Water supply control system based on internet of things water meter and management platform thereof

Abstract

The application discloses a water supply control system based on a water meter of Internet of Things and a management platform thereof, relates to the field of water supply system regulation, and comprises a water meter module of Internet of Things, a multi-sensor module, a data processing module, a transmission fusion module and a cloud device. The application improves the reliability and real-time performance of data transmission of the water meter of Internet of Things by using the transmission fusion module to perform a data shunting mechanism on the NB-IoT module and the LoRa module. The preprocessing module is used to perform noise removal, data repair and other processing on each data subset in the initial NB-IoT module. An appropriate compression algorithm is matched according to the interval of the data subset through the dynamic compression module, a transmission module is dynamically allocated to construct an allocation model for optimized transmission of multiple data subsets, the simultaneous transmission of a large number of water meter data of Internet of Things is ensured, the transmission of multiple water meters of Internet of Things is fast and synchronous, and the system can quickly and accurately judge and effectively manage fault problems.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water supply system regulation, in particular to a water supply control system based on an Internet of Things water meter and a management platform thereof. BACKGROUND

[0002] With the rapid development of the Internet of Things technology, more and more Internet of Things devices are widely deployed to realize smart city, industrial automation, agricultural monitoring and many other application scenarios. Among them, the Internet of Things water meter is an intelligent metering device that combines traditional water meters with Internet of Things technology, which receives transmitted data through a cloud control system to realize remote control.

[0003] For example, Chinese patent CN112269343A discloses an intelligent NB Internet of Things water meter control system, which includes an MCU control unit, an NB communication unit, a valve control unit, a remote server and a remote control terminal. The MCU control unit is connected with the NB communication unit and the valve control unit, wherein: the MCU control unit is used to upload the water meter detection data to the remote server through the NB communication unit; the remote control terminal is used to log in to the remote server, view the water meter detection data, and issue valve control instructions based on the water meter detection data; the NB communication unit is used to pass the valve control instructions to the MCU control unit; and the valve control unit is used to control the water meter to open and close the valve according to the valve control instructions received by the MCU control unit.

[0004] However, in some remote rural areas, mountainous areas or islands, the communication infrastructure construction is relatively lagging behind, and the network signal coverage is insufficient or the signal strength is weak. This will cause the data of the Internet of Things water meter to be unable to be transmitted to the management platform in a timely and stable manner, resulting in data loss or delay; many Internet of Things water meters are powered by batteries to facilitate installation and maintenance. However, a certain amount of power is consumed during data transmission, and in order to prolong the battery life, the existing Internet of Things water meters usually adopt a low-power communication mode. However, this mode will reduce the speed and efficiency of data transmission, resulting in delayed or untimely data transmission; these situations all seriously affect the cloud system to monitor the state of many regions and complex water supply networks and a large number of Internet of Things water meters, resulting in the inability to timely discover faults in the water supply network and the Internet of Things, and thus the inability to effectively control the problem. SUMMARY

[0005] The present application aims to provide a water supply control system based on an Internet of Things water meter and a management platform thereof to solve the problems raised in the background.

[0006] In order to achieve the above object, the present application provides the following technical scheme: the water supply control system based on the water meter of the Internet of Things, comprising a water meter module of the Internet of Things, a multi-sensor module, a data processing module, a transmission fusion module and a cloud device; the water meter module of the Internet of Things comprises a water meter main body of the Internet of Things, an NB-IoT module, a LoRa module and a signal monitoring module;

[0007] The data collected by the water meter main body of the Internet of Things and the multi-sensor module are transmitted to the transmission fusion module through at least one of the NB-IoT module and the LoRa module, wherein the data transmitted through the NB-IoT module is first processed by the data processing module and then transmitted to the transmission fusion module;

[0008] The data processing module comprises a preprocessing module, a dynamic compression module and a dynamic allocation transmission module, the preprocessing module processes the data transmitted by the NB-IoT module, the dynamic compression module compresses the data according to the interval matching of the data subsets and transmits the compressed data to the dynamic allocation transmission module through the appropriate compression algorithm, and the dynamic allocation transmission module synchronously transmits the data of multiple water meters of the Internet of Things;

[0009] The transmission fusion module comprises a fusion gateway unit and a core network fusion unit, the fusion gateway receives the data of the NB-IoT module and the LoRa module, the core network fusion unit centrally allocates and manages the two kinds of data, and transmits the data to the cloud device for unified processing and management.

