Intelligent water purification system based on AI

Abstract

The invention relates to the technical field of water treatment, in particular to an AI-based intelligent water purification system, which is characterized in that a water inlet pipeline and a pressure stabilizing valve are adopted, the pressure of raw water is controlled within a certain range, the influence of pressure fluctuation on the filtering effect is avoided, and stable filtering conditions are obtained; a sensor is adopted to collect data of raw water and purified water in real time, the sampled data are transmitted to an AI decision module in real time, the AI decision module extracts the data of the raw water and the purified water and compares and analyzes the data, and the purified water reaches the standard; a purified water output structure is formed by a water outlet pipeline, a UV sterilization lamp, a flow meter and a water outlet faucet; a special chip is adopted, received data is calculated in real time according to a big data model, and then all modules of the water purifier are regulated and controlled. The problems that a traditional water purifier cannot adapt to water use differences of different regions, water qualities and seasons, the service life of a filter element is not accurately predicted, and efficient, accurate and personalized water purification service is difficult to provide are solved.

Description

Technical Field

[0001] This invention belongs to the field of water treatment technology, specifically relating to an AI-based intelligent water purification system. Background Technology

[0002] Against the backdrop of continuous social development and technological progress, people's pursuit of quality of life is increasing, and their requirements for drinking water quality are also rising accordingly. As a key device for ensuring the safety and health of household water, the optimization and upgrading of the performance and functions of water purifiers has become an important direction for industry development.

[0003] Currently, traditional water purifiers have many limitations in design and application. Regarding filtration adaptability, traditional water purifiers typically use a fixed number of filter cartridges and operate according to preset parameters. However, water quality varies significantly across regions. For example, some northern areas have high TDS (Total Dissolved Solids) levels, containing more calcium and magnesium ions; while some southern areas may have slightly polluted water, containing certain amounts of organic matter, heavy metals, and other pollutants. Furthermore, water quality changes seasonally due to factors such as temperature and rainfall. If water purifiers in northern areas with high TDS and southern areas with slightly polluted water use the same filter cartridge combinations and operating parameters, they will inevitably fail to meet the purification needs of different water qualities. This may result in water purifiers in northern areas with high TDS failing to achieve the required purification effect, failing to effectively remove mineral ions, and leaving the purified water still unsuitable for drinking; while water purifiers in southern areas with slightly polluted water may have excessive filter cartridges, leading to resource waste and increased user costs.

[0004] In terms of filter lifespan management, traditional water purifiers rely on a simplistic method for predicting filter lifespan, typically judging whether the filter needs replacement based solely on the purifier's operating time. However, this method fails to adequately consider the impact of actual water pollution levels on filter lifespan. Different regions and time periods exhibit varying degrees of water pollution, leading to different levels of filter wear. For instance, in areas with severe water pollution, the filter may reach saturation quickly, failing to effectively filter impurities. Conversely, in areas with relatively good water quality, the actual lifespan of the filter may far exceed the lifespan predicted based on operating time. This can easily lead to two extreme situations: first, the purifier's purification effect may already be substandard before the replacement reminder, resulting in the user drinking insufficiently purified water and posing a potential health threat; second, the filter may still have some filtration capacity when the replacement reminder is triggered, making replacement unnecessary and increasing user costs.

[0005] In terms of intelligent applications, the level of intelligence in some AI-enabled water purifiers currently on the market is still relatively limited. Most of these purifiers can only display some basic information; however, they fail to form a complete intelligent closed-loop system of "detection-analysis-iteration-sharing." In the detection stage, while some basic data can be collected, the comprehensiveness and accuracy of the data need improvement. In the analysis stage, there is a lack of in-depth mining and comprehensive analysis of the collected data, making it impossible to make accurate decisions based on different water qualities and user habits. In the iteration stage, the operating parameters and filter combinations of the water purifier cannot be adjusted in a timely manner based on the analysis results to adapt to constantly changing water quality requirements. In the sharing stage, the usage data and experiences of different regions and users cannot be shared and exchanged, limiting further improvement and optimization of the water purifier's performance. Therefore, these AI-enabled water purifiers cannot fundamentally solve the pain points of traditional water purifiers and fail to meet users' needs for high-quality, intelligent water purifiers.

