Water quality detection data online management method and system

Abstract

The invention provides a water quality detection data online management method and system. The method comprises the following steps: acquiring first water quality detection data of a first to-be-detected grid in a to-be-detected water area through a first water quality detection sensor sequence, and sending the first water quality detection data to an online management cloud platform, so that the online management cloud platform stores the first water quality detection data and calls first water quality historical detection data; determining a first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, determining a first water quality detection data reporting frequency according to the first water quality detection data change characteristic value, and then sending the first water quality detection data reporting frequency to a first water quality detection sensor sequence; the first water quality detection sensor sequence feeds back the water quality detection data according to the first water quality detection data reporting frequency, so that the reporting frequency of the water quality detection sensors is dynamically adjusted, and effective water quality monitoring can be ensured under limited resources.

Description

Technical Field

[0001] The present application relates to data processing technology, and in particular to an online management method and system for water quality testing data. Background Art

[0002] With the increasing awareness of environmental protection and the demand for water resource management, water quality testing has become an important means to ensure water resource safety and assess the ecological environment of water bodies. Traditional water quality testing methods usually rely on manual sampling and laboratory analysis, which is not only time-consuming and labor-intensive, but also difficult to achieve real-time monitoring and big data management. In recent years, with the development of Internet of Things technology and cloud computing technology, water quality testing management systems have gradually achieved automation and intelligence.

[0003] Existing water quality detection and management systems usually include multiple water quality detection sensors, which are deployed at different locations in the water area to be detected to collect water quality parameters in real time. However, these systems still have some problems in practical applications. For example, the frequency of sensor data reporting is often fixed and cannot be dynamically adjusted according to water quality changes, resulting in redundant data when the data is stable, and key information may be missed when the data changes dramatically. Summary of the invention

[0004] The present application provides a method and system for online management of water quality detection data, which is used to dynamically adjust the reporting frequency of water quality detection sensors, thereby ensuring effective water quality monitoring under limited resources, while ensuring data accuracy and avoiding unnecessary waste of resources.

[0005] In a first aspect, the present application provides a method for online management of water quality detection data, which is applied to a water quality detection management system, wherein the water quality detection management system includes an online management cloud platform and a plurality of water quality detection sensor sequences, each of which is used to perform water quality detection on a grid to be detected in a water area to be detected, and the online management cloud platform is communicatively connected with each water quality detection sensor in the water quality detection sensor sequence; the method includes:

[0006] Acquire first water quality detection data of a first to-be-detected grid in the to-be-detected water area through a first water quality detection sensor sequence, and send the first water quality detection data to the online management cloud platform, wherein the first water quality detection data includes current water quality detection parameters and current detection time acquired by each water quality detection sensor in the first water quality detection sensor sequence;

[0007] The online management cloud platform stores the first water quality detection data, and calls the first water quality historical detection data to determine the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, wherein the first water quality historical detection data is the water quality detection data before the current detection time;

[0008] The online management cloud platform determines the first water quality detection data reporting frequency according to the first water quality detection data change characteristic value, and sends the first water quality detection data reporting frequency to the first water quality detection sensor sequence, so that the first water quality detection sensor sequence feeds back water quality detection data according to the first water quality detection data reporting frequency, and the first water quality detection data reporting frequency is positively correlated with the first water quality detection data change characteristic value.

[0009] In the above scheme, by deploying multiple water quality detection sensor sequences, the water area to be detected is gridded and monitored in real time, ensuring the comprehensive coverage and real-time nature of water quality data. Water quality changes in each grid can be captured and reported in a timely manner, improving the efficiency and accuracy of water quality monitoring. In addition, the online management cloud platform can not only store the water quality detection data obtained in real time, but also call historical data to determine the changing characteristic values ​​of water quality detection data through comparative analysis. This process realizes the intelligent processing of data, helps to identify the trends and patterns of water quality changes, and provides a basis for subsequent management and decision-making. Then, according to the changing characteristic values ​​of water quality detection data, the reporting frequency of water quality detection data is dynamically adjusted. When the water quality changes greatly, the reporting frequency is increased to obtain more frequent data updates; when the water quality is relatively stable, the reporting frequency is reduced to reduce the cost of data transmission and processing. This dynamic adjustment mechanism improves the flexibility and response speed of the monitoring system.

[0010] It can be seen that through intelligent analysis and dynamic adjustment of reporting frequency, effective water quality monitoring can be ensured under limited resources. While ensuring data accuracy, unnecessary waste of resources, such as data transmission bandwidth and processing power, is avoided.

[0011] Optionally, determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data includes:

[0012] If each water quality detection data in the first water quality detection data is less than the corresponding water quality detection data threshold, the online management cloud platform determines the first water quality detection data change characteristic value according to each water quality detection parameter in the first water quality detection data and each water quality detection parameter in the first water quality historical detection data;

[0013] If a water quality detection parameter greater than a corresponding water quality detection data threshold value exists in the first water quality detection data, the first water quality detection data change characteristic value is determined to be a first preset water quality detection data change characteristic threshold value.

[0014] In the above scheme, when all water quality test data are less than the corresponding threshold, the change characteristic value is determined by analysis based on detailed water quality test parameters and historical data, which helps to finely identify the slow change or stable state of water quality. When water quality test data exceeds the threshold, the change characteristic value is immediately set to the preset maximum threshold, which reflects that the water quality may have a sudden change or abnormal situation, which requires immediate attention and processing. By setting the water quality test data threshold, it is possible to quickly identify and respond to water quality anomalies. Once any water quality parameter exceeding the threshold is detected, the system will immediately set the change characteristic value to the maximum value, thereby triggering more frequent data reporting or other emergency measures, such as issuing alarms, adjusting monitoring frequency, etc., to find out the cause and take measures as soon as possible.

[0015] For water quality that is in a good or relatively stable state, the frequency of data reporting is optimized by analyzing the characteristic values ​​of data changes, reducing unnecessary data transmission and processing. When water quality is abnormal, a rapid response mechanism is used to ensure the timely transmission of important information, thereby improving the overall data processing efficiency and system response speed.

[0016] Optionally, determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data includes:

[0017] The online management cloud platform is based on a first image in the first water quality detection data, where the first image is an image of the first to-be-detected grid at the current detection time;

[0018] The online management cloud platform traverses each pixel in the first image information, and determines the color component mean value corresponding to each color component according to each color component of each pixel in a preset color space;

[0019] The online management cloud platform determines the first water quality color characteristic value according to the color component mean values ​​corresponding to each color component;

[0020] The online management cloud platform determines the first water quality detection data change characteristic value based on the first water quality color characteristic value and the historical water quality color characteristic value corresponding to the first water quality historical detection data.

[0021] In the above scheme, the color information in the image is used, combined with the mean value of the color component in the preset color space, to calculate the water quality color characteristic value, realize the multi-dimensional fusion analysis of water quality data, and improve the comprehensiveness and accuracy of water quality assessment. By traversing each pixel in the image information and calculating the mean value of the color component, the water quality color characteristic value is determined, and then combined with the historical water quality color characteristic value, the algorithm is used to calculate the water quality detection data change characteristic value. Among them, color is an important indicator of water quality changes. The water quality color characteristic value obtained by image analysis can intuitively reflect the changes in water quality. Combined with historical data, the trend and degree of water quality changes can be judged more accurately, providing strong support for water quality management. The above scheme not only takes into account the numerical changes of water quality parameters, but also combines the color information of image data, making water quality monitoring more comprehensive.

[0022] Optionally, after determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, the method further includes:

[0023] The online management cloud platform determines the detection time difference according to the first detection time corresponding to the first water quality historical detection data and the current detection time;

[0024] The online management cloud platform updates the first water quality detection data change characteristic value according to the detection time difference to generate an updated water quality detection data change characteristic value, and the updated water quality detection data change characteristic value is used to update the first water quality detection data change characteristic value.

[0025] In the above scheme, by calculating the detection time difference and updating the characteristic value of the change of the first water quality detection data, dynamic adjustment of the water quality change characteristics is achieved, which helps to more accurately reflect the trend and speed of water quality changes over time, and provide more real-time and accurate data support for water quality management.

