A remote water meter control method and system based on data visualization

Abstract

The application relates to a remote water meter control method and system based on data visualization, which comprises a control unit, a communication unit, a power generation unit, a metering unit and a remote server; the control unit is used for controlling pipeline water flow; the remote server is connected with the control unit through the communication unit and sends control instructions to the control unit; the communication unit is used for connecting the remote server, the control unit and the metering unit; the communication unit sends data acquired by the metering unit to the remote server; the metering unit is used for collecting data of the power generation unit and the control unit, realizes sustainable power supply through the power generation unit, collects two reading data and analyzes the two reading data, further obtains real water flow data, provides a reference condition for real-time data analysis, and can more accurately realize reading of actual water flow data.

Description

Technical Field

[0001] This invention relates to the field of remote water meter control technology, and in particular to a remote water meter control method and system based on data visualization. Background Technology

[0002] Smart water meters are a new type of water meter that uses modern microelectronics, modern sensing technology, and smart IC card technology to measure water consumption, transmit water data, and settle transactions. In addition, smart water meters can also measure water pressure, flow rate, etc. Compared with traditional water meters, which generally only have the functions of flow rate collection and mechanical pointer display of water consumption, this is a great improvement. At the same time, with the development of the Internet, data visualization is also a development trend. In existing technologies, data can be uploaded to the cloud through NB water meters and visualized. However, this requires the water meter to be powered to meet the transmission requirements. Current technologies generally use rechargeable batteries, which need to be replaced and are difficult to meet long-term use.

[0003] Meanwhile, existing electronic water meters include electromagnetic water meters: based on Faraday's principle of electromagnetic induction, when a conductive fluid flows through an external magnetic field, an electromotive force perpendicular to both the flow direction and the magnetic field direction is induced in the fluid, and the flow rate is calculated by measuring this electromotive force. A drawback is that water quality with very poor conductivity may affect the measurement, and a relatively stable power supply is required. Ultrasonic water meters: utilize the angle between the speed of ultrasonic waves propagating in water and the water flow velocity to determine the flow rate. They are less affected by temperature, turbulence, and air bubbles, but are more sensitive to the shape of the flow channel and the installation method; irregular flow may affect accuracy. Both types of meters introduce errors between the readings and the actual data during use, increasing costs for users. Therefore, this invention proposes a remote water meter control method and system based on data visualization. Summary of the Invention

[0004] This invention addresses the technical problems existing in the prior art by providing a remote water meter control method and system based on data visualization.

[0005] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: a remote water meter control method and system based on data visualization;

[0006] A remote water meter control system based on data visualization includes a control unit, a communication unit, a power generation unit, a metering unit, and a remote server;

[0007] The control unit is used to control the flow of water in the pipeline, and the remote server connects to the control unit through a communication unit and sends control commands to the control unit.

[0008] The communication unit is used to connect the remote service, the control unit, and the metering unit; the communication unit sends the data acquired by the metering unit to the remote server;

[0009] The metering unit is used to collect data from the power generation unit and the control unit.

[0010] Furthermore, in the aforementioned remote water meter control system based on data visualization, the control unit includes a solenoid valve and an NB water meter. The solenoid valve is connected to the NB water meter, and its status includes at least one of open, closed, and faulty states. The flow of water is controlled by opening and closing the valve. The NB water meter is used to measure water flow data and sends the water flow data to the remote server in real time.

[0011] Furthermore, in the aforementioned remote water meter control system based on data visualization, the power generation unit includes a lithium battery and a pipeline water flow generator. The lithium battery is used to store the electrical energy generated by the pipeline water flow generator. The lithium battery is connected to the solenoid valve and the NB water meter to provide electrical energy to the solenoid valve and the NB water meter.

[0012] A remote water meter control method based on data visualization, wherein the remote water meter control method based on data visualization is implemented using any one of the aforementioned remote water meter control systems, the control method comprising:

[0013] S1: The remote server sends an opening command to the control unit to open the solenoid valve, allowing water to flow through the pipe and the water flow generator to start generating electricity, and then transmits the generated electricity to the remote server through the communication unit;

[0014] S2: Water flow through the pipeline is measured by the NB water meter, which then transmits the water flow data to the remote server via the communication unit.