[0006] In conclusion, there is an urgent need for a smart water purifier that deeply integrates AI technology to solve the problems of traditional water purifiers in terms of filtration compatibility, filter life management, and intelligent applications, and to provide users with a higher quality, more efficient, and smarter water purification solution. Summary of the Invention

[0007] To address the aforementioned issues, this invention provides an AI-based intelligent water purification system. This system solves the problems of traditional water purifiers' inability to adapt to varying water usage patterns across different regions, water qualities, and seasons; inaccurate filter lifespan prediction; and the lack of a fully intelligent closed-loop system in existing AI water purifiers, which fails to fundamentally resolve these pain points and provide efficient, accurate, and personalized water purification services. To achieve the above objectives, this invention adopts the following technical solution: The AI-based intelligent water purification system includes: a raw water inlet module, which uses an inlet pipe and a pressure regulating valve to control the raw water pressure within a certain range, avoiding pressure fluctuations that could affect the filtration effect and achieving stable filtration conditions; a pre-filtration module, which uses a built-in PP cotton filter element to filter out sediment and large particulate impurities in the raw water, reducing the workload of the adaptive filtration module and extending the service life of the filter element; and a water quality detection module, which uses sensors to collect data on the raw water and purified water in real time, and transmits the sampled data to the AI ​​decision module in real time. The AI ​​decision module extracts and compares the raw water and purified water data, and adjusts itself in real time. The system comprises several modules: an operating status monitoring module to ensure the purified water meets standards; an operating status monitoring module to collect filter operating parameters via differential pressure sensors and timers, determine the degree of filter clogging, calculate the filter performance degradation status, and predict the remaining lifespan of the filter; a purified water output module consisting of an outlet pipe, a UV sterilizing lamp, a flow meter, and a faucet, where the UV sterilizing lamp prevents secondary pollution of the purified water, and the flow meter collects the water output in real time; and an AI decision-making module using a dedicated chip to receive data from the water purifier in real time, perform real-time calculations based on a big data model, and then regulate all modules of the water purifier.

[0008] Furthermore, the AI-based intelligent water purification system also includes an adaptive filtration module, which uses a first-stage pre-filter granular activated carbon filter, a second-stage compressed granular activated carbon filter, a third-stage RO reverse osmosis filter, and a fourth-stage post-filter granular activated carbon filter to form a four-stage independently controlled filtration assembly.

[0009] Furthermore, the AI-based intelligent water purification system also includes a cloud collaboration module for data storage, data analysis, data sharing, and system updates. This module receives local data, water quality reports, and water purifier usage information to form blockchain data. The cloud collaboration module is built on a commercial cloud platform.

[0010] Furthermore, the AI-based intelligent water purification system also includes a user interaction module, which uses a touch screen to display water quality, filter usage status, and predicted remaining lifespan of the filter in real time, and allows users to view water purifier parameter settings.

[0011] Furthermore, the water quality detection module also includes a TDS sensor, a turbidity sensor, a residual chlorine sensor, a heavy metal sensor, and a pH sensor.

[0012] Furthermore, the AI ​​decision-making module can independently control the start / stop of one or more filter stages and the power of the booster pump, and dynamically adjust the working status of the adaptive filtration module in real time.

[0013] Furthermore, each of the following filter elements—the first-stage pre-filter granular activated carbon filter, the second-stage compressed granular activated carbon filter, the third-stage RO reverse osmosis filter, and the fourth-stage post-filter granular activated carbon filter—is equipped with a solenoid valve for control.

[0014] Furthermore, the adaptive filtration module is equipped with a variable frequency booster pump.

[0015] Furthermore, the user interaction module also includes a water purifier mobile APP, which supports iOS / Android / Harmony systems, enabling remote control of the water purifier, real-time viewing of water quality, filter usage, and predicted remaining lifespan of the filter, and receiving filter replacement reminders and water quality abnormality alarms.

[0016] Furthermore, the user interaction module has an audible and visual alarm function.