[0010] Preferably, the preprocessing module performs denoising, data repair and other processing on each data subset in the initial NB-IoT module to provide standardized input for subsequent compression encoding.

[0011] Preferably, the compression algorithm in the dynamic compression module comprises Huffman encoding, LZW algorithm and Deflate algorithm, and the matching method is as follows:

[0012] S1, a distribution histogram of sample data is counted, and the data value range is self-defined divided according to the cumulative distribution function;

[0013] S2, for different interval data subsets, the information entropy is calculated, and the appropriate compression encoding mode is matched;

[0014] S3, a first threshold and a second threshold are set, wherein the first threshold is less than the second threshold, the data subset with the information entropy lower than the first threshold is encoded by Huffman encoding, the data subset between the first threshold and the second threshold is encoded by LZW algorithm, and the data subset with the entropy value higher than the second threshold is directly encoded by Deflate algorithm.

[0015] Preferably, the dynamic allocation transmission module constructs an allocation model for optimizing the transmission of multiple data subsets.

[0016] A typical NB-IoT module uplink transmission scenario, the system uses a single carrier frequency with bandwidth B, a scheduling period contains t time slots, each time slot contains m resource blocks, the system provides data transmission service for n Internet of Things water meters with NB-IoT module, the data arrival rate of Internet of Things water meter i is λ i , the amount of data to be transmitted in the allocation period is L i , let be the scheduling variable, indicating whether to allocate m resource blocks to Internet of Things water meter i in time slot t, and define as the transmission rate of Internet of Things water meter i in time slot t, formula 1 can be obtained by Shannon formula:

[0017]

[0018] Wherein, B is the bandwidth, unit hertz; is the interference of device i on m resource blocks; n0 is the power spectral density of Gaussian white noise; is the channel gain; is the transmission power of Internet of Things water meter i, while optimizing the objective of maximizing system throughput, considering the transmission delay and fairness of each Internet of Things water meter, therefore, the following multi-objective optimization model is constructed, as formula 2:

[0019]

[0020] Formula 3:

[0021]

[0022] Wherein, j represents another Internet of Things water meter, R i represents the average transmission rate of Internet of Things water meter i, R j represents the average transmission rate of Internet of Things water meter j, formula 2 is mainly used to maximize the system throughput; Formula 3 reflects the transmission fairness of the system, and the two formulas are used for multi-Internet of Things water meter to transmit multiple data synchronously.

[0023] Preferably, the fusion gateway unit integrates the network access functions of both the NB-IoT module and the LoRa module, analyzes and converts data of different protocols, and encapsulates them into a format suitable for transmission to the core network.

[0024] Preferably, the core network fusion unit fuses the network functions of the NB-IoT module and the LoRa module, and centrally allocates and manages the resources of the two networks.

[0025] The management platform of the water supply control system based on the Internet of Things water meter comprises a real-time monitoring module, a scheduling management module, a device management module, a user management module, a report statistical module, a prediction module and a mobile application module.

[0026] Preferably, the real-time monitoring module is used for checking the running state of each link of the water supply system, and when an abnormal condition occurs in the system, an alarm is immediately sent out, the abnormal position is automatically located, and the abnormal related information is displayed.

[0027] The device management module is used for managing various devices in the water supply system and performing life cycle maintenance management.

[0028] The user management module is used for managing water user information and statistically analyzing the water use condition of the users.

[0029] The mobile application module is used for real-time checking of the running state of the water supply system by the management personnel, receiving the alarm information sent out by the system and performing remote control operation.

[0030] Preferably, the report statistical module generates various types of reports according to requirements and supports export and printing.

[0031] The prediction module is connected with the device management module and the user management module, and a user water model, a pipe network leakage model and a water quality change model are established by using a random forest algorithm according to historical data of the devices and historical data of the users.

[0032] The scheduling management module is connected with the real-time monitoring module and the prediction module, and a water supply scheduling scheme is formulated by establishing a dynamic programming model according to the real-time collected data and the water use demand prediction.

