A method, device, equipment and storage medium for detecting abnormal communication of smart water meter

Abstract

The present application provides a method, device, equipment and storage medium for detecting communication anomalies of a smart water meter, which relates to the field of communication technology. The method includes: predicting the change rate of the first water consumption data of the first smart water meter based on the historical water consumption data sent by the first smart water meter; judging whether the first water consumption data currently sent by the first smart water meter meets the first preset requirement; if not, obtaining the second water consumption data sent by other smart water meters currently in the same water supply path as the first smart water meter, and the change rate of the second water consumption data of other smart water meters; judging whether the second water consumption data meets the second preset requirement, and if so, determining the actual water consumption data of the current first smart water meter based on the second water consumption data; comparing the actual water consumption data with the first water consumption data, and determining whether the current first smart water meter has communication anomalies. The technical effect of the present application is: timely discovering and solving communication problems of smart water meters, and ensuring the normal operation of water supply services.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method, device, equipment and storage medium for detecting communication anomalies in a smart water meter. Background Art

[0002] With the development of science and technology, the use of smart water meters is becoming more and more widespread. Compared with traditional water meters, smart water meters can automatically read and transmit water usage data, greatly improving the efficiency of data collection and processing.

[0003] However, in actual operation, since water meters are sometimes installed in rural areas or underground, communication signals may be interfered with, which may cause differences between the readings of smart water meters and actual water consumption. If this difference is not discovered and handled in time, it may lead to data errors, affect water billing, and even affect the normal operation of water supply services. Summary of the invention

[0004] The present application provides a smart water meter communication anomaly detection method, device, equipment and storage medium for timely discovering and solving smart water meter communication problems to ensure the normal operation of water supply services.

[0005] In a first aspect, the present application provides a method for detecting communication anomalies in a smart water meter, the method comprising: predicting a change rate of first water use data of the first smart water meter based on historical water use data sent by the first smart water meter; judging whether the first water use data currently sent by the first smart water meter meets a first preset requirement based on the water use data change rate; if not, obtaining second water use data sent by other smart water meters that are currently in the same water supply path as the first smart water meter, and the change rate of the second water use data of the other smart water meters; judging whether the second water use data meets the second preset requirement based on the change rate of the second water use data, and if so, determining the actual water use data of the first smart water meter based on the second water use data; and comparing the actual water use data with the first water use data to determine whether there is a communication anomaly in the first smart water meter.

[0006] By adopting the above technical solution, by predicting the rate of change of water use data, the system can predict possible communication problems in advance, which plays an important role in preventing data errors and improving data accuracy. Secondly, if the data of the first smart water meter does not meet the preset requirements, the system will also obtain and compare the data of other smart water meters on the same water supply path, which can effectively utilize the data correlation between the smart water meters on the same water supply path, and improve the accuracy of determining actual water use data and judging communication anomalies. Comprehensive consideration of historical data, data change rate and other data on the same water supply path allows the system to make more comprehensive and accurate judgments when determining whether there is a communication anomaly, timely discover and solve communication problems, and ensure the normal operation of water supply services.

[0007] Optionally, predicting the change rate of the first water usage data of the first smart water meter based on the historical water usage data sent by the first smart water meter includes: establishing a prediction model based on the historical water usage data sent by the first smart water meter; and predicting the change rate of the first water usage data of the first smart water meter based on the predicted model.

[0008] By adopting the above technical solution and establishing a prediction model, the change rate of water consumption data of the first smart water meter can be predicted more accurately. The prediction model can find out the law of water consumption data change based on historical data, thereby improving the accuracy of the prediction.

[0009] Optionally, the historical water consumption data includes training data and test data, and the prediction model is established based on the historical water consumption data sent by the first smart water meter, including: establishing a learning model for predicting future water consumption based on the training data; and optimizing the learning model through the test data to obtain the prediction model.

[0010] By adopting the above technical solution and using training data to build a learning model, the system can learn the laws and trends of water consumption changes from a large amount of historical data, which can not only improve the accuracy of predictions, but also enable the system to have a certain processing capability for various water use situations. By optimizing the learning model using test data, the generalization ability of the model can be further improved. The optimization process can help the model better adapt to various unseen water use situations, so that the model can make accurate predictions when faced with new and unknown data.

[0011] Optionally, after determining whether the second water use data meets the second preset requirement based on the change rate of the second water use data, the method further includes: if the second water use data does not meet the second preset requirement, sending an alarm message to the staff's terminal device, so that the staff can inspect the smart water meter that does not meet the second preset requirement and the first smart water meter.