[0017] In the technical solution provided by this invention, the raw water inlet module uses an inlet pipe and a pressure stabilizing valve to control the raw water pressure within a certain range, avoiding pressure fluctuations from affecting the filtration effect and obtaining stable filtration conditions; the pre-filtration module uses a built-in PP cotton filter element to filter out sediment and large particulate impurities in the raw water, reducing the workload of the adaptive filtration module and extending the service life of the filter element in the adaptive filtration system; the water quality detection module uses sensors to collect data on raw water and purified water in real time, and transmits the sampled data to the AI ​​decision module in real time. The AI ​​decision module extracts the raw water and purified water data, compares and analyzes them, and adjusts its operation in real time. The system comprises several modules: a filter cartridge monitoring module, an AI decision-making module, and an AI decision-making module. The first module uses a dedicated chip to receive data from the water purifier in real time. The second module addresses the limitations of traditional water purifiers, such as their inability to adapt to varying water quality and seasons, inaccurate filter life prediction, and the lack of a fully intelligent closed-loop system in existing AI water purifiers, which fail to provide efficient, accurate, and personalized water purification services. The third module monitors the filter cartridge's operating parameters using differential pressure sensors and timers to determine its clogging level, calculate performance degradation, and predict its remaining lifespan. The fourth module provides a water purification output structure consisting of an outlet pipe, a UV sterilizer, a flow meter, and a faucet. The UV sterilizer prevents secondary contamination of the purified water, and the flow meter monitors the real-time water flow rate. The fifth module uses a dedicated chip to receive data from the water purifier in real time, performs calculations based on a big data model, and adjusts all modules accordingly. This invention solves the problems of traditional water purifiers failing to adapt to differences in water usage across regions, water quality, and seasons, inaccurate filter lifespan prediction, and the lack of a fully intelligent closed-loop system in existing AI water purifiers. Attached Figure Description

[0018] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention.

[0019] Figure 1 This is a schematic diagram of the system structure of an AI-based intelligent water purification system according to an embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram illustrating the working logic of the AI ​​decision-making module of an AI-based intelligent water purification system according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0022] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0023] An AI-based intelligent water purification system, such as Figure 1-2 As shown, it includes: a raw water inlet module, which uses an inlet pipe and pressure regulating valve to control the raw water pressure within a certain range, avoiding pressure fluctuations that could affect the filtration effect and achieving stable filtration conditions; a pre-filtration module, which uses an internal PP cotton filter element to filter out sediment and large particulate impurities in the raw water, reducing the workload of the adaptive filtration module and extending the service life of the filter element in the adaptive filtration system; and a water quality detection module, which uses sensors to collect data on raw water and purified water in real time, and transmits the sampled data to the AI ​​decision module in real time. The AI ​​decision module extracts the raw water and purified water data, compares and analyzes them, and adjusts its own operating status in real time. The system ensures that the purified water meets standards. The operation status monitoring module uses a differential pressure sensor and timer configured on the filter cartridge to collect operating parameters, determine the degree of filter clogging, calculate the filter cartridge's performance degradation, and predict its remaining lifespan. The purified water output module uses an outlet pipe, UV sterilization lamp, flow meter, and faucet to form the purified water output structure. The UV sterilization lamp prevents secondary pollution of the purified water, and the flow meter collects the water output in real time. The AI ​​decision-making module uses a dedicated chip to receive data from the water purifier in real time, performs real-time calculations based on a big data model, and then regulates all modules of the water purifier.

[0024] After the water purification system is operational, the raw water inlet module is activated, and the water quality detection module and the operation status monitoring module start simultaneously. The raw water first undergoes initial purification through the pre-filtration module, then undergoes deep purification through the adaptive filtration module, and finally flows out as purified water through the purified water output module.

[0025] The water quality testing module and the operational status monitoring module transmit the collected data to the AI ​​decision-making module. Based on the received data, the AI ​​decision-making module runs water quality classification models, adaptive filtration models, filter life prediction models, and self-cleaning models, adjusting control parameters in real time to ensure the normal operation of the water purifier module. The AI ​​decision-making module then uploads the received data to the cloud collaboration module, which analyzes the uploaded data, iteratively updates the big data model, and shares the updated big data model, contributing to the continuous optimization of water purifier performance locally, regionally, and on a larger scale.

[0026] The specific water quality classification model employs a CNN-LSTM-Attention fusion algorithm. CNN is used to extract local features of water quality parameters, LSTM is used to capture the temporal trend of water quality changes, and Attention is used to optimize the weights of key water quality features. The model training data covers water source samples from all provinces in China, and can output the raw water pollution level and key pollutant categories, providing a basis for optimizing filtration strategies.