[0015] S3: Calculate the data of the first NB water meter using the preset power consumption-water flow model;

[0016] S4: Calculate the data of the second NB water meter based on the water meter loss curve;

[0017] S5: Take a weighted average of the data from the first NB water meter and the data from the second NB water meter to obtain the final real water meter data, and display it on the remote server for users to view.

[0018] Furthermore, in the aforementioned remote water meter control method based on data visualization, the preset electricity-water flow model in step S3 includes:

[0019] Given the amount of electricity generated, E, convert the amount of electricity generated into power, P:

[0020]

[0021] t is time, and the flow rate Q can be obtained from the properties of the water and the performance data of the pipeline water flow generator:

[0022]

[0023] ρ is the density of water, g is the acceleration due to gravity, H is the head of water, and ηG is the power generation efficiency of the pipeline water turbine.

[0024] Furthermore, the aforementioned remote water meter control method based on data visualization also needs to consider head loss along the pipeline:

[0025]

[0026] Where I is the pipe length, d is the pipe diameter, v is the average flow velocity of the water, and λ is the friction loss.

[0027] Furthermore, in the aforementioned remote water meter control method based on data visualization, the steps for implementing the water meter loss curve include:

[0028] Data collection: Collect long-term water meter readings and actual water flow data passing through the water meters;

[0029] Error analysis: The actual water meter readings collected are compared with the accurate water flow rate to calculate the error for each data point;

[0030] Curve establishment: Based on the error data, an error model, namely the water meter loss curve, is established using statistical analysis methods;

[0031] Error correction: The new water meter readings are corrected based on the established water meter loss curve.

[0032] Furthermore, the aforementioned remote water meter control method based on data visualization also includes the following in the water meter loss curve:

[0033]

[0034] ω is the error value, and N(i) and N(j) are the actual reading of the water meter and the actual water flow data, respectively.

[0035] An electronic device, characterized in that it comprises:

[0036] Memory, used to store computer software programs;

[0037] A processor is used to read and execute the computer software program, thereby implementing any of the data visualization-based remote water meter control methods described above.

[0038] A non-transitory computer-readable storage medium storing a computer software program, which, when executed by a processor, implements any one of the data visualization-based remote water meter control methods described above.

[0039] The beneficial effects of this invention are:

[0040] This system combines a power generation-water flow model with a water meter loss curve model, improving the accuracy of water flow measurement. Through this data fusion, it can provide more accurate readings than traditional water meters, especially when the meter is worn or its lifespan is affected.

[0041] Real-time remote monitoring and control: The remote monitoring and control system, implemented through the communication unit, allows users to receive and analyze water meter data in real time from any location, enabling timely water flow control decisions, which improves the efficiency of water resource management.

[0042] Self-powered: The power generation unit in the system design, such as the pipeline flow generator, provides self-sufficient energy for the power supply of water meters and solenoid valves, thereby reducing dependence on external power supply. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating the remote water meter control method based on data visualization according to the present invention.

[0044] Figure 2 This is a flowchart illustrating the steps for implementing the water meter loss curve in one embodiment of the present invention.

[0045] Figure 3 A schematic diagram of an embodiment of the electronic device provided in this invention;

[0046] Figure 4 This is a schematic diagram of an embodiment of a computer-readable storage medium provided in this invention. Detailed Implementation

[0047] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0048] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0049] In the description of this application, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0050] Example 1:

[0051] A remote water meter control system based on data visualization includes a control unit, a communication unit, a power generation unit, a metering unit, and a remote server;

[0052] The control unit is used to control the flow of water in the pipeline, and the remote server connects to the control unit through a communication unit and sends control commands to the control unit.

[0053] The communication unit is used to connect the remote service, the control unit, and the metering unit; the communication unit sends the data acquired by the metering unit to the remote server;

[0054] The metering unit is used to collect data from the power generation unit and the control unit.