[0012] By adopting the above technical solution and setting preset requirements, the system can monitor water usage data in real time. Once abnormal data is found, the staff will be notified immediately through alarm information. This can not only ensure the accuracy of the data, but also detect and deal with possible problems as soon as possible to prevent the problem from further expanding.

[0013] Optionally, the comparing the actual water usage data and the first water usage data to determine whether there is a communication abnormality in the current first smart water meter includes: if the actual water usage data is equal to the first water usage data, determining that the communication of the current first smart water meter is normal communication; if the actual water usage data is not equal to the first water usage data, calculating the difference between the actual water usage data and the first water usage data; judging whether the difference is within a preset range, and if it is not within the preset range, determining that there is a communication abnormality in the first smart water meter.

[0014] By adopting the above technical solution and comparing the actual water usage data with the first water usage data, it is possible to accurately determine whether the communication of the smart water meter is normal, which not only improves the accuracy of communication monitoring, but also improves the responsiveness of the system. When the actual water usage data is not equal to the first water usage data, the system will calculate the difference between the two and make a judgment, which can not only accurately identify abnormal situations, but also detect possible communication problems as early as possible to prevent the problem from further expanding. In addition, the system can automatically compare and judge the data without manual intervention, which greatly improves work efficiency.

[0015] Optionally, the determining whether the difference is within a preset range further includes: if the difference is within the preset range, continuously acquiring the difference between the actual water use data and the first water use data; if the difference is within the preset range within the preset time period, sending a reminder message to the staff's terminal device to enable the staff to check or adjust the first smart water meter.

[0016] By adopting the above technical solution, by continuously obtaining the difference between the actual water consumption data and the first water consumption data, the system can monitor the operating status of the smart water meter in real time and dynamically adjust the working strategy according to these data. This real-time monitoring and dynamic adjustment not only improves the flexibility of the system, but also enables the system to better adapt to various possible operating conditions. At the same time, when the difference within the preset time is within the preset range, the system will send a reminder message to the staff's terminal device so that the staff can check or adjust it in time. In addition, this solution also enhances the automation and intelligence of the smart water meter monitoring system. The system can automatically obtain data, automatically judge the status, and automatically send reminders, which greatly reduces the workload of manual operation and improves work efficiency.

[0017] Optionally, after comparing the actual water usage data with the first water usage data to determine whether there is a communication anomaly in the first smart water meter, it also includes: if it is determined that there is a communication anomaly in the first smart water meter, recording and storing abnormal information, the abnormal information includes the time when the communication anomaly of the first smart water meter occurred, the water usage data of the first smart water meter, the water usage data of the second smart water meter and the actual water usage data.

[0018] By adopting the above technical solution, when it is determined that the first smart water meter has a communication anomaly, the anomaly information including the time of the anomaly, the water consumption data of the first smart water meter, the water consumption data of the second smart water meter and the actual water consumption data is recorded and stored. This facilitates subsequent fault analysis and prevention work, makes the entire fault handling process clearer and more standardized, and improves the stability and reliability of the system.

[0019] In a second aspect, the present application provides a smart water meter communication anomaly detection device, the device comprising: a prediction module, a judgment module, an acquisition module, a determination module and an output module; wherein the prediction module is used to predict the change rate of the first water use data of the first smart water meter based on the historical water use data sent by the first smart water meter; the judgment module is used to judge whether the first water use data currently sent by the first smart water meter meets the first preset requirement based on the water use data change rate; the acquisition module is used to, if not, obtain the second water use data sent by other smart water meters that are currently in the same water supply path as the first smart water meter, and the change rate of the second water use data of the other smart water meters; the determination module is used to judge whether the second water use data meets the second preset requirement based on the change rate of the second water use data, and if so, determine the actual water use data of the current first smart water meter based on the second water use data; the output module is used to compare the actual water use data with the first water use data to determine whether there is a communication anomaly in the current first smart water meter.

[0020] By adopting the above technical solution, by predicting the rate of change of water use data, the system can predict possible communication problems in advance, which plays an important role in preventing data errors and improving data accuracy. Secondly, if the data of the first smart water meter does not meet the preset requirements, the system will also obtain and compare the data of other smart water meters on the same water supply path, which can effectively utilize the data correlation between the smart water meters on the same water supply path, and improve the accuracy of determining actual water use data and judging communication anomalies. Comprehensive consideration of historical data, data change rate and other data on the same water supply path allows the system to make more comprehensive and accurate judgments when determining whether there is a communication anomaly, timely discover and solve communication problems, and ensure the normal operation of water supply services.