[0026] As time goes by, water quality conditions may change. By considering the detection time difference and updating the characteristic value of water quality detection data change accordingly, the timeliness and accuracy of the data can be ensured, which helps to avoid misjudgment or delayed processing due to data lag, and improves the efficiency and effectiveness of water quality management. In addition, according to the updated characteristic value of water quality detection data change, the online management cloud platform can further adjust the reporting frequency of water quality detection data. For areas with rapid changes or large fluctuations in water quality, the monitoring frequency can be increased to obtain more detailed data; while for areas with relatively stable water quality or small changes, the monitoring frequency can be appropriately reduced to reduce costs. This dynamic adjustment strategy helps to optimize the allocation of monitoring resources and improve monitoring efficiency. In addition, by updating the characteristic value of water quality detection data change in real time, the system can respond to water quality changes more quickly. Once abnormal or trending changes in water quality are found, the system can immediately take measures, such as adjusting monitoring parameters and issuing alarms, to ensure water quality safety.

[0027] Optionally, the online management cloud platform determines the reporting frequency of the first water quality detection data according to the characteristic value of the change of the first water quality detection data, including:

[0028] If the first water quality detection data change characteristic value is less than the preset first characteristic value, the online management cloud platform determines that the first water quality detection data reporting frequency is the first reporting frequency;

[0029] If the first water quality detection data change characteristic value is greater than or equal to a preset first characteristic value, and less than a preset second characteristic value, the online management cloud platform determines that the first water quality detection data reporting frequency is a second reporting frequency, and the second reporting frequency is greater than the first reporting frequency;

[0030] If the first water quality detection data change characteristic value is greater than or equal to the preset second characteristic value, and less than or equal to the preset water quality detection data change characteristic threshold, the online management cloud platform determines that the first water quality detection data reporting frequency is the third reporting frequency, and the third reporting frequency is greater than the second reporting frequency.

[0031] In the above scheme, by setting multiple characteristic value thresholds and comparing the characteristic value of the first water quality detection data with these thresholds, the reporting frequency of the water quality detection data is dynamically adjusted. This dynamic adjustment mechanism can flexibly adjust the monitoring density according to the actual situation of water quality changes, which not only ensures the validity and accuracy of the data, but also avoids unnecessary waste of resources.

[0032] In periods when water quality is relatively stable, reducing the reporting frequency can reduce the frequency and amount of data transmission, thereby reducing the burden on the system and improving monitoring efficiency. In cases where water quality changes significantly or there may be risks, increasing the reporting frequency can obtain water quality data more timely, providing strong support for rapid response and effective treatment.

[0033] Through intelligent adjustment of reporting frequency, optimal allocation of monitoring resources is achieved. For areas or time periods that need special attention, the monitoring frequency and depth can be increased; for relatively stable areas or time periods, the monitoring frequency can be reduced to invest resources in more needed areas. By presetting multiple characteristic value thresholds and dynamically adjusting the reporting frequency according to actual conditions, the water quality detection management system has greater flexibility and adaptability.

[0034] Optionally, the water quality detection management system further includes: a monitoring terminal, the monitoring terminal being communicatively connected to the online management cloud platform; correspondingly, after determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, it further includes:

[0035] The online management cloud platform generates a water quality detection data change characteristic value array according to the water quality detection data change characteristic values ​​corresponding to each to-be-detected grid in the to-be-detected water area, wherein each water quality detection data change characteristic value in the water quality detection data change characteristic value array corresponds to each to-be-detected grid in the to-be-detected grid array corresponding to the to-be-detected water area;

[0036] The online management cloud platform generates a water quality change dynamic cloud map according to the water quality detection data change characteristic value array, wherein the water quality change dynamic cloud map includes a grid array graphic for representing the grid array to be detected, and color elements filled in each grid graphic element of the grid array graphic, wherein the color intensity of the color element is positively correlated with the corresponding water quality detection data change characteristic value;

[0037] The online management cloud platform sends the dynamic cloud map of water quality changes to the monitoring terminal, so that the monitoring terminal displays the dynamic cloud map of water quality changes.

[0038] In the above scheme, water quality test data is converted into intuitive interactive interface information by generating a dynamic cloud map of water quality changes. The cloud map displayed on the monitoring terminal can clearly reflect the water quality change characteristics of each grid in the water area to be tested, so that managers can understand the water quality status and its changing trends at a glance. Through the real-time update and display of the dynamic cloud map of water quality changes, managers can quickly capture water quality anomalies or potential risks, so as to take timely measures to deal with them, thereby improving the overall efficiency of water quality management.

[0039] In addition, the introduction of monitoring terminals enables the changing characteristic values ​​of water quality test data and its dynamic cloud map to be shared among different departments or teams. This information sharing mechanism promotes cross-departmental collaboration and communication, and helps to form a joint force to jointly deal with water quality issues. Improve user experience: For managers using monitoring terminals, the intuitive display of the dynamic cloud map of water quality changes lowers the threshold for use and improves user experience. Users can quickly understand the water quality status through the cloud map without having to have professional data analysis skills, which improves work efficiency.

[0040] Optionally, the online management cloud platform generates a dynamic cloud map of water quality changes according to the water quality detection data change characteristic value array, and further includes:

[0041] If the online management cloud platform determines that the target water quality detection parameter in the first water quality detection data corresponding to the first grid to be detected is greater than the target water quality detection parameter in the second water quality detection data corresponding to the second grid to be detected, and the first water quality detection data change characteristic value corresponding to the first grid to be detected is greater than the second water quality detection data change characteristic value corresponding to the second grid to be detected, then a diffusion vector element is set between the first grid graphic and the second grid graphic of the grid array graphic, and the diffusion vector element is used to point from the first grid graphic to the second grid graphic, the first grid graphic and the second grid graphic correspond to the first grid to be detected and the second grid to be detected, respectively, and the first grid to be detected and the second grid to be detected are adjacent grids to be detected.

[0042] In the above scheme, by setting diffusion vector elements between adjacent grids of the grid array graph, the diffusion trend of water pollution or change can be intuitively displayed. These diffusion vector elements not only indicate the direction of diffusion, but also reflect the intensity and speed of diffusion through the color, thickness, length and other characteristics of the diffusion vector, providing managers with richer information and helping to more accurately judge the trend and scope of water quality changes.

[0043] It can be seen that the introduction of diffusion vector elements enables the dynamic cloud map of water quality changes to not only display the water quality status, but also reflect the dynamic process of water quality changes.

[0044] In a second aspect, the present application provides a water quality detection management system, including: an online management cloud platform and a plurality of water quality detection sensor sequences, each of which is used to perform water quality detection on a to-be-detected grid in a to-be-detected water area, and the online management cloud platform is communicatively connected with each water quality detection sensor in the water quality detection sensor sequence;

[0045] Acquire first water quality detection data of a first to-be-detected grid in the to-be-detected water area through a first water quality detection sensor sequence, and send the first water quality detection data to the online management cloud platform, wherein the first water quality detection data includes current water quality detection parameters and current detection time acquired by each water quality detection sensor in the first water quality detection sensor sequence;

[0046] The online management cloud platform stores the first water quality detection data, and calls the first water quality historical detection data to determine the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, wherein the first water quality historical detection data is the water quality detection data before the current detection time;

[0047] The online management cloud platform determines the first water quality detection data reporting frequency according to the first water quality detection data change characteristic value, and sends the first water quality detection data reporting frequency to the first water quality detection sensor sequence, so that the first water quality detection sensor sequence feeds back water quality detection data according to the first water quality detection data reporting frequency, and the first water quality detection data reporting frequency is positively correlated with the first water quality detection data change characteristic value.

[0048] Optionally, determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data includes:

[0049] If each water quality detection data in the first water quality detection data is less than the corresponding water quality detection data threshold, the online management cloud platform determines the first water quality detection data change characteristic value according to each water quality detection parameter in the first water quality detection data and each water quality detection parameter in the first water quality historical detection data;

[0050] If a water quality detection parameter greater than a corresponding water quality detection data threshold value exists in the first water quality detection data, the first water quality detection data change characteristic value is determined to be a first preset water quality detection data change characteristic threshold value.