[0055] The control unit includes a solenoid valve and an NB water meter. The solenoid valve is connected to the NB water meter, and the solenoid valve status includes at least one of open, closed, and fault. Opening and closing controls whether water flows. The NB water meter is used to measure water flow data and send the water flow data to the remote server in real time.

[0056] The power generation unit includes a lithium battery and a pipeline water flow generator. The lithium battery is used to store the electrical energy generated by the pipeline water flow generator. The lithium battery is connected to the solenoid valve and the NB water meter to provide electrical energy to the solenoid valve and the NB water meter.

[0057] In this embodiment, the basic configuration of the pipeline water flow generator is as follows:

[0058] Output voltage 12V (1.2MPa)

[0059] Maximum output current 200mA (12V)

[0060] Line-to-line resistance: 10.5 ± 0.5 Ω

[0061] Insulation resistance 10mΩ

[0062] The outlet is sealed and can withstand a pressure of 0.6 MPa.

[0063] The maximum pressure resistance of the open outlet is 1.2 MPa.

[0064] Start with a water pressure of 0.05 MPa;

[0065] The aforementioned pipeline water flow generator is installed at the front end of the NB water meter, and a solenoid valve is installed between the NB water meter and the pipeline water flow generator. The specific working principle is as follows: the APP (remote server) backend sends a command to the solenoid valve to open it, and water flows through the pipeline water flow generator to start generating electricity and storing energy in the lithium battery; the water flow passes through the solenoid valve, the NB water meter measures the flow, and transmits the data to the APP in real time. The APP backend analyzes the received real-time data, and if an anomaly is detected, it sends a command to close the solenoid valve.

[0066] Example 2:

[0067] A remote water meter control method based on data visualization, wherein the remote water meter control method based on data visualization is implemented using any one of the aforementioned remote water meter control systems, the control method comprising:

[0068] S1: The remote server sends an opening command to the control unit to open the solenoid valve, allowing water to flow through the pipe and the water flow generator to start generating electricity, and then transmits the generated electricity to the remote server through the communication unit;

[0069] S2: Water flow through the pipeline is measured by the NB water meter, which then transmits the water flow data to the remote server via the communication unit.

[0070] S3: Calculate the data of the first NB water meter using the preset power consumption-water flow model;

[0071] S4: Calculate the data of the second NB water meter based on the water meter loss curve;

[0072] S5: Take a weighted average of the data from the first NB water meter and the data from the second NB water meter to obtain the final real water meter data, and display it on the remote server for users to view.

[0073] In this embodiment, the remote server sends a command to the control unit to open the solenoid valve. Once the solenoid valve is open, water begins to flow through the pipe and into the water generator. The generator uses the flowing water to generate electricity, and the generated electricity is recorded by the metering unit. The metering unit sends the measured generated electricity back to the remote server via the communication unit. When water flows through the NB water meter, the water meter measures the water flow rate. The measured water flow rate data is also transmitted back to the remote server via the communication unit. The collected generated electricity data is converted using a pre-set power-water flow rate model. The model reflects the relationship between generated electricity and water flow rate, allowing the corresponding water flow rate data to be calculated from the generated electricity. In the second NB water meter data, the potential losses that may occur during the use of the NB water meter need to be considered. Using the water meter loss curve, the NB water meter reading is adjusted based on long-term data and statistical analysis to calculate the corrected water flow rate. Finally, the first NB water meter data (based on the measurement of generated electricity) and the second NB water meter data (based on the reading corrected by the historical loss curve) are combined. A more accurate data reflecting the actual water flow rate is obtained through a weighted average, which is called "real water meter data".

[0074] Furthermore, in step S3, the preset power-water flow model includes:

[0075] Given the amount of electricity generated, E, convert the amount of electricity generated into power, P:

[0076]

[0077] t is time, and the flow rate Q can be obtained from the properties of the water and the performance data of the pipeline water flow generator:

[0078]

[0079] ρ is the density of water, g is the acceleration due to gravity, H is the head of water, and ηG is the power generation efficiency of the pipeline water turbine.