[0021] In the third aspect, the present application provides an electronic device, adopting the following technical solution: including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a computer program such as any of the above-mentioned smart water meter communication anomaly detection methods.

[0022] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: storing a computer program that can be loaded by a processor and execute any of the above-mentioned smart water meter communication anomaly detection methods.

[0023] In summary, the present application includes at least one of the following beneficial technical effects:

[0024] 1. Timely discover and solve smart water meter communication problems to ensure the normal operation of water supply services;

[0025] 2. Discover possible communication problems as early as possible to prevent them from further expanding. The system can automatically compare and judge the data without manual intervention, greatly improving work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a method for detecting abnormal communication of a smart water meter provided in an embodiment of the present application;

[0027] Figure 2 It is a structural diagram of a smart water meter communication anomaly detection device provided in an embodiment of the present application;

[0028] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0029] Explanation of the accompanying drawings: 1. Prediction module; 2. Judgment module; 3. Acquisition module; 4. Determination module; 5. Output module; 1000. Electronic device; 1001. Processor; 1002. Communication bus; 1003. User interface; 1004. Network interface; 1005. Memory. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0031] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0032] Smart water meters, also known as electronic water meters or automatic reading water meters, are devices that can automatically record and report water usage data. Through wireless communication technology, smart water meters can send detailed water usage data in real time or periodically to a central server for water suppliers and users to view and analyze. This automated data collection and reporting method greatly improves the accuracy and efficiency of data reading.

[0033] Smart water meters can automatically and in real time collect and send water consumption data, reducing the workload and time of manual meter reading and improving the efficiency of data collection and processing. By eliminating the errors that may occur in manual meter reading, smart water meters can provide more accurate water consumption data, thereby improving the accuracy of settlement. Smart water meters can provide detailed water consumption data and analysis reports to help water suppliers and users better monitor and manage water resources. By analyzing the data of smart water meters, various problems can be discovered and handled in a timely manner, such as water leaks, abnormal water use, abnormal communication, etc.

[0034] Smart water meters rely on wireless communication technology. If the network signal is unstable or interfered with, the accuracy and timeliness of data transmission may be affected. If the smart water meter cannot send or receive data normally, it may cause water consumption data to be lost or incorrect, affecting the accuracy of settlement. If the communication anomaly lasts for a long time, it may cause the service of the smart water meter to be interrupted, affecting the user experience. Communication anomalies may require professional technicians to inspect and repair, increasing maintenance costs. If the smart water meter cannot send data normally, it may not be able to detect and deal with various problems in a timely manner, such as water leaks, abnormal water use, etc.

[0035] Therefore, the present application proposes the following solution to the above problem: first, collect the historical water consumption data of the first smart water meter, and predict its water consumption data change rate based on the data. This change rate can determine the water consumption pattern and trend of any water meter. The first smart water meter can be any smart water meter.

[0036] Then, it is determined whether the current water usage data sent by the smart water meter meets some preset requirements. These requirements may be set based on historical data and predicted change rates. If the current water usage data does not meet the preset requirements, it is considered that the smart water meter may have communication anomalies.

[0037] Therefore, the second water consumption data and the corresponding change rate are obtained from other smart water meters on the same water supply path as the first smart water meter. The same water supply path can be a group of smart water meters connected to the same water source or water supply system. These water meters may serve the same building (such as an apartment building or office building), or multiple buildings in the same area. This means that these water meters have similar water consumption patterns and trends. The current total water consumption can be obtained through the same water supply path, and then the water consumption data of other water meters are obtained, that is, the water consumption data of the first smart water meter can be obtained. Then, it is determined whether these second water consumption data meet another set of preset requirements. If they meet, these data are considered to be credible, and then the actual water consumption data of the first smart water meter is determined based on these data.

[0038] Finally, the actual water usage data is compared with the water usage data sent by the first smart water meter. If there is a significant difference between the two, it is determined that there is a communication anomaly in the first smart water meter.

[0039] In general, this solution can detect and handle communication anomalies in a timely manner by comparing and analyzing the water consumption data and change rate of smart water meters to ensure data accuracy and service stability.

[0040] Figure 1 is a flow chart of a method for detecting abnormal communication of a smart water meter provided in an embodiment of the present application. It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but the steps are not necessarily executed in the order indicated by the arrows; unless otherwise specified in this document, there is no strict order restriction for the execution of the steps, and the steps may be executed in other orders; and Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0041] This application discloses a method for detecting abnormal communication of a smart water meter. Figure 1 As shown, the method includes S101-S105.

