CN116818672A - River water quality monitoring system based on Internet of things - Google Patents
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Abstract
The application provides a river water quality monitoring system based on the Internet of things, and relates to the technical field of water quality monitoring. The system forms a multi-hop self-organizing network among a plurality of water body data collectors arranged in the river, acquires and monitors water quality data of the river in real time and uploads the data to a local analysis and monitoring module, so that the communication distance can be prolonged, and the reliability of data transmission is ensured; collecting and summarizing the collected water quality data and river basic data through a local analysis and monitoring module, and predicting the water environment by utilizing a two-dimensional water quality model to realize accurate simulation and prediction of the water quality of the river water body; the water quality data and the river basic data are transmitted to the data storage server for distributed storage, so that the remote monitoring center can acquire the water quality of the river in real time and visually and timely monitor and automatically early warn the water quality of the river on line through the visual platform of the Internet of things, and informatization, modernization and intellectualization of the remote monitoring of the water body of the river are realized, and abnormal analysis and early warning of the water quality of the river can be effectively carried out in time.
Description
Technical Field
The application relates to the technical field of water quality monitoring, in particular to a river water quality monitoring system based on the Internet of things.
Background
The water quality monitoring is a process of monitoring and measuring the types of pollutants in a water body, the concentration and the change trend of various pollutants and evaluating the water quality condition; with the rapid increase and expansion of urban quantity and scale, urban domestic sewage is increasingly serious, and from the view of the sewage discharge structure of China, the residential sewage discharge amount exceeds the industrial sewage discharge amount for the first time, and the residential sewage is always in the first place in the urban sewage discharge of China in the last ten years, and the specific gravity is increased year by year. With the increasing level of awareness, protection and management of urban rivers are increasingly emphasized.
At present, the water quality monitoring of urban rivers is scattered in different departments, monitoring information is scattered and cannot be organically fused, a plurality of monitoring devices are used for manual fixed-point monitoring and manual recording, time and labor are wasted, the efficiency is low, an information sharing mechanism is not sound, the release time delay is delayed, the water quality monitoring and early warning cannot be automatically carried out, the informatization, modernization and intellectualization levels are far insufficient, and the water quality abnormality analysis and early warning cannot be timely and effectively carried out.
Disclosure of Invention
The application aims to provide a river water quality monitoring system based on the Internet of things, which is characterized in that a multi-hop self-organizing network is formed among a plurality of water body data collectors arranged in a river, water quality data of the river are collected and monitored in real time and uploaded to a local analysis and monitoring module, the communication distance between the water body data collectors and the local analysis and monitoring module can be prolonged, the reliability of data transmission is ensured, then the collected water quality data and river basic data are collected and summarized through the local analysis and monitoring module, the analysis and calculation of a two-dimensional water quality model is utilized for carrying out water environment prediction, accurate simulation and prediction of the water quality of the river water body are realized, and pollutants in the water body and analysis and pollution intensity are timely found and local early warning are carried out; further, the water quality data and the river basic data are transmitted to a data storage server for distributed storage, so that the remote monitoring center can acquire the water quality of the river and the equipment of the Internet of things in real time and perform visual and real-time on-line monitoring and automatic early warning on the equipment of the Internet of things through the visual platform of the Internet of things, and the informatization, modernization and intellectualization of the remote monitoring of the river water body are realized, so that the abnormal analysis and early warning of the water quality of the river can be effectively performed in time.
In order to solve the technical problems, the application adopts the following technical scheme:
in a first aspect, an embodiment of the present application provides a river water quality monitoring system based on the internet of things, including:
the system comprises a plurality of water body data collectors, a local analysis monitoring module, a data storage server, a remote monitoring center and a network communication module, wherein the local analysis monitoring module, the data storage server and the remote monitoring center are in communication connection and data transmission through the network communication module;
the water body data collector is used for collecting and monitoring water quality data of the river in real time and uploading the water quality data to the local analysis and monitoring module;
the local analysis and monitoring module is used for collecting, summarizing, analyzing and calculating collected water quality data and river basic data and predicting water environment;
the data storage server is used for carrying out distributed storage on the collected water quality data and river basic data;
the remote monitoring center is used for acquiring water quality data and river basic data in the data storage server in real time, and carrying out on-line monitoring and early warning on the river water quality through the constructed visual platform of the Internet of things.
