the water extraction execution module determines the water output of the hot water bucket and the water output of the normal temperature water, the following steps are adopted: Step 1: Obtain the required hot water flow rate and normal temperature water flow rate under the set temperature through the preliminary test data; Step 2: After mixing the water, detect the temperature difference at the water outlet. If it is less than 3°C, continue to discharge water until the end. If it is greater than 3°C, proceed to the next step. Step 3: Look up the table based on the positive and negative values of the temperature difference and change only the flow rate of the hot water first; Step 4: Detect the temperature difference at the water outlet. If it is less than 3°C, continue to discharge water until the end. If it is greater than 10°C, return to step 3. If it is greater than 3°C but less than 10°C, perform PID adjustment. Step 5: Perform PID adjustment. If the temperature difference can be adjusted to less than 3°C, continue to discharge water until the end. If it cannot be achieved, adjust the flow rate of normal temperature water through the flow control pump. Step 6: Adjust the flow rate of normal temperature water through the flow control pump until the temperature difference is less than 3°C.

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