Unit water resource monitoring management system based on Internet of Things

Abstract

The invention relates to the technical field of power plant equipment operation and maintenance, and provides a unit water resource monitoring and management system based on the Internet of Things, which collects multi-dimensional data of flow, pressure, temperature, water quality and the like of unit water resources in real time through the Internet of Things technology, and performs deep analysis by using a data processing module. And error data and normal operation data can be accurately identified. Particularly, the system is internally provided with a data error position determination unit, an error data source can be accurately positioned, an operation and maintenance route generation unit is combined, an optimal maintenance route is automatically generated according to a preset sensor information base and a maintenance model, and the workload of maintenance personnel is remarkably reduced. In addition, the system also has fine management and efficient scheduling functions, provides a scientific decision basis for operation and maintenance of the unit, and improves stable supply and reasonable utilization of water resources. The accuracy and efficiency of unit water resource monitoring are effectively improved, and an innovative technical solution is provided for water resource management and maintenance.

Description

Technical Field

[0001] The present invention relates to the technical field of power plant equipment operation and maintenance, and in particular to a unit water resource monitoring and management system based on the Internet of Things. Background Art

[0002] In actual applications, the unit water resource monitoring and management system based on the Internet of Things has achieved real-time monitoring of water resources for air-cooled units with its universality and intelligent management capabilities. The Internet of Things technology system can accurately collect and analyze unit water usage data, providing strong support for the efficient scheduling and conservation of water resources. The unit water resource monitoring and management system based on the Internet of Things not only improves the utilization efficiency of water resources, but also effectively reduces operation and maintenance costs, showing its great potential in water resource management for air-cooled units.

[0003] The usage of the unit water resource monitoring and management system based on the Internet of Things mainly includes the following steps: first, install Internet of Things sensors at the key water use points of the unit. The sensors can monitor the key parameters of water resources such as flow, pressure, and temperature in real time; second, transmit these data to the central monitoring platform in real time through the wireless network. The platform uses advanced algorithms to process and analyze the data to generate detailed water use reports and early warning information. Finally, based on the monitoring results, the system can automatically adjust the allocation and scheduling of water resources, or issue instructions to operators to guide them to make manual adjustments.

[0004] In actual use, the unit water resource monitoring and management system based on the Internet of Things has the following technical pain points. In harsh industrial environments, sensors are affected by factors such as temperature, humidity, and electromagnetic interference, resulting in unstable or inaccurate data collection. After long-term operation, the sensors experience performance degradation or failure, and require regular maintenance and calibration. However, due to the long distance of the unit water location of the Internet of Things and the hidden installation location of the sensor, maintenance personnel need to do a lot of work when repairing the sensor. In order to improve the efficiency of sensor maintenance by maintenance personnel, the present invention provides a unit water resource monitoring and management system based on the Internet of Things. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a unit water resource monitoring and management system based on the Internet of Things, which solves the problem that the location of the unit water of the Internet of Things is far away and the sensor installation position is hidden, resulting in a large workload for maintenance personnel when performing sensor maintenance.

[0006] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0007] The present invention provides a unit water resources monitoring and management system based on the Internet of Things, comprising:

[0008] The data acquisition module obtains the unit water resource monitoring and management data, which includes water resource flow data, water resource pressure data, water resource temperature data, water quality data, unit operation status data, meteorological data, sensor status data, and timestamp data;

[0009] The data association module obtains the water resource monitoring and management data of the unit from the data acquisition module, and collects the water resource flow data, water resource pressure data, water resource temperature data, water quality data, unit operation status data, meteorological data, sensor status data and timestamp data into data point sets. Each data point in the data point set includes data value, collection time and sensor ID. The integrated data is stored in the database to obtain a relational database.

[0010] A data processing module receives the real-time data of the unit water resource monitoring, substitutes the real-time data of the unit water resource monitoring into the unit water resource monitoring model, obtains the unit water resource monitoring result, identifies the unit water resource monitoring result, and obtains the unit water resource monitoring result identification result, which includes erroneous data and normal operation data;

[0011] The data error location determination unit retrieves the error data in the unit water resources monitoring result, and obtains the type of error data and the location of the error information according to the original information of the error data in the unit water resources monitoring result;

[0012] The operation and maintenance route generation unit matches the type of error data and the location of the error information with the preset sensor information library to obtain the type of error data and the sensor corresponding to the error information, and substitutes the type of error data and the sensor corresponding to the error information into the preset maintenance route planning model to obtain the sensor maintenance route.