[0051] Optionally, determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data includes:

[0052] The online management cloud platform is based on a first image in the first water quality detection data, where the first image is an image of the first to-be-detected grid at the current detection time;

[0053] The online management cloud platform traverses each pixel in the first image information, and determines the color component mean value corresponding to each color component according to each color component of each pixel in a preset color space;

[0054] The online management cloud platform determines the first water quality color characteristic value according to the color component mean values ​​corresponding to each color component;

[0055] The online management cloud platform determines the first water quality detection data change characteristic value based on the first water quality color characteristic value and the historical water quality color characteristic value corresponding to the first water quality historical detection data.

[0056] Optionally, after determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, the method further includes:

[0057] The online management cloud platform determines the detection time difference according to the first detection time corresponding to the first water quality historical detection data and the current detection time;

[0058] The online management cloud platform updates the first water quality detection data change characteristic value according to the detection time difference to generate an updated water quality detection data change characteristic value, and the updated water quality detection data change characteristic value is used to update the first water quality detection data change characteristic value.

[0059] Optionally, the online management cloud platform determines the reporting frequency of the first water quality detection data according to the characteristic value of the change of the first water quality detection data, including:

[0060] If the first water quality detection data change characteristic value is less than the preset first characteristic value, the online management cloud platform determines that the first water quality detection data reporting frequency is the first reporting frequency;

[0061] If the first water quality detection data change characteristic value is greater than or equal to a preset first characteristic value, and less than a preset second characteristic value, the online management cloud platform determines that the first water quality detection data reporting frequency is a second reporting frequency, and the second reporting frequency is greater than the first reporting frequency;

[0062] If the first water quality detection data change characteristic value is greater than or equal to the preset second characteristic value, and less than or equal to the preset water quality detection data change characteristic threshold, the online management cloud platform determines that the first water quality detection data reporting frequency is the third reporting frequency, and the third reporting frequency is greater than the second reporting frequency.

[0063] Optionally, the water quality detection management system further includes: a monitoring terminal, the monitoring terminal being communicatively connected to the online management cloud platform; correspondingly, after determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, it further includes:

[0064] The online management cloud platform generates a water quality detection data change characteristic value array according to the water quality detection data change characteristic values ​​corresponding to each to-be-detected grid in the to-be-detected water area, wherein each water quality detection data change characteristic value in the water quality detection data change characteristic value array corresponds to each to-be-detected grid in the to-be-detected grid array corresponding to the to-be-detected water area;

[0065] The online management cloud platform generates a water quality change dynamic cloud map according to the water quality detection data change characteristic value array, wherein the water quality change dynamic cloud map includes a grid array graphic for representing the grid array to be detected, and color elements filled in each grid graphic element of the grid array graphic, wherein the color intensity of the color element is positively correlated with the corresponding water quality detection data change characteristic value;

[0066] The online management cloud platform sends the dynamic cloud map of water quality changes to the monitoring terminal, so that the monitoring terminal displays the dynamic cloud map of water quality changes.

[0067] Optionally, the online management cloud platform generates a dynamic cloud map of water quality changes according to the water quality detection data change characteristic value array, and further includes:

[0068] If the online management cloud platform determines that the target water quality detection parameter in the first water quality detection data corresponding to the first grid to be detected is greater than the target water quality detection parameter in the second water quality detection data corresponding to the second grid to be detected, and the first water quality detection data change characteristic value corresponding to the first grid to be detected is greater than the second water quality detection data change characteristic value corresponding to the second grid to be detected, then a diffusion vector element is set between the first grid graphic and the second grid graphic of the grid array graphic, and the diffusion vector element is used to point from the first grid graphic to the second grid graphic, the first grid graphic and the second grid graphic correspond to the first grid to be detected and the second grid to be detected, respectively, and the first grid to be detected and the second grid to be detected are adjacent grids to be detected.

[0069] In a third aspect, the present application provides an electronic device, including:

[0070] processor; and,

[0071] A memory, configured to store executable instructions of the processor;

[0072] The processor is configured to perform any possible method described in the first aspect by executing the executable instructions.

[0073] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement any possible method described in the first aspect.

[0074] The online management method and system for water quality detection data provided in the present application obtain the first water quality detection data of the first grid to be detected in the water area to be detected through the first water quality detection sensor sequence, and send the first water quality detection data to the online management cloud platform so that the online management cloud platform stores the first water quality detection data, and calls the first water quality historical detection data to determine the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, and determine the first water quality detection data reporting frequency according to the first water quality detection data change characteristic value, and then, send the first water quality detection data reporting frequency to the first water quality detection sensor sequence, so that the first water quality detection sensor sequence feeds back the water quality detection data according to the first water quality detection data reporting frequency, thereby realizing dynamic adjustment of the reporting frequency of the water quality detection sensor, which can ensure effective water quality monitoring under limited resources, and avoid unnecessary waste of resources while ensuring data accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0076] Figure 1 is a flow chart of a method for online management of water quality detection data according to an exemplary embodiment of the present application;

[0077] Figure 2 is a flow chart of a method for online management of water quality detection data according to another exemplary embodiment of the present application;

[0078] Figure 3 is a schematic structural diagram of a water quality detection management system according to an exemplary embodiment of the present application;

[0079] Figure 4 It is a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present application.

[0080] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0081] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0082] In order to solve the above problems, the embodiment provided by the present application divides the water area to be tested into multiple grids to be tested by deploying multiple water quality detection sensor sequences, and arranges corresponding water quality detection sensors in each grid. This grid layout ensures comprehensive coverage of water quality data, so that the water quality conditions in the entire water area can be monitored and recorded in real time. The water quality data is collected in real time by the sensors in each grid, ensuring the timeliness and accuracy of the data.

[0083] Among them, the online management cloud platform is the core processing unit of the embodiment provided by this application, which is responsible for receiving, storing and analyzing data from various water quality detection sensors. The cloud platform can not only store the current water quality detection data in real time, but also call historical data and determine the changing characteristic values ​​of the water quality detection data through comparative analysis. This process realizes the intelligent processing of data, helps to identify the trends and patterns of water quality changes, and provides a scientific basis for subsequent management and decision-making.

[0084] According to the changing characteristic values ​​of water quality test data, the online management cloud platform can dynamically adjust the reporting frequency of water quality test data of each grid. When the water quality changes greatly, the reporting frequency is increased to obtain more detailed data updates; when the water quality is relatively stable, the reporting frequency is reduced to reduce the cost of data transmission and processing. This dynamic adjustment mechanism not only improves the flexibility of the monitoring system, but also avoids unnecessary waste of resources.

[0085] In addition, the embodiment provided by this application also introduces image analysis, by traversing each pixel in the water quality image, calculating the mean of the color component, and then determining the water quality color characteristic value. This method realizes the multi-dimensional fusion analysis of water quality data and improves the comprehensiveness and accuracy of water quality assessment. By combining image color information with historical data, the system can more accurately judge the trend and degree of water quality changes.

[0086] In addition, the embodiment provided in the present application also provides a dynamic cloud map of water quality changes, which converts complex water quality detection data into intuitive visual information. Through the cloud map displayed by the monitoring terminal, managers can understand the water quality status and its changing trend of the entire water area at a glance. At the same time, the communication connection between the monitoring terminal and the online management cloud platform realizes real-time data sharing and cross-departmental collaboration, and improves the overall efficiency and effectiveness of water quality management. When abnormal water quality or potential risks are detected, the system can immediately issue an early warning signal and display the diffusion trend of water quality changes through dynamic cloud maps and diffusion vector elements. This early warning and emergency response mechanism helps managers take timely measures to prevent the further spread of water pollution and protect the safety of the ecological environment of the water area.

[0087] Figure 1 FIG. 1 is a flow chart of a method for online management of water quality test data according to an exemplary embodiment of the present application. Figure 1 As shown, the water quality detection data online management method provided in this embodiment includes:

[0088] S101. Acquire first water quality detection data of a first to-be-detected grid in a to-be-detected water area through a first water quality detection sensor sequence.

[0089] The water quality detection data online management method provided in this embodiment can be applied to a water quality detection management system. The water quality detection management system includes an online management cloud platform and multiple water quality detection sensor sequences, each of which is used to perform water quality detection on a grid to be detected in the water area to be detected, and the online management cloud platform is connected in communication with each water quality detection sensor in the water quality detection sensor sequence.

