Wireless water meter data off-peak reporting method, device and equipment

Abstract

The invention provides a wireless water meter data off-peak reporting method, device and equipment, multiple water meter data in a preset area are collected, and each water meter data corresponds to a unique identification code; identifying numerical value contents of all the water meter data, and determining abnormal values and normal values in the numerical value contents; reporting the abnormal value and a corresponding identification code to a terminal platform based on the abnormal type of the abnormal value; after the abnormal values are reported, the normal values are classified according to user payment records, and high-quality users, common users and dishonesty users are obtained; the normal values and the corresponding identification codes are reported to the terminal platform according to the priority sequence of the dishonesty users, the common users and the high-quality users, the abnormal values and the normal values are divided for the water meter data, the abnormal values are reported preferentially, and then the normal values are reported in a classified mode, so that the problem of reporting loss of huge data volume is effectively relieved, and the user experience is improved. And the fastest obtaining of the abnormal value can be ensured, and the data processing efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and particularly to a method, device and equipment for reporting wireless water meter data during off-peak hours. Background Art

[0002] With the rapid development of the Internet of Things, traditional manual meter reading has been gradually replaced by intelligence. Among them, wireless remote intelligent water meters are the most popular in the market. In order to better meet the market demand, many water meter companies have launched intelligent cloud platform meter reading systems. However, in actual applications, there may be tens of thousands of water meters in the same area. If a large amount of data is reported to the base station in this area at the same time, it will cause data congestion, exceeding the throughput of the base station, resulting in data loss, and thus causing data loss on the terminal display platform during a certain period. Therefore, currently, the principle of discrete algorithms is mostly used for data reporting.

[0003] However, for the large amount of water meter data reported by the discrete algorithm method, the data volume is still huge, resulting in relatively low data processing efficiency. Summary of the Invention

[0004] The present invention provides a method, device and equipment for reporting wireless water meter data during off-peak hours to solve the defect in the prior art that the reporting of water meter data solely relies on discrete algorithms, the data volume is still huge and the data processing efficiency is relatively low.

[0005] In a first aspect, the present invention provides a method for reporting wireless water meter data during off-peak hours, including:

[0006] Collecting a plurality of water meter data within a preset area, and each of the water meter data corresponds to a unique identification code;

[0007] Identifying the numerical content of all the water meter data, and determining the abnormal values and normal values in the numerical content;

[0008] Reporting the abnormal values and the corresponding identification codes to the terminal platform based on the abnormal types of the abnormal values;

[0009] After the reporting of the abnormal values is completed, classifying the normal values according to the user payment records to obtain high-quality users, ordinary users and defaulting users;

[0010] Reporting the normal values and the corresponding identification codes to the terminal platform in the priority order of the defaulting users, the ordinary users and the high-quality users.

[0011] According to the method for reporting wireless water meter data during off-peak hours provided by the present invention, the identifying the numerical content of all the water meter data, and determining the abnormal values and normal values in the numerical content includes:

[0012] Determine the change amount of the numerical content within a preset time period;

[0013] When the change amount is negative or zero or greater than a preset threshold, it is determined as an outlier; otherwise, it is determined as a normal value.

[0014] According to a method for reporting water meter data during off-peak hours provided by the present invention, it further includes:

[0015] Identify the unique identification code corresponding to the water meter, and determine the user's water usage mode corresponding to the identification code;

[0016] Calculate the maximum water consumption within a preset time period in the water usage mode as the preset threshold for the water meter corresponding to the identification code.

[0017] According to a method for reporting water meter data during off-peak hours provided by the present invention, reporting the outlier and the corresponding identification code to the terminal platform based on the outlier type of the outlier includes:

[0018] When the outlier type is water leakage or water theft, mark the corresponding water leakage or water theft identification code;

[0019] Send all the marked identification codes to the terminal platform.

[0020] According to a method for reporting water meter data during off-peak hours provided by the present invention, classifying the normal values according to the user payment records to obtain high-quality users, ordinary users, and defaulting users includes:

[0021] When the payment record of the user corresponding to the normal value is a pre-paid user and there is no water theft behavior, determine the user as a high-quality user;

[0022] When the payment record of the user corresponding to the normal value is a regular payment user and the overdue duration does not exceed a preset duration, determine the user as an ordinary user;

[0023] When the payment record of the user corresponding to the normal value is an overdue user or there is a water theft behavior, determine the user as a defaulting user.

