CN114860816A - Water pollution intelligent early warning system integration method, device and related equipment - Google Patents
Water pollution intelligent early warning system integration method, device and related equipment Download PDFInfo
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Abstract
The invention relates to the technical field of water pollution intelligent early warning system integration, and provides a water pollution intelligent early warning system integration method, a water pollution intelligent early warning system integration device and related equipment, wherein the water pollution intelligent early warning system integration method comprises the following steps: acquiring water environment data in real time and carrying out point location layout; carrying out cloud storage on the water environment data; constructing and training a big data mining analysis model; integrating the analysis data output by the big data mining analysis model and displaying the result; feeding the display result back to the point location layout for point layout optimization; the efficiency and the accuracy of tracing the water pollution are effectively improved, the degree of dependence on the accuracy of the mechanism model parameters is reduced, and the operation of tracing the water pollution is more convenient; and the display result is fed back to the point location layout, so that the effect of point location layout optimization is realized. The method can effectively improve the efficiency and accuracy of tracing the water pollution, enables the operation of tracing the water pollution to be more convenient and fast, provides decision basis for pollution prevention and control, and has wide application range.
Description
Technical Field
The invention relates to the technical field of water pollution intelligent early warning system integration, in particular to a water pollution intelligent early warning system integration method, a water pollution intelligent early warning system integration device, computer equipment and a computer readable storage medium.
Background
With the continuous development of human society and the increase of global overall temperature, water resources play an indispensable role in life, work, production and manufacture of people. In order to ensure the excellent water quality of water resources, the water resources are monitored and protected in real time.
The existing monitoring system mainly adopts a mode of automatically monitoring standard stations entering and exiting key positions and manually collecting selected stations, the standard stations need land acquisition, building, operation and maintenance, the cost is high, and the data acquisition period is 4 hours; manual stations need to take water and test manually, once a week or a month, the river water pollution traceability data volume is insufficient, and the real-time performance is not high. The sensing layer monitoring equipment corresponding to the data integration technology of the existing monitoring system is single, the data volume is small, the conventional server and socket mode can stably receive and integrate, and the data mining analysis degree is limited. The existing water pollution tracing is based on the limited monitoring data of a conventional station, the coverage of a drainage basin is insufficient, the data volume is insufficient, time delay exists, and rapid and accurate tracing is difficult to achieve.
Therefore, the existing monitoring system has low monitoring efficiency, poor accuracy, troublesome operation and small application range.
Disclosure of Invention
Aiming at the defects of the related technologies, the invention provides an integrated method and device of a water pollution intelligent early warning system, a computer device and a computer readable storage medium, which can effectively improve the efficiency and accuracy of water pollution tracing, enable the operation of water pollution tracing to be more convenient and fast, and provide decision basis for pollution prevention and treatment.
In order to solve the technical problem, in a first aspect, an embodiment of the present invention provides an integrated method of a water pollution intelligent early warning system, including the following steps:
acquiring water environment data in real time and carrying out point location layout;
carrying out cloud storage on the water environment data;
constructing and training a big data mining analysis model;
integrating the analysis data output by the big data mining analysis model and displaying the result;
and feeding the display result back to the point location layout for point layout optimization.
Preferably, the step of acquiring water environment data in real time and performing point location layout specifically includes the following substeps:
respectively acquiring standard water quality data, integrated outdoor water quality data, small trend water quality data and micro in-situ water quality data in real time through a standard water quality monitoring system, an integrated outdoor water quality on-line monitoring system, a small trend on-line monitoring system and a micro in-situ on-line monitoring system;
and carrying out point location layout and integration on the standard water quality monitoring system, the integrated outdoor water quality on-line monitoring system, the small-sized trend on-line monitoring system and the miniature in-situ on-line monitoring system.
Preferably, the standard water quality monitoring system is arranged on the entry and exit section of the district and a key concern area;
the integrated outdoor water quality online monitoring system is arranged at a main stream inflow estuary and a first-level tributary river section;
the small-sized trend water quality on-line monitoring system is arranged on the secondary branch;
the miniature in-situ on-line monitoring system is arranged on the capillary branch.