[0033] Compared with the prior art, the control system has the following beneficial effects:

[0034] 1. In the control system, data transmission is performed through the self-adaptive switching mechanism of the NB-IoT module and the LoRa module, the data shunting mechanism in the transmission fusion module is used to improve the reliability and real-time performance of the data transmission of the Internet of Things water meter, the preprocessing module is used to perform noise removal and data repair on each data subset in the initial NB-IoT module, the dynamic compression module is used to match the interval of the data subset with a suitable compression algorithm to reduce the size of the transmission data, the dynamic allocation transmission module is used to construct a distribution model for optimized transmission of multiple data subsets, the time delay of data transmission is reduced, and the simultaneous transmission of a large number of Internet of Things water meter data is ensured to be fast and synchronous, thereby improving the fast and accurate judgment and effective management of the system on fault problems.

[0035] 2, The management platform realizes real-time collection and transmission of water supply data, management personnel can understand the running state of the water supply system through cloud devices or mobile APP at any time, discover and handle problems in time, through analysis of real-time data and water demand prediction, water supply scheduling is more scientific and reasonable. According to the actual water consumption, the water supply strategy can be adjusted in time to avoid the occurrence of insufficient water supply or high water pressure, improve the reliability and stability of water supply, and at the same time, the management platform accumulates a large amount of historical data, which provides a scientific basis for the decision of water supply enterprises through analysis and mining of these data BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 The flowchart of the water supply control system based on the water meter of the Internet of Things of the present application is shown in the figure.

[0037] Figure 2 The flowchart of the management platform of the water supply control system based on the water meter of the Internet of Things of the present application is shown in the figure. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0039] Embodiment one: refer to Figure 1 The water supply control system based on the water meter of the Internet of Things, including the water meter module of the Internet of Things, the multi-sensor module, the data processing module, the transmission fusion module and the cloud device.

[0040] The water meter module of the Internet of Things includes the main body of the water meter of the Internet of Things, the NB-IoT module (narrowband Internet of Things), the LoRa module (long-range radio) and the signal monitoring module.

[0041] The IoT water meter module is based on the IoT water meter main body, which is the core equipment for water supply data collection, using advanced ultrasonic or electromagnetic measurement technology. The ultrasonic water meter uses the principle that the propagation speed of ultrasonic waves in water is affected by the flow velocity. By accurately measuring the time difference of ultrasonic wave propagation in the forward and reverse directions, the flow velocity and flow rate are calculated, and then the user's water consumption is obtained. This measurement method has the advantages of high precision, no mechanical wear, and small pressure loss, which can ensure long-term stable and accurate measurement of water consumption. The electromagnetic water meter is based on Faraday's law of electromagnetic induction. When the conductive water flows in the magnetic field, it will generate an induced electromotive force proportional to the flow rate. By detecting the electromotive force, the water flow is measured. It has the characteristics of wide measurement range, good linearity and high stability, and can adapt to various complex water environments.

[0042] The NB-IoT module operates in the licensed frequency band, with low power consumption, wide coverage, low cost, and mass connectivity. It can realize long-distance communication under low bandwidth conditions, which is very suitable for IoT water meters that need to transmit small amounts of data stably for a long time. The LoRa module works in the unlicensed frequency band and has the characteristics of long distance, low power consumption and low cost, especially suitable for IoT water meter data transmission in remote or rural areas with poor network coverage. At the same time, the IoT water meter also has a low-power design, using high-efficiency energy-saving chips and circuits, combined with intelligent sleep and wake-up mechanisms, effectively extending the service life of the battery, reducing the frequency of battery replacement, and reducing maintenance costs.

[0043] The multi-sensor module includes pressure sensors, water level sensors, and water quality sensors:

[0044] The pressure sensor is distributed at key node positions in the water supply network, and can monitor the water pressure in the network in real time. By detecting the change of pressure, it can timely find the abnormal pressure in the network, such as high pressure that may cause pipe rupture, and low pressure that may affect normal water use.

[0045] The water level sensor is installed in water sources such as reservoirs and water tanks to accurately monitor the water level. This is of great significance to water supply enterprises in terms of rational scheduling of water sources and ensuring the continuity of water supply.

[0046] The water quality sensor is used to detect various key indicators of water quality, including pH value, turbidity, residual chlorine, heavy metal content, etc. These sensors can collect water quality data in real time, providing strong support for ensuring water quality safety.

[0047] These sensors are equipped with corresponding communication interfaces, which can transmit the collected data to the IoT water meter module through wired transmission;

[0048] The signal monitoring module monitors parameters such as signal strength and signal-to-noise ratio in real time to determine the quality of the current network environment. When the signal quality of the NB-IoT module is poor and the communication conditions of the LoRa module are met, the system automatically switches to the LoRa module (LoRa transmission is primary, and NB-IoT transmission is secondary); otherwise, when the NB-IoT network returns to a good state, the system switches back to the NB-IoT module (NB-IoT transmission is primary, and LoRa transmission is secondary). This adaptive switching mechanism ensures that the terminal device is always in the best communication state, improving the reliability and stability of data transmission.