[0090] In this step, the first water quality detection data of the first grid to be detected in the water area to be detected is obtained through the first water quality detection sensor sequence, and the first water quality detection data is sent to the online management cloud platform. The first water quality detection data includes the current water quality detection parameters and the current detection time obtained by each water quality detection sensor in the first water quality detection sensor sequence.

[0091] Specifically, in the water quality detection management system, water quality detection is first performed by deploying a first water quality detection sensor sequence in the first grid to be detected. The sensor sequence includes multiple water quality detection sensors, each of which is responsible for detecting different water quality parameters, such as pH value, dissolved oxygen, ammonia nitrogen content, etc. These sensors will collect the current water quality detection parameters in real time and record the current detection time to form the first water quality detection data. Subsequently, these data are sent to the online management cloud platform through the communication interface for further processing and analysis.

[0092] S102: Determine a first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data.

[0093] In this step, the online management cloud platform stores the first water quality detection data and calls the first water quality historical detection data to determine the first water quality detection data change characteristic value based on the first water quality detection data and the first water quality historical detection data. The first water quality historical detection data is the water quality detection data before the current detection time.

[0094] Specifically, after receiving the first water quality test data, the online management cloud platform first stores it in the cloud database to ensure the reliability and traceability of the data. Subsequently, the cloud platform will call the first water quality historical test data of the first grid to be tested in the previous time period from the database according to the current test time. These data are used for comparative analysis with the current water quality test data to identify the characteristics of water quality changes.

[0095] The online management cloud platform analyzes the first water quality detection data and its corresponding historical data, and uses a preset algorithm to calculate the characteristic value of the change of the first water quality detection data. This characteristic value reflects the trend and degree of change of water quality parameters over time.

[0096] In a possible implementation, if the first water quality detection data P = {p1, p2, ..., p i ,…,p n} are all less than the corresponding water quality detection data threshold, the online management cloud platform uses formula 1 and calculates the value of the first water quality detection data P = {p1, p2, ..., p i ,…,p n} and the first water quality historical detection data Q = {q1, q2, ..., q i ,…,q n}Determine the first water quality detection data change characteristic value k, where p i is the i-th water quality detection data in the first water quality detection data P, n is the number of water quality detection data in the first water quality detection data P, and formula 1 is:

[0097]

[0098] Among them, k1 is the first preset water quality detection data change characteristic threshold;

[0099] If the first water quality detection data P = {p1, p2, ..., p i ,…,p n}, if there is water quality detection data greater than the corresponding water quality detection data threshold, then the first water quality detection data change characteristic value is determined to be the first preset water quality detection data change characteristic threshold

[0100] It is worth noting that in the above formula 1, the relative change rate of each water quality detection parameter between the current value and the historical value (that is, the ratio of the absolute value of the difference to the historical value) is first calculated, and then the maximum value of these change rates is found to reflect the severity of the overall water quality parameter changes.

[0101] By calculating the relative rate of change of each water quality parameter and taking the maximum value of these rates as the characteristic value of change, the overall degree of change of the water quality parameters can be accurately reflected. This method is more sensitive and accurate than simply comparing the absolute values ​​of the parameters, and is particularly suitable for situations where water quality changes are relatively gentle or gradually accumulate. In addition, by introducing the first preset water quality detection data change characteristic threshold, it is possible to effectively avoid excessive impact on the overall water quality change characteristic value due to abnormal fluctuations in a single water quality parameter (such as sudden increase or decrease), which helps the system to more robustly identify the true trend of water quality changes, rather than being misled by short-term abnormal fluctuations.

[0102] Then, the reporting frequency of water quality test data is adjusted dynamically according to the change characteristic value, which can ensure that the monitoring density is increased when the water quality changes greatly and more detailed data is obtained; and the monitoring frequency is reduced when the water quality is relatively stable, thereby optimizing resource allocation and avoiding unnecessary waste of resources. When the characteristic value of water quality change is detected to exceed a certain threshold, the system can respond quickly to water quality problems by increasing the reporting frequency, issuing an alarm or triggering other emergency measures to ensure water quality safety.

[0103] S103. The online management cloud platform determines a reporting frequency of the first water quality detection data according to a characteristic value of a change in the first water quality detection data.

[0104] In this step, the online management cloud platform determines the first water quality detection data reporting frequency according to the first water quality detection data change characteristic value, and sends the first water quality detection data reporting frequency to the first water quality detection sensor sequence, so that the first water quality detection sensor sequence feeds back water quality detection data according to the first water quality detection data reporting frequency, and the first water quality detection data reporting frequency is positively correlated with the first water quality detection data change characteristic value.

[0105] Specifically, the online management cloud platform dynamically adjusts the reporting frequency of the first water quality detection data according to the calculated characteristic value of the change of the first water quality detection data. The specific adjustment rules are as follows:

[0106] If the change characteristic value is less than the preset first characteristic value, it means that the water quality is relatively stable, and the reporting frequency is set to a lower first reporting frequency.

[0107] If the change characteristic value is between the first and second characteristic values, it means that the water quality has a certain fluctuation, and the reporting frequency is increased to the second reporting frequency.

[0108] If the change characteristic value reaches or exceeds the preset second characteristic value, but does not exceed the change characteristic threshold, it means that the water quality has changed significantly, and the reporting frequency is further increased to the third reporting frequency.

[0109] The cloud platform sends the adjusted reporting frequency to the first water quality detection sensor sequence, and the sensor sequence feeds back the water quality detection data to the cloud platform according to the new reporting frequency.

[0110] In this embodiment, first water quality detection data of the first grid to be detected in the water area to be detected is obtained through the first water quality detection sensor sequence, and the first water quality detection data is sent to the online management cloud platform so that the online management cloud platform stores the first water quality detection data, and calls the first water quality historical detection data to determine the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, and determine the first water quality detection data reporting frequency according to the first water quality detection data change characteristic value, and then, the first water quality detection data reporting frequency is sent to the first water quality detection sensor sequence, so that the first water quality detection sensor sequence feeds back the water quality detection data according to the first water quality detection data reporting frequency, thereby realizing dynamic adjustment of the reporting frequency of the water quality detection sensor, which can ensure effective water quality monitoring under limited resources, and avoid unnecessary waste of resources while ensuring data accuracy.

[0111] Figure 2 FIG. 1 is a flow chart of a method for online management of water quality test data according to another exemplary embodiment of the present application. Figure 2 As shown, the water quality detection data online management method provided in this embodiment includes:

[0112] S201. Acquire first water quality detection data of a first to-be-detected grid in a to-be-detected water area through a first water quality detection sensor sequence.

[0113] In this step, the first water quality detection data of the first grid to be detected in the water area to be detected is obtained through the first water quality detection sensor sequence, and the first water quality detection data is sent to the online management cloud platform. The first water quality detection data includes the current water quality detection parameters and the current detection time obtained by each water quality detection sensor in the first water quality detection sensor sequence.

[0114] Specifically, the first water quality detection sensor sequence may include an image sensor, for example, a high-definition camera, through which a water quality image of a first grid to be detected in the water area to be detected is acquired, for example, a water surface image.

[0115] S202: Determine a first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data.

[0116] In this step, the online management cloud platform stores the first water quality detection data and calls the first water quality historical detection data to determine the first water quality detection data change characteristic value based on the first water quality detection data and the first water quality historical detection data. The first water quality historical detection data is the water quality detection data before the current detection time.

[0117] In a possible design, the online management cloud platform is based on a first image in the first water quality detection data, where the first image is an image of the first grid to be detected at the current detection time;

[0118] The online management cloud platform traverses each pixel in the first image information, and determines the color component mean value corresponding to each color component according to each color component of each pixel in a preset color space;

[0119] The online management cloud platform uses formula 2 and determines the first water quality color characteristic value C according to the color component mean value corresponding to each color component. Formula 2 is:

[0120]

[0121] Where R is the number of preset rules in the preset fuzzy rule base, is the jth input parameter x in the i-th rule of the preset fuzzy rule base j For fuzzy sets The membership function, c ij is a fuzzy set The central eigenvalue of ij is a fuzzy set The width eigenvalue, ω i is the output weight of the i-th rule, and m is used to represent the number of color components in the preset color space;

[0122] The online management cloud platform uses formula 3 and calculates the color characteristic value C of the first water quality according to the color characteristic value C of the historical water quality corresponding to the first water quality historical detection data. ′ Determine the first water quality detection data change characteristic value k, formula 3 is:

[0123]

[0124] Among them, k2 is the second preset water quality detection data change characteristic threshold.

