A smart water meter remote maintenance method, device and Internet of Things system

Abstract

The present invention relates to the technical field of remote maintenance of water meters, and specifically to a remote maintenance method and device for smart water meters and an Internet of Things system thereof, comprising the following steps: S1. data acquisition and caching, which includes real-time acquisition of water meter data and caching the acquired data to a storage device to prevent data loss; S2. data transmission, which includes transmitting the cached data to an Internet of Things terminal via a network, and supports one of NB‑IoT, LoRa or 4G / 5G networks; the present invention can acquire water meter data in real time to promptly discover and handle abnormal situations, thereby reducing the number of manual meter readings and on-site maintenance, and reducing labor costs; remote maintenance can quickly respond to and solve problems; automated data acquisition and transmission reduce manual errors; and through data analysis, faults can be predicted and prevented in advance, thereby reducing the occurrence of sudden faults without the need for on-site operations.

Description

Technical Field

[0001] The present invention relates to the technical field of water meter remote maintenance, and in particular to a smart water meter remote maintenance method, device and Internet of Things system thereof. Background Art

[0002] A water meter is an instrument for measuring water flow. It is usually installed on water supply pipes in homes, businesses or public facilities to record the amount of water used. Traditional water meters mainly rely on mechanical counting to record water flow, while smart water meters are water meters based on advanced sensing technology and information and communication technology. They can automatically record and transmit water use data and realize remote monitoring and management. The development of smart water meters has gone through mechanical water meters, electronic water meters to smart water meters.

[0003] Generally, the maintenance method of smart water meters is to monitor the operating status of water meters in real time through the background system, remotely upgrade the firmware of water meters through wireless networks, and then regularly dispatch maintenance personnel to conduct on-site inspections to ensure that the sensors and communication modules of water meters are working properly. Therefore, the complex wireless communication environment often leads to low signal coverage and poor transmission stability. Since data is transmitted through wireless networks, how to ensure data security and privacy is also an important problem. In addition, traditional manual meter reading requires manual on-site meter reading regularly, which is inefficient and prone to errors. Fault detection relies on user reports or regular inspections, which has large delays. Water use data collection lags and cannot be monitored and managed in real time. Therefore, for the maintenance of smart water meters, on-site maintenance methods are backward, time-consuming and labor-intensive.

[0004] In summary, it is necessary to propose a smart water meter remote maintenance method, device and Internet of Things system to solve the above problems. Summary of the invention

[0005] The object of the present invention is to provide a smart water meter remote maintenance method, device and Internet of Things system thereof to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A smart water meter remote maintenance method, which is implemented based on a smart water meter remote maintenance device and an Internet of Things system, comprises the following steps:

[0008] S1. Data collection and caching: real-time collection of water meter data and caching of the collected data to a storage device to prevent data loss;

[0009] S2. Data transmission: transmit the cached data to the IoT terminal through the network, supporting one of NB-IoT, LoRa or 4G / 5G networks;

[0010] S3. Remote control and configuration, remote switch control and remote configuration update of water meters, including modification of working parameters including acquisition frequency and operation strategy, and real-time monitoring of the operating status of water meter equipment;

[0011] S4. Abnormal detection and alarm: analyze water consumption and detect abnormal changes; detect water quality to ensure water supply safety; when abnormal conditions are detected, upload alarm information to the IoT terminal and send alarm notifications to management personnel;

[0012] S5. User interactive services, providing users with a way to query water consumption and bill information; sending water reminders and bill notifications to users, providing channels for user feedback and problem solving;

[0013] S6. Data analysis and report generation: conduct multi-dimensional analysis of the collected data, provide water consumption trends and forecast information, generate various statistical reports, and store the data in the cloud for a long time;

[0014] S7. Security permission management, manage user permissions based on role-based access control, encrypt data to ensure data security, record and audit system operation logs, and conduct real-time monitoring and retrospective analysis.