[0049] The data processing module includes a preprocessing module, a dynamic compression module, and a dynamic allocation transmission module.

[0050] The preprocessing module performs denoising, data repair, and other processing on each data subset in the initial NB-IoT module to provide standardized input for subsequent compression encoding. The Kalman filter algorithm is used for adaptive denoising of data subsets, which can significantly improve data quality. The denoised data subsets are subjected to missing value interpolation and outlier removal processing to obtain complete and clean data subsets.

[0051] Traditional general compression algorithms include Huffman encoding, LZW algorithm, and Deflate algorithm. Due to the limitation of compression performance due to the non-stationary characteristics of data distribution, the dynamic compression module matches the appropriate compression algorithm according to the interval matching of the data subset, as follows:

[0052] First, the distribution histogram of the sample data is calculated, and the data value range is divided according to the cumulative distribution function; then, for different interval data subsets, the information entropy is calculated, and the appropriate compression encoding method is matched; finally, the first threshold and the second threshold are set, where the first threshold is less than the second threshold, the data subset with information entropy less than the first threshold is encoded using Huffman encoding, the data subset between the first threshold and the second threshold is encoded using LZW algorithm, and the data subset with entropy value higher than the second threshold is directly encoded using Deflate algorithm.

[0053] Considering the data transmission requirements of the Internet of Things water meter module, the dynamic allocation transmission module constructs a distribution model for the optimized transmission of multiple data subsets.

[0054] In a typical NB-IoT module uplink transmission scenario, the system uses a single carrier frequency with a bandwidth of B, and a scheduling period contains t time slots, each time slot contains m resource blocks. The system provides data transmission services for n Internet of Things water meters with NB-IoT modules, and the data arrival rate of Internet of Things water meter i is λ i , the amount of data to be transmitted in the allocation period is L i , and is a scheduling variable, indicating whether m resource blocks are allocated to the IoT water meter i at time slot t. is the transmission rate of the IoT water meter i at time slot t, and formula 1 can be obtained from the Shannon formula:

[0055]

[0056] where B is the bandwidth, in hertz; is the interference of device i on m resource blocks; n0 is the Gaussian white noise power spectral density; is the channel gain; is the transmission power of the IoT water meter i. While optimizing the objective of maximizing system throughput, the transmission delay and fairness of each IoT water meter are also considered, so the following multi-objective optimization model is constructed, as shown in formula 2:

[0057]

[0058] Formula 3:

[0059]

[0060] where j represents another IoT water meter, R i represents the average transmission rate of the IoT water meter i, R j represents the average transmission rate of the IoT water meter j, and the main function of formula 2 is to maximize the system throughput. Through a series of specific parameter settings and calculation logic, this formula can promote the system to achieve the highest possible throughput in data transmission and other aspects to meet the system's demand for data processing capacity.

[0061] At the same time, formula 3 assumes the important responsibility of embodying the transmission fairness of the system. It uses the network minimum potential energy model, which outputs a corresponding value by comprehensively considering the resource allocation of each part of the system. This value has a special significance, that is, the smaller the value, the more balanced the resources obtained by each part of the system in the resource allocation process, and each IoT water meter can more fairly obtain resources in the transmission process. The failure between the water supply network and the IoT water meter often does not occur independently, and the network near a certain failure point and multiple IoTs will have problems. If a certain IoT water meter transmits faster, while a certain IoT water meter transmits slower, it will affect the system's rapid and accurate judgment, so this model avoids the situation where the transmission network is excessively concentrated on some IoT water meters, leading to the transmission scarcity of other IoT water meters, thereby ensuring the fairness and stability of the entire system transmission.

[0062] The transmission fusion module includes a fusion gateway unit and a core network fusion unit.

[0063] The fusion gateway unit is the key hub for connecting the Internet of Things water meter module to the cloud device. It integrates the network access functions of NB-IoT modules and LoRa modules, and can receive data from both modules simultaneously. In terms of data processing, the fusion gateway unit analyzes and converts data of different protocols, and encapsulates them into a format suitable for transmission to the core network. At the same time, it is responsible for managing the access, authentication and authorization of Internet of Things water meters.