Preferably, the cloud storage of the water environment data specifically includes the following sub-steps:
the cloud deck is built in a cloud network, computing, resource storage, network security service and operation and maintenance management service mode;
and performing data fusion processing on the water environment data and storing the water environment data in the holder.
Preferably, the building of the big data mining analysis model and the training specifically include the following sub-steps:
constructing a big data computing base platform through a distributed system integration framework, a computing engine and a data warehouse tool;
establishing a corresponding big data mining analysis model according to the water environment data through the big data computing base platform;
and carrying out model training on the big data mining analysis model.
Preferably, the integrating and displaying the analysis data output according to the big data mining analysis model specifically includes the following substeps:
collecting geographic space data of a water quality environment and monitoring data of the Internet of things by using a traceability analysis model algorithm;
integrating an early warning traceability analysis platform through an intelligent monitoring information system according to the geospatial data and the monitoring data of the Internet of things;
and visually and accurately displaying the real-time condition of each water quality, the water pollution tracing result and the water environment management collaborative business process through the early warning tracing analysis platform.
Preferably, the geospatial data comprises: remote sensing image data, GIS map service, digital elevation model and micro-service architecture.
In a second aspect, an embodiment of the present invention further provides an integrated device of an intelligent early warning system for water pollution, including:
the point location distribution module is used for acquiring water environment data in real time and carrying out point location distribution;
the storage module is used for carrying out cloud storage on the water environment data;
the big data center module is used for constructing and training a big data mining analysis model;
the integration module is used for integrating the analysis data output by the big data mining analysis model and displaying the result;
and the optimization module is used for feeding back the display result to the point location layout to perform point location optimization processing.
In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program that is stored in the memory and can be run on the processor, and when the processor executes the computer program, the steps in the above-mentioned intelligent early warning system integration method for water pollution are implemented.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps in the above-mentioned water quality pollution intelligent early warning system integration method are implemented.
Compared with the prior art, the method obtains the water environment data in real time and carries out point location distribution; carrying out cloud storage on the water environment data; constructing and training a big data mining analysis model; integrating the analysis data output by the big data mining analysis model and displaying the result; feeding the display result back to the point location layout for point layout optimization; the efficiency and the accuracy of tracing the water pollution are effectively improved, and meanwhile, a result is obtained by training through a big data mining analysis model, so that the degree of dependence on the accuracy of the mechanism model parameters is reduced, and the operation of tracing the water pollution is more convenient; the display result is fed back to the point location layout, so that the effect of point location layout optimization is achieved, and the application range is wide.
Drawings
The present invention will be described in detail below with reference to the accompanying drawings. The foregoing and other aspects of the invention will become more apparent and more readily appreciated from the following detailed description, taken in conjunction with the accompanying drawings. In the drawings:
FIG. 1 is a flow chart of the method of the water pollution intelligent early warning system integration method of the invention;
FIG. 2 is a flowchart illustrating a method embodied in step S1 according to the present invention;
FIG. 3 is a flowchart illustrating a method embodied in step S2 according to the present invention;
FIG. 4 is a flowchart illustrating a method embodied in step S3 according to the present invention;
FIG. 5 is a flowchart illustrating a method embodied in step S4 according to the present invention;
FIG. 6 is a flow chart of the method of the water pollution intelligent early warning system integration method of the invention;
FIG. 7 is a block diagram of the water pollution intelligent early warning system integrated device of the present invention;
fig. 8 is a block diagram of a computer device of the present invention.
In the figure, 200, an intelligent early warning system integrated device for water pollution 201, a point location distribution module 202, a storage module 203, a big data center module 204, an integrated module 205, an optimization module 300, computer equipment 301, a memory 302 and a processor.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings.
The embodiments/examples described herein are specific embodiments of the present invention, are intended to be illustrative of the concepts of the present invention, are intended to be illustrative and exemplary, and should not be construed as limiting the embodiments and scope of the invention. In addition to the embodiments described herein, those skilled in the art will be able to employ other technical solutions which are obvious based on the disclosure of the claims and the specification of the present application, and these technical solutions include those which make any obvious replacement or modification of the embodiments described herein, and all of which are within the scope of the present invention.