[0013] Furthermore, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the data association module is also used for:

[0014] The water resource monitoring and management data of the unit is obtained in real time through the data acquisition module. The water resource monitoring and management data of the unit includes water resource flow data, water resource pressure data, water resource temperature data, water quality data, unit operation status data, meteorological data, sensor status data and timestamp data;

[0015] The real-time water resource monitoring and management data of the unit is integrated to form a data set. Each data point in the data set includes the data value, collection time and sensor ID. The data value includes the monitoring result, the collection time records the time when the data is collected, and the sensor ID;

[0016] Create a corresponding data table in the database according to the data points to store the data point set, insert the constructed data point set into the data table of the relational database, and associate the data points in the database through the sensor ID and timestamp to obtain the corresponding relationship between each data point and the collection time of its sensor.

[0017] Furthermore, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the data processing module is also used for:

[0018] The data processing module receives the unit water resource monitoring data transmitted from the data acquisition module in real time, performs preliminary processing on the received real-time data, and builds a unit water resource monitoring model based on machine learning according to the needs and goals of the unit water resource monitoring;

[0019] The parameters of the unit water resources monitoring model are set, and the pre-processed real-time data is input into the unit water resources monitoring model. The unit water resources monitoring model performs calculations based on the input data to generate the unit water resources monitoring results.

[0020] Furthermore, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the data error position determination unit is also used for:

[0021] From the water resource monitoring results of the unit, potential erroneous data are screened out by setting thresholds, rules or deviations between model predictions and actual values, and the screened erroneous data are integrated into an erroneous data set;

[0022] For each erroneous data point, trace its original information including data source, collection time and sensor ID, and compare the original information of the erroneous data with the standard range of normal data or historical data to obtain abnormal data;

[0023] According to the characteristics of the erroneous data and the comparison results, the erroneous data are classified, each error type is marked, and for each erroneous data point, its position in the water resources monitoring system is analyzed.

[0024] Furthermore, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the data error position determination unit is also used for:

[0025] For each erroneous data point that is screened out, extract its features including numerical value, change trend, and correlation with other data;

[0026] Compare the extracted features with those of normal data to identify features that are obviously inconsistent with normal data. Set classification rules based on the features of erroneous data, such as values ​​outside the normal range and irregular data changes;

[0027] According to the set classification rules, the error data is classified and a label is assigned to each error type. For each error data point, its original information including data source, collection time and sensor ID is traced;

[0028] Locate the location of the erroneous data point, sensor installation location, and data collection node in the water resources monitoring system based on the sensor ID and collection time;

[0029] The classified and marked error data and their location information in the system are integrated into an error data report, and the error data report is output to maintenance personnel.

[0030] Furthermore, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the operation and maintenance route generating unit is also used for:

[0031] Obtain the type of error data and the location of error information from the data error location determination unit, match the extracted error data information with a preset sensor information library, and match the sensor corresponding to the error data through the sensor ID, location information or error feature field;

[0032] According to the matching results, the sensors involved in the erroneous data and their locations are determined, the sensor information is matched with the input parameters required by the preset maintenance route planning model, and the associated sensor information is substituted into the preset maintenance route planning model. The preset maintenance route planning model calculates the optimal or suboptimal maintenance route based on the input sensor information, the location of the maintenance personnel, and traffic conditions.

[0033] Furthermore, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the operation and maintenance route generating unit is also used for:

[0034] Acquire the associated sensor information including sensor ID, location and error type from the data error location determination unit and the sensor information library;

[0035] The sensor information is matched with the input parameters required by the preset maintenance route planning model. According to the actual needs and maintenance strategy, the maintenance route planning model is matched in the preset model library, and the model configuration is received and configured. The model configuration includes setting the starting position of the maintenance personnel, traffic conditions considerations, and maintenance priorities.