[0080] In this embodiment, we assume we have the following data:

[0081] Electricity generation (E) = 1 kWh (electricity generation in 1 hour)

[0082] Generator efficiency (ηG) = 90% = 0.9 (dimensionless)

[0083] Water head (H) = 10 meters (m)

[0084] Gravitational acceleration (g) = 9.81 m / s² 2 )

[0085] The density of water (ρ) = 1000 kg per cubic meter (kg / m³) 3 )

[0086] To deduce the flow rate (Q), use the following formula:

[0087]

[0088] Since we assume that 1 kWh is generated in 1 hour, then P is 1000 watts (W).

[0089] Next, the flow rate is calculated using the power after efficiency correction:

[0090]

[0091] Substitute the known values ​​into:

[0092]

[0093] This means that 0.014 cubic meters of water per second generates 1 kWh of electricity, or 1000 watts of power, through the turbine. This is a theoretical calculation, and the actual value may vary due to various factors, such as the actual operating conditions of the turbine and generator.

[0094] Furthermore, head loss along the pipeline also needs to be considered:

[0095]

[0096] Where I is the pipe length, d is the pipe diameter, v is the average flow velocity of the water, and λ is the friction loss.

[0097] Furthermore, the steps for implementing the water meter loss curve include:

[0098] S41: Data Collection: Collect long-term water meter readings and actual water flow through the water meters;

[0099] S42: Error Analysis: Compare the collected actual water meter readings with the accurate water flow rate and calculate the error for each data point;

[0100] S43: Curve Establishment: Based on the error data, establish an error model using statistical analysis methods, namely the water meter loss curve;

[0101] S44: Error Correction: Correct the new water meter reading based on the established water meter loss curve.

[0102] Furthermore, the water meter loss curve also includes:

[0103]

[0104] ω is the error value, and N(i) and N(j) are the actual reading of the water meter and the actual water flow data, respectively.

[0105] In this embodiment: data collection involves installing a water meter and taking periodic readings to record the water meter reading (R_m) for each time period (e.g., hourly, daily, or monthly).

[0106] Use a separate, precise measuring device (such as a calibrated flow meter) to simultaneously measure the actual water flow rate F passing through the water meter.

[0107] Error analysis involves calculating the error (\varepsilon) for each time period's water meter reading and the actual flow rate obtained from independent measuring devices: [\varepsilon=R_m-F]

[0108] Perform statistical analysis on all data points to determine if a consistent error pattern exists (e.g., whether the error increases or decreases with increasing flow rate).

[0109] Curve establishment involves using the collected error data and their corresponding actual flow values ​​to perform regression analysis and create a model. For example, linear regression, multinomial regression, or other appropriate statistical models can be used.

[0110] The established model will form a mathematical formula or graph that represents the relationship between error and actual flow rate, i.e., the water meter loss curve.

[0111] Error correction is performed using the water meter loss curve for new water meter readings. If a mathematical formula is used, the current water meter reading is interpolated into the formula, and the expected error is calculated. If a graph is used, the error associated with the current reading can be read from the graph.

[0112] The water meter reading is adjusted using the expected error to obtain the corrected flow rate value: [F_{correction} = R_m - \varepsilon]

[0113] The corrected flow rate (F_{correction}) is considered to be closer to the actual water flow rate.

[0114] Example:

[0115] Assuming that regression analysis yields the following linear water meter loss curve equation:

[0116] [\varepsilon=a\cdotR_m+b]

[0117] Where (a) and (b) are coefficients obtained through regression analysis, (\varepsilon) is the expected error, and (R_m) is the water meter reading.

[0118] For new readings, first calculate the expected error using the formula:

[0119] [\varepsilon_{expected}=a\cdotR_m+b]

[0120] Then the readings are corrected:

[0121] [F_{correction} = R_m - \varepsilon_{expected}]

[0122] Use (F_{correction}) as an estimate of the actual flow.

[0123] Ultimately, this corrected flow rate value can be used for water resource management, billing calculations, and more. This process may need to be repeated periodically to account for the effects of new wear and tear, aging water meters, or changes in environmental conditions.