[0064] During data transmission, different data of the Internet of Things water meter are allocated to the NB-IoT module and LoRa module network for transmission according to the type and urgency of the data. For example, critical data such as control instructions of the Internet of Things water meter are transmitted quickly through the NB-IoT module network to ensure real-time performance; while a large amount of historical data or non-critical monitoring data are transmitted through the LoRa module network to save cost and bandwidth. In different network environments, the proportion of data allocated to the NB-IoT module and LoRa module is different.

[0065] In the core network fusion unit, the network functions of NB-IoT modules and LoRa modules are fused. By establishing a unified network management platform, centralized deployment and management of two kinds of network resources are realized. For example, in terms of traffic management, according to the priority and real-time demand of business, the bandwidth resources of NB-IoT module and LoRa module network are reasonably allocated to ensure the smooth operation of important business.

[0066] The fusion gateway receives two kinds of data of NB-IoT module and LoRa module, and after centralized deployment and management of the two kinds of data by the core network fusion unit, it is transmitted to the cloud device.

[0067] In this embodiment, the Internet of Things water meter calculates the water flow speed and flow, combines the multi-sensor module to measure the water pressure, water level and water quality indicators in the water supply pipe network, and transmits data through the NB-IoT module and the LoRa module adaptive switching mechanism. Through the data shunting mechanism in the transmission fusion module, the reliability and real-time performance of the Internet of Things water meter data transmission are improved. At the same time, the resources of the two technologies are reasonably utilized, the power consumption and cost of the system are reduced, the overall performance is improved, the advantages of NB-IoT operator network coverage and LoRa long-distance communication are combined, and comprehensive coverage of various complex environments such as cities, remote areas, indoor environments can be achieved, ensuring that the Internet of Things water meter can operate stably in any location. Among them, the NB-IoT module has the advantages of long-term stable transmission, and the preprocessing module is used to denoise and data repair the initial NB-IoT module data subsets. After the dynamic compression module matches the appropriate compression algorithm according to the interval of the data subset, the size of the transmission data is reduced, the dynamic allocation transmission module constructs a multi-data subset optimized transmission allocation model, and the data transmission delay is reduced. For the simultaneous transmission of a large number of Internet of Things water meter data, multiple Internet of Things water meters are ensured to transmit quickly and synchronously, and the system's rapid and accurate judgment and effective management of fault problems are improved.

[0068] Embodiment two: according to Figure 2 As shown in the figure: the management platform of the water supply control system based on the Internet of Things water meter includes a real-time monitoring module, a scheduling management module, a device management module, a user management module, a report statistical module, a prediction module and a mobile application module.

[0069] The real-time monitoring module is an important display window of the water supply management platform. Management personnel can use this module to view the running status of each link of the water supply system in real time and comprehensively. The monitoring content covers the real-time changes of the water level of the water source, the production situation of the water plant, including the treatment process of raw water, the production progress of clean water, the distribution of pipe network pressure, whether the water quality indicators meet the standards, and the real-time readings of user Internet of Things water meters, etc. The monitoring interface adopts intuitive graphical design, and displays data in various forms such as maps, charts and instrument panels. Through the pipe network map, the pipe network pressure distribution of each region can be seen intuitively, and the regions with abnormal pressure will be marked with prominent colors; the trend of water level change with time can be clearly shown by using the line chart; the key indicator values of water quality can be displayed in real time through the instrument panel.

[0070] When abnormal situations occur in the system, such as low water pressure in the pipe network, water quality exceeding standards, water meter failure, etc., the real-time monitoring module will immediately issue an alarm. The alarm methods include sound prompts, pop-up reminders, SMS notifications, and other forms to ensure that management personnel can promptly detect the situation. At the same time, the system will automatically locate the abnormal position and display detailed information related to the abnormality, such as the type of abnormality, the time of occurrence, possible causes, etc. Management personnel can quickly respond to these information and take appropriate measures to handle the situation, such as adjusting the operating parameters of the water pump, starting the emergency plan, arranging maintenance personnel for repair, etc., to ensure the normal operation of the water supply system.