[0036] The beneficial effects of the present invention are mainly reflected in the following aspects:

[0037] The present invention collects various monitoring data of the unit's water resources in real time through the Internet of Things technology, such as flow, pressure, temperature, water quality, etc., and combines advanced data processing and analysis technology to quickly and accurately reflect the real-time status of the unit's water resources and promptly discover potential problems. The system's built-in data error location determination unit can efficiently identify and locate erroneous data, and quickly screen out potential erroneous data by setting thresholds, rules or model predictions and deviations from actual values, providing maintenance personnel with accurate fault information and reducing troubleshooting time.

[0038] The operation and maintenance route generation unit can automatically generate the optimal or suboptimal sensor maintenance route according to the type and location of the erroneous data, combined with the preset sensor information library and maintenance route planning model, thereby improving maintenance efficiency and reducing the workload of maintenance personnel. Through the comprehensive collection, integration and processing of the unit water resource monitoring data, the system can provide important references for unit operation and maintenance, realize the fine management and efficient scheduling of water resources, and improve the stable supply and rational use of water resources. Through real-time monitoring and data analysis, the system of the present invention can promptly detect and handle potential faults, reduce downtime caused by faults, and thus improve the reliability and stability of the entire unit water resource monitoring and management system.

[0039] In summary, the IoT-based unit water resources monitoring and management system of the present invention shows significant beneficial effects in improving monitoring efficiency and accuracy, accurately locating erroneous data, optimizing maintenance routes, achieving fine management and efficient scheduling, and improving system reliability and stability, providing strong support for the effective management and utilization of unit water resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0041] Figure 1 A schematic diagram of a unit water resources monitoring and management system based on the Internet of Things provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. 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. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings.

[0043] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0044] The present invention provides a unit water resources monitoring and management system based on the Internet of Things, comprising:

[0045] The data acquisition module obtains the unit water resource monitoring and management data, which includes water resource flow data, water resource pressure data, water resource temperature data, water quality data, unit operation status data, meteorological data, sensor status data, and timestamp data;

[0046] The data acquisition module is responsible for obtaining the unit water resources monitoring and management data in the technical solution of the present invention. The unit water resources monitoring and management data includes water resources flow data, water resources pressure data, water resources temperature data, water quality data, unit operation status data, meteorological data, sensor status data and timestamp data.

[0047] Specifically, the data acquisition module connects various sensor devices to the network through the Internet of Things technology to achieve real-time data collection and transmission. Sensors are distributed in various links of the unit's water resources, such as water inlets, outlets, pipelines, water storage tanks, etc., to monitor various states of water resources.

[0048] Through the data acquisition module, comprehensive information about the unit's water resources can be obtained in real time, providing accurate data support for subsequent data processing, error location, and operation and maintenance route generation. At the same time, the real-time and accuracy of the data acquisition module also improves the reliability and efficiency of the entire system.

[0049] Therefore, the data acquisition module plays a vital role in the entire unit water resources monitoring and management system. It is the foundation and premise of the entire system and provides a strong guarantee for the normal operation of the system.

[0050] The data association module obtains the water resource monitoring and management data of the unit from the data acquisition module, and collects the water resource flow data, water resource pressure data, water resource temperature data, water quality data, unit operation status data, meteorological data, sensor status data and timestamp data into data point sets. Each data point in the data point set includes data value, collection time and sensor ID. The integrated data is stored in the database to obtain a relational database.

[0051] The data association module is responsible for obtaining the unit water resource monitoring and management data from the data acquisition module in the technical solution of the present invention, and integrating these data into a data point set. Specifically, the data obtained by the data association module from the data acquisition module includes water resource flow data, water resource pressure data, water resource temperature data, water quality data, unit operation status data, meteorological data, sensor status data and timestamp data.

[0052] The data association module integrates these data according to specific rules to form a set of data points. Each data point contains the data value, collection time and sensor ID, which can improve the integrity and accuracy of the data. At the same time, through the association of sensor ID and timestamp, data points can be easily tracked and located, which facilitates subsequent data processing and analysis.

