Water quality on-line monitoring system and method

Abstract

The invention relates to the technical field of data analysis, and particularly discloses a water quality on-line monitoring system and method, and the system comprises a server and a terminal; the server is used for acquiring water regimen data, water quality data and pollution monitoring data; the analysis module is used for analyzing the water regimen data, the water quality data and the pollution monitoring data and identifying pollution events; the server is used for creating an emergency patrol task according to the pollution event and sending the emergency patrol task to the terminal; the server is also used for counting the execution times of the emergency patrol task of the patrol user, judging whether the execution times exceed a threshold value or not, and marking the patrol user as an experience patrol user if the execution times exceed the threshold value; and the server is also used for receiving a self-established daily patrol plan uploaded by the experienced user through the terminal and replacing a preset daily patrol plan. According to the technical scheme, the monitoring data and the patrol task distribution link are linked, the patrol effect is improved, and the water pollution occurrence probability is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data analysis, in particular to a water quality online monitoring system and method. BACKGROUND

[0002] In recent years, with the increasing demand for comprehensive management of river basin water environment, the traditional water quality monitoring mode has gradually exposed some core problems such as serious data island and insufficient cross-system cooperation. The existing monitoring system usually operates independently based on scattered sensing devices, manual patrol records and multi-source business systems (such as sewage treatment facility operation data, section water quality parameters, pollution source account, etc.), resulting in a lack of effective correlation between basic data, water quality data, water regime data, pollution source data and river patrol management information, making it difficult to achieve unified analysis and dynamic decision-making. For example, water quality abnormal events often need to rely on manual data retrieval and comparison by multiple departments, which is inefficient and difficult to accurately trace the source, seriously restricting the timeliness and scientificity of water environment management.

[0003] In the prior art, although there are water quality online monitoring systems based on the Internet of Things, their functions are mostly limited to single-point data collection and visualization display, and they lack the ability of standardized access, correlation analysis and deep mining of multi-source heterogeneous data. At the same time, for manual patrol, it is usually a one-way task assignment, which is difficult to mobilize the enthusiasm of the patrol personnel and to achieve early detection and early disposal.

[0004] Therefore, there is a need for a water quality online monitoring system and method that can link monitoring data with patrol task assignment links, improve patrol effectiveness and reduce the probability of water pollution. SUMMARY

[0005] One of the purposes of the present application is to provide a water quality online monitoring system that can link monitoring data with patrol task assignment links, improve patrol effectiveness and reduce the probability of water pollution.

[0006] To solve the above technical problems, the present application provides the following technical solutions:

[0007] A water quality online monitoring system, comprising a server and a terminal; the server comprises a data acquisition module, a data storage module, a data analysis module, a warning module and a task management module;

[0008] The terminal comprises a management end and a patrol end;

[0009] The data acquisition module is used to acquire water regime data, water quality data and pollution monitoring data;

[0010] The data storage module is used to preprocess and store the water regime data, water quality data and pollution monitoring data;

[0011] The data analysis module is configured to analyze water regime data, water quality data, and pollution monitoring data, and identify pollution events.

[0012] The early warning module is configured to generate pollution early warning information based on the pollution events, and send the early warning information to the management terminal.

[0013] The task management module is configured to create an emergency patrol task based on the pollution events, and send the emergency patrol task to the patrol terminal, and is further configured to count the number of times of execution of the emergency patrol task by a patrol user, and determine whether the number of times of execution exceeds a threshold value, and if the number of times of execution exceeds the threshold value, mark the patrol user as an experienced patrol user, and is further configured to receive a self-built daily patrol plan uploaded by the experienced user through the patrol terminal, and replace a preset daily patrol plan.

[0014] Further, the task management module is further configured to determine a verification period based on a patrol period, and determine whether a pollution event occurs in the patrol range in the verification period, and if no pollution event occurs, record as a valid self-built patrol, wherein the verification period is from the end time of the patrol to the start time of the next patrol.

[0015] Further, the task management module is further configured to determine whether the number of times of the valid self-built patrol exceeds a preset number of times, and if the number of times exceeds the preset number of times, open a patrol frequency setting permission.

[0016] Further, the server further comprises a reporting module, and the terminal further comprises a public terminal.

[0017] The reporting module is configured to receive pollution information reported by the public terminal, analyze the reported pollution information, and determine whether the reported pollution information is true, and if the reported pollution information is true, identify the reported pollution information as a pollution event.

[0018] Further, the task management module is further configured to receive a field situation briefing uploaded by the patrol terminal.

[0019] Further, the analysis performed by the analysis module includes index trend analysis, threshold value analysis, and spatial correlation analysis.