[0071] The dispatch management module formulates a scientific and reasonable water supply dispatching plan based on real-time data collection and accurate water demand prediction, combined with factors such as water source level, pipe network pressure, and user water consumption. This dynamic programming model takes into account the physical characteristics of the water supply system, user water consumption patterns, equipment operating parameters, and other factors, allowing accurate simulation of the water supply system's operation under different conditions. By establishing a pipe network hydraulic model, it accurately calculates water flow velocity, pressure distribution, and other parameters in different pipe sections, providing a basis for reasonable allocation of water supply flow; using a user water demand prediction model, it predicts user water consumption in different time periods and regions to adjust water supply strategies in advance.

[0072] The water supply dispatching plan covers key parameters such as the start and stop time of the water pump, the operating frequency, and the opening and closing state of the valve. During peak water consumption periods, based on the predicted increase in water consumption, the dispatch management module will start standby water pumps in advance, increase the operating frequency of the water pump, and increase the water supply flow to ensure that user water demand is met; during low water consumption periods, the number and frequency of water pump operation are appropriately reduced to reduce energy consumption and achieve energy-saving operation. At the same time, through remote control technology, management personnel can remotely control the operation of water supply equipment through the management platform and adjust water supply strategies in a timely manner. When the pipe network pressure in a certain area is found to be too high or too low, management personnel can remotely adjust the opening of related valves to optimize the hydraulic distribution of the pipe network and ensure the stability of water supply.

[0073] The equipment management module is responsible for comprehensive and detailed management of various equipment in the water supply system, including Internet of Things water meters, pressure sensors, water level sensors, water quality sensors, water pumps, valves, etc. This module records detailed information about the equipment, such as equipment model, manufacturer, installation location, purchase time, equipment number, etc., and establishes an independent equipment file for each piece of equipment. The equipment file not only contains basic information about the equipment, but also records technical parameters, maintenance records, fault repair records, and operation state monitoring data.

[0074] Through the device management module, the device can be maintained and managed throughout its life cycle. First, according to the type of device, the use environment, the running time and other factors, set a reasonable device maintenance period and detailed maintenance plan. When the device needs maintenance, the system will automatically send a reminder to notify the maintenance personnel to carry out the corresponding maintenance work. After the maintenance personnel complete the maintenance work, they need to record the specific content of the maintenance, the replaced parts, the maintenance time and other information in the device management module. When the device fails, the system can quickly locate the faulty device according to the information in the device file and real-time monitoring data, and analyze the possible causes of the failure through the fault diagnosis algorithm, and provide corresponding repair suggestions. For example, when the Internet of Things water meter appears data anomaly, the system can analyze its communication log, measurement data trend, etc. to determine whether it is a communication module failure, a measurement component failure or other causes, and provide targeted repair solutions.

[0075] The user management module realizes the all-round and fine management of water supply users. The management of user information covers the input, modification and query operations of basic information such as user name, address, contact information, water meter number, water use nature (such as residential water, commercial water, industrial water, etc.). Through in-depth statistics and analysis of user water use, such as statistics of monthly water use, quarterly water use, annual water use, analysis of user water use peak and valley periods, and water use change law in different seasons, etc., personalized water use suggestions and services can be provided for users. For example, for commercial users with large water use, water saving modification suggestions can be provided; for residential users, reasonable water use time arrangement suggestions can be provided according to their water use habits to help users save water.

[0076] At the same time, the user management module is deeply connected with banks, third-party payment platforms, etc. to support users to conveniently query water bill and make online payment through the management platform or mobile APP. Users only need to bind their water meter information and payment method on the platform to query the current water fee balance, arrears, etc. at any time, and complete the payment of water fee through various payment channels such as bank card payment, WeChat payment, Alipay payment, etc. After successful payment, the payment information will be updated to the user management module in real time, which is convenient for users to check the payment record at any time, and also provides convenience for the financial management of water supply enterprises.

[0077] The report statistics module generates various types of reports according to the diverse needs of users, including daily reports, weekly reports, monthly reports, annual reports, etc. The report content is comprehensive and covers the operation data of the water supply system, such as the total water consumption per day, week, month, and year, the water consumption distribution of each region, the water pressure change in different time periods, the statistical analysis of water quality monitoring data, etc.; equipment management data, such as the running time of equipment, maintenance frequency, failure rate, etc.; user water consumption data, such as the ranking of water consumption of each user, water consumption growth trend, etc.