[0042] S101, predicting a change rate of first water usage data of the first smart water meter according to historical water usage data sent by the first smart water meter.

[0043] In one example, in a method for detecting abnormal communication of a smart water meter, firstly, based on the historical water consumption data sent by the first smart water meter, a change rate of first water consumption data of the first smart water meter is predicted. Since the change rate of water consumption data reflects the usage and possible abnormal conditions of the water meter, if the change rate of water consumption data is significantly different from the expected or historical data, it may mean that there is a problem with the communication of the water meter.

[0044] The specific method for implementing this step is to first collect historical water consumption data sent by the first smart water meter, which may include daily, weekly or monthly water consumption. Then, use this historical data to build a prediction model, for example, machine learning algorithms such as linear regression, support vector machine or deep neural network can be used. These models can learn the changing trends and patterns of water consumption data from historical data, and predict the rate of change of water consumption data in the future based on this.

[0045] Historical water use data can also be divided into training data and test data. Training data is used to build a learning model, while test data is used to optimize the model to ensure that the model's prediction results are as accurate as possible. The effect of this is that the rate of change of future water use data can be predicted more accurately, and possible communication anomalies can be discovered early, so that measures can be taken early to avoid possible losses.

[0046] Obtain the historical operation data of the first smart water meter. The historical operation data can be the water consumption data of the past year. Collect all water consumption data of the past year, including the total daily water consumption. Divide the data of the past year into two parts. The data of the first 9 months can be used as training data, and the data of the last 3 months can be used as test data. Here, linear regression can be selected as the prediction model. Input the training data into the model to let the model learn the changing trend and pattern of water consumption. After the training is completed, use the test data of the last 3 months to verify the prediction effect of the model. If the difference between the prediction result and the actual data is within an acceptable range, then this prediction model can be used to predict the rate of change of water consumption data in the future.

[0047] S102: judging, based on the water usage data change rate, whether the first water usage data currently sent by the first smart water meter meets the first preset requirement.

[0048] In one example, after predicting the water usage data change rate of the first smart water meter, it is necessary to judge whether the first water usage data currently sent by the first smart water meter meets the first preset requirement based on the water usage data change rate. By comparing the predicted water usage data change rate with the actual received data, it is possible to discover and confirm in advance whether there is a possible communication anomaly.

[0049] The specific implementation method includes setting a preset requirement first, which can be a range of the water consumption data change rate, or a certain expectation of the water consumption data change trend. For example, it can be set that if the water consumption data change rate for three consecutive days exceeds the preset range, or the change trend does not meet the expectation, then it is considered that the preset requirement is not met.

[0050] When receiving new water consumption data sent by the first smart water meter, the water consumption data change rate is calculated in real time and compared with the preset requirements. If it is found that the preset requirements are not met, then the first smart water meter may have communication anomalies.

[0051] For example, suppose our preset requirement is that the water consumption data change rate should be within the range of -10% to 10%. After receiving the new water consumption data sent by the first smart water meter, the calculated water consumption data change rate is 15%, which exceeds our preset range. Therefore, it can be judged that the water consumption data sent by the first smart water meter may not meet the preset requirements and there may be communication anomalies.

[0052] The effect of implementing this step is that possible communication anomalies can be discovered in time, so that measures can be taken in advance, such as inspecting or repairing the first smart water meter, to avoid possible losses. In this way, the normal operation of the water supply system can be ensured and the operating efficiency and reliability of the water supply system can be improved.

[0053] After determining whether the second water use data meets the second preset requirement according to the change rate of the second water use data, the method also includes: if the second water use data does not meet the second preset requirement, sending an alarm message to the terminal device of the staff, so that the staff can inspect the smart water meter that does not meet the second preset requirement and the first smart water meter.

[0054] In one example, in the above process, if the second water consumption data does not meet the second preset requirement, this may mean that the smart water meter is abnormal or there is a problem in the water supply path. In order to solve this problem, an alarm message will be sent to the terminal device of the staff, so that the staff can repair the smart water meter that does not meet the second preset requirement and the first smart water meter.

[0055] The reason for this is that the abnormality of the smart water meter may lead to inaccurate water consumption data and even affect the normal operation of water supply services. Timely detection and handling of such abnormalities can avoid greater losses and ensure the normal and continuous water supply services.

[0056] Through the management system of the smart water meter, the information of the smart water meter that does not meet the second preset requirement and the first smart water meter is sent to the terminal device of the staff in the form of alarm information. For example, if the second water consumption data of any water meter does not meet the second preset requirement, the system will automatically generate an alarm message, including the number, location, current water consumption data and change rate of the water meter, and then send it to the mobile phone or computer of the staff through SMS, email or notification function of the application.