[0125] It is worth noting that the above formula 2 is used to calculate the first water quality color feature value, which integrates the color information in the image and is processed by a fuzzy logic system to extract the color characteristics of the water quality. Specifically, by traversing each pixel in the first image and calculating the mean of each color component of each pixel in a preset color space (such as RGB, HSV, etc.), formula 2 can fully capture the color characteristics of the water quality image. By using the preset rules and membership functions in the fuzzy rule library, each color component is fuzzified, making the calculation of the color feature value more flexible and accurate. This processing method can cope with the ambiguity and uncertainty of color information and improve the robustness of color feature extraction. In addition, by assigning different output weights to each fuzzy rule, the adjustment of the importance of different color components and rules can be achieved, thereby optimizing the calculation results of the color feature value. In addition, since water quality color is an important indicator of water quality changes, the color feature value calculated by formula 2 can fully reflect the changes in water quality and provide more abundant information for water quality assessment.

[0126] The above formula 3 is used to calculate the first water quality detection data change characteristic value according to the first water quality color characteristic value C and the historical water quality color characteristic value corresponding to its historical data. Specifically, by calculating the relative change between the current color characteristic value and the historical color characteristic value, formula 3 can quantify the degree of change of water quality color over time, and provide an intuitive indicator for water quality monitoring. In addition, a second preset water quality detection data change characteristic threshold is introduced to ensure that the change characteristic value will not grow indefinitely. When the color change exceeds a certain threshold, the change characteristic value will be limited to the second preset water quality detection data change characteristic threshold, which helps to avoid data anomalies in extreme cases. The calculated water quality detection data change characteristic value will be directly used to guide the reporting frequency of water quality detection data. When the color change is large, it means that the water quality may change significantly. At this time, the data reporting frequency should be increased to obtain more detailed water quality information; on the contrary, when the color change is small, the reporting frequency can be appropriately reduced to save resources. It can be seen that the dynamic adjustment of the reporting frequency through the calculation result of formula 3 can not only ensure that sufficient data support is obtained at critical moments, but also reduce unnecessary data transmission and processing costs when the water quality is relatively stable, thereby improving the overall monitoring efficiency.

[0127] Furthermore, the online management cloud platform may also determine the detection time difference Δt according to the first detection time corresponding to the first water quality historical detection data and the current detection time;

[0128] The online management cloud platform uses formula 4 and updates the first water quality detection data change characteristic value k according to the detection time difference Δt to generate an updated water quality detection data change characteristic value. The updated water quality detection data change characteristic value is used to update the first water quality detection data change characteristic value. Formula 4 is:

[0129]

[0130] Among them, k ′ To update the water quality detection data change characteristic value, update the water quality detection data change characteristic value k ′ Used to update the first water quality detection data change characteristic value k.

[0131] It is worth noting that by introducing the detection time difference, Formula 4 realizes the dynamic adjustment of the characteristic value of water quality detection data change. This adjustment method takes into account the time factor, so that the characteristic value can more accurately reflect the time rate of water quality change, and provide more refined data support for subsequent monitoring and decision-making. The introduction of the detection time difference enhances the timeliness of the data. As time goes by, the water quality status may change. By updating the characteristic value considering the time difference, it can be ensured that the characteristic value is always synchronized with the current water quality status, avoiding misjudgment or delayed processing due to data lag. The updated characteristic value of water quality detection data change will be directly used to guide the optimization of water quality monitoring strategy. When the time difference is small and the characteristic value is large, it means that the water quality has changed significantly in a short period of time. At this time, it is necessary to increase the monitoring frequency to obtain more detailed data; on the contrary, when the time difference is large and the characteristic value does not change much, the monitoring frequency can be appropriately reduced to save resources.

[0132] By dynamically adjusting the reporting frequency of water quality test data, the application of Formula 4 can improve the overall efficiency of water quality monitoring. Increasing the monitoring frequency in key areas or time periods can help capture the details of water quality changes in a timely manner; while reducing the monitoring frequency in relatively stable areas or time periods can reduce the cost of data transmission and processing and achieve optimal allocation of resources.

[0133] The real-time updated water quality test data change characteristic values ​​enable the online management cloud platform to respond to water quality changes more quickly. Once abnormal or trending changes in water quality are found, the system can immediately take measures to intervene, such as adjusting monitoring parameters, issuing alarms, etc., to ensure water quality safety.

[0134] S203. The online management cloud platform determines the reporting frequency of the first water quality detection data according to the characteristic value of the change of the first water quality detection data.

[0135] In this step, the online management cloud platform determines the first water quality detection data reporting frequency according to the first water quality detection data change characteristic value, and sends the first water quality detection data reporting frequency to the first water quality detection sensor sequence, so that the first water quality detection sensor sequence feeds back water quality detection data according to the first water quality detection data reporting frequency, and the first water quality detection data reporting frequency is positively correlated with the first water quality detection data change characteristic value.

[0136] In a possible implementation, if the first water quality detection data change characteristic value is less than a preset first characteristic value, the online management cloud platform determines that the first water quality detection data reporting frequency is the first reporting frequency;

[0137] If the first water quality detection data change characteristic value is greater than or equal to the preset first characteristic value, and less than the preset second characteristic value, the online management cloud platform determines that the first water quality detection data reporting frequency is the second reporting frequency, and the second reporting frequency is greater than the first reporting frequency;

[0138] If the first water quality detection data change characteristic value is greater than or equal to the preset second characteristic value, and less than or equal to the preset water quality detection data change characteristic threshold, the online management cloud platform determines that the first water quality detection data reporting frequency is the third reporting frequency, and the third reporting frequency is greater than the second reporting frequency.

[0139] Specifically, the system can preset three characteristic value thresholds: preset first characteristic value, preset second characteristic value and preset water quality detection data change characteristic threshold. These thresholds are set according to historical data analysis and actual monitoring needs to guide the adjustment of reporting frequency.

[0140] When the calculated first water quality detection data change characteristic value k is less than the preset first characteristic value, it indicates that the water quality change is relatively stable. The online management cloud platform will determine the reporting frequency of the first water quality detection data as the first reporting frequency, which is relatively low, to reduce data transmission and processing costs.

[0141] When the first water quality detection data change characteristic value is greater than or equal to the preset first characteristic value and less than the preset second characteristic value, it indicates that the water quality has begun to change to a certain extent and the monitoring density needs to be appropriately increased. Therefore, the platform adjusts the reporting frequency to the second reporting frequency.

[0142] When the first water quality test data change characteristic value is greater than or equal to the preset second characteristic value and less than or equal to the preset water quality test data change characteristic threshold, it indicates that the water quality has changed significantly or there may be an abnormality, which requires close attention. At this time, the platform sets the reporting frequency to the third reporting frequency to ensure that sufficiently frequent data updates can be obtained.

[0143] By dynamically adjusting the reporting frequency, the system can reasonably allocate monitoring resources according to the actual situation of water quality changes. When the water quality is stable, data transmission can be reduced to save costs; when the water quality changes significantly, the monitoring density can be increased to ensure the timeliness of the data.

[0144] Increasing the reporting frequency during critical periods helps capture the details of water quality changes and provide more accurate data support for water quality management and decision-making. At the same time, reducing the reporting frequency during stable periods avoids unnecessary data transmission and processing, thereby improving monitoring efficiency.

[0145] When water quality is abnormal or changes significantly, the system can quickly adjust the reporting frequency to ensure timely acquisition and processing of relevant data. This rapid response mechanism helps to quickly identify problems and take corresponding measures to ensure water quality safety.

[0146] The entire reporting frequency adjustment process is based on automatic analysis and algorithm judgment, realizing the automation and intelligent management of water quality monitoring. By presetting characteristic value thresholds and dynamic adjustment strategies, the system can automatically adapt to changes in water quality, improving the flexibility and accuracy of management. In addition, for managers using monitoring terminals, dynamically adjusting the reporting frequency not only improves the validity and accuracy of data, but also reduces unnecessary information interference. This allows managers to focus more on changes in key data, improving work efficiency and user experience.