[0078] The report statistics module supports the export and printing functions of the report. The exported report format can be Excel, PDF, etc. common format, which is convenient for managers to further analyze and archive data. Through in-depth analysis of report data, it can help water supply enterprises understand the operation trend and law of the water supply system, find potential problems and optimization space. By analyzing water consumption data in different time periods, it can reasonably arrange water supply scheduling plan and optimize energy allocation; by analyzing the operation data of equipment, it can timely find potential equipment failure hazards and maintain in advance to reduce equipment failure rate; by analyzing user water consumption data, it can develop more reasonable water fee policy and promote water saving.

[0079] The prediction module uses random forest algorithm to establish user water consumption model, pipe network leakage model and water quality change model through in-depth analysis of a large amount of historical data. The user water consumption model analyzes historical water consumption data, water consumption habits, life rules, seasonal factors, weather changes and other multi-dimensional data of users to mine the potential rules and patterns of user water consumption and predict future water consumption. By analyzing the rules that the water consumption of residential users in summer is usually higher than that in winter, the water consumption of commercial users in weekends and holidays changes significantly, etc., the user's water demand can be more accurately predicted to provide scientific basis for water supply scheduling.

[0080] The pipe network leakage model can accurately identify the leakage points in the pipe network and predict the degree and development trend of leakage by real-time monitoring and analysis of pipe network pressure, flow, flow rate and other data, combining with the topological structure of pipe network, pipe material characteristics and other information, and using random forest algorithm to establish the model. For example, when the pressure in the pipe network abnormally decreases and the flow abnormally fluctuates, the model can analyze and judge the possible location of leakage and predict the expansion speed of leakage according to the data trend, so as to arrange maintenance personnel to repair in time and reduce the waste of water resources and economic loss.

[0081] The water quality change model predicts the change of water quality according to the real-time water quality monitoring data collected by water quality sensors, as well as the water quality characteristics of the water source, water treatment process, seasonal changes and other factors. For example, in the summer high temperature season, the reproduction of algae may cause changes in some indicators of water quality. Through the water quality change model, this change trend can be predicted in advance, and the water supply enterprise can adjust the water treatment process in advance to ensure the safety of water supply. By continuously optimizing and updating these models, they can better adapt to the dynamic changes of the water supply system and improve the accuracy and reliability of the prediction.

[0082] In order to facilitate the operation and inquiry of management personnel and users at any time and anywhere, the water supply management platform develops a powerful mobile application module, namely the mobile phone APP. For management personnel, through the APP, the running state of the water supply system can be viewed in real time, the alarm information sent by the system can be received, and remote control operation can be performed in the first time. For example, when the management personnel receives an alarm of abnormal pipe network pressure during an outing, detailed abnormal information can be immediately viewed through the APP, and the running parameters of relevant water pumps or valves can be remotely adjusted to solve the problem in time and ensure the normal operation of the water supply system.

[0083] For users, through the mobile phone APP, the water consumption situation can be conveniently inquired, including real-time water consumption, historical water consumption, water consumption details, etc.; water bill can be viewed at any time to understand the arrears and make online payment; if a water consumption equipment failure or other problem is found, the APP can be used to make a failure repair, fill in the repair information and upload relevant photos or videos, so that the water supply enterprise can understand the situation in time and arrange maintenance personnel to handle it. The APP interface is designed simply and conveniently, and the humanized interaction design is easy for users to use. At the same time, the APP supports the push function, and the water supply enterprise can push the information such as water stop notice, water quality announcement, water saving propaganda, etc. to the users to strengthen the communication and interaction with the users and improve the satisfaction and participation of the users.