Example one
Referring to fig. 1 to fig. 6, fig. 1 is a flow chart of a method of the water pollution intelligent early warning system integration method of the present invention; FIG. 2 is a flowchart illustrating a method embodied in step S1 according to the present invention; FIG. 3 is a flowchart illustrating a method embodied in step S2 according to the present invention; FIG. 4 is a flowchart illustrating a method embodied in step S3 according to the present invention; FIG. 5 is a flowchart illustrating a method embodied in step S4 according to the present invention; FIG. 6 is a flow chart of the method of the water pollution intelligent early warning system integration method of the invention.
The invention provides an integration method of an intelligent early warning system for water pollution, which comprises the following steps:
and S1, acquiring water environment data in real time and carrying out point location layout.
The water environment quality monitoring and control instrument multi-source monitoring equipment is used for acquiring water environment data in real time, the water environment quality monitoring and control instrument multi-source monitoring equipment acquires data through a network, the network is set to be a sensing layer, and the sensing layer is used for acquiring the water environment data. The water environment quality monitoring, measuring and controlling instrument multi-source monitoring equipment data acquisition network is adopted, and extremely rich full-time-space full-time-period real-time water environment data can be acquired at low cost as much as possible.
The Internet of things (IoT) can extend an interconnection terminal to any object, and various intelligent sensing devices such as a sensor, a radio frequency identification and a monitoring analyzer can communicate, collect and exchange various different information of a monitored physical object by utilizing an intelligent sensing technology, an identification technology and a communication sensing technology. The point location arrangement of the multi-source monitoring equipment of the water environment quality monitoring and control instrument is carried out according to one network, so that the higher monitoring accuracy is ensured.
And S2, carrying out cloud storage on the water environment data.
Specifically, the Cloud storage mode is based on functions of cluster application, a grid technology or a distributed file system and the like, through cooperative work of software sets, original data, parameter data and the like of each level of the multi-source monitoring equipment are rapidly provided for each traceability early-warning model algorithm in a resource pool storage mode, and the early-warning traceability model algorithm is accessed through a Web service Application Program Interface (API) in the calling process of the early-warning traceability model, so that the safety of the data is ensured, the storage space is saved, the traceability early-warning result is faster and more accurate, and basic environment support and safety operation and maintenance guarantee are provided for integration of a water environment quality instrument measurement and control system. The water environment quality monitoring big data are integrated and accurately fused to form a processing center, the processing center is a storage layer, water environment data are stored and gathered through the storage layer, and the data processing effect is good. The mass water environment monitoring big data of the intelligent perception multi-source monitoring network is stored into a cloud, so that the mass monitoring data can be accurately, safely and quickly stored, shared and called.
And S3, constructing a big data mining analysis model and training.
The water environment hill monitoring big data integration accurate fusion processing center is set to be a big data center layer, the big data center layer is used for building a big data mining analysis model and training, and data integration, cleaning and fusion are sequentially carried out, so that a model training result is obtained.
Specifically, the center layer transmits information acquired by the sensing layer accurately and timely, integrates and cleans the information, processes abnormal phenomena and problems in a related mode, extracts data information through data mining and fusion technologies, manages parameters of the model, and comprehensively utilizes a deep learning technology to achieve creation and training of an early warning traceability algorithm.
And S4, integrating the analysis data output by the big data mining analysis model and displaying the result.
The intelligent perception multi-source monitoring network massive water environment monitoring big data storage cloud is set to be an application layer, water environment data information is integrated and a model framework is built through the application layer, so that integrated data are visual, a user can conveniently and directly check the integrated data, the monitoring effect is good, and water environment pollution tracing can be accurately and quickly performed.
Specifically, through an information system integrated early warning traceability analysis platform, real-time conditions of water quality, water pollution traceability results, water environment management collaborative business processes and the like are visually and accurately displayed, so that water pollution events can be quickly and accurately traced to the source and can be timely solved.
And S5, feeding the display result back to the point location layout for point location optimization processing.
The display result is fed back to the step S1, and point position arrangement is optimized according to the display result, so that the multi-source monitoring equipment of the water environment quality monitoring and control instrument can acquire real-time data of the water environment, and is continuously optimized in operation, and the monitoring effect is good.