[0124] In another embodiment, a machine learning model is used to correct the reading error of the water meter:

[0125] Data preparation

[0126] Collect sufficient labeled data: For machine learning models, the required data should include water meter readings (input variable X) and independently measured actual water flow (target variable Y).

[0127] Data cleaning: Ensure data accuracy by removing outliers and inconsistencies.

[0128] Data splitting: The dataset is divided into training and testing sets, usually using a split ratio of 70%-30% or 80%-20%.

[0129] Feature selection

[0130] Select various features that affect the accuracy of water meter readings, such as time, temperature, and water pressure.

[0131] Feature engineering: creating new features by transforming or combining existing features to improve the predictive power of a model.

[0132] Select Model

[0133] Choose an appropriate machine learning model, such as linear regression, decision tree, random forest, support vector machine, or neural network.

[0134] Considering the nature of the problem, we can start with a simple model and gradually increase its complexity until we find the best-fitting model.

[0135] Training Model

[0136] Use the training dataset to train the selected model.

[0137] Cross-validation is performed to ensure the model's generalization ability, and hyperparameters are tuned to optimize model performance.

[0138] Test Evaluation

[0139] Evaluate the model's performance using a test set.

[0140] Use appropriate evaluation metrics, such as mean squared error (MSE), root mean squared error (RMSE), or R² score.

[0141] Model calibration

[0142] The trained model is used to predict the error of the water meter.

[0143] For new water meter readings, a trained model is used to predict errors and then the readings are corrected.

[0144] Model Deployment

[0145] Deploy the trained and successfully tested model to the production system or integrate it into the existing remote water meter control system.

[0146] Assume we choose to use a linear regression model. The dataset contains the following features: time (T), water temperature (WT), water meter reading (R), and exact flow rate (F).

[0147] By analyzing the effects of time (T) and water temperature (WT) on flow rate (F), it is determined which features need to be included in the model.

[0148] Use scientific computing libraries (such as scikit-learn for Python) to build a regression model.

[0149] The model is trained using training set data to ensure that it learns the mapping from water meter readings (R) and other features (T, WT) to actual flow (F).

[0150] The model is evaluated using a test set to examine the difference between the predicted and actual values.

[0151] The trained model is used to predict the error of the new water meter readings and make corresponding corrections.

[0152] The corrected flow data is then returned to the control system.

[0153] Example 3:

[0154] Please see Figure 3 , Figure 3 This is a schematic diagram illustrating an embodiment of the electronic device provided in this invention. For example... Figure 3As shown, this embodiment of the invention provides an electronic device 500, including a memory 510, a processor 520, and a computer program 511 stored in the memory 510 and executable on the processor 520. When the processor 520 executes the computer program 511, it performs the following steps:

[0155] S1: The remote server sends an opening command to the control unit to open the solenoid valve, allowing water to flow through the pipe and the water flow generator to start generating electricity, and then transmits the generated electricity to the remote server through the communication unit;

[0156] S2: Water flow through the pipeline is measured by the NB water meter, which then transmits the water flow data to the remote server via the communication unit.

[0157] S3: Calculate the data of the first NB water meter using the preset power consumption-water flow model;

[0158] S4: Calculate the data of the second NB water meter based on the water meter loss curve;

[0159] S5: Take a weighted average of the data from the first NB water meter and the data from the second NB water meter to obtain the final real water meter data, and display it on the remote server for users to view.

[0160] Please see Figure 4 , Figure 4 This is a schematic diagram illustrating an embodiment of a computer-readable storage medium provided by an embodiment of the present invention. For example... Figure 4 As shown, this embodiment provides a computer-readable storage medium 600, on which a computer program 611 is stored. When the computer program 611 is executed by a processor, it performs the following steps:

[0161] S1: The remote server sends an opening command to the control unit to open the solenoid valve, allowing water to flow through the pipe and the water flow generator to start generating electricity, and then transmits the generated electricity to the remote server through the communication unit;

[0162] S2: Water flow through the pipeline is measured by the NB water meter, which then transmits the water flow data to the remote server via the communication unit.