[0147] S204. The online management cloud platform generates a water quality detection data change characteristic value array according to the water quality detection data change characteristic values ​​corresponding to each to-be-detected grid in the to-be-detected water area.

[0148] In this embodiment, the water quality detection and management system may also include: a monitoring terminal, and the monitoring terminal is communicatively connected to the online management cloud platform.

[0149] In this step, the online management cloud platform generates a water quality detection data change characteristic value array according to the water quality detection data change characteristic value corresponding to each grid to be detected in the water area to be detected, and each water quality detection data change characteristic value in the water quality detection data change characteristic value array corresponds to each grid to be detected in the grid array to be detected corresponding to the water area to be detected.

[0150] S205. The online management cloud platform generates a dynamic cloud map of water quality changes based on the characteristic value array of water quality detection data changes.

[0151] In this step, the online management cloud platform generates a dynamic cloud map of water quality changes based on the water quality detection data change characteristic value array. The dynamic cloud map of water quality changes includes a grid array graphic for representing the grid array to be detected, and color elements filled in each grid graphic element of the grid array graphic, wherein the color intensity of the color element is positively correlated with the corresponding water quality detection data change characteristic value.

[0152] Furthermore, if the online management cloud platform determines that the target water quality detection parameter in the first water quality detection data corresponding to the first grid to be detected is greater than the target water quality detection parameter in the second water quality detection data corresponding to the second grid to be detected, and the first water quality detection data change characteristic value corresponding to the first grid to be detected is greater than the second water quality detection data change characteristic value corresponding to the second grid to be detected, then a diffusion vector element is set between the first grid graphic and the second grid graphic of the grid array graphic, and the diffusion vector element is used to point from the first grid graphic to the second grid graphic, wherein the first grid graphic and the second grid graphic correspond to the first grid to be detected and the second grid to be detected, respectively, and the first grid to be detected and the second grid to be detected are adjacent grids to be detected.

[0153] Specifically, the online management cloud platform first extracts the target water quality detection parameters based on the water quality detection data corresponding to each grid to be detected in the water area to be detected. These parameters may include but are not limited to dissolved oxygen content, ammonia nitrogen content, pH value, etc., depending on the monitoring requirements and system configuration.

[0154] Next, for any two adjacent grids to be detected (such as the first grid to be detected and the second grid to be detected), the platform will compare their target water quality detection parameter values ​​and the corresponding water quality detection data change characteristic values ​​at the same time point.

[0155] If it is found that the target water quality detection parameter value of the first grid to be detected is greater than the corresponding value of the second grid to be detected, and the water quality detection data change characteristic value of the first grid to be detected is also greater than the corresponding value of the second grid to be detected, this indicates that there may be water quality pollution or significant changes in the first grid to be detected, and there is a tendency to spread to the second grid to be detected.

[0156] Once the diffusion trend of water quality changes or pollution is determined, the online management cloud platform will set diffusion vector elements between the corresponding first grid graphic (representing the first grid to be detected) and the second grid graphic (representing the second grid to be detected) on the generated dynamic cloud map of water quality changes.

[0157] Diffusion vector elements can be represented by arrows pointing from the first grid graphic to the second grid graphic, intuitively showing the diffusion direction of water pollution or changes. To enhance the visualization effect, diffusion vector elements can also be dynamically adjusted according to the intensity and speed of water quality changes. For example, areas with faster diffusion speeds can be represented by longer and thicker arrows; areas with greater diffusion intensity can be highlighted by using darker arrows or adding a flashing effect.

[0158] As water quality test data is continuously updated, the online management cloud platform will calculate and update the water quality test data change characteristic values ​​of each grid to be tested and the diffusion trend between adjacent grids in real time. The system will generate new dynamic cloud maps of water quality changes regularly or as needed and display them on the monitoring terminal. Monitoring personnel can quickly identify the diffusion direction and speed of water quality pollution or changes by observing the diffusion vector elements on the cloud map, and take corresponding countermeasures.

[0159] In the above scheme, by setting diffusion vector elements between adjacent grids of the grid array graphic, the diffusion trend of water pollution or changes can be intuitively displayed. These diffusion vector elements not only indicate the direction of diffusion, but also reflect the intensity and speed of diffusion through the color, thickness, length and other characteristics of the diffusion vector, providing managers with richer information and helping to more accurately judge the trend and scope of water quality changes. It can be seen that the introduction of diffusion vector elements enables the dynamic cloud map of water quality changes to reflect the dynamic process of water quality changes while showing the water quality status.

[0160] It is worth noting that the online management cloud platform can also obtain all the grids to be detected adjacent to the first grid to be detected to form a sequence of adjacent grids to be detected. If the online management cloud platform determines that the target water quality detection parameter in the first water quality detection data corresponding to the first grid to be detected is greater than the target water quality detection parameter in the water quality detection data of any grid to be detected in the adjacent grid sequence to be detected and / or the first water quality detection data change characteristic value corresponding to the first grid to be detected is greater than the water quality detection data change characteristic value of any grid to be detected in the adjacent grid sequence to be detected, a feature mark is generated on the first grid graphic of the grid array graphic.

[0161] Specifically, the online management cloud platform first determines all the grids to be detected that are adjacent to the first grid to be detected (hereinafter referred to as the "target grid"). This usually includes grids that share boundaries or vertices with the target grid. These adjacent grids can be efficiently found through spatial relationship query or index mechanism.

[0162] The system collects water quality detection data of the target grid and its adjacent grids (forming a sequence of adjacent grids to be detected), especially target water quality detection parameters and their corresponding water quality detection data change characteristic values.

[0163] Then, the system compares the water quality test data of the target grid with the water quality test data of its adjacent grids. If a target water quality test parameter of the target grid is greater than the corresponding parameter of any adjacent grid, or the characteristic value of the change of the water quality test data of the target grid is greater than the corresponding value of any adjacent grid, the system will identify the target grid as an abnormal or key focus grid.

[0164] Once the target grid is identified as an abnormal or focused grid, the online management cloud platform will generate feature marks on the corresponding target grid graphic (i.e., the first grid graphic) on the grid array graphic of the generated water quality change dynamic cloud map. These feature marks can be special color filling, bold borders, highlights, or specific icons to attract the attention of monitoring personnel.

[0165] The updated dynamic cloud map of water quality changes will be sent to the monitoring terminal for display. The monitoring personnel can intuitively see which grids are abnormal or need special attention, so as to take timely measures to deal with possible water quality problems. As the water quality test data is continuously updated, the system will regularly re-evaluate the water quality status of each grid and update the dynamic cloud map of water quality changes to ensure that the monitoring personnel can always obtain the latest water quality information.

[0166] By generating feature marks directly on the grid array graphics, the system can quickly attract the attention of monitoring personnel, enabling them to quickly locate grids with abnormal water quality. This greatly improves the efficiency of anomaly detection and helps to promptly detect and deal with water quality problems. Feature marks not only indicate the location of abnormal grids, but also provide monitoring personnel with an intuitive overview of water quality conditions through their significant performance on the cloud map. This enables monitoring personnel to make more accurate and timely decisions based on comprehensive water quality information. The system helps monitoring personnel focus limited resources and attention on areas that need the most attention by automatically identifying and marking abnormal grids. This helps to optimize the allocation of water quality monitoring and management resources and improve overall monitoring efficiency and management effectiveness. For monitoring personnel, the introduction of feature marks reduces the threshold for use and the complexity of data analysis. Monitoring personnel can quickly understand the water quality status through intuitive cloud maps without having to deeply understand the complex data analysis process, thereby improving user experience and work efficiency.

[0167] S206. The online management cloud platform sends the dynamic cloud map of water quality changes to the monitoring terminal.

[0168] The online management cloud platform sends the dynamic cloud map of water quality changes to the monitoring terminal, so that the monitoring terminal displays the dynamic cloud map of water quality changes.