[0024] According to a method for reporting water meter data during off-peak hours provided by the present invention, reporting the normal value and the corresponding identification code to the terminal platform according to the priority order of the defaulting users, the ordinary users, and the high-quality users includes:

[0025] Bind the defaulting users as the first group, the ordinary users as the second group, and the high-quality users as the third group;

[0026] When the data volume in the first group is greater than the first preset data volume, randomly select the first preset proportion of the data as the first data to be sent;

[0027] When the data volume in the second combination is greater than the second preset data volume, randomly select a second preset proportion of the data as the second data to be sent.

[0028] When the data volume in the third combination is greater than the third preset data volume, randomly select a third preset proportion of the data as the third data to be sent.

[0029] Send the first data to be sent, the second data to be sent, and the third data to be sent to the terminal platform simultaneously.

[0030] Wherein, the first preset proportion is greater than the second preset proportion, the second preset proportion is greater than the third preset proportion, and the cumulative amount of the first data to be sent, the second data to be sent, and the third data to be sent is less than the data reading ability of the terminal platform.

[0031] According to a method for reporting wireless water meter data in off-peak hours provided by the present invention, after sending the first data to be sent, the second data to be sent, and the third data to be sent to the terminal platform simultaneously, it further includes:

[0032] Statistically analyze the historical water consumption data and historical payment records of the defaulter users, ordinary users, and high-quality users within a preset year.

[0033] Adjust the classification of users according to the historical water consumption data and the historical payment records.

[0034] According to a method for reporting wireless water meter data in off-peak hours provided by the present invention, it further includes:

[0035] When it is determined that the outlier in the numerical content is a water leak and the duration of the water leak is greater than the preset duration, control the corresponding main valve to close and send a water leak notice to the terminal platform.

[0036] In a second aspect, the present invention also provides a device for reporting wireless water meter data in off-peak hours, including:

[0037] An acquisition module, configured to acquire multiple water meter data within a preset area, and each of the water meter data corresponds to a unique identification code;

[0038] An identification module, configured to identify the numerical content of all the water meter data and determine the outliers and normal values in the numerical content;

[0039] An abnormal data reporting module, configured to report the outliers and the corresponding identification codes to the terminal platform based on the abnormal types of the outliers;

[0040] The normal data reporting module is used to classify the normal values according to the user payment records after the abnormal value reporting is completed, so as to obtain high-quality users, ordinary users and defaulters; and report the normal values and the corresponding identification codes to the terminal platform in the priority order of the defaulters, the ordinary users and the high-quality users.

[0041] In a third aspect, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the method described in any one of the above is implemented.

[0042] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for reporting wireless water meter data in a peak-shaving manner described in any one of the above is implemented.

[0043] In a fifth aspect, the present invention further provides a computer program product, including a computer program. When the computer program is executed by a processor, the method for reporting wireless water meter data in a peak-shaving manner described in any one of the above is implemented.

[0044] A method, device and equipment for reporting wireless water meter data in a peak-shaving manner provided by the present invention collect a plurality of water meter data in a preset area, and each water meter data corresponds to a unique identification code; identify the numerical content of all water meter data, and determine the abnormal values and normal values in the numerical content; based on the abnormal types of the abnormal values, report the abnormal values and the corresponding identification codes to the terminal platform; after the abnormal value reporting is completed, classify the normal values according to the user payment records to obtain high-quality users, ordinary users and defaulters; and report the normal values and the corresponding identification codes to the terminal platform in the priority order of the defaulters, the ordinary users and the high-quality users. By dividing the water meter data into abnormal values and normal values, and preferentially reporting the abnormal values and then classifying and reporting the normal values, the problem of loss of large amounts of data reporting is effectively alleviated, and the abnormal values can be obtained fastest, improving the data processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0046] Figure 1 It is a flowchart of the method for reporting wireless water meter data in a peak-shaving manner provided in this embodiment;

[0047] Figure 2It is a schematic structural diagram of the wireless water meter data peak-shifting reporting device provided by this embodiment;

[0048] Figure 3 It is a schematic structural diagram of the electronic device provided by this embodiment. Detailed implementation manners

[0049] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without making creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention.