[0163] S3: Calculate the data of the first NB water meter using the preset power consumption-water flow model;

[0164] S4: Calculate the data of the second NB water meter based on the water meter loss curve;

[0165] S5: Take a weighted average of the data from the first NB water meter and the data from the second NB water meter to obtain the final real water meter data, and display it on the remote server for users to view.

[0166] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0167] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0168] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0169] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0170] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0171] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0172] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A remote water meter control method based on data visualization, characterized in that, It includes a control unit, a communication unit, a power generation unit, a metering unit, and a remote server; The control unit is used to control the flow of water in the pipeline, and the remote server connects to the control unit through a communication unit and sends control commands to the control unit. The communication unit is used to connect the remote service, the control unit, and the metering unit; the communication unit sends the data acquired by the metering unit to the remote server; The metering unit is used to collect data from the power generation unit and the control unit; S1: The remote server sends an opening command to the control unit to open the solenoid valve, allowing water to flow through the pipe and the water flow generator to start generating electricity, and then transmits the generated electricity to the remote server through the communication unit; S2: Water flow through the pipeline is measured by the NB water meter, which then transmits the water flow data to the remote server via the communication unit. S3: Calculate the first NB water meter data using the preset power-water flow model, and use the preset power-water flow model to convert the collected power generation data. The model can reflect the relationship between power generation and water flow, allowing the corresponding water flow data to be calculated from power generation. S4: Calculate the second NB water meter data based on the water meter loss curve, and adjust the NB water meter reading using the water meter loss curve, based on long-term data and statistical analysis, and calculate the corrected water flow rate. S5: Take a weighted average of the data from the first NB water meter and the data from the second NB water meter to obtain the final real water meter data, and display it on the remote server for users to view. The preset power-water flow model includes: Given the amount of electricity generated, E, convert the amount of electricity generated into power, P: ； t is time, and the flow rate Q can be obtained from the properties of the water and the performance data of the pipeline water flow generator: ； Here, g is the density of water, g is the acceleration due to gravity, and H is the head of water. It is the power generation efficiency of the pipeline water flow machine; In pipelines, head loss along the pipeline also needs to be considered: ； Where I is the pipe length, d is the pipe diameter, and v is the average flow velocity of the water. It is the friction loss along the friction path.

2. The remote water meter control method based on data visualization according to claim 1, characterized in that, The control unit includes a solenoid valve and an NB water meter. The solenoid valve is connected to the NB water meter, and the solenoid valve status includes at least one of open, closed, and fault. Opening and closing controls whether water flows. The NB water meter is used to measure water flow data and send the water flow data to the remote server in real time.

3. The remote water meter control method based on data visualization according to claim 1, characterized in that, The power generation unit includes a lithium battery and a pipeline water flow generator. The lithium battery is used to store the electrical energy generated by the pipeline water flow generator. The lithium battery is connected to the solenoid valve and the NB water meter to provide electrical energy to the solenoid valve and the NB water meter.

4. The remote water meter control method based on data visualization according to claim 1, characterized in that, The steps for implementing the water meter loss curve include: Data collection: Collect long-term water meter readings and actual water flow data passing through the water meters; Error analysis: The actual water meter readings collected are compared with the accurate water flow rate to calculate the error for each data point; Curve establishment: Based on the error data, an error model, namely the water meter loss curve, is established using statistical analysis methods; Error correction: The new water meter readings are corrected based on the established water meter loss curve.

5. The remote water meter control method based on data visualization according to claim 4, characterized in that, The water meter loss curve also includes: ； It is the error value. and These are the actual water meter reading and the actual water flow data, respectively.

6. An electronic device, characterized in that, include: Memory, used to store computer software programs; A processor is configured to read and execute the computer software program, thereby implementing the remote water meter control method based on data visualization as described in any one of claims 1-5.

7. A non-transitory computer-readable storage medium, characterized in that, The storage medium stores a computer software program, which, when executed by a processor, implements a remote water meter control method based on data visualization as described in any one of claims 1-5.

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