[0084] Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments or make equivalent replacements for part of the technical features, and any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A water supply control system based on an Internet of Things water meter, characterized by, It comprises an Internet of Things water meter module, a multi-sensor module, a data processing module, a transmission fusion module and a cloud device; the Internet of Things water meter module comprises an Internet of Things water meter main body, an NB-IoT module, a LoRa module and a signal monitoring module; The data collected by the Internet of Things water meter main body and the multi-sensor module is transmitted to the transmission fusion module through at least one of the NB-IoT module and the LoRa module, wherein the data transmitted through the NB-IoT module is first processed by the data processing module and then transmitted to the transmission fusion module; The data processing module comprises a preprocessing module, a dynamic compression module and a dynamic allocation transmission module; the preprocessing module processes the data transmitted by the NB-IoT module, and the processed data is compressed by the dynamic compression module according to an appropriate compression algorithm matched with the interval of the data subset and then transmitted to the dynamic allocation transmission module for synchronous transmission of multiple Internet of Things water meter data; The compression algorithm in the dynamic compression module comprises Huffman coding, LZW algorithm and Deflate algorithm, and the matching method is as follows: S1, a distribution histogram of sample data is counted, and the data value range is self-defined according to the cumulative distribution function; S2, for different interval data subsets, an appropriate compression coding mode is matched by calculating the information entropy thereof; S3, a first threshold and a second threshold are set, wherein the first threshold is smaller than the second threshold; Huffman coding is adopted for the data subset whose information entropy is lower than the first threshold; LZW algorithm is adopted for the data subset between the first threshold and the second threshold; and Deflate algorithm is directly adopted for the data subset whose entropy value is higher than the second threshold; The dynamic allocation transmission module constructs an allocation model for optimized transmission of multiple data subsets; A typical NB-IoT module uplink transmission scenario, the system uses a single carrier frequency with bandwidth B, a scheduling period contains t time slots, each time slot contains m resource blocks, the system provides data transmission service for n Internet of Things water meters with NB-IoT module, the data arrival rate of Internet of Things water meter i is λ i , the amount of data to be transmitted in the allocation period is L i , let be a scheduling variable, indicating whether to allocate m resource blocks to Internet of Things water meter i in time slot t, and let be the transmission rate of Internet of Things water meter i in time slot t, formula 1 can be obtained by Shannon formula: Wherein, B is bandwidth, unit hertz; is the interference of device i on m resource blocks; n0is the Gaussian white noise power spectral density; is the channel gain; is the transmission power of the Internet of Things water meter i, while optimizing the objective of maximizing the system throughput, the transmission delay and fairness of each Internet of Things water meter are taken into account, therefore, the following multi-objective optimization model is constructed, as shown in formula 2: Formula 3: where j represents another water meter of the Internet of Things, R i represents the average transmission rate of the water meter i of the Internet of Things, R j represents the average transmission rate of the water meter j of the Internet of Things, the main function of formula 2 is to realize the maximization of the system throughput; formula 3 embodies the transmission fairness of the system, and the two formulas are used for multi-data synchronous transmission of multiple water meters of the Internet of Things; The transmission fusion module comprises a fusion gateway unit and a core network fusion unit; the fusion gateway receives the data of the NB-IoT module and the LoRa module, centrally deploys and manages the two kinds of data through the core network fusion unit, and transmits the data to the cloud device for unified processing and management.

2. The water supply control system based on the internet of things water meter according to claim 1, characterized in that: The preprocessing module performs denoising and data repair on each data subset in the initial NB-IoT module, thereby providing standardized input for subsequent compression coding.

3. The water supply control system based on the internet of things water meter according to claim 1, characterized in that: The fusion gateway unit integrates the network access functions of the NB-IoT module and the LoRa module, analyzes and converts data of different protocols, and uniformly encapsulates the data into a format suitable for transmission to the core network.

4. The water supply control system based on the internet of things water meter according to claim 1, characterized in that: The core network fusion unit fuses the network functions of the NB-IoT module and the LoRa module, and centrally deploys and manages the two kinds of network resources.

5. A management platform of a water supply control system based on an Internet of Things water meter, characterized by, The water supply control system based on the Internet of Things water meter of any one of claims 1-4 comprises a real-time monitoring module, a scheduling management module, a device management module, a user management module, a report statistical module, a prediction module and a mobile application module.

6. The management platform of the water supply control system based on the Internet of Things water meter according to claim 5, characterized in that: The real-time monitoring module is used for checking the running state of each link of the water supply system, and when an abnormal condition occurs in the system, an alarm is immediately sent out, the abnormal position is automatically located, and abnormal related information is displayed; The device management module is used for managing various devices in the water supply system and performing whole life cycle maintenance management; The user management module is used for managing water supply user information, and performing statistics and analysis on user water consumption; The mobile application module is used for management personnel to check the running state of the water supply system in real time, receive alarm information sent by the system, and perform remote control operation.

7. The management platform of the Internet of Things water meter-based water supply control system according to claim 6, characterized in that: The report statistics module generates various types of reports according to requirements, supports export and printing; The prediction module is connected with the device management module and the user management module, and establishes a user water consumption model, a pipe network leakage model and a water quality change model by using a random forest algorithm according to historical data of the devices and historical data of the users; The dispatching management module is connected with the real-time monitoring module and the prediction module, and formulates a water supply dispatching scheme by establishing a dynamic programming model according to real-time collected data and water consumption demand prediction.

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