[0015] Based on the above method, the present invention also proposes a smart water meter remote maintenance device, which includes a data acquisition and transmission module, a remote control management module, an abnormality detection and alarm module, a user interactive service module, a data analysis and reporting module, and a security authority management module. The data acquisition and transmission module is used for water meter data acquisition, caching and transmission, the remote control management module is used for remote switch control, remote configuration and equipment status monitoring, the abnormality detection and alarm module is used for abnormal water use detection, water quality monitoring and alarm notification, the user interactive service module is used for user query, user notification and customer service support, the data analysis and reporting module is used for data analysis, report generation and data storage, and the security authority management module is used for user authority management, data encryption and security auditing.

[0016] Preferably, the data acquisition and transmission module further includes a water meter data acquisition unit, a data cache unit and a data transmission unit;

[0017] The water meter data collection unit uses sensors and metering chips to ensure data accuracy and is used to collect water meter readings and basic water consumption data in real time;

[0018] The data cache unit uses a built-in memory or an external storage device to temporarily store the collected data to prevent data loss;

[0019] The data transmission unit is used for integrating wireless communication and supports multiple communication protocols.

[0020] Preferably, the data transmission unit transmits data to the Internet of Things terminal via one of NB-IoT, LoRa, and 4G / 5G networks.

[0021] Preferably, the remote control management module further includes a remote switch control unit, a remote configuration unit and a device status monitoring unit;

[0022] The remote switch control unit uses an electric valve and a remote control protocol to allow the water meter to be remotely switched on and off to control the water supply;

[0023] The remote configuration unit performs remote configuration updates through OTA technology, and is used to remotely modify the working parameters of the water meter, including the collection frequency and the valve operation strategy;

[0024] The device status monitoring unit integrates a status monitoring sensor and a reporting mechanism, and is used to monitor the operating status of the water meter device in real time, including battery power and communication status.

[0025] Preferably, the abnormal detection alarm module further includes an abnormal water use detection unit, a water quality monitoring unit and an alarm notification unit;

[0026] The abnormal water use detection unit performs analysis based on historical data and real-time data and uses a machine learning algorithm to detect abnormal changes in water use, including water leakage or illegal water use;

[0027] The water quality monitoring unit is integrated with a water quality sensor, and the detection parameters include turbidity and pH value, which are used to detect changes in water quality and ensure water supply safety;

[0028] The alarm notification unit supports SMS, email, and App notification methods, and is used to upload alarm information to the IoT terminal when an abnormal situation is detected, and send alarm notifications to management personnel at the same time.

[0029] Preferably, the user interactive service module further includes a user query unit, a user notification unit and a customer service support unit;

[0030] The user query unit develops a user-friendly mobile phone app or web page interface to allow users to query water consumption and bill information;

[0031] The user notification unit integrates a message push service for sending water use reminders and bill notification information to users;

[0032] The customer service support unit integrates an online customer service system and a hotline service to provide a channel for user feedback and problem solving.

[0033] Preferably, the data analysis report module further includes a data analysis unit, a report generation unit and a data storage unit;

[0034] The data analysis unit uses big data analysis technology and supports multi-dimensional analysis to analyze the collected data and provide water use trend and forecast information;

[0035] The report generation unit integrates a report generation tool, supports multiple formats of output, and is used to generate various statistical reports, including monthly water use reports and abnormal water use reports;

[0036] The data storage unit uses a cloud storage service to ensure data security and reliability and is used to store historical data for a long time for subsequent analysis and reference.

[0037] Preferably, the security authority management module further includes a user authority management unit, a data encryption unit and a security audit unit;

[0038] The user authority management unit sets different authority levels based on role-based access control to manage the authority of different users and ensure the security of the device and the Internet of Things;

[0039] The data encryption unit adopts the advanced encryption standard encryption algorithm to encrypt the transmitted and stored data to prevent data leakage;

[0040] The security audit unit integrates log management and audit systems, supports real-time monitoring and backtracking analysis, and is used to record and audit system operation logs and track security events.