[0057] S013: If not, obtain the second water use data sent by other smart water meters that are currently in the same water supply path as the first smart water meter, and the change rate of the second water use data of other smart water meters.

[0058] In one example, after determining that the water consumption data sent by the first smart water meter does not meet the preset requirements, that is, there may be a communication anomaly, it is necessary to further confirm whether this anomaly actually exists and its possible cause. To this end, it is necessary to obtain the second water consumption data sent by other smart water meters that are currently in the same water supply path as the first smart water meter, as well as the change rate of the second water consumption data of these other smart water meters, and other smart water meters that share the same water supply path or line with a specific smart water meter in the water supply system. The water supply path refers to the path that water flows from the water supply source (such as a water plant or a well) through the pipeline network and finally reaches the user (such as a household, commercial building or public facility). In this process, multiple smart water meters may pass through. These smart water meters may be located on the same main water supply line, or they may be located on smaller water supply lines branching off from the main water supply line.

[0059] Communication anomalies may be caused by a variety of reasons, such as water meter failure, communication equipment failure, water supply system failure, etc. By comparing the data of multiple smart water meters in the same water supply path, the nature and possible causes of the anomaly can be determined more accurately, so that more effective measures can be taken.

[0060] The specific implementation includes determining which smart water meters are in the same water supply path as the first smart water meter. This can be determined through a design diagram of the water supply system or a data management system. Then, the water consumption data and water consumption data change rate of these smart water meters are collected, which data can usually be obtained through the data management system of the water supply company.

[0061] Assume that there are three smart water meters in the same water supply path, namely, water meter A, water meter B, and water meter C; collect their water consumption data and water consumption data change rate, and find that their data change rates are within the preset range. This means that although the data of the first smart water meter is abnormal, the data of other smart water meters in the same water supply path are normal. This may indicate that the cause of the abnormality is more likely to be a problem with the first smart water meter itself, rather than a problem with the water supply system.

[0062] S104, judging whether the second water consumption data meets the second preset requirement according to the second water consumption data change rate, and if so, determining the actual water consumption data of the current first smart water meter according to the second water consumption data.

[0063] In one example, after collecting the second water consumption data and the second water consumption data change rate of other smart water meters in the same water supply path, the next step is to determine whether the second water consumption data meets the second preset requirement based on the second water consumption data change rate. If so, we can use the second water consumption data to determine the actual water consumption data of the current first smart water meter.

[0064] The reason is that if the water consumption data and change rate of other smart water meters in the same water supply path meet the preset requirements, then these data have a high degree of credibility. We can infer the actual water consumption data of the first smart water meter based on these reliable data, even if the original data of the first smart water meter may be abnormal.

[0065] The specific implementation includes first setting a second preset requirement, which may be the same as the first preset requirement or may be different, depending on the actual situation. Then, the collected second water consumption data and the second water consumption data change rate are compared with the second preset requirement.

[0066] For example, suppose our second preset requirement is that the water consumption data change rate should be within the range of -5% to 5%. We found that the water consumption data change rates of water meters A, B, and C in the same water supply path are 2%, 3%, and 4%, respectively, which are all within the preset range. Therefore, we believe that these second water consumption data meet the second preset requirement and have a high degree of credibility. Then, the actual water consumption data of the first smart water meter can be inferred based on these second water consumption data.

[0067] S105, comparing the actual water usage data with the first water usage data to determine whether there is a communication anomaly in the current first smart water meter.

[0068] In one example, after the previous steps, the second water consumption data of other smart water meters in the same water supply path are obtained, and these data are used to infer the actual water consumption data of the first smart water meter. The actual water consumption data is compared with the first water consumption data sent by the first smart water meter to determine whether there is a communication anomaly in the current first smart water meter.

[0069] By comparing the actual water consumption data with the first water consumption data, it is possible to determine whether the data of the first smart water meter is accurate, and further determine whether there is a communication anomaly. If the two data differ greatly, there is likely to be a communication anomaly, because in the absence of external interference, the reading of the smart water meter should be consistent with the actual water consumption.

[0070] The specific implementation method is that we can set a threshold value, and if the difference between the actual water consumption data and the first water consumption data exceeds the threshold value, it is considered that there is a communication anomaly in the first smart water meter. For example, the threshold value is set to 5%, and if the difference between the actual water consumption data and the first water consumption data exceeds 5%, it is considered that there is a communication anomaly.