[0053] The integrated data is stored in a relational database, which enables centralized data management and efficient access. The relational database has powerful data query and processing capabilities, can support complex data analysis and mining operations, and provide strong support for the operation and maintenance of the unit water resources monitoring and management system.

[0054] Therefore, the data association module plays a vital role in the entire system. It can not only improve the integrity and accuracy of the data, but also improve the data processing efficiency and analysis capabilities, providing a strong guarantee for the normal operation and optimization of the system.

[0055] A data processing module receives the real-time data of the unit water resource monitoring, substitutes the real-time data of the unit water resource monitoring into the unit water resource monitoring model, obtains the unit water resource monitoring result, identifies the unit water resource monitoring result, and obtains the unit water resource monitoring result identification result, which includes erroneous data and normal operation data;

[0056] The data processing module is the core part of the technical solution of the present invention, which is responsible for processing and analyzing the real-time data of the unit water resources monitoring. Specifically, the workflow of the data processing module is as follows:

[0057] First, the data processing module will receive the unit water resource monitoring data from the data acquisition module in real time. These data cover multiple aspects such as water resource flow, pressure, temperature, water quality, unit operating status, meteorological conditions and sensor status. At the same time, each data point is attached with an accurate timestamp.

[0058] Next, the data processing module will substitute these real-time data into the pre-built unit water resource monitoring model. The unit water resource monitoring model is trained based on a large amount of historical data and machine learning algorithms. The unit water resource monitoring model can conduct in-depth analysis and processing of the input data to obtain the monitoring results of the unit water resources.

[0059] Then, the data processing module will identify the monitoring results. By comparing the preset normal range values ​​and historical data, it can accurately determine which data are erroneous and which data are operating normally. In this way, maintenance personnel can quickly locate the sensors or equipment that need maintenance based on these identification results.

[0060] Finally, the data processing module will output the identification results of the unit water resource monitoring results, including erroneous data and normal data. These identification results not only provide clear maintenance guidance for maintenance personnel, but also provide valuable data support for system optimization and upgrade.

[0061] In general, the data processing module provides a strong guarantee for the normal operation and maintenance of the system by receiving, processing and analyzing the unit water resource monitoring data in real time. Its efficiency and accuracy enable maintenance personnel to respond to and handle various faults quickly, thereby improving the stable supply and efficient use of the unit's water resources.

[0062] The data error location determination unit retrieves the error data in the unit water resources monitoring result, and obtains the type of error data and the location of the error information according to the original information of the error data in the unit water resources monitoring result;

[0063] The data error location determination unit is a key link in the technical solution of the present invention for accurately locating and identifying erroneous data. Its workflow is described in detail as follows:

[0064] First, the data error location determination unit screens out the data marked as errors from the unit water resource monitoring results retrieved by the data processing module. These data are abnormal values ​​caused by sensor failure, data transmission errors or environmental factors.

[0065] Next, the data error location determination unit will deeply analyze the original information of these erroneous data. The original information contains the data acquisition time, sensor ID and other relevant parameters. By carefully comparing and analyzing this information, the unit can determine the specific type of erroneous data, such as numerical deviation, missing data or unstable data.

[0066] Most importantly, the data error location determination unit can also accurately locate the specific location of the erroneous data in the unit's water resource monitoring system based on the sensor ID and timestamp in the original information. In this way, maintenance personnel can quickly find the problematic sensor or equipment and carry out targeted repairs or replacements.

[0067] In summary, the data error location determination unit provides valuable fault information to maintenance personnel by accurately analyzing and locating error data, thus improving maintenance efficiency and accuracy. The existence of this link improves the stability and reliability of the unit water resource monitoring system and provides strong support for the effective management and utilization of water resources.

[0068] The operation and maintenance route generation unit matches the type of error data and the location of the error information with the preset sensor information library to obtain the type of error data and the sensor corresponding to the error information, and substitutes the type of error data and the sensor corresponding to the error information into the preset maintenance route planning model to obtain the sensor maintenance route.