Specifically, water environment data are acquired in real time and point location distribution is carried out; carrying out cloud storage on the water environment data; constructing and training a big data mining analysis model; integrating the analysis data output by the big data mining analysis model and displaying the result; feeding the display result back to the point location layout for point layout optimization; the efficiency and the accuracy of tracing the water pollution are effectively improved, and meanwhile, a result is obtained by training through a big data mining analysis model, so that the degree of dependence on the accuracy of the mechanism model parameters is reduced, and the operation of tracing the water pollution is more convenient; the display result is fed back to the point location layout, so that the effect of point location layout optimization is achieved, and the application range is wide.
In this embodiment, step S1 specifically includes the following sub-steps:
s11, respectively acquiring standard water quality data, integrated outdoor water quality data, small trend water quality data and micro in-situ water quality data in real time through a standard water quality monitoring system, an integrated outdoor water quality on-line monitoring system, a small trend on-line monitoring system and a micro in-situ on-line monitoring system.
Wherein, the integration technology is based on four sources of a water quality measurement and control instrument, and a core module comprises four sources. The four sources refer to four different types of intelligent water environment quality monitoring measurement and control instruments, including a standard water quality monitoring system, an integrated outdoor water quality on-line monitoring system, a small-sized trend on-line monitoring system and a miniature in-situ on-line monitoring system; the four-in-one integrated mode refers to an innovative system integration mode for monitoring the water environment quality, and comprises a water environment quality monitoring measurement and control instrument multi-source monitoring equipment data acquisition network, an intelligent perception multi-source monitoring network mass water environment monitoring big data storage cloud, a water environment quality monitoring big data integration accurate fusion processing center, and a water quality multi-source pollution intelligent monitoring information system integration early warning traceability analysis platform for respectively constructing a perception layer, a storage layer, a center layer and an application layer integrated by the information system.
S12, point location layout and integration are carried out on the standard water quality monitoring system, the integrated outdoor water quality on-line monitoring system, the small-sized trend on-line monitoring system and the miniature in-situ on-line monitoring system.
Specifically, standard water quality data, integrated outdoor water quality data, small trend water quality data and micro in-situ water quality data are respectively obtained in real time through a standard water quality monitoring system, an integrated outdoor water quality on-line monitoring system, a small trend on-line monitoring system and a micro in-situ on-line monitoring system. And carrying out point location layout and integration on the standard water quality monitoring system, the integrated outdoor water quality on-line monitoring system, the small-sized trend on-line monitoring system and the miniature in-situ on-line monitoring system. The monitoring point layout optimization effect is good, and the use is convenient.
In this embodiment, the standard water quality monitoring system is disposed in the entrance and exit section and the key focus area; the integrated outdoor water quality online monitoring system is arranged at a main stream inflow estuary and a first-level tributary river section; the small-sized trend water quality on-line monitoring system is arranged on the secondary branch; the miniature in-situ on-line monitoring system is arranged on the capillary branch.
Wherein, the first-stage branch flow is a river directly connected into the main stream of the river. The secondary substream refers to a river that flows directly into the primary substream.
Specifically, according to the different characteristics in basin, overall consideration trunk branch, width, flow direction, quality of water condition etc. utilize "four sources" water quality monitoring equipment to carry out the perception layer and lay comprehensively: rigidly laying a standard water quality monitoring system in the entry and exit section and the key attention area of the jurisdiction; an integrated outdoor water quality online monitoring system is arranged at a main stream river inlet and a primary branch river section; the secondary branch is used as a supplement to be provided with a small-sized trend on-line monitoring system; and a miniature in-situ online monitoring system is additionally distributed in the capillary tributaries, a network for data acquisition of multi-source monitoring equipment of the water environment quality monitoring and control instrument is constructed, and the system is continuously optimized in operation.
In this embodiment, step S2 specifically includes the following sub-steps:
and S21, building the holder in a cloud network, computing, storage resource and network security service and operation and maintenance management service mode.
And S22, performing data fusion processing on the water environment data and storing the water environment data in the holder.