[0020] Further, the reported pollution information includes a photo, a pollution situation text description, a discovery time, and a discovery location.

[0021] Further, the data collection module is configured to acquire fixed-point monitoring video data and unmanned aerial vehicle aerial video data.

[0022] The task management module is further configured to determine a duration of time during which no pollution event occurs after the self-built daily patrol plan is executed, and if the duration of time exceeds a preset pollution-free time, open an access permission to video data of a corresponding patrol terminal.

[0023] Further, the analysis module is also used for counting whether the public reported pollution information appears on the patrol route of the self-built patrol plan in history, if exists, the analysis module is also used for analyzing the relationship between the discovery time of the public reported pollution and the patrol time period in the self-built patrol plan, judging whether the self-built patrol plan has a preventive effect on the pollution event not automatically monitored and discovered; if has the preventive effect, marking as a professional patrol user.

[0024] The second purpose of the present application is to provide a water quality online monitoring method using the above system.

[0025] The present scheme realizes intelligent identification of pollution events through standardized collection and analysis of water regime, water quality and pollution source data, greatly improving the timeliness and accuracy of abnormal discovery. In terms of patrol tasks, according to the number of emergency patrol task executions, experienced patrol users are determined, and higher autonomy is given, allowing them to develop self-built patrol plans, and according to subsequent test results to evaluate their effectiveness, gradually opening the task frequency setting authority, stimulating the enthusiasm of grassroots personnel. Compared with fixed patrol routes and periodic tasks, experienced patrol users can adjust patrol focus and time period flexibly according to the pollution characteristics of the river basin, enterprise pollution habits and time period changes and other characteristics that cannot be directly reflected by data, so as to realize discovery and disposal before pollution appears or even before it forms a non-point source diffusion, thereby improving patrol effect and reducing the probability of water pollution. In addition, pollution events are reported through the public end, greatly expanding the monitoring range and discovery ability.

[0026] In summary, the present scheme realizes the organic integration of sensing data and governance tasks, optimizes the governance collaborative process and patrol response mechanism, and can reduce the probability of water pollution. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 is a logic block diagram of a water quality online monitoring system embodiment one. DETAILED DESCRIPTION

[0028] The following will be further described in detail through specific embodiments:

[0029] Embodiment one

[0030] As shown in the figure, the water quality online monitoring system of the present embodiment includes a server and a terminal. Figure 1 The server includes a data acquisition module, a data storage module, a data analysis module, a reporting module, a warning module and a task management module.

[0031]

[0032] ​The terminal includes a management terminal, a patrol terminal and a public terminal according to the authority and function division; in the embodiment, the terminal is a smart phone with a special APP, the user identity is recognized through the user login account, and the corresponding authority and function are given; the management terminal user is mainly a management user, including the river chief office, local water conservancy bureau, local environmental protection bureau and the like; the patrol terminal user is mainly a patrol user, including river section chiefs at all levels (such as streets, towns, villages, and river patrol personnel) and the like; and the public terminal user is mainly a public user, including social public and enterprise users.

[0033] The data collection module is used for acquiring water regime data, water quality data and pollution monitoring data through a preset interface respectively;

[0034] The water regime data comes from a related hydrological site, including a river name, a section name, a horizontal code, a vertical code, a water period code, a monitoring date, a water level, a flow rate, a flow, a flood warning and the like;

[0035] The water quality data comes from a river monitoring site, including a river name, a section name, a horizontal code, a vertical code, a water period code, a monitoring date, a monitoring value of each monitoring item and the like;

[0036] The pollution monitoring data comes from a sewage treatment plant, a key pollution source (such as a sewage outlet and a preset enterprise collection point) and the like, including a monitoring item number, a measurement point name, a monitoring point code, an enterprise type (if it is an enterprise), a monitoring value and the like;

[0037] The data storage module is used for preprocessing and storing the water regime data, the water quality data and the pollution monitoring data, the preprocessing including format processing, such as the same time format and uniform monitoring index unit; and data cleaning, such as identifying and eliminating abnormal values (such as 0 value, 9999 value and the like).

[0038] The data analysis module is used for analyzing the water regime data, the water quality data and the pollution monitoring data, and identifying pollution events. The analysis adopted by the analysis module includes index trend analysis, threshold analysis and spatial correlation analysis.

[0039] The index trend analysis is used for monitoring the change trend, fluctuation range and sudden increase and decrease of a certain monitoring value in a set time period, so as to preliminarily identify an abnormal event; for example, a rapid rise of ammonia nitrogen concentration in a section within a short time is identified through a moving average method, which is out of the normal fluctuation interval, and an abnormal event is preliminarily identified.