[0041] Based on the above method and device, the present invention also proposes an Internet of Things system, including a smart water meter remote maintenance device, an Internet of Things, and an Internet of Things terminal linked to the Internet of Things.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention realizes remote switch control and remote configuration so that the operator can remotely control the water meter, including switching the water source and adjusting the water meter parameters, without on-site operation, which greatly improves the management efficiency and flexibility; through the machine learning algorithm to analyze historical and real-time data, it can accurately detect water leakage or illegal water use behavior, and issue alarm notifications in time, which is helpful to quickly respond and reduce water resource losses; integrated sensors detect water quality parameters, such as turbidity and pH value, to ensure the safety of water supply and prevent the potential impact of water quality problems on user health; convenient query and notification services are provided through mobile phone App or web page interface, so that users can understand water consumption and bill information in real time; big data analysis technology is used to perform multi-dimensional analysis on the collected data, generate water consumption trends and forecast information, and provide managers with scientific decision-making basis; the present invention also supports the output of various statistical reports in multiple formats, such as monthly water use reports and abnormal water use reports, to help managers fully understand the operation status of water meters and problem discovery; role-based access control and advanced encryption standard encryption algorithm ensure the secure management of user permissions and the transmission and storage security of data, and effectively prevent data leakage and unauthorized access. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A flow chart of a remote maintenance method for a smart water meter according to the present invention;

[0044] Figure 2 This is a module diagram of a smart water meter remote maintenance device of the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Example 1

[0047] See also Figure 1 ,The present invention proposes a remote maintenance device for a smart water meter, which includes a data acquisition and transmission module, a remote control management module, an abnormality detection and alarm module, a user interactive service module, a data analysis and reporting module, and a security authority management module;

[0048] Among them, it should be noted that the data acquisition and transmission module is used for water meter data acquisition, caching and transmission, the remote control management module is used for remote switch control, remote configuration and equipment status monitoring, the abnormal detection and alarm module is used for abnormal water use detection, water quality monitoring and alarm notification, the user interactive service module is used for user query, user notification and customer service support, the data analysis and reporting module is used for data analysis, report generation and data storage, and the security authority management module is used for user authority management, data encryption and security auditing.

[0049] In this embodiment, it should also be noted that the data acquisition and transmission module also includes a water meter data acquisition unit, a data cache unit and a data transmission unit. The water meter data acquisition unit uses sensors and metering chips to ensure data accuracy and is used to collect water meter readings and basic water consumption data in real time. The data cache unit uses a built-in memory or an external storage device to temporarily store the collected data to prevent data loss. The data transmission unit is used to integrate wireless communication and support multiple communication protocols. The data transmission unit transmits data to the Internet of Things terminal via one of the NB-IoT, LoRa, and 4G / 5G networks.

[0050] In this embodiment, it should also be noted that the remote control management module also includes a remote switch control unit, a remote configuration unit and an equipment status monitoring unit. The remote switch control unit uses an electric valve and a remote control protocol to allow remote switching of the water meter and control of the water supply. The remote configuration unit performs remote configuration updates through OTA technology and is used to remotely modify the working parameters of the water meter, including the collection frequency and valve operation strategy. The equipment status monitoring unit integrates status monitoring sensors and reporting mechanisms for real-time monitoring of the operating status of the water meter equipment, including battery power and communication status.

[0051] In this embodiment, it should also be noted that the abnormal detection alarm module also includes an abnormal water use detection unit, a water quality monitoring unit and an alarm notification unit. The abnormal water use detection unit performs analysis based on historical data and real-time data, and adopts a machine learning algorithm to detect abnormal changes in water consumption, including water leakage or illegal water use. The water quality monitoring unit integrates a water quality sensor, and the detection parameters include turbidity and pH value, which are used to detect changes in water quality and ensure water supply safety. The alarm notification unit supports SMS, email, and App notification methods, and is used to upload alarm information to the Internet of Things terminal when an abnormal situation is detected, and send alarm notifications to management personnel at the same time.