Specifically, a cloud network, computing, storage resources, network security service and operation and maintenance management service mode is used for building 'intelligent sensing multi-source monitoring network mass water environment monitoring big data storage cloud'. The water environment data are subjected to data fusion processing and then stored on the cloud deck, so that the data security can be ensured, the storage space is saved, the source tracing early warning result is quicker and more accurate, and the basic environment support and the safety operation and maintenance guarantee are provided for the integration of a water environment quality instrument measurement and control system.
In this embodiment, step S3 specifically includes the following sub-steps:
and S31, constructing a big data computing base platform through the distributed system integration architecture, the computing engine and the data warehouse tool.
The distributed system integrated architecture (Hadoop), the computing engine (Spark) and the data warehouse tool (Hive) are used as a big data basic capability layer, a data center is built on a big data assembly, the data center comprises an ETL assembly line such as a data analysis program and a machine learning program, and the data center comprises core functions such as a data management system, a data warehouse system, a data visualization system and a model algorithm system.
And S32, establishing a corresponding big data mining analysis model according to the water environment data through the big data computing basic platform.
And S33, carrying out model training on the big data mining analysis model.
Specifically, a big data computing base platform is constructed by utilizing big data and artificial intelligence technology through a distributed system integration framework, a computing engine and a data warehouse tool; establishing a corresponding big data mining analysis model according to the water environment data through the big data computing base platform by combining service scenes such as water environment decision, water pollution early warning and tracing and the like; and carrying out model training on the big data mining analysis model. The method comprises the steps of forming a water environment quality monitoring big data integration accurate fusion processing center, constructing a big data mining analysis model capable of providing an accurate analysis result through the big data center, and performing big data analysis through the big data mining analysis model, so that the data analysis processing of monitoring of a monitoring system is rapid, and point location layout can be optimized according to a model training structure.
In this embodiment, step S4 specifically includes the following sub-steps:
s41, collecting the geographic space data of the water quality environment and the monitoring data of the Internet of things by using a traceability analysis model algorithm.
And S42, integrating an early warning traceability analysis platform through an intelligent monitoring information system according to the geospatial data and the Internet of things monitoring data.
And S43, visually and accurately displaying the real-time condition of each water quality, the water pollution tracing result and the water environment management collaborative business process through the early warning tracing analysis platform. The intelligent perception multi-source monitoring network massive water environment monitoring big data storage cloud is set into the application layer, and the water environment data information is integrated and the model framework is constructed through the application layer, so that the integrated data are visual, a user can conveniently and directly check the integrated data, the monitoring effect is good, and the water environment pollution tracing can be accurately and quickly performed.
In this embodiment, the geospatial data includes: remote sensing image data, GIS map service, digital elevation model and micro-service architecture.
Specifically, a water quality integrated multi-source pollution intelligent monitoring information system integrated early warning and tracing analysis platform is built by means of water quality monitoring data and information system integration by means of technologies of remote sensing image data, GIS map service, digital elevation model and micro-service architecture (Eureka + GateWay + Feign + Ribbon + Config + Hystrix).
In this embodiment, the invention can break through the key early warning and tracing technologies of water quality monitoring, early warning, analysis and tracing service chains, comprehensively use all levels of water quality monitoring data based on a multi-source equipment monitoring system, and is based on technologies such as IoT, Cloud storage, big data Hadoop, Spark, Hive, micro-service architecture and the like; through the construction of an IoT network, a Cloud storage Cloud, a big data center and a micro-service architecture platform, a set of quick and effective comprehensive pollution traceability assessment method based on big data processing is formed, the efficiency and the accuracy of water pollution traceability are effectively improved, meanwhile, the early warning traceability model is based on a deep learning algorithm, the dependence degree on the accuracy of mechanism model parameters is reduced, and the operation of water pollution traceability is more convenient.
Example two
Fig. 7 shows a block diagram of an integrated device of an intelligent early warning system for water pollution according to the present invention, in which fig. 7 is a block diagram. The embodiment of the present invention further provides an integrated device 200 of an intelligent early warning system for water pollution, which comprises:
the point location arrangement module 201 is used for acquiring water environment data in real time and carrying out point location arrangement;
the storage module 202 is used for performing cloud storage on the water environment data;
the big data center module 203 is used for constructing and training a big data mining analysis model;
the integration module 204 is used for integrating the analysis data output by the big data mining analysis model and displaying the result;
and the optimization module 205 is configured to feed back the display result to the point location layout to perform point location optimization.