[0040] Threshold analysis is used to compare the monitoring value with the set standard value, and the value exceeding the set standard value is directly identified as an abnormal situation; the set standard value can directly use the water quality standard set by the relevant country / region; it can also be the historical baseline data of the collected section / enterprise, for example, if the ammonia nitrogen concentration of a certain enterprise discharge port in the past three days is 3 times higher than the average value in the past year, it is considered abnormal.

[0041] Spatial correlation analysis is used to identify the spatial correlation between the pollution source and the pollution section after identifying the abnormal situation by using GIS spatial analysis technology to spatially match the upstream section, surrounding discharge port, enterprise distribution, etc. of the current monitoring point, so as to identify the spatial correlation between the pollution source and the pollution section; for example, if a section continuously exceeds the standard and there is an abnormal discharge from a sewage treatment plant near its upstream, it may be a pollution source.

[0042] The analysis module is also used to grade (e.g. general, serious, urgent) according to the pollutant type, exceeding multiple, and affected range according to the preset rules to determine the final pollution event after identifying the abnormal event. For example, if ammonia nitrogen continuously exceeds 2 times and exceeds 6 hours, it is evaluated as a "serious pollution event".

[0043] The pollution event information includes: monitoring point name, monitoring project involved and exceeding multiple, suspected pollution source (such as discharge enterprise), pollution level evaluation, etc.

[0044] The reporting module is used to receive the pollution information reported by the public end, analyze the reported pollution information, and determine whether it is true. If it is true, it is identified as a pollution event. For example, the public reports a pollution situation found by the public end by taking a photo, attaching a text description of the pollution situation, the time of discovery, and the location of discovery as pollution information. The reported pollution information can be identified by image recognition to determine whether the water surface is polluted, and the pollution information can be sent to the management end for manual identification and reply. Image recognition includes floating garbage, oil floating objects, water discoloration, foam abnormalities, biological abnormalities (e.g. a large number of dead fish on the water surface), etc. Public who reports useful information in priority can be rewarded to improve enthusiasm.

[0045] The early warning module is used to generate pollution early warning information according to the pollution event, and send the early warning information to the management end.

[0046] The task management module is configured to create an emergency patrol task according to a pollution event, and send the emergency patrol task to the patrol terminal. The emergency patrol task includes a task level, brief information of the pollution event, and a task target and patrol requirements. The task level includes general, serious, and emergency, which correspond to the level of the pollution event. The brief information of the pollution event includes a pollution type, a section involved, an abnormal index, a source clue (for example, public reporting or automatic monitoring), and a pollution event location. The task target and patrol requirements include verifying whether the pollution situation is true, taking photos / videos of the pollution site, collecting water samples, and filling in a field situation report.

[0047] The task management module is further configured to receive the field situation report uploaded by the patrol terminal.

[0048] The task management module is further configured to count the number of times of execution of the emergency patrol task by the patrol user, and determine whether the number of times of execution exceeds a threshold value. If the number of times of execution exceeds the threshold value, the patrol user is marked as an experienced patrol user.

[0049] The task management module is further configured to receive a self-built daily patrol plan uploaded by the experienced user through the patrol terminal, and replace the preset daily patrol plan. The self-built patrol plan includes a patrol route, a patrol time period, and a patrol focus (for example, a pollution discharge outlet of an xxx plant).

[0050] The task management module is further configured to determine an inspection time period according to the patrol time period, and determine whether a pollution event occurs in the patrol range in the inspection time period. If no pollution event occurs, the self-built patrol is recorded as valid. The inspection time period is from the end time of the patrol to the start time of the next patrol.

[0051] The task management module is further configured to determine whether the number of times of valid self-built patrols exceeds a preset number of times. If the number of times of valid self-built patrols exceeds the preset number of times, a patrol frequency permission is opened, and the experienced patrol user is allowed to customize a patrol frequency. The gradual opening of the permission facilitates management and improves the self-determination permission of the patrol personnel.

[0052] The embodiment also provides a water quality online monitoring method using the system.

[0053] The scheme realizes intelligent identification and accurate tracing of pollution events by standardizing collection and storage of water regime, water quality, and pollution source data, and cooperating with trend analysis, threshold value determination, and spatial analysis algorithms, greatly improving the timeliness and accuracy of abnormality discovery. For example, in the case of a sudden increase in ammonia nitrogen concentration at a section, the system can automatically compare historical data and discharge data of upstream and downstream pollution discharge outlets, quickly locate a suspected pollution source, and avoid the inefficient process of manual multi-departmental collaborative inquiry.