[0169] In addition, it is worth noting that in the embodiments provided above, the water area to be inspected can be a closed indoor water area, such as a farm, especially a cage farm. In the water quality detection management system, it can also include a drain array and a water inlet array arranged in the water area to be inspected. After determining that the first water quality detection data reporting frequency is the third reporting frequency, the online management cloud platform can also determine the distance between the grid center position of the first grid to be inspected and the positions of each drain in the drain array, and at least determine the drain with the smallest distance as the target drain;

[0170] The online management cloud platform generates a drainage instruction, which is used to instruct the target drainage outlet to perform a drainage operation; and / or,

[0171] The online management cloud platform determines the distance between the grid center position of the first to-be-detected grid and the positions of each water inlet in the water inlet array, and at least determines the water inlet with the shortest distance as the target drain outlet;

[0172] The online management cloud platform generates water inlet instructions, which are used to instruct the target water inlet to perform water inlet operations.

[0173] Specifically, in the water quality monitoring of closed indoor waters, when the first water quality detection data reporting frequency is determined to be the third reporting frequency (i.e., the highest frequency), the system will further perform automatic control measures to improve the water quality. The following are the specific implementation steps:

[0174] Determine the target drain outlet:

[0175] The online management cloud platform first obtains the grid center position coordinates of the first grid to be detected.

[0176] Then, the distance between the center position and each drain position in the drain array is calculated.

[0177] The drain outlet with the shortest distance is selected as the target drain outlet so as to drain the water from the polluted area as quickly as possible.

[0178] Generate and execute drain instructions:

[0179] The online management cloud platform automatically generates drainage instructions based on the location information of the target drain outlet.

[0180] The command is sent to the control system of the target drain outlet via network communication, instructing it to start the drainage operation to quickly discharge the polluted water.

[0181] Optionally, determine the target water inlet:

[0182] If fresh water needs to be added to accelerate the recovery of water quality, the system will also calculate the distance between the first grid to be detected and each water inlet in the water inlet array.

[0183] Select the water inlet with the shortest distance as the target water inlet.

[0184] Generate and execute water inlet instructions:

[0185] The online management cloud platform generates water inlet instructions for the target water inlet.

[0186] The command is sent to the control system of the target water inlet through the network, instructing it to start the water inlet operation and introduce fresh water to improve the water quality.

[0187] When water quality monitoring data shows that water quality has deteriorated and reached a level that requires emergency treatment, the system can quickly locate the nearest drain and / or water inlet, and automatically generate and execute control instructions. This immediate response mechanism greatly shortens the processing time of water quality anomalies and effectively prevents the spread of pollution. By calculating the precise distance between the grid to be detected and the drain and water inlet, the system can select the optimal control point for operation, thereby achieving optimal allocation of water resources and maximizing the efficiency of use. Timely drainage and water inlet operations help to quickly restore water quality, protect the ecological environment of indoor waters, and promote the sustainable use of water resources.

[0188] Figure 3 Schematic diagram of a water quality detection management system according to an exemplary embodiment of the present application. Figure 3 As shown, the water quality detection management system 300 provided in this embodiment includes:

[0189] An online management cloud platform 310 and a plurality of water quality detection sensor sequences 320, each of which is used to perform water quality detection on a to-be-detected grid in the to-be-detected water area, and the online management cloud platform 310 is in communication connection with each water quality detection sensor in the water quality detection sensor sequence 320;

[0190] Acquire first water quality detection data of a first to-be-detected grid in the to-be-detected water area through the first water quality detection sensor sequence 320, and send the first water quality detection data to the online management cloud platform 310, wherein the first water quality detection data includes current water quality detection parameters and current detection time acquired by each water quality detection sensor in the first water quality detection sensor sequence 320;

[0191] The online management cloud platform 310 stores the first water quality detection data, and calls the first water quality historical detection data to determine the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, wherein the first water quality historical detection data is the water quality detection data before the current detection time;

[0192] The online management cloud platform 310 determines a first water quality detection data reporting frequency according to the first water quality detection data change characteristic value, and sends the first water quality detection data reporting frequency to the first water quality detection sensor sequence 320, so that the first water quality detection sensor sequence 320 feeds back water quality detection data according to the first water quality detection data reporting frequency, and the first water quality detection data reporting frequency is positively correlated with the first water quality detection data change characteristic value.

[0193] Optionally, determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data includes:

[0194] If each water quality detection data in the first water quality detection data is less than the corresponding water quality detection data threshold, the online management cloud platform 310 determines the first water quality detection data change characteristic value according to each water quality detection parameter in the first water quality detection data and each water quality detection parameter in the first water quality historical detection data;

[0195] If a water quality detection parameter greater than a corresponding water quality detection data threshold value exists in the first water quality detection data, the first water quality detection data change characteristic value is determined to be a first preset water quality detection data change characteristic threshold value.

[0196] Optionally, determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data includes:

[0197] The online management cloud platform 310 is based on the first image in the first water quality detection data, where the first image is an image of the first to-be-detected grid at the current detection time;

[0198] The online management cloud platform 310 traverses each pixel in the first image information, and determines the color component mean value corresponding to each color component according to each color component of each pixel in a preset color space;

[0199] The online management cloud platform 310 determines the first water quality color characteristic value according to the color component mean values ​​corresponding to each color component;

[0200] The online management cloud platform 310 determines the first water quality detection data change characteristic value according to the first water quality color characteristic value and the historical water quality color characteristic value corresponding to the first water quality historical detection data.

[0201] Optionally, after determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, the method further includes:

[0202] The online management cloud platform 310 determines the detection time difference according to the first detection time corresponding to the first water quality historical detection data and the current detection time;

[0203] The online management cloud platform 310 updates the first water quality detection data change characteristic value according to the detection time difference to generate an updated water quality detection data change characteristic value, and the updated water quality detection data change characteristic value is used to update the first water quality detection data change characteristic value.

[0204] Optionally, the online management cloud platform 310 determines the first water quality detection data reporting frequency according to the first water quality detection data change characteristic value, including:

[0205] If the first water quality detection data change characteristic value is less than the preset first characteristic value, the online management cloud platform 310 determines that the first water quality detection data reporting frequency is the first reporting frequency;

[0206] If the first water quality detection data change characteristic value is greater than or equal to a preset first characteristic value and less than a preset second characteristic value, the online management cloud platform 310 determines that the first water quality detection data reporting frequency is a second reporting frequency, and the second reporting frequency is greater than the first reporting frequency;

[0207] If the first water quality detection data change characteristic value is greater than or equal to the preset second characteristic value, and less than or equal to the preset water quality detection data change characteristic threshold, the online management cloud platform 310 determines that the first water quality detection data reporting frequency is the third reporting frequency, and the third reporting frequency is greater than the second reporting frequency.

[0208] Optionally, the water quality detection management system further includes: a monitoring terminal 330, the monitoring terminal 330 is communicatively connected to the online management cloud platform 310; correspondingly, after determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, it also includes:

[0209] The online management cloud platform 310 generates a water quality detection data change characteristic value array according to the water quality detection data change characteristic values ​​corresponding to each to-be-detected grid in the to-be-detected water area, wherein each water quality detection data change characteristic value in the water quality detection data change characteristic value array corresponds to each to-be-detected grid in the to-be-detected grid array corresponding to the to-be-detected water area;

[0210] The online management cloud platform 310 generates a water quality change dynamic cloud map according to the water quality detection data change characteristic value array, wherein the water quality change dynamic cloud map includes a grid array graphic for representing the grid array to be detected, and color elements filled in each grid graphic element of the grid array graphic, wherein the color intensity of the color element is positively correlated with the corresponding water quality detection data change characteristic value;

[0211] The online management cloud platform 310 sends the dynamic cloud map of water quality changes to the monitoring terminal 330, so that the monitoring terminal 330 displays the dynamic cloud map of water quality changes.

[0212] Optionally, the online management cloud platform 310 generates a dynamic cloud map of water quality changes according to the water quality detection data change characteristic value array, and further includes:

[0213] If the online management cloud platform 310 determines that the target water quality detection parameter in the first water quality detection data corresponding to the first grid to be detected is greater than the target water quality detection parameter in the second water quality detection data corresponding to the second grid to be detected, and the first water quality detection data change characteristic value corresponding to the first grid to be detected is greater than the second water quality detection data change characteristic value corresponding to the second grid to be detected, then a diffusion vector element is set between the first grid graphic and the second grid graphic of the grid array graphic, and the diffusion vector element is used to point from the first grid graphic to the second grid graphic, the first grid graphic and the second grid graphic correspond to the first grid to be detected and the second grid to be detected, respectively, and the first grid to be detected and the second grid to be detected are adjacent grids to be detected.