In some embodiments of the present application, the plurality of water body data collectors form a multi-hop ad hoc network system through a wireless communication manner.
In some embodiments of the application, the local analysis and monitoring module uses a two-dimensional water quality model to analyze and predict the water environment of the water quality data acquired by the plurality of water data collectors.
In some embodiments of the present application, the wireless communication means between the plurality of water body data collectors includes zero or more cascaded wireless repeaters.
In some embodiments of the application, the data storage server classifies, segments, and partitions the collected water quality data and river base data.
In some embodiments of the present application, the remote monitoring center performs privacy calculations on the data stored by the data storage server in a classified, fragmented, and partitioned manner.
In some embodiments of the present application, the system further comprises an image acquisition and preprocessing module for acquiring river remote sensing images in the monitored area and preprocessing the acquired river remote sensing image data.
In some embodiments of the present application, the preprocessing the acquired river remote sensing image data includes:
acquiring an acquired river remote sensing image, and correcting the river remote sensing image to obtain a corrected river remote sensing image;
filtering the corrected river remote sensing image, and carrying out resolution fusion on the filtered river remote sensing image;
and performing color enhancement processing on the remote sensing image with the fused resolution to obtain a preprocessed river remote sensing image.
Compared with the prior art, the embodiment of the application has at least the following advantages or beneficial effects:
the embodiment of the application provides a river water quality monitoring system based on the Internet of things, which is characterized in that a multi-hop self-organizing network is formed among a plurality of water body data collectors arranged in a river, water quality data of the river are collected and monitored in real time and uploaded to a local analysis and monitoring module, the communication distance between the water body data collectors and the local analysis and monitoring module can be prolonged, the reliability of data transmission is ensured, then the collected water quality data and river basic data are collected and summarized through the local analysis and monitoring module, the analysis and calculation of a two-dimensional water quality model is utilized for carrying out water environment prediction, accurate simulation and prediction of the water quality of the river water are realized, and pollutants in the water body and analysis and pollution intensity are timely found and local early warning are carried out; further, the water quality data and the river basic data are transmitted to a data storage server for distributed storage, so that the remote monitoring center can acquire the water quality of the river and the equipment of the Internet of things in real time and perform visual and real-time on-line monitoring and automatic early warning on the equipment of the Internet of things through the visual platform of the Internet of things, and the informatization, modernization and intellectualization of the remote monitoring of the river water body are realized, so that the abnormal analysis and early warning of the water quality of the river can be effectively performed in time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic structural diagram of an embodiment of a river water quality monitoring system based on the Internet of things of the present application;
fig. 2 is a flowchart of preprocessing collected river remote sensing image data in an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Example 1
Referring to fig. 1-2, an embodiment of the application provides a river water quality monitoring system based on the internet of things, which is characterized in that a multi-hop self-organizing network is formed among a plurality of water body data collectors arranged in a river, water quality data of the river are collected and monitored in real time and uploaded to a local analysis and monitoring module, the communication distance between the water body data collectors and the local analysis and monitoring module can be prolonged, the reliability of data transmission is ensured, then the collected water quality data and river basic data are collected and summarized through the local analysis and monitoring module, analysis and calculation of a two-dimensional water quality model is utilized for carrying out water environment prediction, accurate simulation and prediction of the water quality of the river are realized, and pollutants in the water body and analysis and pollution intensity are timely found and local early warning are carried out; further, the water quality data and the river basic data are transmitted to a data storage server for distributed storage, so that the remote monitoring center can acquire the water quality of the river and the equipment of the Internet of things in real time and perform visual and real-time on-line monitoring and automatic early warning on the equipment of the Internet of things through the visual platform of the Internet of things, and the informatization, modernization and intellectualization of the remote monitoring of the river water body are realized, so that the abnormal analysis and early warning of the water quality of the river can be effectively performed in time.