[0054] In terms of patrol tasks, experienced patrol users are determined according to the number of emergency patrol task executions. Compared with relying on daily patrol frequency or time length, emergency tasks are more sudden, complex and goal-oriented, and can more effectively reflect the real ability of patrol personnel to identify, respond and dispose pollution events. Daily patrol is a passive task with fixed route and fixed time, which is easy to be formal and cannot fully reflect the judgment and on-site processing ability of personnel in emergency situations. Therefore, taking the execution of emergency patrol tasks as the ability index is more representative and practical. Experienced patrol users are given higher autonomy, allowing them to develop self-built patrol plans and evaluate their effectiveness according to subsequent inspection results, gradually opening up the task frequency setting authority, which stimulates the enthusiasm of grassroots personnel. Compared with fixed patrol routes and periodic tasks, experienced patrol users can flexibly adjust patrol priorities and time periods according to the pollution characteristics of the river basin, enterprise pollution habits and time period changes and other characteristics that cannot be directly reflected by data, so as to achieve discovery and disposal before pollution appears or even before it forms a non-point source diffusion, thereby improving patrol effect and reducing the probability of water pollution.

[0055] In addition, pollution events are reported by the public end and combined with image recognition algorithms for preliminary screening, which greatly expands the monitoring range and discovery ability.

[0056] In summary, the present scheme realizes the organic integration of perception data and governance tasks, optimizes the governance collaborative process and patrol response mechanism, and can reduce the probability of water pollution.

[0057] Embodiment Two

[0058] The difference between this embodiment and embodiment one is that in this embodiment, the data acquisition module is used to acquire fixed-point monitoring video data and unmanned aerial vehicle aerial video data through a preset interface; for example, the fixed-point monitoring video data is acquired from a livestock and poultry breeding video monitoring terminal;

[0059] The task management module is also used to judge the duration of no pollution event after the self-built daily patrol plan, and if the duration exceeds the preset pollution-free time, the access authority of the corresponding patrol end video data is opened. According to the duration of no pollution, video monitoring and unmanned aerial vehicle aerial photography are opened as intelligence sharing, providing more autonomous analysis dimensions for patrol personnel.

[0060] The embodiment introduces point monitoring video and unmanned aerial vehicle aerial video as supplementary data sources, further expands the perception means, and provides more abundant reference basis for identification and patrol decision of pollution events. When a patrol user does not appear pollution events in his / her responsibility area for a period of time, the system automatically judges that the patrol plan of the user is scientific and effective, and on this basis, gradually opens the access permission of video monitoring data and unmanned aerial vehicle aerial data. The self-analysis and judgment ability of experienced patrol users is improved, and the video and other unstructured data are converted into “intelligence resources” for grassroots governance, so as to make the patrol users have higher precision and initiative in aspects of patrol route planning, key area identification, pollution traceability inference and the like. It is helpful to improve the ability of patrol personnel to find problems and prevent risks.

[0061] Embodiment three

[0062] The difference between the embodiment and the embodiment two is that the analysis module is further used to count whether the patrol route of the self-built patrol plan has public pollution information in history, and if there is, the analysis module is further used to analyze the relationship between the discovery time of the public pollution and the patrol time period in the self-built patrol plan, to judge whether the self-built patrol plan has a preventive effect on pollution events not discovered through automatic monitoring. If there is a preventive effect, mark it as a professional patrol user. Subsequently, the professional patrol user can be arranged to carry out experience sharing and the like activities, so as to improve the overall professional level of the patrol users.

[0063] Specifically, the patrol time period is compared with the historical pollution discovery time: if the discovery time is within the inspection time period (it is explained that the earlier patrol time period has the opportunity to prevent in advance), it is judged to be related; if the pollution discovery time is in the patrol time period (it is explained that the pollution has occurred, and the patrol has no opportunity to discover and prevent in advance), it is judged to be unrelated.

[0064] If there is a relationship, the water quality data and pollution monitoring data corresponding to the patrol time period are analyzed, and whether the monitoring value is higher than the historical baseline data and lower than the set standard value is compared. If not, it is judged that the patrol time period has a preventive effect (the data cannot be identified in advance, for example, the pollution behavior is prevented in advance); if yes, it is judged that the patrol time period has no preventive effect (it is analyzed that there is a slight water quality index anomaly, but it does not reach the pollution event standard, the water quality has a deteriorating trend, and it is often difficult to directly block the formation of pollution, and it is difficult for the patrol personnel to reflect the role of preventing a trouble from arising).