Specifically, water environment data are acquired in real time through the point location arrangement module 201 and point location arrangement is carried out; performing cloud storage on the water environment data through a storage module 202; constructing and training a big data mining analysis model through a big data center module 203; integrating the analysis data output by the big data mining analysis model through an integration module 204 and displaying the result; the display result is fed back to the point location layout through the optimization module 205 to perform point location optimization processing. Constructing a big data computing basic platform by using a big data and artificial intelligence technology through a distributed system integration architecture, a computing engine and a data warehouse tool; establishing a corresponding big data mining analysis model according to the water environment data through the big data computing base platform by combining service scenes such as water environment decision, water pollution early warning traceability and the like; and carrying out model training on the big data mining analysis model. The method comprises the steps of forming a water environment quality monitoring big data integration accurate fusion processing center, constructing a big data mining analysis model capable of providing an accurate analysis result through the big data center, and performing big data analysis through the big data mining analysis model, so that the data analysis processing of monitoring of a monitoring system is rapid, and point location layout can be optimized according to a model training structure.
In this embodiment, the point location arrangement module 201 is further configured to respectively obtain standard water quality data, integrated outdoor water quality data, small trend water quality data and micro in-situ water quality data in real time through a standard water quality monitoring system, an integrated outdoor water quality on-line monitoring system, a small trend on-line monitoring system and a micro in-situ on-line monitoring system. And carrying out point location layout and integration on the standard water quality monitoring system, the integrated outdoor water quality on-line monitoring system, the small-sized trend on-line monitoring system and the miniature in-situ on-line monitoring system.
Wherein, the integration technology is based on four sources of a water quality measurement and control instrument, and a core module comprises four sources. The four sources refer to four different types of intelligent water environment quality monitoring measurement and control instruments, including a standard water quality monitoring system, an integrated outdoor water quality on-line monitoring system, a small-sized trend on-line monitoring system and a miniature in-situ on-line monitoring system; the four-in-one integrated mode refers to an innovative system integration mode for monitoring the water environment quality, and comprises a water environment quality monitoring measurement and control instrument multi-source monitoring equipment data acquisition network, an intelligent perception multi-source monitoring network mass water environment monitoring big data storage cloud, a water environment quality monitoring big data integration accurate fusion processing center, and a water quality multi-source pollution intelligent monitoring information system integration early warning traceability analysis platform for respectively constructing a perception layer, a storage layer, a center layer and an application layer integrated by the information system.
Specifically, standard water quality data, integrated outdoor water quality data, small-sized trend water quality data and micro in-situ water quality data are obtained in real time through a standard water quality monitoring system, an integrated outdoor water quality on-line monitoring system, a small-sized trend on-line monitoring system and a micro in-situ on-line monitoring system respectively. And carrying out point location layout and integration on the standard water quality monitoring system, the integrated outdoor water quality on-line monitoring system, the small-sized trend on-line monitoring system and the miniature in-situ on-line monitoring system. The monitoring point layout optimization effect is good, and the use is convenient.
In this embodiment, the standard water quality monitoring system is disposed in the entrance and exit section and the key focus area; the integrated outdoor water quality online monitoring system is arranged at a main stream inflow estuary and a first-level tributary river section; the small-sized trend water quality on-line monitoring system is arranged on the secondary branch; the miniature in-situ on-line monitoring system is arranged on the capillary branch.
Wherein, the first-level branch flow is a river directly connected into the main stream of the river. The secondary substream is a river that flows directly into the primary substream.
Specifically, according to the different characteristics in basin, overall consideration trunk branch, width, flow direction, quality of water condition etc. utilize "four sources" water quality monitoring equipment to carry out the perception layer and lay comprehensively: rigidly laying a standard water quality monitoring system in the entry and exit section and the key attention area of the jurisdiction; an integrated outdoor water quality online monitoring system is arranged at a main stream river inlet and a primary branch river section; the secondary branch is used as a supplement to be provided with a small-sized trend on-line monitoring system; and a miniature in-situ online monitoring system is additionally distributed in the capillary tributaries, a network for data acquisition of multi-source monitoring equipment of the water environment quality monitoring and control instrument is constructed, and the system is continuously optimized in operation.