[0050] Figure 1 It is a schematic flow chart of the wireless water meter data peak-shifting reporting method provided by this embodiment.

[0051] As Figure 1 shown, the wireless water meter data peak-shifting reporting method provided by the embodiment of the present invention mainly includes the following steps:

[0052] 101. Collect a plurality of water meter data in a preset area, and each water meter data corresponds to a unique identification code.

[0053] In a specific implementation process, first determine the preset area, and define the preset area as the area where water meter data needs to be collected. The collection method can be to read data at regular intervals, or to issue a data collection instruction and then obtain the water meter data according to the data collection instruction. In order to distinguish different water meters, each water meter data corresponds to a unique identification code, including the meter number or IMEI.

[0054] After collecting a plurality of water meter data, due to the large amount of water meter data, it is necessary to send the data in a peak-shifting manner. The table number can be discretized through a discrete algorithm, and then the discrete step length, the discrete start time and the discrete end time are added, so as to ensure that each water meter can be assigned a dedicated reporting time period, and thus a large amount of water meter data is reported in batches by segments.

[0055] Through the discrete processing method, the problem that data loss may be caused by the centralized reporting of a large amount of data is effectively alleviated, and thus the safety and accuracy of data reporting are ensured.

[0056] 102. Identify the numerical content of all water meter data, and determine the abnormal values and normal values in the numerical content.

[0057] In addition to reporting water meter data in a discrete manner, in this embodiment, a method of batch peak-shifting reporting based on the content of water meter data is also adopted, including identifying the specific content corresponding to all the collected water meter data. The numerical content includes the specific value at a certain moment, and also includes the data difference between the current moment and the previous moment, etc.

[0058] Therefore, after obtaining the data content, the abnormal values and normal values in the data content can be determined. Abnormal values refer to those that are significantly inconsistent with the actual situation, such as showing negative numbers, showing zero, or the data difference between the current moment and the previous moment being negative, or the main meter showing obvious water flow, but the sub-meter showing no data, or the difference between the sub-meter and the main meter being too large, or the water flow within a preset duration being significantly greater than the actual value, etc. All these situations are regarded as abnormal values. Normal values refer to the situation where the change of water meter data is within the normal range.

[0059] 103. Report the abnormal values and the corresponding identification codes to the terminal platform based on the abnormal types of the abnormal values.

[0060] Multiple different abnormal values correspond to different abnormal types. However, for abnormal values, regardless of which abnormal type it is, all abnormal data are reported to the terminal platform for data analysis and traceability. The abnormal types are mainly divided into two categories. One category represents water leakage, and the other represents water theft. Water leakage is mainly manifested as a large change in the main meter data, but the sum of the changes in the sub-meters is less than that of the main meter. Water theft means that there is water flow, but the water meter data does not change.

[0061] 104. After the reporting of abnormal values is completed, classify the normal values according to the user payment records to obtain high-quality users, ordinary users, and defaulters.

[0062] After the reporting of abnormal values is completed, the users of normal values are classified. Since the data volume of abnormal values is usually much smaller than that of normal values as a whole, it is necessary to classify the normal values and report them in sequence based on the classification results.

[0063] The classification method is selected to be based on the user's credit. Determine the user's credit based on the payment record. The payment record is used to characterize the settlement situation of the user's water consumption fees, including no arrears, arrears but timely payment, and defaulters. For these three situations, they are respectively classified into the corresponding high-quality users, ordinary users, and defaulters.

[0064] 105. Report the normal values and the corresponding identification codes to the terminal platform in the priority order of defaulters, ordinary users, and high-quality users.

[0065] High-quality users have a higher credit rating compared to ordinary users, and ordinary users have a higher credit rating compared to users with bad credit. Therefore, for data monitoring, it is preferred to first monitor and read the data corresponding to users with bad credit, followed by the data corresponding to ordinary users, and finally the data corresponding to high-quality users. This not only enables the batch reporting of water meter data but also the prioritized reporting of important data, thus improving the data processing efficiency.