[0071] Assume that the actual water consumption data is 100 cubic meters, and the first water consumption data sent by the first smart water meter is 105 cubic meters. The difference between the two is 5 cubic meters, or 5%, which is exactly equal to the set threshold. Therefore, it is determined that there is a communication anomaly in the first smart water meter.

[0072] The above solution can more accurately determine whether there is a communication anomaly, thereby discovering and solving the problem earlier, avoiding data errors caused by communication anomalies, and ensuring the normal operation of the water supply system and the accuracy of data. In addition, this step also provides important information for subsequent fault location and repair, which helps to improve the operation and maintenance efficiency of the water supply system.

[0073] Compare the actual water usage data with the first water usage data to determine whether there is a communication abnormality in the current first smart water meter, including: if the actual water usage data is equal to the first water usage data, determine that the communication of the current first smart water meter is normal communication; if the actual water usage data is not equal to the first water usage data, calculate the difference between the actual water usage data and the first water usage data; determine whether the difference is within a preset range, if not within the preset range, determine that there is a communication abnormality in the first smart water meter.

[0074] In one example, in the smart water meter monitoring system, when the actual water consumption data is equal to the first water consumption data, it can be determined that the current communication of the first smart water meter is normal. If the data is completely consistent, it means that the data is not disturbed during the transmission process, and there is no data loss or error, so it can be considered that the communication is normal.

[0075] However, if the actual water usage data is not equal to the first water usage data, the difference between the actual water usage data and the first water usage data needs to be calculated, and it is necessary to determine whether the difference between the two is within an acceptable range. If the difference is too large, it may indicate that there is a communication abnormality.

[0076] For example, the preset range is set to 5%. If the calculated difference exceeds this preset range, for example, the actual water consumption data is 200 cubic meters, and the first water consumption data is 210 cubic meters, the difference is 10 cubic meters, and the difference ratio relative to the actual water consumption data is 5%, which is exactly equal to the preset range. Therefore, in this case, it will be judged that there is an abnormality in the communication of the first smart water meter. The effect of this is that communication anomalies can be discovered and confirmed in a timely manner, thereby preventing data errors caused by communication anomalies and ensuring the accuracy and completeness of the data. At the same time, this can also help determine the specific location of the problem, which is of great guiding significance for subsequent fault location and repair.

[0077] Determining whether the difference is within a preset range also includes: if the difference is within the preset range, continuously obtaining the difference between the actual water usage data and the first water usage data; if the difference is within the preset range within a preset time period, sending a reminder message to the staff's terminal device to enable the staff to check or adjust the first smart water meter.

[0078] In one example, in a smart water meter monitoring system, if the calculated difference between the actual water consumption data and the first water consumption data is within a preset range, the communication is not immediately determined to be normal, but the difference between the two is continuously obtained. This is because even if the difference is within the preset range, it may be an accidental phenomenon or a short period of normal communication, and continuous monitoring is required to obtain a more accurate judgment.

[0079] The specific implementation includes setting a preset time, such as 30 minutes. During this time, the difference between the actual water consumption data and the first water consumption data is continuously obtained, and it is determined whether they are both within a preset range. If the difference is within the preset range within this preset time, a reminder message is sent to the terminal device of the staff, so that the staff can check or adjust the smart water meter.

[0080] For example, the preset range is set to 5% and the preset duration is set to 30 minutes. During these 30 minutes, the difference between the actual water consumption data and the first water consumption data is obtained every 5 minutes. If all the obtained differences are within 5%, it is considered that the communication within these 30 minutes is normal, and then a reminder message is sent to the staff's mobile phone or computer through SMS, email or application notification function.

[0081] After comparing the actual water usage data with the first water usage data to determine whether there is a communication anomaly in the current first smart water meter, it also includes: if it is determined that there is a communication anomaly in the current first smart water meter, recording and storing abnormal information, the abnormal information includes the time when the communication anomaly of the first smart water meter occurred, the water usage data of the first smart water meter, the water usage data of the second smart water meter and the actual water usage data.

[0082] In one example, in order to more accurately locate and solve the problem, when it is determined that the first smart water meter has a communication anomaly, the system automatically records and stores the anomaly information. The information includes the time when the communication anomaly occurred, the water consumption data of the first smart water meter, the water consumption data of the second smart water meter, and the actual water consumption data.