[0027] The specific adaptive filtration model is based on the aforementioned raw water pollution level and core pollutant categories, combined with the user's water usage habits data and filter cartridge pressure difference data over the past month. Iterative algorithms are used to calculate the control parameters that meet the water purification target and minimize filter cartridge wear, specifically the filter cartridge flow rate, pressure difference, booster pump power, etc.

[0028] The specific filter cartridge life prediction model employs a regression algorithm. Input parameters include the filter cartridge's cumulative operating time, purified water volume, pressure difference rate, and raw water pollution level. Combined with user water usage data, the model calculates and predicts the remaining filter cartridge life and remaining purified water volume. When the predicted remaining filter cartridge life is less than or equal to 30 days, the user's interactive terminal will issue an audible and visual alarm and provide a notification, which can also be simultaneously sent to the mobile app.

[0029] Specific self-cleaning models: There are three main ways to trigger self-cleaning in water purifiers: one is to trigger self-cleaning at a fixed period; the second is to trigger it when the filter element pressure difference exceeds the set clogging value; and the third is to trigger it manually by the user. When self-cleaning is triggered, the inlet valve is closed and the flushing valve is opened, using pulsed water flow to flush impurities on the surface of the filter element. The self-cleaning function can extend the life of the filter element.

[0030] When the filter life prediction model predicts that the remaining life of the filter element is less than or equal to 30 days, the user interaction terminal will issue an audible and visual alarm and information prompt, and a reminder can also be sent simultaneously to the mobile APP.

[0031] The cloud-based collaborative module contains a vast amount of knowledge base data related to water purifiers, water purification, and water pollution. Users can learn independently through the APP and user interaction terminals, enriching their knowledge of water purification and improving the user experience.

[0032] In this embodiment, the AI-based intelligent water purification system further includes an adaptive filtration module, which uses a first-stage pre-filter granular activated carbon filter, a second-stage compressed granular activated carbon filter, a third-stage RO reverse osmosis filter, and a fourth-stage post-filter granular activated carbon filter to form a four-stage independently controlled filtration assembly.

[0033] With its four-stage independently controlled filtration system, it fully leverages the advantages of each filter element for highly efficient purification. Combined with AI-powered real-time water quality analysis and dynamic parameter adjustments, it adapts to different regions, seasons, and water qualities, ensuring stable purification performance. The AI ​​adaptive filtration model precisely controls the solenoid valves and variable frequency booster pumps of each filter element, minimizing wear and tear on the filter modules while maintaining filtration effectiveness. Furthermore, this module works in conjunction with the overall system to help predict filter lifespan more accurately, extending filter lifespan, reducing user costs, and comprehensively improving the water purifier's performance and user experience.

[0034] In this embodiment, the AI-based intelligent water purification system also includes a cloud collaboration module for data storage, data analysis, data sharing, and system updates. It receives local data, water quality reports, and water purifier usage information to form blockchain data. The cloud collaboration module is built on a commercial cloud platform.

[0035] Built on a commercial cloud platform, this system boasts powerful data storage capabilities, comprehensively collecting data from the device itself, water quality reports, and water purifier usage, forming a blockchain-based data set to provide rich material for subsequent analysis. Through data analysis, it can accurately extract data value, providing a basis for optimizing water purifier compatibility and adjusting filtration control. Data sharing facilitates unified regional management, improving management efficiency. Furthermore, this module supports system updates, ensuring the water purifier always maintains advanced performance, comprehensively enhancing its intelligence, adaptability, and regional scalability, providing users with a superior user experience.

[0036] In this embodiment, the user interaction module uses a touch screen to display water quality, filter cartridge usage, and predicted remaining lifespan of the filter cartridge in real time, and allows users to view the water purifier parameter settings.

[0037] Featuring a touchscreen design, this system provides users with an intuitive and convenient interface. Through this module, users can obtain real-time water quality information, clearly understand the current water quality status, and stay informed. They can also check the filter cartridge status and predict its remaining lifespan at any time, allowing for timely filter replacement and preventing expired cartridges from affecting water purification performance. Furthermore, users can view and adjust water purifier parameter settings to meet personalized water usage needs. This module significantly reduces the difficulty of using the water purifier, allowing users to easily control its operation and effectively improving the user experience and satisfaction.