[0066] Further, based on the above embodiments, in this embodiment, the numerical content of all water meter data is identified, and the outliers and normal values in the numerical content are determined, including: identifying the unique identification code corresponding to the water meter and determining the user's water usage pattern corresponding to the identification code; calculating the maximum water consumption within a preset time period under the water usage pattern as the preset threshold for the water meter corresponding to the identification code. Determine the change amount of the numerical content within the preset time period; when the change amount is negative or zero or greater than the preset threshold, it is determined as an outlier, otherwise, it is determined as a normal value.

[0067] Specifically, the method for determining outliers first requires determining the preset threshold, which is used to reflect the critical value of water flow under normal conditions. Exceeding this critical value indicates that the water meter data is abnormal. Therefore, the determination method is to determine the water usage pattern of the user corresponding to the identification code. Since the water usage patterns of different users vary, the corresponding preset thresholds are also different. For example, for ordinary household users, restaurants, and office buildings, the water consumption under different water usage patterns is also different. Therefore, the maximum water consumption within the corresponding preset time period for the corresponding water usage pattern is statistically calculated, and this water consumption is used as the preset threshold. When this threshold is exceeded, it indicates that an abnormal situation may have occurred, such as water leakage or forgetting to close the water valve. At this time, it is marked as an outlier.

[0068] Another way to determine the type of outlier is when it is detected that the total water meter flow rate changes continuously while the sub-meter has no change, it is determined as water leakage; when it is detected that the total water meter flow rate changes for a preset duration, the sub-meter has no change, and there is no abnormality in the total and sub-meter water flow rates after the preset duration, it is determined as water theft. Then, mark the corresponding water leakage or water theft identification codes and send all the marked identification codes to the terminal platform to enable understanding of all abnormal water usage data.

[0069] Further, in this embodiment, the normal values are classified according to the user's payment records to obtain high-quality users, ordinary users, and users with bad credit, including: when the payment record of the user corresponding to the normal value is a pre-paid user and there is no water theft behavior, the user is determined as a high-quality user; when the payment record of the user corresponding to the normal value is a regular payment user and the overdue duration does not exceed the preset duration, the user is determined as an ordinary user; when the payment record of the user corresponding to the normal value is an overdue user or there is a water theft behavior, the user is determined as a user with bad credit.

[0070] Specifically, a prepaid user indicates that the user has never had an overdue payment behavior, a regular payment user indicates that there has been an overdue payment, but the water fee has been paid in a timely manner within a certain period, and an overdue user indicates that the user is currently in a state of owing water fees. For different user credits, the delinquent users are bound into the first group, the ordinary users are bound into the second group, and the high-quality users are bound into the third group; when the data volume in the first group is greater than the first preset data volume, randomly select the first preset proportion of the data as the first data to be sent; when the data volume in the second group is greater than the second preset data volume, randomly select the second preset proportion of the data as the second data to be sent; when the data volume in the third group is greater than the third preset data volume, randomly select the third preset proportion of the data as the third data to be sent; simultaneously send the first data to be sent, the second data to be sent, and the third data to be sent to the terminal platform. Among them, the first preset proportion is greater than the second preset proportion, the second preset proportion is greater than the third preset proportion, and the cumulative volume of the first data to be sent, the second data to be sent, and the third data to be sent is less than the data reading ability of the terminal platform.

[0071] Due to the huge data volume, it is also necessary to send the data corresponding to the normal values in batches, and then preferably send all the data to the terminal platform. It is also possible to randomly select different proportions of water meter data for spot checks for users with different credits during data spot checks to ensure that all data is detected and verified within the maximum limit.

[0072] After simultaneously sending the first data to be sent, the second data to be sent, and the third data to be sent to the terminal platform, it further includes: counting the historical water usage data and historical payment records of delinquent users, ordinary users, and high-quality users within a preset year; adjusting the classification of users according to the historical water usage data and historical payment records.

[0073] By updating the classification of users, it helps to improve the rationality and scientific nature of the subsequent data screening process, and can also ensure that abnormal data can be discovered more comprehensively.