[0069] The operation and maintenance route generation unit is a key part of the technical solution of the present invention for efficiently generating sensor maintenance routes. Its detailed workflow is as follows:

[0070] First, the operation and maintenance route generation unit receives the type of error data and the location of the error information from the data error location determination unit. This information is obtained by in-depth analysis of the error data in the unit water resources monitoring results, and includes the specific type of error data and the specific location of the error information in the system.

[0071] Next, the operation and maintenance route generation unit will match the types of these error data and the locations of the error information with the preset sensor information library. The sensor information library stores detailed information on all sensors in the unit's water resource monitoring system, including the sensor's type, location, maintenance history, etc. Through matching, the unit can accurately find the sensors corresponding to the error data and obtain relevant information about these sensors.

[0072] Then, the operation and maintenance route generation unit will substitute the type of error data and the sensor information corresponding to the error information into the preset maintenance route planning model. This model is built based on factors such as the layout of the unit's water resources, the distribution of sensors, the location of maintenance personnel, and traffic conditions. It can automatically generate the optimal or suboptimal sensor maintenance route based on the input information.

[0073] Finally, the operation and maintenance route generation unit will output the generated sensor maintenance route. This route will list in detail the sensors that need to be maintained, their locations, and the order of maintenance. Maintenance personnel can efficiently repair and replace sensors based on this route, thereby improving the normal monitoring and operation of the unit's water resources.

[0074] In summary, the operation and maintenance route generation unit can efficiently generate sensor maintenance routes by matching error data with the sensor information library and substituting it into the maintenance route planning model. The existence of this link improves maintenance efficiency, reduces the workload of maintenance personnel, and provides strong support for the effective management and utilization of water resources for the unit.

[0075] Specifically, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the data association module is also used for:

[0076] The water resource monitoring and management data of the unit is obtained in real time through the data acquisition module. The water resource monitoring and management data of the unit includes water resource flow data, water resource pressure data, water resource temperature data, water quality data, unit operation status data, meteorological data, sensor status data and timestamp data;

[0077] The real-time water resource monitoring and management data of the unit is integrated to form a data set. Each data point in the data set includes the data value, collection time and sensor ID. The data value includes the monitoring result, the collection time records the time when the data is collected, and the sensor ID;

[0078] Create a corresponding data table in the database according to the data points to store the data point set, insert the constructed data point set into the data table of the relational database, and associate the data points in the database through the sensor ID and timestamp to obtain the corresponding relationship between each data point and the collection time of its sensor.

[0079] Specifically, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the data processing module is also used for:

[0080] The data processing module receives the unit water resource monitoring data transmitted from the data acquisition module in real time, performs preliminary processing on the received real-time data, and builds a unit water resource monitoring model based on machine learning according to the needs and goals of the unit water resource monitoring;

[0081] The parameters of the unit water resources monitoring model are set, and the pre-processed real-time data is input into the unit water resources monitoring model. The unit water resources monitoring model performs calculations based on the input data to generate the unit water resources monitoring results.

[0082] Specifically, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the data error position determination unit is also used to:

[0083] From the water resource monitoring results of the unit, potential erroneous data are screened out by setting thresholds, rules or deviations between model predictions and actual values, and the screened erroneous data are integrated into an erroneous data set;

[0084] For each erroneous data point, trace its original information including data source, collection time and sensor ID, and compare the original information of the erroneous data with the standard range of normal data or historical data to obtain abnormal data;

[0085] According to the characteristics of the erroneous data and the comparison results, the erroneous data are classified, each error type is marked, and for each erroneous data point, its position in the water resources monitoring system is analyzed.

[0086] Specifically, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the data error position determination unit is also used to:

[0087] For each erroneous data point that is screened out, extract its features including numerical value, change trend, and correlation with other data;

[0088] Compare the extracted features with those of normal data to identify features that are obviously inconsistent with normal data. Set classification rules based on the features of erroneous data, such as values ​​outside the normal range and irregular data changes;

[0089] According to the set classification rules, the error data is classified and a label is assigned to each error type. For each error data point, its original information including data source, collection time and sensor ID is traced;

[0090] Locate the location of the erroneous data point, sensor installation location, and data collection node in the water resources monitoring system based on the sensor ID and collection time;

[0091] The classified and marked error data and their location information in the system are integrated into an error data report, and the error data report is output to maintenance personnel.