[0052] In this embodiment, it should also be noted that the user interactive service module also includes a user query unit, a user notification unit and a customer service support unit. The user query unit develops a user-friendly mobile phone App or web interface to allow users to query water consumption and bill information. The user notification unit integrates a message push service to send water use reminders and bill notification information to users. The customer service support unit integrates an online customer service system and hotline service to provide channels for user feedback and problem solving.

[0053] In this embodiment, it should also be noted that the data analysis report module also includes a data analysis unit, a report generation unit and a data storage unit. The data analysis unit adopts big data analysis technology and supports multi-dimensional analysis. It is used to analyze the collected data and provide water use trends and forecast information. The report generation unit integrates a report generation tool and supports output in multiple formats. It is used to generate various statistical reports, including monthly water use reports and abnormal water use reports. The data storage unit uses cloud storage services to ensure data security and reliability, and is used to store historical data for a long time for subsequent analysis and reference.

[0054] In this embodiment, it should also be noted that the security authority management module also includes a user authority management unit, a data encryption unit and a security audit unit. The user authority management unit is based on role-based access control and sets different authority levels to manage the permissions of different users and ensure the security of the device and the Internet of Things. The data encryption unit adopts the Advanced Encryption Standard encryption algorithm to encrypt the transmitted and stored data to prevent data leakage. The security audit unit integrates the log management and audit system, supports real-time monitoring and backtracking analysis, and is used to record and audit system operation logs and track security incidents.

[0055] Example 2

[0056] See also Figure 2 , a remote maintenance method based on the above-mentioned smart water meter remote maintenance device, which is implemented based on the Internet of Things system, includes the following steps:

[0057] S1. Data collection and caching: real-time collection of water meter data and caching of the collected data to a storage device to prevent data loss;

[0058] S2. Data transmission: transmit the cached data to the IoT terminal through the network, supporting one of NB-IoT, LoRa or 4G / 5G networks;

[0059] S3. Remote control and configuration, remote switch control and remote configuration update of water meters, including modification of working parameters including acquisition frequency and operation strategy, and real-time monitoring of the operating status of water meter equipment;

[0060] S4. Abnormal detection and alarm: analyze water consumption and detect abnormal changes; detect water quality to ensure water supply safety; when abnormal conditions are detected, upload alarm information to the IoT terminal and send alarm notifications to management personnel;

[0061] S5. User interactive services, providing users with a way to query water consumption and bill information; sending water reminders and bill notifications to users, providing channels for user feedback and problem solving;

[0062] S6. Data analysis and report generation: conduct multi-dimensional analysis of the collected data, provide water consumption trends and forecast information, generate various statistical reports, and store the data in the cloud for a long time;

[0063] S7. Security permission management, manage user permissions based on role-based access control, encrypt data to ensure data security, record and audit system operation logs, and conduct real-time monitoring and retrospective analysis.

[0064] Example 3

[0065] See also Figure 1 to Figure 2 In the actual application scenario of remote maintenance of smart water meters, the remote maintenance method of smart water meters specifically includes the following steps:

[0066] S1: Data collection and caching

[0067] Select sensor: Choose high-precision water meter sensors, including ultrasonic water meters or electromagnetic water meters, to ensure data accuracy;

[0068] Install sensors: Install water meter sensors at key points in the water pipe system to ensure real-time collection of water consumption data;

[0069] Data reading: Regularly read water flow data through RS485 or M-Bus interface sensor interface;

[0070] Data calibration: Use linear regression algorithm to calibrate the collected data to eliminate sensor errors;

[0071] The collected data is calibrated using a linear regression algorithm, specifically, the following steps are included:

[0072] Get the original data set of the sensor, including the measured values ​​and the corresponding true values, divide the data set into input features (X) and output labels (Y), use the linear regression algorithm to train the model, get the calibration coefficient, and apply the calibration coefficient to the new measured data for calibration, see formula (1):