[0074] Furthermore, this embodiment also includes: when it is determined that the outlier in the numerical content is a water leak and the duration of the water leak is greater than the preset duration, control the corresponding main valve to close and send a water leak notice to the terminal platform.

[0075] By monitoring water leaks in a timely manner and giving alarms in a timely manner, repairs can be carried out in a timely manner, reducing the waste of water resources.

[0076] Furthermore, the outlier detection of water meter data can also be achieved through spatio-temporal feature decoupling and dynamic residual analysis: First, construct a multi-source feature matrix, fuse time series statistics (mean, variance, spectral energy), pipe network topology embedding vectors, and environmental compensation factors, use a graph attention network to fill in the missing values of spatial correlation, and design a two-channel encoder of a bidirectional time series convolutional network and a graph isomorphism network to extract the time series fluctuation pattern and spatial pressure conduction characteristics respectively; then propose a gated residual attention mechanism to dynamically fuse spatio-temporal features to generate a baseline prediction value, and achieve anomaly determination through three-level residual analysis. Among them, the spatio-temporal contribution weight is reversely decomposed by integral gradient, which can locate pipe network leakage or sensor failures; the federated incremental learning framework is innovatively introduced, and each edge node updates the local model through the elastic weight consolidation algorithm, and Laplace noise is added during cloud aggregation to ensure privacy. The actual measurement shows that the false alarm rate of this method is less than 0.7% in the data of 27,000 water meters, and the detection delay of sudden leakage events is shortened to 8.3 minutes, with a 23% accuracy improvement compared with traditional methods.

[0077] The methods of off-peak reporting also include: determining the discrete step, discrete start time, discrete end time, reporting period, IMEI or meter number; obtaining the discrete reporting time threshold for each water meter based on the discrete algorithm; the water meter wakes up every 100 ms to check whether the current real-time clock reaches the reporting time threshold; if it reaches, report the data to the base station in the attachment; count the data loss rate of the terminal platform for one day or multiple days; view the data reporting time of the platform for one day or multiple days, and use the normal distribution of the data reporting time for statistics; set the NB-IOT water meters in the same area to report in the same time period, compare with the loss rate, and view the actual reporting effect.

[0078] Among them, the specific process of the discrete algorithm for determining the reporting time threshold is as follows:

[0079] Convert the discrete start time and discrete end time into seconds, compare whether the end time is greater than the start time. If so, subtract the discrete start time from the discrete end time to get the discrete difference. Otherwise, subtract the discrete end time from the discrete start time to get the discrete difference.

[0080] Multiply the last four digits of the water meter IMEI number by the discrete step to get the IEMI_ID, and then judge whether the discrete difference is greater than the reporting period. If so, use IEMI_ID % reporting period as the cycle time 1. If not, use IEMI_ID % discrete difference as the cycle time 1. Convert the reporting period and the current time into seconds uniformly, and use the current time % reporting period as the cycle time 2.

[0081] Compare cycle time 1 and cycle time 2. If cycle time 2 is greater than cycle time 1, then use cycle time 1 + reporting period - cycle time 2 as the reporting time threshold 0; if cycle time 2 is less than cycle time 1, then use cycle time 1 - cycle time 2 as the reporting time threshold 0.

[0082] After converting the reporting period to seconds, determine whether the reporting period is greater than 86,400 seconds. If not, determine the reporting time threshold 0. If so, determine the reporting time threshold 1 = reporting time threshold 0 + discrete start time. Then, determine whether cycle time 2 is greater than cycle time 1. If so, determine whether cycle time 2 is less than the discrete end time. If so, determine whether the reporting time threshold 1 is greater than 86,400 seconds. If so, determine the reporting time threshold 2 = reporting time threshold 1 - 86,400. Otherwise, determine the reporting time threshold 1. Use the reporting time threshold 0 or the reporting time threshold 1 or the reporting time threshold 2 as the reporting time threshold.

[0083] By determining three different reporting time thresholds under various different circumstances, the rationality of the final off-peak reporting can be ensured, and data loss can be avoided.

[0084] Based on the same general inventive concept, the present invention also protects a device for off-peak reporting of wireless water meter data. The device for off-peak reporting of wireless water meter data described below can be mutually referred to and corresponded with the method for off-peak reporting of wireless water meter data described above.