As shown in fig. 1, the river water quality monitoring system based on the internet of things includes: the system comprises a plurality of water body data collectors, a local analysis monitoring module, a data storage server, a remote monitoring center and a network communication module, wherein the local analysis monitoring module, the data storage server and the remote monitoring center are in communication connection and data transmission through the network communication module;
the water body data collector is used for collecting and monitoring water quality data of the river in real time and uploading the water quality data to the local analysis and monitoring module;
the local analysis and monitoring module is used for collecting, summarizing, analyzing and calculating collected water quality data and river basic data and predicting water environment;
the data storage server is used for carrying out distributed storage on the collected water quality data and river basic data;
the remote monitoring center is used for acquiring water quality data and river basic data in the data storage server in real time, and carrying out on-line monitoring and early warning on the river water quality through the constructed visual platform of the Internet of things.
The plurality of water body data collectors form a multi-hop self-organizing network system through a wireless communication mode. The water body acquisition points can be preset according to the actual conditions of the river channel, the water body data collectors are arranged at the water body acquisition points, one or more water body monitoring indexes of the water body data collectors can be arranged according to the requirements, such as a plurality of water quality indexes of water temperature, pH, conductivity, COD, TOC, ammonia nitrogen, nitrate nitrogen, phosphate, chlorophyll and the like, and the indexes can be synthesized into a comprehensive index when in use, so that the river water quality can be evaluated conveniently; the wireless communication mode among the plurality of water body data collectors comprises zero or more cascaded wireless repeaters, so that the data information is cooperatively collected and transmitted, the wireless repeaters can adopt low-power consumption equipment realized based on the Lora or zigbee technology, the communication distance can be enhanced, the long-distance data transmission between the water body data collectors and the local analysis and monitoring module is facilitated, and the reliability of the data transmission is ensured.
The local analysis and monitoring module can be arranged at one or a section of river in a monitoring area and is in wireless connection with a plurality of water body data collectors arranged in the river section, water body data, river basic data (such as hydrological conditions of river names, positions, flow rates, length and width, section forms and the like) and the like collected by each water body data collector are collected, summarized and managed in real time, analysis calculation and water body environment prediction are carried out locally based on the data, and the water quality condition of the river is detected in time, so that automatic water quality monitoring and early warning is realized, the inefficiency of manual monitoring and recording is replaced, and time cost and labor cost are saved.
Further, the local analysis and monitoring module analyzes and predicts the water environment by utilizing a two-dimensional water quality model on the water quality data acquired by the water body data collectors. For water quality data acquired by a water body data acquisition device with a sewage outlet, the two-dimensional concentration change of the water quality can be used for carrying out water quality simulation and prediction by the following formula (1):
wherein C is the pollutant concentration at the longitudinal distance x from the sewage outlet and the point y from the shore, E x 、E y The dispersion coefficients in the x and y directions, u x 、u y The flow velocity components of the environment medium in the x and y directions are respectively, and S (x, y, C and t) is the input quantity of pollutants in unit time and unit volume.
For a water body data collector with a sewage outlet, the pollutant concentration of any point (x, y) of a water body nearby the water body data collector can be obtained according to a two-dimensional random simulation model by adopting a formula (1) when the water body data collector adopts the shore sewage to carry out the following steps:
pollution discharge intensity Q A Flow rate and velocity of flowu x Degradation coefficient k and diffusion empirical coefficient alpha y Can be considered a random variable, i.e., the concentration of contaminants at any point within the contaminated zone is an indeterminate random variable.