[0073] Y = \beta_0 + \beta_1 X + \epsilon (1);

[0074] Where (Y) is the true value, (X) is the sensor measurement, (\beta_0) is the deviation, (\beta_1) is the proportionality coefficient, and (\epsilon) is the error term;

[0075] Data formatting: Format the collected data into JSON or XML format for easy subsequent processing;

[0076] Data compression: Use GZIP to compress data to reduce transmission and storage space;

[0077] Data cache: store data in SD card or local server to prevent data loss;

[0078] Data synchronization: Set up a scheduled task to regularly synchronize cache data to the main server;

[0079] S2: Data Transmission

[0080] Network selection: Select the appropriate transmission network according to the actual environment, including NB-IoT, LoRa or 4G / 5G network;

[0081] Data packaging: Use MQTT protocol or HTTP protocol to package data into message format;

[0082] Connection establishment: Establish a connection with the IoT terminal through the NB-IoT module or 4G module;

[0083] Data encryption: Use AES or RSA encryption algorithm to encrypt data to ensure transmission security;

[0084] Use the RSA encryption algorithm to encrypt data. Specifically, the following steps are included:

[0085] Key generation: Generate public key (e, n) and private key (d, n);

[0086] Data encryption: Encrypt data using the public key (e, n);

[0087] Encrypted data output: output encrypted data;

[0088] The encryption process is shown in formula (2):

[0089] C = M^e \mod n (2);

[0090] The decryption process is shown in formula (3):

[0091] M = C^d \mod n (3);

[0092] Where (M) is the plaintext, (C) is the ciphertext, (e) is the encryption exponent in the public key, (d) is the decryption exponent in the private key, and (n) is the modulus;

[0093] Data transmission: Send the encrypted data to the IoT terminal through the network;

[0094] Data reception confirmation: Receive confirmation messages from IoT terminals to ensure successful data transmission;

[0095] Error handling: Set up a retransmission mechanism to automatically retransmit data when transmission fails;

[0096] Transmission log record: record the log of each data transmission to facilitate subsequent analysis and troubleshooting;

[0097] S3: Remote control and configuration

[0098] Connection establishment: Establish a remote connection with the water meter device via VPN or TLS;

[0099] Parameter reading: read the working parameters of the current water meter equipment, including acquisition frequency and switch status;

[0100] Configuration file generation: Generates files containing new configurations using standard formats including XML or JSON;

[0101] Parameter verification: Before sending a new configuration, verify the correctness of the configuration parameters to prevent incorrect configuration;

[0102] Parameter delivery: Send the new configuration file to the water meter device through remote commands;

[0103] Parameter application: After receiving the new configuration, the water meter device automatically applies the new working parameters;

[0104] Status monitoring: real-time monitoring of the operating status of water meter equipment to ensure successful application of configuration;

[0105] Feedback collection: Collect feedback information from water meter equipment to confirm the effect of configuration changes;

[0106] S4: Anomaly detection and alarm

[0107] Data collection: Regularly collect water consumption data and water quality data from water meters;

[0108] Data preprocessing: denoising and smoothing the collected data using moving average or Kalman filtering;

[0109] Threshold setting: Set the threshold of normal range based on historical data;

[0110] Anomaly detection: Use time series analysis algorithms to detect unusual changes in data;

[0111] Use time series analysis algorithms to detect abnormal changes in data. Specifically, the following steps are included:

[0112] Collect time series data, smooth and denoise the data, train the model using the ARIMA time series analysis algorithm, and use the trained model to detect anomalies in the data;

[0113] The ARIMA model includes the autoregressive (AR) part, the difference (I) part and the moving average (MA) part, as shown in formula (4):

[0114] Y_t=c+\sum_{i=1}^{p}\phi_iY_{ti}+\sum_{i=1}^{q}\theta_i\epsilon_{ti}+\epsilon_t (4);