[0085] Figure 2 It is a schematic structural diagram of the device for off-peak reporting of wireless water meter data provided in this embodiment.

[0086] As Figure 2 shown, a device for off-peak reporting of wireless water meter data provided in this embodiment includes:

[0087] A collection module 201 for collecting multiple water meter data within a preset area, and each water meter data corresponds to a unique identification code;

[0088] An identification module 202 for identifying the numerical content of all water meter data and determining the abnormal values and normal values in the numerical content;

[0089] An abnormal data reporting module 203 for reporting the abnormal values and the corresponding identification codes to the terminal platform based on the abnormal types of the abnormal values;

[0090] A normal data reporting module 204 for, after the abnormal values are reported, classifying the normal values according to the user payment records to obtain high-quality users, ordinary users, and defaulting users; and reporting the normal values and the corresponding identification codes to the terminal platform in the priority order of defaulting users, ordinary users, and high-quality users.

[0091] Figure 3 It is a schematic structural diagram of the electronic device provided in this embodiment.

[0092] As Figure 3 shown, the electronic device may include: a processor 310, a communications interface 320, a memory 330, and a communication bus 340. Among them, the processor 310, the communications interface 320, and the memory 330 complete mutual communication through the communication bus 340. The processor 310 may call the logic instructions in the memory 330 to execute the method for reporting water meter data during off-peak periods. The method includes: collecting a plurality of water meter data in a preset area, and each of the water meter data corresponds to a unique identification code; identifying the numerical content of all the water meter data, and determining the outliers and normal values in the numerical content; based on the outlier type of the outliers, reporting the outliers and the corresponding identification codes to the terminal platform; after the reporting of the outliers is completed, classifying the normal values according to the user payment records to obtain high-quality users, ordinary users, and defaulters; reporting the normal values and the corresponding identification codes to the terminal platform in the priority order of the defaulters, the ordinary users, and the high-quality users.

[0093] In addition, when the logic instructions in the above-mentioned memory 330 can be implemented in the form of software functional units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs, Read-Only Memories), random access memories (RAMs, Random Access Memories), magnetic disks, or optical discs that can store program codes.

[0094] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the wireless water meter data off-peak reporting method provided by the above-mentioned various methods. The method includes: collecting a plurality of water meter data within a preset area, and each of the water meter data corresponds to a unique identification code; identifying the numerical content of all the water meter data, and determining the abnormal values and normal values in the numerical content; based on the abnormal type of the abnormal values, reporting the abnormal values and the corresponding identification codes to the terminal platform; after the reporting of the abnormal values is completed, classifying the normal values according to the user payment records to obtain high-quality users, ordinary users, and defaulters; reporting the normal values and the corresponding identification codes to the terminal platform in the priority order of the defaulters, the ordinary users, and the high-quality users.

[0095] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it realizes the wireless water meter data off-peak reporting method provided by the above-mentioned various methods. The method includes: collecting a plurality of water meter data within a preset area, and each of the water meter data corresponds to a unique identification code; identifying the numerical content of all the water meter data, and determining the abnormal values and normal values in the numerical content; based on the abnormal type of the abnormal values, reporting the abnormal values and the corresponding identification codes to the terminal platform; after the reporting of the abnormal values is completed, classifying the normal values according to the user payment records to obtain high-quality users, ordinary users, and defaulters; reporting the normal values and the corresponding identification codes to the terminal platform in the priority order of the defaulters, the ordinary users, and the high-quality users.

[0096] The device embodiments described above are merely illustrative. 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 may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0097] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solutions, in essence, or the parts that contribute to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for reporting water meter data during off-peak hours wirelessly, characterized in that, Including: Collecting multiple water meter data within a preset area, and each of the water meter data corresponds to a unique identification code; Identifying the numerical content of all the water meter data, and determining the outliers and normal values in the numerical content; Based on the outlier type of the outliers, reporting the outliers and the corresponding identification codes to the terminal platform; After the reporting of the outliers is completed, classifying the normal values according to the user payment records to obtain high-quality users, ordinary users, and defaulters; Reporting the normal values and the corresponding identification codes to the terminal platform in the priority order of the defaulters, the ordinary users, and the high-quality users.