[0065] The embodiment evaluates whether the self-built patrol plan has a front-end intervention effect on these non-automatic detection pollution events by analyzing the overlap of the time when the public discovers pollution and the patrol time period in the patrol plan. Thus, high-level patrol users are identified.

[0066] Embodiment four

[0067] The embodiment is different from the embodiment one in that the task management module is used to create a whole-line patrol task every preset time and send it to the patrol terminal. Through regular whole-line patrol, it is ensured that there is no omission in patrol.

[0068] The above is only an embodiment of the present application, and the present application is not limited to the field involved in this embodiment. The common knowledge of specific structures and properties in the scheme is not described in detail. The ordinary skilled person in the art knows all the ordinary technical knowledge in the field of the present application before the filing date or the priority date, can know all the prior art in the field, and has the ability to apply conventional experimental means before that date. The ordinary skilled person in the art can perfect and implement the present scheme based on the disclosure given in the present application, and their own ability. Some typical known structures or known methods should not be an obstacle for the ordinary skilled person in the art to implement the present application. It should be noted that, for those skilled in the art, without departing from the structure of the present application, a number of modifications and improvements can be made, which should also be considered as the protection scope of the present application. These will not affect the effect and practicality of the present application. The protection scope of the present application should be subject to the content of its claims. The specific implementation in the specification can be used to explain the content of the claims.

Claims

1. An online water quality monitoring system, comprising: The system comprises a server and a terminal, wherein the server comprises a data acquisition module, a data storage module, a data analysis module, a warning module and a task management module; The terminal comprises a management terminal and a patrol terminal; The data acquisition module is configured to acquire water regime data, water quality data and pollution monitoring data; The data storage module is configured to preprocess and store the water regime data, the water quality data and the pollution monitoring data; The data analysis module is configured to analyze the water regime data, the water quality data and the pollution monitoring data, and identify pollution events; The warning module is configured to generate pollution warning information according to the pollution events, and send the warning information to the management terminal; The task management module is configured to create an emergency patrol task according to the pollution events, and send the emergency patrol task to the patrol terminal, and is further configured to count the number of times of execution of the emergency patrol task by a patrol user, and determine whether the number of times of execution exceeds a threshold value, and if the number of times of execution exceeds the threshold value, mark the patrol user as an experienced patrol user, and is further configured to receive a self-built daily patrol plan uploaded by the experienced user through the patrol terminal, and replace a preset daily patrol plan.

2. The water quality on-line monitoring system of claim 1, wherein: The task management module is further configured to determine a verification period according to a patrol period, and determine whether a pollution event occurs in the patrol range in the verification period, and if no pollution event occurs, record as a valid self-built patrol, wherein the verification period is from the end time of the patrol to the start time of the next patrol.

3. The water quality on-line monitoring system of claim 2, wherein: The task management module is further configured to determine whether the number of times of the valid self-built patrol exceeds a preset number of times, and if the number of times exceeds the preset number of times, open a patrol frequency setting permission.

4. The water quality on-line monitoring system of claim 3, wherein: The server further comprises a reporting module, and the terminal further comprises a public terminal; The reporting module is configured to receive pollution information reported by the public terminal, analyze the reported pollution information, and determine whether the reported pollution information is true, and if the reported pollution information is true, identify the pollution information as a pollution event.

5. The water quality on-line monitoring system of claim 4, wherein: The task management module is further configured to receive a field situation briefing uploaded by the patrol terminal.

6. The water quality on-line monitoring system of claim 5, wherein: The analysis performed by the analysis module comprises index trend analysis, threshold value analysis and spatial correlation analysis.

7. The water quality on-line monitoring system of claim 6, wherein: The reported pollution information comprises a photo, a pollution situation text description, a discovery time and a discovery location.

8. The water quality on-line monitoring system of claim 7, wherein: The data acquisition module is configured to acquire fixed-point monitoring video data and unmanned aerial vehicle aerial video data; The task management module is further configured to determine a duration during which no pollution event occurs after the self-built daily patrol plan is implemented, and if the duration exceeds a preset pollution-free time, open an access permission for video data of the corresponding patrol terminal.

9. The water quality on-line monitoring system of claim 8, wherein: The analysis module is further configured to count a patrol route of the self-built patrol plan, and determine whether public reported pollution information exists in history, and if the public reported pollution information exists, the analysis module is further configured to analyze a relationship between a discovery time of the public reported pollution information and a patrol period in the self-built patrol plan, and determine whether the self-built patrol plan has a preventive effect on pollution events that are not automatically monitored and discovered, and if the self-built patrol plan has the preventive effect, mark the self-built patrol plan as a professional patrol user.

10. A method of online monitoring of water quality, characterized in that, The system of any one of claims 1-8.

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