[0115] Where (Y_t) is the current value of the time series data, (c) is the constant term, (\phi_i) is the autoregressive coefficient, (Y_{ti}) is the lagged value, (\theta_i) is the moving average coefficient, and (\epsilon_t) is the error term;

[0116] Water quality analysis: Analyze water quality data using chemical sensors and SVM algorithms;

[0117] The water quality data is analyzed using chemical sensors and SVM algorithms. Specifically, the following steps are included:

[0118] Use chemical sensors to collect water quality data, normalize and denoise the data, extract effective features from the data, use the support vector machine (SVM) algorithm to train the model, and use the trained model to classify the water quality data, as shown in formula (5):

[0119] w\cdotx+b=0 (5);

[0120] Where, for a binary classification problem, (w) is the weight vector, (x) is the feature vector, and (b) is the bias term;

[0121] The goal is to maximize the margin: \max\frac{2}{|w|};

[0122] The constraints are: y_i(w\cdotx_i+b)\geq1;

[0123] Where (y_i) is the class label of the sample (+1 or -1), (x_i) is the sample feature vector;

[0124] Alarm generation: Generates alarm information when an anomaly is detected, including the anomaly type and time;

[0125] Alarm sending: send alarm information to management personnel via SMS, email or application push;

[0126] Alarm record: All alarm information is recorded in a log file for subsequent analysis and processing;

[0127] S5: User Interaction Services

[0128] User registration: Users register an account through a mobile APP or website and bind the water meter device;

[0129] Data query: Users can query real-time water consumption and historical water consumption records on the APP or website;

[0130] Bill generation: The system automatically generates monthly or quarterly bills based on water consumption, using pre-defined templates;

[0131] Billing notification: Send billing notifications to users via SMS or email;

[0132] Water usage reminder: When the water usage reaches the set threshold, a water usage reminder is sent to the user;

[0133] Feedback collection: Users submit water-related questions and feedback through the app or website;

[0134] Problem handling: The system automatically classifies and assigns user feedback issues to corresponding customer service personnel for processing;

[0135] Service improvement: Continuously improve user service experience based on user feedback and suggestions;

[0136] S6: Data analysis and report generation

[0137] Data aggregation: The data collected from all water meter devices are aggregated and stored in a central database;

[0138] Data cleaning: Clean the aggregated data to remove invalid data and outliers;

[0139] Data classification: organize data by time, location and user;

[0140] Trend analysis: Use ARIMA or LSTM to analyze water use trends;

[0141] Predictive models: Use linear regression or decision trees to predict future water use;

[0142] Report generation: Generate various statistical reports, including water usage trends and regional water usage, in Excel or PDF format;

[0143] Report sending: regularly send the generated reports to relevant managers;

[0144] Data storage: All analytical data and reports are stored in cloud storage services for long-term preservation and access;

[0145] S7: Security Rights Management

[0146] User authentication: Use two-factor authentication to ensure the authenticity of the user's identity;

[0147] Role definition: define different user roles, including administrator, operator, and general user permissions;

[0148] Permission allocation: Assign corresponding permissions according to roles to ensure that users can only access and operate resources within their permission scope;

[0149] The data encryption process is the same as the data encryption in step S2;

[0150] Logging: Record all system operation logs, including user logins, data access, and configuration changes;

[0151] Log audit: Regularly audit operation logs to detect and analyze suspicious activities;

[0152] Abnormal handling: When abnormal activities are detected, warnings are automatically triggered and corresponding security measures are taken;

[0153] Security updates: Regularly update system security patches and protection measures to ensure system security.