In this embodiment, the storage module 202 is further configured to build a cloud deck in a manner of a cloud network, a computing, a storage resource, a network security service, and an operation and maintenance management service. And performing data fusion processing on the water environment data and storing the water environment data in the holder.
Specifically, a cloud network, computing, storage resources, network security service and operation and maintenance management service mode is used for building 'intelligent sensing multi-source monitoring network mass water environment monitoring big data storage cloud'. The water environment data are subjected to data fusion processing and then stored on the cloud deck, so that the safety of the data can be ensured, the storage space is saved, the source tracing early warning result is quicker and more accurate, and the basic environment support and the safety operation and maintenance guarantee are provided for the integration of a water environment quality instrument measurement and control system.
In this embodiment, the big data center module 203 is further configured to build a big data computing base platform through a distributed system integration architecture, a computing engine, and a data warehouse tool; establishing a corresponding big data mining analysis model according to the water environment data through the big data computing base platform; and carrying out model training on the big data mining analysis model.
The distributed system integrated architecture (Hadoop), the computing engine (Spark) and the data warehouse tool (Hive) are used as a big data basic capability layer, a data center is built on a big data assembly, the data center comprises an ETL assembly line such as a data analysis program and a machine learning program, and the data center comprises core functions such as a data management system, a data warehouse system, a data visualization system and a model algorithm system.
Specifically, a big data computing base platform is constructed by utilizing big data and artificial intelligence technology through a distributed system integration framework, a computing engine and a data warehouse tool; establishing a corresponding big data mining analysis model according to the water environment data through the big data computing base platform by combining service scenes such as water environment decision, water pollution early warning traceability and the like; and carrying out model training on the big data mining analysis model. The method comprises the steps of forming a water environment quality monitoring big data integration accurate fusion processing center, constructing a big data mining analysis model capable of providing an accurate analysis result through the big data center, and performing big data analysis through the big data mining analysis model, so that the data analysis processing of monitoring of a monitoring system is rapid, and point location layout can be optimized according to a model training structure.
In this embodiment, the integration module 204 is further configured to collect geospatial data of the water quality environment and internet of things monitoring data by using a traceability analysis model algorithm. And integrating an early warning traceability analysis platform through an intelligent monitoring information system according to the geospatial data and the Internet of things monitoring data. And visually and accurately displaying the real-time condition of each water quality, the water pollution tracing result and the water environment management collaborative business process through the early warning tracing analysis platform. The intelligent perception multi-source monitoring network massive water environment monitoring big data storage cloud is set into the application layer, and the water environment data information is integrated and the model framework is constructed through the application layer, so that the integrated data are visual, a user can conveniently and directly check the integrated data, the monitoring effect is good, and the water environment pollution tracing can be accurately and quickly performed.
In this embodiment, the geospatial data includes: remote sensing image data, GIS map service, digital elevation model and micro-service architecture.
Specifically, a water quality integrated multi-source pollution intelligent monitoring information system integrated early warning and tracing analysis platform is built by means of water quality monitoring data and information system integration by means of technologies of remote sensing image data, GIS map service, digital elevation model and micro-service architecture (Eureka + GateWay + Feign + Ribbon + Config + Hystrix).
In this embodiment, the invention can break through the key early warning and tracing technologies of water quality monitoring, early warning, analysis and tracing service chains, comprehensively use all levels of water quality monitoring data based on a multi-source equipment monitoring system, and is based on technologies such as IoT, Cloud storage, big data Hadoop, Spark, Hive, micro-service architecture and the like; through the construction of an IoT network, a Cloud storage Cloud, a big data center and a micro-service architecture platform, a set of quick and effective comprehensive pollution traceability assessment method based on big data processing is formed, the efficiency and the accuracy of water pollution traceability are effectively improved, meanwhile, the early warning traceability model is based on a deep learning algorithm, the dependence degree on the accuracy of mechanism model parameters is reduced, and the operation of water pollution traceability is more convenient.