[0038] In this embodiment, the water quality detection module also includes a TDS sensor, a turbidity sensor, a residual chlorine sensor, a heavy metal sensor, and a pH sensor.

[0039] Equipped with a TDS sensor, it accurately detects the total dissolved solids in water, providing a direct reflection of water purity; a turbidity sensor quickly captures suspended particles in water, measuring the clarity of the water; a residual chlorine sensor accurately measures the residual chlorine content in the water, ensuring safe and odorless drinking water; a heavy metal sensor sensitively identifies various heavy metal ions, preventing heavy metals from harming health; and a pH sensor accurately measures the acidity or alkalinity of the water. These sensors work together to comprehensively and accurately acquire various water quality indicators, providing a reliable basis for AI to analyze water quality in real time and dynamically adjust operating parameters, thereby ensuring that the water purifier can adapt to different water qualities and stably output high-quality purified water.

[0040] In this embodiment, the AI ​​decision module can individually control the start / stop of one or more filter stages and the power of the booster pump, and dynamically adjust the working status of the adaptive filtration module in real time.

[0041] The AI ​​decision-making module boasts powerful independent control capabilities, enabling precise control over the start and stop of one or more filter stages, and flexible adjustment of the booster pump power. This feature allows it to quickly and accurately adjust the adaptive filtration module's operating status in real-time based on water quality conditions. When facing different regions, seasons, and water qualities, it ensures that each filter stage operates at its optimal state, guaranteeing efficient filtration while minimizing unnecessary energy loss and filter wear. This further enhances water purification adaptability and filtration control precision, providing a solid guarantee for the stable output of high-quality purified water and comprehensively improving the water purifier's performance.

[0042] In this embodiment, each of the following filter elements is equipped with a solenoid valve for control: the first-stage pre-filter granular activated carbon filter, the second-stage compressed granular activated carbon filter, the third-stage RO reverse osmosis filter, and the fourth-stage post-filter granular activated carbon filter.

[0043] Each filter stage is equipped with a solenoid valve for control, greatly enhancing the adaptability of the water purifier. AI can precisely control the start and stop of each filter stage based on real-time water quality, dynamically adjusting operating parameters to adapt to different regions, seasons, and water qualities, ensuring stable water purification results. In terms of filtration control, it can more accurately activate filters as needed, ensuring filtration effectiveness while reducing waste. Furthermore, independent solenoid valve control facilitates precise monitoring of each filter stage's usage, helping to more accurately predict filter lifespan. It can also work in conjunction with the self-cleaning model to extend filter life, reduce user costs, and comprehensively improve the water purifier's performance and user experience.

[0044] In this embodiment, the adaptive filtration module is equipped with a variable frequency booster pump.

[0045] The variable frequency booster pump works seamlessly with the AI ​​adaptive filtration model, precisely and flexibly adjusting its power based on real-time water quality and filtration needs. In different regions and seasons, and with varying water qualities, it dynamically provides the perfect pressure, ensuring that each filter element fully performs its filtration function, greatly enhancing water purification adaptability and stabilizing purification results. Simultaneously, precise pressure control minimizes wear and tear on the filter modules while maintaining filtration effectiveness. Furthermore, in conjunction with filter life prediction and self-cleaning models, it helps extend filter life, reduce user costs, and comprehensively improve the water purifier's performance.

[0046] In this embodiment, the user interaction module also includes a water purifier mobile APP. The mobile APP supports iOS / Android / Harmony system operation, enabling the mobile APP to remotely control the water purifier, view water quality, filter usage status, and filter prediction remaining life information in real time, and receive filter replacement reminders and water quality abnormality alarm information.

[0047] The mobile app supports iOS, Android, and Harmony operating systems, offering broad coverage and greatly enhancing ease of use and universality. With this app, users can overcome spatial limitations, remotely control the water purifier, and easily manage its operation. Real-time monitoring of water quality, filter usage, and predicted remaining lifespan provides users with complete control over the water purification status. Furthermore, filter replacement reminders and water quality anomaly alarms promptly notify users to take appropriate measures, ensuring both effective purification and water safety. This module simplifies operation and comprehensively enhances the user experience and the water purifier's intelligence level.

[0048] In this embodiment, the user interaction module has an audible and visual alarm function.