[0154] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A remote maintenance method for a smart water meter, which is implemented based on a remote maintenance device for a smart water meter and an Internet of Things system, and is characterized in that: The following steps are involved: S1: Data collection and caching. Select water meter sensors, including ultrasonic water meters or electromagnetic water meters. Install water meter sensors at key nodes of the water pipe system to ensure real-time water consumption data collection. Read water flow data regularly through the RS485 or M-Bus interface sensor interface. Use linear regression algorithm to calibrate the collected data. Use linear regression algorithm to calibrate the collected data. Obtain the original data set of the sensor, including the measured value and the corresponding true value. Divide the data set into input feature X and output label Y. Use linear regression algorithm to train the model to obtain the calibration coefficient. Apply the calibration coefficient to the new measured data for calibration, see formula (1): Y = \beta_0 + \beta_1 X + \epsilon (1); In the formula, Y is the true value, X is the sensor measurement value, \beta_0 is the deviation, \beta_1 is the proportional coefficient, \epsilon is the error term, format the collected data into JSON or XML format, use GZIP to compress the data, store the data in the SD card or local server, set a scheduled task to regularly synchronize the cached data to the main server; S2: Data transmission. Select a suitable transmission network according to the actual environment, including NB-IoT, LoRa or 4G / 5G network. Use MQTT protocol or HTTP protocol to package data into message format. Establish a connection with the IoT terminal through NB-IoT module or 4G module. Use RSA encryption algorithm to encrypt data, generate public key (e, n) and private key (d, n), encrypt data with public key (e, n), and output the encrypted data. The encryption process is shown in formula (2): C = M^e \mod n (2); The decryption process is shown in formula (3): M = C^d \mod n (3); In the formula, M is plain text, C is cipher text, e is the encryption exponent in the public key, d is the decryption exponent in the private key, and n is the modulus. The encrypted data is sent to the IoT terminal through the network, and the confirmation message of the IoT terminal is received. A retransmission mechanism is set to automatically retransmit the data when the transmission fails, and a log of each data transmission is recorded; S3. Remote control and configuration, remote switch control and remote configuration update of water meters, including modification of working parameters including acquisition frequency and operation strategy, and real-time monitoring of the operating status of water meter equipment; S4: Abnormal detection and alarm, regularly collect water consumption data and water quality data from water meters, denoise and smooth the collected data, use moving average or Kalman filtering, set the threshold of the normal range according to historical data, use time series analysis algorithm to detect abnormal changes in the data, smooth and denoise the data, use ARIMA time series analysis algorithm to train the model, and use the trained model to detect abnormal points in the data. The ARIMA model includes autoregressive AR part, differential I part and moving average MA part, see formula (4): Y_t=c+\sum_{i=1}^{p}\phi_iY_{ti}+\sum_{i=1}^{q}\theta_i\epsilon_{ti}+\epsilon_t (4); In the formula, Y_t is the current value of the time series data, c is the constant term, \phi_i is the autoregressive coefficient, Y_{ti} is the lag value, \theta_i is the moving average coefficient, \epsilon_t is the error term, and the water quality data is analyzed using chemical sensors and SVM algorithms. The water quality data is collected using chemical sensors, the data is normalized and denoised, and effective features are extracted from the data. The model is trained using the support vector machine SVM algorithm, and the trained model is used to classify the water quality data, as shown in formula (5): w\cdotx+b=0 (5); In the formula, for the binary classification problem, w is the weight vector, x is the feature vector, and b is the bias term; The goal is to maximize the margin: \max\frac{2}{|w|}; The constraints are: y_i(w\cdotx_i+b)\geq1; In the formula, y_i is the category label of the sample +1 or -1, x_i is the sample feature vector, and an alarm message is generated when an anomaly is detected, including the anomaly type and time. The alarm message is sent to the management personnel via SMS, email or application push, and all alarm messages are recorded in the log file for subsequent analysis and processing; S5. User interactive services, providing users with ways to query water usage and bill information, sending water usage reminders and bill notifications to users, and providing channels for user feedback and problem solving; S6. Data analysis and report generation: conduct multi-dimensional analysis of the collected data, provide water consumption trends and forecast information, generate various statistical reports, and store the data in the cloud for a long time; S7. Security authority management: manage user authority based on role-based access control, encrypt data to ensure data security, record and audit system operation logs, and conduct real-time monitoring and retrospective analysis; The intelligent water meter remote maintenance