When the sewage outlet is positioned at the center of the river channel and adopts a central sewage discharging mode, the sewage is obtained by (1):
wherein E is y ＝α y H-gH；C 0 The background concentration of the pollutants is that H is the average water depth, g is the gravity acceleration, and I is the river hydraulic power slope. According to the function of random variable and its distribution theory, when the pollution discharge intensity Q A Flow velocity u x Degradation coefficient k and diffusion empirical coefficient alpha y Four random variables are independent of each other and their probability density functions are f 1 (Q A )，f 2 (k)，f 3 (α y ) And f 4 (u x ) When the random variable C is smaller than a certain specified concentration value C, the probability can be expressed as:
after any point coordinates (x, y) of the polluted water body are given, the two coordinates (2), (3), (4) are combined, and the pollution discharge intensity Q is based A Flow velocity u x Degradation coefficient k and diffusion empirical coefficient alpha y The probability distribution of the mass concentration C of any point coordinate (x, y) of the polluted water body of the river can be obtained, so that the accurate simulation and prediction of the water quality of the river water body are realized, the pollutants in the water body are timely found, the pollution intensity is analyzed, and the local early warning is carried out.
In addition, the data storage server classifies, slices and partitions the collected water quality data and river basic data for distributed storage. And the remote monitoring center performs privacy calculation on the data stored by the data storage servers in classification, segmentation and partition.
The data storage server can be realized by adopting a distributed database, the distributed database can be realized by using a plurality of different databases, can be relational, such as MYSQL, or non-relational, such as REDIS, NOSQL and the like, so that the distributed storage of various water quality data and river basic data can be satisfied, and the operations of data classification, fragmentation, partition storage and the like can be provided during storage. The types of various data acquired by a plurality of water body data collectors can be identified and respectively stored in different databases; the data can be fragmented during storage, large-volume complete data are divided into a plurality of fragments and stored in a partitioned mode, then privacy calculation is carried out through a remote monitoring center to obtain the data, the fragmented and partitioned stored data are safely aggregated into complete original data, and then subsequent data processing and analysis are carried out, so that the safety problems of data loss, theft and the like caused by the excessively concentrated storage of the data can be prevented. And safety access and privacy calculation are carried out on the data stored in a distributed mode through the distributed data storage of the data storage server, the data slicing of the remote monitoring center, the privacy sharing and other privacy calculation, so that the safety of the data storage and calculation is improved.
The remote monitoring center is developed based on an ArcGIS Server platform, has an advanced GIS analysis function, reserves a data interface, and can be used for docking with a water quality supervision platform related to a government department and sharing data. The user can connect the remote monitoring center through the PC terminal or the mobile terminal and realize the remote real-time monitoring of river water quality and related Internet of things equipment.
Further, the river water quality monitoring system based on the Internet of things further comprises an image acquisition and preprocessing module, wherein the image acquisition and preprocessing module is used for acquiring river remote sensing images in a monitoring area and preprocessing the acquired river remote sensing image data.
As shown in fig. 2, the preprocessing of the collected river remote sensing image data includes the following steps:
s1, acquiring an acquired river remote sensing image, and correcting the river remote sensing image to obtain a corrected river remote sensing image;
s2, carrying out filtering treatment on the corrected river remote sensing image, and carrying out resolution fusion on the filtered river remote sensing image;
and S3, performing color enhancement treatment on the remote sensing image subjected to resolution fusion to obtain a river remote sensing image subjected to pretreatment.