[0083] The time when the communication anomaly occurred can help understand the specific time period when the problem occurred in order to find possible causes. The water consumption data of the first smart water meter and the second smart water meter can help compare the data differences between the two devices to determine whether there is a device failure or data transmission problem. The actual water consumption data can be used as a benchmark to check and verify whether the data of the smart water meter is accurate.

[0084] The process of recording and storing this anomaly information can be accomplished through automated software tools. These tools can be configured to automatically activate when a communication anomaly is detected, collect the relevant data and store it in a database or other suitable storage device. In this way, when further analysis or troubleshooting of the communication anomaly is required, the relevant data is ready for easy query and use.

[0085] Based on the above method, the present application also discloses a smart water meter communication anomaly detection device, such as Figure 2 As shown, Figure 2 It is a structural diagram of a smart water meter communication anomaly detection device provided in an embodiment of the present application.

[0086] A smart water meter communication anomaly detection device comprises: a prediction module 1, a judgment module 2, an acquisition module 3, a determination module 4 and an output module 5; wherein the prediction module 1 is used to predict the change rate of first water use data of the first smart water meter according to the historical water use data sent by the first smart water meter; the judgment module 2 is used to judge whether the first water use data currently sent by the first smart water meter meets the first preset requirement according to the water use data change rate; the acquisition module 3 is used to obtain the second water use data sent by other smart water meters currently in the same water supply path as the first smart water meter, and the change rate of the second water use data of other smart water meters if not; the determination module 4 is used to judge whether the second water use data meets the second preset requirement according to the change rate of the second water use data, and if so, determine the actual water use data of the current first smart water meter according to the second water use data; the output module 5 is used to compare the actual water use data with the first water use data to determine whether the current first smart water meter has communication anomalies.

[0087] In one example, the above-mentioned device is also used to establish a prediction model based on the historical water consumption data sent by the first smart water meter; and predict the change rate of the first water consumption data of the first smart water meter based on the prediction model.

[0088] In one example, the above-mentioned device is also used to establish a learning model for predicting future water consumption based on training data; and optimize the learning model through test data to obtain a prediction model.

[0089] In one example, if the second water consumption data does not meet the second preset requirement, an alarm message is sent to a terminal device of a staff member so that the staff member can inspect the smart water meter that does not meet the second preset requirement and the first smart water meter.

[0090] In one example, the above-mentioned device is also used to determine that the current communication of the first smart water meter is normal communication if the actual water usage data is equal to the first water usage data; if the actual water usage data is not equal to the first water usage data, calculate the difference between the actual water usage data and the first water usage data; judge whether the difference is within a preset range, and if it is not within the preset range, determine that there is an abnormality in the communication of the first smart water meter.

[0091] In one example, if the difference is within a preset range, the difference between the actual water consumption data and the first water consumption data is continuously obtained; if the difference is within a preset range within a preset time period, the above device is also used to send a reminder message to the staff's terminal device to enable the staff to check or adjust the first smart water meter.

[0092] In one example, the above-mentioned device is also used to compare actual water usage data with the first water usage data, and after determining whether there is a communication anomaly in the current first smart water meter, it also includes: if it is determined that there is a communication anomaly in the current first smart water meter, recording and storing abnormal information, the abnormal information includes the time when the communication anomaly of the first smart water meter occurred, the water usage data of the first smart water meter, the water usage data of the second smart water meter and the actual water usage data.

[0093] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0094] See also Figure 3 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As shown, the electronic device 1000 may include: at least one processor 1001 , at least one network interface 1004 , a user interface 1003 , a memory 1005 , and at least one communication bus 1002 .

[0095] The communication bus 1002 is used to realize the connection and communication between these components.

[0096] The user interface 1003 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 1003 may also include a standard wired interface and a wireless interface.

[0097] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0098] Among them, the processor 1001 may include one or more processing cores. The processor 1001 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 1005, and calling data stored in the memory 1005. Optionally, the processor 1001 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 1001 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 1001, and it can be implemented separately through a chip.

[0099] Among them, the memory 1005 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 1005 may optionally also be at least one storage device located away from the aforementioned processor 1001. As Figure 3 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of a method for detecting abnormal communication of a smart water meter.

[0100] exist Figure 3 In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 1001 can be used to call an application program stored in the memory 1005 for a smart water meter communication anomaly detection method. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.

[0101] An electronic device readable storage medium stores instructions, which, when executed by one or more processors, enable the electronic device to execute one or more of the methods described in the above embodiments.