[0092] Specifically, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the operation and maintenance route generation unit is also used for:

[0093] Obtain the type of error data and the location of error information from the data error location determination unit, match the extracted error data information with a preset sensor information library, and match the sensor corresponding to the error data through the sensor ID, location information or error feature field;

[0094] According to the matching results, the sensors involved in the erroneous data and their locations are determined, the sensor information is matched with the input parameters required by the preset maintenance route planning model, and the associated sensor information is substituted into the preset maintenance route planning model. The preset maintenance route planning model calculates the optimal or suboptimal maintenance route based on the input sensor information, the location of the maintenance personnel, and traffic conditions.

[0095] Specifically, in the unit water resource monitoring and management system based on the Internet of Things provided by the present invention, the operation and maintenance route generation unit is also used for:

[0096] Acquire the associated sensor information including sensor ID, location and error type from the data error location determination unit and the sensor information library;

[0097] The sensor information is matched with the input parameters required by the preset maintenance route planning model. According to the actual needs and maintenance strategy, the maintenance route planning model is matched in the preset model library, and the model configuration is received and configured. The model configuration includes setting the starting position of the maintenance personnel, traffic conditions considerations, and maintenance priorities.

[0098] The technical solution of the present invention solves the problem that the location of the water unit of the Internet of Things is far away and the sensor is installed in a hidden position, which causes maintenance personnel to have a large workload when repairing the sensor in the following ways:

[0099] Acquire the unit water resource monitoring and management data, including water resource flow, pressure, temperature, water quality, unit operating status, weather, sensor status and timestamp data, to provide a basis for subsequent analysis. Integrate the collected data into a set of data points, each of which contains the data value, collection time and sensor ID, and store them in a relational database. Associate data points by sensor ID and timestamp to facilitate tracking and positioning. Receive real-time data, substitute it into the unit water resource monitoring model, generate monitoring results, and identify erroneous data and normal operating data.

[0100] Retrieve error data and determine the type and location of the error data based on the original information. Generate an error data report by extracting features, comparing normal data, classifying error data, and locating the location of error data points in the system. Match the type and location of the error data with the preset sensor information library to determine the sensor corresponding to the error data. Substitute it into the maintenance route planning model and calculate the optimal or suboptimal maintenance route based on sensor information, maintenance personnel location, traffic conditions and other factors, thereby improving maintenance efficiency and reducing workload.

[0101] Together, these measures form a complete system that can accurately locate sensor failures and provide efficient maintenance routes, thus solving the problem of heavy maintenance workload caused by the remote location of IoT units and hidden sensor installations.

[0102] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations, and the above-described embodiments of the present invention do not constitute a limitation on the scope of protection of the present invention.

Claims

1. A unit water resources monitoring and management system based on the Internet of Things, characterized in that: include: The data acquisition module obtains the unit water resource monitoring and management data, which includes water resource flow data, water resource pressure data, water resource temperature data, water quality data, unit operation status data, meteorological data, sensor status data, and timestamp data; The data association module obtains the water resource monitoring and management data of the unit from the data acquisition module, and collects the water resource flow data, water resource pressure data, water resource temperature data, water quality data, unit operation status data, meteorological data, sensor status data and timestamp data into data point sets. Each data point in the data point set includes data value, collection time and sensor ID. The integrated data is stored in the database to obtain a relational database. A data processing module receives the real-time data of the unit water resource monitoring, substitutes the real-time data of the unit water resource monitoring into the unit water resource monitoring model, obtains the unit water resource monitoring result, identifies the unit water resource monitoring result, and obtains the unit water resource monitoring result identification result, which includes erroneous data and normal operation data; The data error location determination unit retrieves the error data in the unit water resources monitoring result, and obtains the type of error data and the location of the error information according to the original information of the error data in the unit water resources monitoring result; The operation and maintenance route generation unit matches the type of error data and the location of the error information with the preset sensor information library to obtain the type of error data and the sensor corresponding to the error information, and substitutes the type of error data and the sensor corresponding to the error information into the preset maintenance route planning model to obtain the sensor maintenance route.