[0214] Figure 4 is a schematic diagram of the structure of an electronic device according to an exemplary embodiment of the present application. Figure 4 As shown, this embodiment provides an electronic device 400, including: a processor 401 and a memory 402; wherein:

[0215] The memory 402 is used to store computer programs, and the memory may also be a flash memory.

[0216] The processor 401 is used to execute the execution instructions stored in the memory to implement each step in the above method. For details, please refer to the relevant description in the above method embodiment.

[0217] Optionally, the memory 402 may be independent or integrated with the processor 401 .

[0218] When the memory 402 is a device independent of the processor 401, the electronic device 400 may further include:

[0219] The bus 403 is used to connect the memory 402 and the processor 401 .

[0220] This embodiment further provides a readable storage medium, in which a computer program is stored. When at least one processor of an electronic device executes the computer program, the electronic device executes the methods provided in the above-mentioned various implementation modes.

[0221] This embodiment also provides a program product, which includes a computer program stored in a readable storage medium. At least one processor of the electronic device can read the computer program from the readable storage medium, and at least one processor executes the computer program so that the electronic device implements the methods provided in the above various embodiments.

[0222] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0223] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for online management of water quality detection data, characterized in that: Applied to a water quality detection management system, the water quality detection management system includes an online management cloud platform and a plurality of water quality detection sensor sequences, each of the water quality detection sensor sequences is used to perform water quality detection on a to-be-detected grid in a to-be-detected water area, and the online management cloud platform is communicatively connected with each water quality detection sensor in the water quality detection sensor sequence; the method includes: Acquire first water quality detection data of a first to-be-detected grid in the to-be-detected water area through a first water quality detection sensor sequence, and send the first water quality detection data to the online management cloud platform, wherein the first water quality detection data includes current water quality detection parameters and current detection time acquired by each water quality detection sensor in the first water quality detection sensor sequence; The online management cloud platform stores the first water quality detection data, and calls the first water quality historical detection data to determine the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, wherein the first water quality historical detection data is the water quality detection data before the current detection time; The online management cloud platform determines the first water quality detection data reporting frequency according to the first water quality detection data change characteristic value, and sends the first water quality detection data reporting frequency to the first water quality detection sensor sequence, so that the first water quality detection sensor sequence feeds back water quality detection data according to the first water quality detection data reporting frequency, and the first water quality detection data reporting frequency is positively correlated with the first water quality detection data change characteristic value.

2. The method for online management of water quality detection data according to claim 1, characterized in that: The determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data includes: If each water quality detection data in the first water quality detection data is less than the corresponding water quality detection data threshold, the online management cloud platform determines the first water quality detection data change characteristic value according to each water quality detection parameter in the first water quality detection data and each water quality detection parameter in the first water quality historical detection data; If a water quality detection parameter greater than a corresponding water quality detection data threshold value exists in the first water quality detection data, the first water quality detection data change characteristic value is determined to be a first preset water quality detection data change characteristic threshold value.

3. The method for online management of water quality detection data according to claim 1, characterized in that: The determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data includes: The online management cloud platform is based on a first image in the first water quality detection data, where the first image is an image of the first to-be-detected grid at the current detection time; The online management cloud platform traverses each pixel in the first image information, and determines the color component mean value corresponding to each color component according to each color component of each pixel in a preset color space; The online management cloud platform determines the first water quality color characteristic value according to the color component mean values ​​corresponding to each color component; The online management cloud platform determines the first water quality detection data change characteristic value based on the first water quality color characteristic value and the historical water quality color characteristic value corresponding to the first water quality historical detection data.

4. The method for online management of water quality detection data according to claim 2 or 3, characterized in that: After determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, the method further includes: The online management cloud platform determines the detection time difference according to the first detection time corresponding to the first water quality historical detection data and the current detection time; The online management cloud platform updates the first water quality detection data change characteristic value according to the detection time difference to generate an updated water quality detection data change characteristic value, and the updated water quality detection data change characteristic value is used to update the first water quality detection data change characteristic value.

5. The method for online management of water quality detection data according to claim 2 or 3, characterized in that: The online management cloud platform determines the reporting frequency of the first water quality detection data according to the first water quality detection data change characteristic value, including: If the first water quality detection data change characteristic value is less than the preset first characteristic value, the online management cloud platform determines that the first water quality detection data reporting frequency is the first reporting frequency; If the first water quality detection data change characteristic value is greater than or equal to a preset first characteristic value, and less than a preset second characteristic value, the online management cloud platform determines that the first water quality detection data reporting frequency is a second reporting frequency, and the second reporting frequency is greater than the first reporting frequency; If the first water quality detection data change characteristic value is greater than or equal to the preset second characteristic value, and less than or equal to the preset water quality detection data change characteristic threshold, the online management cloud platform determines that the first water quality detection data reporting frequency is the third reporting frequency, and the third reporting frequency is greater than the second reporting frequency.

6. The method for online management of water quality detection data according to claim 2 or 3, characterized in that: The water quality detection management system further includes: a monitoring terminal, which is in communication connection with the online management cloud platform; correspondingly, after determining the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, it also includes: The online management cloud platform generates a water quality detection data change characteristic value array according to the water quality detection data change characteristic values ​​corresponding to each to-be-detected grid in the to-be-detected water area, wherein each water quality detection data change characteristic value in the water quality detection data change characteristic value array corresponds to each to-be-detected grid in the to-be-detected grid array corresponding to the to-be-detected water area; The online management cloud platform generates a water quality change dynamic cloud map according to the water quality detection data change characteristic value array, wherein the water quality change dynamic cloud map includes a grid array graphic for representing the grid array to be detected, and color elements filled in each grid graphic element of the grid array graphic, wherein the color intensity of the color element is positively correlated with the corresponding water quality detection data change characteristic value; The online management cloud platform sends the dynamic cloud map of water quality changes to the monitoring terminal, so that the monitoring terminal displays the dynamic cloud map of water quality changes.

7. The method for online management of water quality detection data according to claim 6, characterized in that: The online management cloud platform generates a dynamic cloud map of water quality changes according to the water quality detection data change characteristic value array, and further includes: If the online management cloud platform determines that the target water quality detection parameter in the first water quality detection data corresponding to the first grid to be detected is greater than the target water quality detection parameter in the second water quality detection data corresponding to the second grid to be detected, and the first water quality detection data change characteristic value corresponding to the first grid to be detected is greater than the second water quality detection data change characteristic value corresponding to the second grid to be detected, then a diffusion vector element is set between the first grid graphic and the second grid graphic of the grid array graphic, and the diffusion vector element is used to point from the first grid graphic to the second grid graphic, the first grid graphic and the second grid graphic correspond to the first grid to be detected and the second grid to be detected, respectively, and the first grid to be detected and the second grid to be detected are adjacent grids to be detected.

8. A water quality detection and management system, characterized in that: include: An online management cloud platform and a plurality of water quality detection sensor sequences, each of which is used to perform water quality detection on a to-be-detected grid in a to-be-detected water area, and the online management cloud platform is communicatively connected with each water quality detection sensor in the water quality detection sensor sequence; Acquire first water quality detection data of a first to-be-detected grid in the to-be-detected water area through a first water quality detection sensor sequence, and send the first water quality detection data to the online management cloud platform, wherein the first water quality detection data includes current water quality detection parameters and current detection time acquired by each water quality detection sensor in the first water quality detection sensor sequence; The online management cloud platform stores the first water quality detection data, and calls the first water quality historical detection data to determine the first water quality detection data change characteristic value according to the first water quality detection data and the first water quality historical detection data, wherein the first water quality historical detection data is the water quality detection data before the current detection time; The online management cloud platform determines the first water quality detection data reporting frequency according to the first water quality detection data change characteristic value, and sends the first water quality detection data reporting frequency to the first water quality detection sensor sequence, so that the first water quality detection sensor sequence feeds back water quality detection data according to the first water quality detection data reporting frequency, and the first water quality detection data reporting frequency is positively correlated with the first water quality detection data change characteristic value.

9. An electronic device, characterized in that: include: processor; as well as, A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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