EXAMPLE III
Referring to fig. 8, fig. 8 is a block diagram of a computer device according to the present invention. The embodiment of the present invention further provides a computer device 300, which includes a memory 301, a processor 302, and a computer program stored in the memory 301 and capable of running on the processor, and when the processor 302 executes the computer program, the steps in the water pollution intelligent early warning system integration method according to the first embodiment of the present invention are implemented.
Example four
The embodiment of the invention also provides a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the steps in the water quality pollution intelligent early warning system integration method of the embodiment I are realized.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (10)
1. An integration method of a water pollution intelligent early warning system is characterized by comprising the following steps:
acquiring water environment data in real time and carrying out point location layout;
carrying out cloud storage on the water environment data;
constructing and training a big data mining analysis model;
integrating the analysis data output by the big data mining analysis model and displaying the result;
and feeding the display result back to the point location layout for point layout optimization.
2. The water quality pollution intelligent early warning system integration method as claimed in claim 1, wherein the step of acquiring water environment data in real time and performing point location layout specifically comprises the following substeps:
respectively acquiring standard water quality data, integrated outdoor water quality data, small trend water quality data and micro in-situ water quality data in real time through a standard water quality monitoring system, an integrated outdoor water quality on-line monitoring system, a small trend on-line monitoring system and a micro in-situ on-line monitoring system;
and carrying out point location layout and integration on the standard water quality monitoring system, the integrated outdoor water quality on-line monitoring system, the small-sized trend on-line monitoring system and the miniature in-situ on-line monitoring system.
3. The water pollution intelligent early warning system integration method of claim 2, wherein the standard water quality monitoring system is arranged in the entry and exit section and the key attention area of the jurisdiction;
the integrated outdoor water quality online monitoring system is arranged at a main stream inflow estuary and a first-level tributary river section;
the small-sized trend water quality on-line monitoring system is arranged on the secondary branch;
the miniature in-situ on-line monitoring system is arranged on the capillary branch.
4. The water quality pollution intelligent early warning system integration method as claimed in claim 1, wherein the cloud storage of the water environment data specifically comprises the following substeps:
the cloud deck is built through a cloud network, calculation, storage resources, network security service and operation and maintenance management service;
and performing data fusion processing on the water environment data and storing the water environment data in the holder.
5. The water quality pollution intelligent early warning system integration method as claimed in claim 1, wherein the building of the big data mining analysis model and the training specifically comprises the following substeps:
constructing a big data computing base platform through a distributed system integrated architecture, a computing engine and a data warehouse tool;
establishing a corresponding big data mining analysis model according to the water environment data through the big data computing base platform;
and carrying out model training on the big data mining analysis model.
6. The water pollution intelligent early warning system integration method as claimed in claim 1, wherein the sub-steps of integrating the analysis data output by the big data mining analysis model and displaying the result specifically comprise:
collecting geographic space data of a water quality environment and monitoring data of the Internet of things by using a traceability analysis model algorithm;
integrating an early warning traceability analysis platform through an intelligent monitoring information system according to the geospatial data and the monitoring data of the Internet of things;
and visually and accurately displaying the real-time condition of each water quality, the water pollution tracing result and the water environment management collaborative business process through the early warning tracing analysis platform.
7. The water quality pollution intelligent early warning system integration method as claimed in claim 6, wherein the geospatial data comprises: remote sensing image data, GIS map service, digital elevation model and micro-service architecture.
8. The utility model provides a water pollution intelligence early warning system integrated device which characterized in that includes:
the point location distribution module is used for acquiring water environment data in real time and carrying out point location distribution;
the storage module is used for carrying out cloud storage on the water environment data;
the big data center module is used for constructing and training a big data mining analysis model;
the integration module is used for integrating the analysis data output by the big data mining analysis model and displaying the result;
and the optimization module is used for feeding back the display result to the point location layout to perform point location optimization processing.
9. A computer device, comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to implement the steps of the water quality pollution intelligent early warning system integration method as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps in the water quality pollution intelligent early warning system integrated method according to any one of claims 1 to 7 are realized.
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