2. The unit water resource monitoring and management system based on the Internet of Things as claimed in claim 1, characterized in that: The data association module is further used for: The water resource monitoring and management data of the unit is obtained in real time through the data acquisition module. The water resource monitoring and management data of the unit includes water resource flow data, water resource pressure data, water resource temperature data, water quality data, unit operation status data, meteorological data, sensor status data and timestamp data; The real-time water resource monitoring and management data of the unit is integrated to form a data set. Each data point in the data set includes the data value, collection time and sensor ID. The data value includes the monitoring result, the collection time records the time when the data is collected, and the sensor ID; Create a corresponding data table in the database according to the data points to store the data point set, insert the constructed data point set into the data table of the relational database, and associate the data points in the database through the sensor ID and timestamp to obtain the corresponding relationship between each data point and the collection time of its sensor.

3. The unit water resource monitoring and management system based on the Internet of Things as claimed in claim 1, characterized in that: The data processing module is also used for: The data processing module receives the unit water resource monitoring data transmitted from the data acquisition module in real time, performs preliminary processing on the received real-time data, and builds a unit water resource monitoring model based on machine learning according to the needs and goals of the unit water resource monitoring; The parameters of the unit water resources monitoring model are set, and the pre-processed real-time data is input into the unit water resources monitoring model. The unit water resources monitoring model performs calculations based on the input data to generate the unit water resources monitoring results.

4. The unit water resource monitoring and management system based on the Internet of Things as claimed in claim 1, characterized in that: The data error position determination unit is further used for: From the water resource monitoring results of the unit, potential erroneous data are screened out by setting thresholds, rules or deviations between model predictions and actual values, and the screened erroneous data are integrated into an erroneous data set; For each erroneous data point, trace its original information including data source, collection time and sensor ID, and compare the original information of the erroneous data with the standard range of normal data or historical data to obtain abnormal data; According to the characteristics of the erroneous data and the comparison results, the erroneous data are classified, each error type is marked, and for each erroneous data point, its position in the water resources monitoring system is analyzed.

5. The unit water resource monitoring and management system based on the Internet of Things as claimed in claim 4, characterized in that: The data error position determination unit is further used for: For each erroneous data point that is screened out, extract its features including numerical value, change trend, and correlation with other data; Compare the extracted features with those of normal data to identify features that are obviously inconsistent with normal data. Set classification rules based on the features of erroneous data, such as values ​​outside the normal range and irregular data changes; According to the set classification rules, the error data is classified and a label is assigned to each error type. For each error data point, its original information including data source, collection time and sensor ID is traced; Locate the location of the erroneous data point, sensor installation location, and data collection node in the water resources monitoring system based on the sensor ID and collection time; The classified and marked error data and their location information in the system are integrated into an error data report, and the error data report is output to maintenance personnel.

6. The unit water resource monitoring and management system based on the Internet of Things as claimed in claim 1, characterized in that: The operation and maintenance route generating unit is further used for: Obtain the type of error data and the location of error information from the data error location determination unit, match the extracted error data information with a preset sensor information library, and match the sensor corresponding to the error data through the sensor ID, location information or error feature field; According to the matching results, the sensors involved in the erroneous data and their locations are determined, the sensor information is matched with the input parameters required by the preset maintenance route planning model, and the associated sensor information is substituted into the preset maintenance route planning model. The preset maintenance route planning model calculates the optimal or suboptimal maintenance route based on the input sensor information, the location of the maintenance personnel, and traffic conditions.

7. The unit water resource monitoring and management system based on the Internet of Things as claimed in claim 6, characterized in that: The operation and maintenance route generating unit is further used for: Acquire the associated sensor information including sensor ID, location and error type from the data error location determination unit and the sensor information library; The sensor information is matched with the input parameters required by the preset maintenance route planning model. According to the actual needs and maintenance strategy, the maintenance route planning model is matched in the preset model library, and the model configuration is received and configured. The model configuration includes setting the starting position of the maintenance personnel, traffic conditions considerations, and maintenance priorities.

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