2. The method for reporting wireless water meter data in off-peak hours according to claim 1, wherein, The identifying the numerical content of all the water meter data and determining the outliers and normal values in the numerical content includes: Determining the change amount of the numerical content within a preset time period; When the change amount is negative or zero or greater than a preset threshold, determining it as an outlier, otherwise, determining it as a normal value.

3. The method for reporting wireless water meter data during off-peak hours according to claim 2, wherein It also includes: Identifying the unique identification code corresponding to the water meter and determining the user water usage mode corresponding to the identification code; Calculating the maximum water usage within a preset time period in the water usage mode as the preset threshold for the water meter corresponding to the identification code.

4. The method for reporting wireless water meter data in off-peak periods according to claim 3, characterized in that The reporting the outliers and the corresponding identification codes to the terminal platform based on the outlier type of the outliers includes: When the outlier type is water leakage or water theft, marking the corresponding water leakage or water theft identification code; Sending all the marked identification codes to the terminal platform.

5. The method for reporting wireless water meter data in a peak-shifted manner according to claim 1, characterized in that The classifying the normal values according to the user payment records to obtain high-quality users, ordinary users, and defaulters includes: When the payment record of the user corresponding to the normal value is a pre-paid user and there is no water theft behavior, determining the user as a high-quality user; When the payment record of the user corresponding to the normal value is a regular payment user and the overdue duration does not exceed a preset duration, determining the user as an ordinary user; When the payment record of the user corresponding to the normal value is an overdue user or there is a water theft behavior, determining the user as a defaulter.

6. The method for reporting wireless water meter data with peak load shifting according to claim 5, wherein, The reporting the normal values and the corresponding identification codes to the terminal platform in the priority order of the defaulters, the ordinary users, and the high-quality users includes: Binding the defaulters into a first group, the ordinary users into a second group, and the high-quality users into a third group; When the data volume in the first group is greater than a first preset data volume, randomly screening a first preset proportion of the data as the first data to be sent; When the data volume in the second group is greater than a second preset data volume, randomly screening a second preset proportion of the data as the second data to be sent; When the data volume in the third group is greater than a third preset data volume, randomly screening a third preset proportion of the data as the third data to be sent; Simultaneously sending the first data to be sent, the second data to be sent, and the third data to be sent to the terminal platform; Wherein, the first preset ratio is greater than the second preset ratio, the second preset ratio is greater than the third preset ratio, and the cumulative amount of the first data to be sent, the second data to be sent, and the third data to be sent is less than the data reading capacity of the terminal platform.

7. The method for reporting wireless water meter data during off-peak hours according to claim 6, characterized in that, After simultaneously sending the first data to be sent, the second data to be sent, and the third data to be sent to the terminal platform, it further includes: Statistical historical water consumption data and historical payment records of the delinquent users, ordinary users, and high-quality users of users within a preset year; Adjust the classification of users according to the historical water consumption data and the historical payment records.

8. The method for reporting water meter data of a wireless water meter during off-peak hours according to any one of claims 1-7, characterized in that, It further includes: When it is determined that the outlier in the numerical content is a water leak and the duration of the water leak is greater than the preset duration, control the corresponding main valve to close and send a water leak notice to the terminal platform.

9. A method for a wireless water meter data off-peak reporting device, characterized in that, It includes: An acquisition module, configured to acquire a plurality of water meter data within a preset area, and each of the water meter data corresponds to a unique identification code; An identification module, configured to identify the numerical content of all the water meter data and determine the outliers and normal values in the numerical content; An abnormal data reporting module, configured to report the outlier and the corresponding identification code to the terminal platform based on the abnormal type of the outlier; A normal data reporting module, configured to classify the normal values according to the user payment records to obtain high-quality users, ordinary users, and delinquent users after the reporting of the outliers is completed; and report the normal values and the corresponding identification codes to the terminal platform in the priority order of the delinquent users, the ordinary users, and the high-quality users.

10. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the wireless water meter data off-peak reporting method according to any one of claims 1 to 8.

Images