[0049] During the operation of the water purifier, if any water quality abnormalities occur, such as excessive heavy metals, high microbial levels, nearing the end of the filter's lifespan, or equipment malfunction, the audible and visual alarm function will activate immediately. The sound alarm and flashing lights will immediately draw the user's attention, allowing them to be aware of any abnormalities without constantly monitoring the device. This not only ensures the user's water safety and prevents health risks due to water quality issues, but also reminds the user to replace the filter or repair the equipment in a timely manner, reducing further damage to the water purifier and effectively improving its convenience and safety.

[0050] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. An AI-based intelligent water purification system, characterized in that, The AI-based intelligent water purification system includes: The raw water inlet module is used to control the raw water pressure within a certain range using an inlet pipe and a pressure regulating valve, so as to avoid pressure fluctuations from affecting the filtration effect and obtain stable filtration conditions. The pre-filter module uses a built-in PP cotton filter element to filter out sediment and large particulate impurities in the raw water, reducing the workload of the adaptive filter module and extending the service life of the adaptive filter system filter element. The water quality testing module uses sensors to collect data on raw water and purified water in real time. The sampled data is transmitted to the AI ​​decision-making module in real time. The AI ​​decision-making module extracts the raw water and purified water data, compares and analyzes them, and adjusts its own operating status in real time to ensure that the purified water meets the standards. The operation status monitoring module is used to collect the operating parameters of the filter element through the differential pressure sensor and timer configured in the filter element, determine the degree of filter element blockage, calculate the performance degradation status of the filter element, and obtain the prediction result of the remaining life of the filter element. The water purification output module is used to form a water purification output structure consisting of a water outlet pipe, a UV ultraviolet germicidal lamp, a flow meter and a water outlet faucet. The UV ultraviolet germicidal lamp can avoid secondary pollution of the purified water, and the flow meter collects the water output in real time. The AI ​​decision-making module uses a dedicated chip to receive data from the water purifier in real time, performs real-time calculations based on a big data model, and then regulates all modules of the water purifier.

2. The AI-based intelligent water purification system according to claim 1, characterized in that, The AI-based intelligent water purification system also includes an adaptive filtration module, which uses a first-stage pre-filter granular activated carbon filter, a second-stage compressed granular activated carbon filter, a third-stage RO reverse osmosis filter, and a fourth-stage post-filter granular activated carbon filter to form a four-stage independently controlled filtration assembly.

3. The AI-based intelligent water purification system according to claim 1, characterized in that, The AI-based intelligent water purification system also includes a cloud collaboration module for data storage, data analysis, data sharing, and system updates. It receives local data, water quality reports, and water purifier usage information to form blockchain data. The cloud collaboration module is built on a commercial cloud platform.

4. The AI-based intelligent water purification system according to claim 1, characterized in that, The AI-based intelligent water purification system also includes a user interaction module, which uses a touch screen to display water quality, filter usage status, and predicted remaining lifespan of the filter in real time, and allows users to view water purifier parameter settings.

5. The AI-based intelligent water purification system according to claim 1, characterized in that, The water quality detection module also includes a TDS sensor, a turbidity sensor, a residual chlorine sensor, a heavy metal sensor, and a pH sensor.

6. The AI-based intelligent water purification system according to claim 1, characterized in that, The AI ​​decision-making module can individually control the start / stop of one or more filter stages and the power of the booster pump, and dynamically adjust the working status of the adaptive filtration module in real time.

7. The AI-based intelligent water purification system according to claim 2, characterized in that, Each of the first-stage pre-filter granular activated carbon filter, the second-stage compressed granular activated carbon filter, the third-stage RO reverse osmosis filter, and the fourth-stage post-filter granular activated carbon filter is equipped with a solenoid valve for control.

8. The AI-based intelligent water purification system according to claim 2, characterized in that, The adaptive filtration module is equipped with a variable frequency booster pump.

9. The AI-based intelligent water purification system according to claim 4, characterized in that, The user interaction module also includes a water purifier mobile APP, which supports iOS / Android / Harmony systems, enabling remote control of the water purifier, real-time viewing of water quality, filter usage, and predicted remaining lifespan of the filter, and receiving filter replacement reminders and water quality abnormality alarms.

10. The AI-based intelligent water purification system according to claim 4, characterized in that, The user interaction module has an audible and visual alarm function.

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