device includes a data acquisition and transmission module, a remote control management module, an abnormality detection and alarm module, a user interactive service module, a data analysis and reporting module, and a security authority management module. The data acquisition and transmission module is used for water meter data acquisition, caching and transmission. The remote control management module is used for remote switch control, remote configuration and equipment status monitoring. The abnormality detection and alarm module is used for abnormal water use detection, water quality monitoring and alarm notification. The user interactive service module is used for user query, user notification and customer service support. The data analysis and reporting module is used for data analysis, report generation and data storage. The security authority management module is used for user authority management, data encryption and security auditing. The data acquisition and transmission module also includes a water meter data acquisition unit, a data cache unit and a data transmission unit; The water meter data collection unit uses sensors and metering chips to ensure data accuracy and is used to collect water meter readings and basic water consumption data in real time; The data cache unit uses a built-in memory or an external storage device to temporarily store the collected data to prevent data loss; The data transmission unit is used to integrate wireless communication and support multiple communication protocols; The data transmission unit transmits data to the Internet of Things terminal via one of NB-IoT, LoRa, and 4G / 5G networks; The remote control management module also includes a remote switch control unit, a remote configuration unit and a device status monitoring unit; The remote switch control unit uses an electric valve and a remote control protocol to allow the water meter to be remotely switched on and off to control the water supply; The remote configuration unit performs remote configuration updates through OTA technology, and is used to remotely modify the working parameters of the water meter, including the acquisition frequency and the valve operation strategy; The device status monitoring unit integrates status monitoring sensors and reporting mechanisms to monitor the operating status of the water meter device in real time, including battery power and communication status; The user interactive service module also includes a user query unit, a user notification unit and a customer service support unit; The user query unit develops a user-friendly mobile phone app or web page interface to allow users to query water consumption and bill information; The user notification unit integrates a message push service for sending water use reminders and bill notification information to users; The customer service support unit integrates an online customer service system and a hotline service to provide a channel for user feedback and problem solving; The abnormal detection alarm module also includes an abnormal water use detection unit, a water quality monitoring unit and an alarm notification unit; The abnormal water use detection unit performs analysis based on historical data and real-time data and uses a machine learning algorithm to detect abnormal changes in water use, including water leakage or illegal water use; The water quality monitoring unit is integrated with a water quality sensor, and the detection parameters include turbidity and pH value, which are used to detect changes in water quality and ensure water supply safety; The alarm notification unit supports SMS, email, and App notification methods, and is used to upload alarm information to the IoT terminal when an abnormal situation is detected, and send an alarm notification to the management personnel at the same time; The data analysis report module also includes a data analysis unit, a report generation unit and a data storage unit; The data analysis unit uses big data analysis technology and supports multi-dimensional analysis to analyze the collected data and provide water use trend and forecast information; The report generation unit integrates a report generation tool, supports multiple formats of output, and is used to generate various statistical reports, including monthly water use reports and abnormal water use reports; The data storage unit uses a cloud storage service to ensure data security and reliability and is used to store historical data for a long time for subsequent analysis and reference; The security authority management module also includes a user authority management unit, a data encryption unit and a security audit unit; The user authority management unit sets different authority levels based on role-based access control to manage the authority of different users and ensure the security of the device and the Internet of Things; The data encryption unit adopts an encryption algorithm to encrypt the transmitted and stored data to prevent data leakage; The security audit unit integrates log management and audit systems, supports real-time monitoring and backtracking analysis, and is used to record and audit system operation logs and track security events.

2. An Internet of Things system, characterized in that , including the smart water meter remote maintenance device as claimed in claim 1, an Internet of Things, and an Internet of Things terminal linked to the Internet of Things.

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