Then, the river distribution three-dimensional model can be constructed based on the collected river related information and the preprocessed remote sensing image, and the method comprises the following steps:
firstly, acquiring a preprocessed river remote sensing image, acquired distribution conditions of cities and mountains and geographic position coordinates of rivers, mountains and urban buildings; constructing an initial distribution model based on the acquired related data;
secondly, obtaining the topography, the topography information and the surrounding building information of a river distribution area, and mapping the topography, the topography information and the surrounding building information of the river distribution area into the initial distribution model to obtain a three-dimensional scene model;
and finally, acquiring the drop height, the flow direction and other related data of the river, and adjusting, optimizing and rendering the three-dimensional scene model based on the acquired data to obtain a river distribution three-dimensional model. And integrating the river distribution three-dimensional model into the remote monitoring center, combining the river water quality data acquired and uploaded by the water body data acquisition device, acquiring the water temperature, the flow rate, the water quantity and other related data of the river comprehensively in real time, performing intelligent analysis and processing by utilizing machine learning and an artificial intelligence algorithm based on the acquired data, finding abnormal conditions from the data in time, and giving an automatic alarm.
It should be noted that, in the embodiment of the present application, the technical content that is not specifically described in the embodiment of the present application may be implemented by using the existing related technology, which belongs to the prior art, and is not described in detail in the embodiment of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed system, module and method may be implemented in other manners. The above-described system, module embodiments are merely illustrative, and the flowcharts and block diagrams in the figures, for example, illustrate the architecture, functionality, and operation of possible implementations of systems, modules, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
It will be evident to those skilled in the art that the application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (8)
1. River water quality monitoring system based on thing networking, characterized by comprising: the system comprises a plurality of water body data collectors, a local analysis monitoring module, a data storage server, a remote monitoring center and a network communication module, wherein the local analysis monitoring module, the data storage server and the remote monitoring center are in communication connection and data transmission through the network communication module;
the water body data collector is used for collecting and monitoring water quality data of the river in real time and uploading the water quality data to the local analysis and monitoring module;
the local analysis and monitoring module is used for collecting, summarizing, analyzing and calculating collected water quality data and river basic data and predicting water environment;
the data storage server is used for carrying out distributed storage on the collected water quality data and river basic data;
the remote monitoring center is used for acquiring water quality data and river basic data in the data storage server in real time, and carrying out on-line monitoring and early warning on the river water quality through the constructed visual platform of the Internet of things.
2. The river water quality monitoring system based on the internet of things according to claim 1, wherein the plurality of water body data collectors form a multi-hop self-organizing network system through a wireless communication mode.
3. The river water quality monitoring system based on the internet of things according to claim 1, wherein the local analysis monitoring module utilizes a two-dimensional water quality model to analyze and predict water environments of water quality data acquired by a plurality of water data collectors.
4. The river water quality monitoring system based on the internet of things according to claim 2, wherein the wireless communication mode among the plurality of water body data collectors comprises zero or more cascaded wireless repeaters.
5. The river water quality monitoring system based on the internet of things according to claim 1, wherein the data storage server classifies, segments and partitions the collected water quality data and river basic data.
6. The river water quality monitoring system based on the internet of things according to claim 5, wherein the remote monitoring center performs privacy calculation on data stored in the data storage servers in a classified, fragmented or partitioned mode.
7. The river water quality monitoring system based on the internet of things according to claim 1, further comprising an image acquisition and preprocessing module for acquiring river remote sensing images in the monitored area and preprocessing the acquired river remote sensing image data.
8. The river water quality monitoring system based on the internet of things of claim 7, wherein the preprocessing of the collected river remote sensing image data comprises:
acquiring an acquired river remote sensing image, and correcting the river remote sensing image to obtain a corrected river remote sensing image;
filtering the corrected river remote sensing image, and carrying out resolution fusion on the filtered river remote sensing image;
and performing color enhancement processing on the remote sensing image with the fused resolution to obtain a preprocessed river remote sensing image.
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| CN118039013A (en) * | 2024-04-12 | 2024-05-14 | 山东省海洋资源与环境研究院(山东省海洋环境监测中心、山东省水产品质量检验中心) | Ocean water quality detection data processing method and system |
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| CN118039013A (en) * | 2024-04-12 | 2024-05-14 | 山东省海洋资源与环境研究院(山东省海洋环境监测中心、山东省水产品质量检验中心) | Ocean water quality detection data processing method and system |
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