[0102] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0103] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0104] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0105] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0106] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0107] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0108] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for detecting abnormal communication of a smart water meter, characterized in that: The method comprises: predicting a change rate of first water usage data of the first smart water meter based on historical water usage data sent by the first smart water meter; According to the water consumption data change rate, determining whether the first water consumption data currently sent by the first smart water meter meets the first preset requirement; If not, obtaining the second water consumption data sent by other smart water meters currently in the same water supply path as the first smart water meter, and the change rate of the second water consumption data of the other smart water meters; According to the change rate of the second water use data, determine whether the second water use data meets the second preset requirement; if so, determine the actual water use data of the first smart water meter according to the second water use data; if the second water use data does not meet the second preset requirement, send an alarm message to the terminal device of the staff, so that the staff can repair the smart water meter that does not meet the second preset requirement and the first smart water meter; Comparing the actual water usage data with the first water usage data, determining whether there is currently a communication anomaly with the first smart water meter; The comparing the actual water usage data with the first water usage data to determine whether there is a communication abnormality in the current first smart water meter includes: if the actual water usage data is equal to the first water usage data, determining that the communication of the current first smart water meter is normal; If the actual water usage data is not equal to the first water usage data, calculating the difference between the actual water usage data and the first water usage data; Determining whether the difference is within a preset range, and if not, determining that there is an abnormality in the communication of the first smart water meter; If the difference is within the preset range, continuously obtaining the difference between the actual water consumption data and the first water consumption data; If the difference is within the preset range within the preset time period, a reminder message is sent to the terminal device of the staff so that the staff can check or adjust the first smart water meter.

2. A method for detecting communication anomalies of a smart water meter according to claim 1, characterized in that: The method of predicting the change rate of first water usage data of the first smart water meter based on historical water usage data sent by the first smart water meter includes: establishing a prediction model based on the historical water usage data sent by the first smart water meter; and predicting the change rate of first water usage data of the first smart water meter based on the prediction model.

3. A method for detecting abnormal communication of a smart water meter according to claim 1, characterized in that: The historical water consumption data includes training data and test data. The prediction model is established based on the historical water consumption data sent by the first smart water meter, including: establishing a learning model for predicting future water consumption based on the training data; and optimizing the learning model through the test data to obtain the prediction model.

4. A method for detecting communication anomalies of a smart water meter according to claim 1, characterized in that: After comparing the actual water usage data with the first water usage data to determine whether there is a communication anomaly in the first smart water meter, the method also includes: if it is determined that there is a communication anomaly in the first smart water meter, recording and storing abnormal information, the abnormal information includes the time when the communication anomaly of the first smart water meter occurred, the water usage data of the first smart water meter and the actual water usage data.

5. A smart water meter communication anomaly detection device, characterized in that: The device comprises: a prediction module (1), a judgment module (2), an acquisition module (3), a determination module (4) and an output module (5); wherein the prediction module (1) is used to predict the change rate of first water consumption data of the first smart water meter based on historical water consumption data sent by the first smart water meter; the judgment module (2) is used to judge whether the first water consumption data currently sent by the first smart water meter meets the first preset requirement based on the water consumption data change rate; and the acquisition module (3) is used to, if not, obtain second water consumption data sent by other smart water meters currently in the same water supply path as the first smart water meter, and the change rate of the second water consumption data of the other smart water meters; The determination module (4) is used to determine whether the second water use data meets the second preset requirement based on the change rate of the second water use data, and if so, determine the actual water use data of the current first smart water meter based on the second water use data; if the second water use data does not meet the second preset requirement, send an alarm message to the terminal device of the staff, so that the staff can repair the smart water meter that does not meet the second preset requirement and the first smart water meter; the output module (5) is used to compare the actual water use data with the first water use data to determine whether there is a communication abnormality in the current first smart water meter; the comparison of the actual water use data with the first water use data to determine whether there is a communication abnormality in the current first smart water meter includes: if the actual water use data is equal to the first water use data, determine that the communication of the current first smart water meter is normal communication; If the actual water usage data is not equal to the first water usage data, calculating the difference between the actual water usage data and the first water usage data; Determining whether the difference is within a preset range, and if not, determining that there is an abnormality in the communication of the first smart water meter; If the difference is within the preset range, continuously obtaining the difference between the actual water consumption data and the first water consumption data; If the difference is within the preset range within the preset time period, a reminder message is sent to the terminal device of the staff so that the staff can check or adjust the first smart water meter.

6. An electronic device, characterized in that: The electronic device comprises a processor (1001), a memory (1005), a user interface (1003) and a network interface (1004), wherein the memory (1005) is used to store instructions, the user interface (1003) and the network interface (1004) are used to communicate with other devices, and the processor (1001) is used to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 4.

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