A reservoir monitoring system based on the Internet of Things

Abstract

The present invention relates to the field of intelligent monitoring technology, and specifically to a reservoir monitoring system based on the Internet of Things. It includes a drone, a server and a user terminal. The server includes an inspection planning module, which is prefabricated with a GIS map of the reservoir area for formulating the inspection route of the drone; an image acquisition module, which is used to obtain the aerial image of the water surface taken by the drone; an image recognition module, which is used to identify the aerial image, and identify floating objects on the water surface according to the aerial effect. When there are floating objects, the position of the floating objects is identified according to the drone data and the position of the abnormal area in the aerial image. The drone data includes the drone positioning coordinates and the drone flight altitude; the floating object identification module is used to identify the type of floating objects according to the aerial image, and identify whether it is a floating object that affects the water quality. It can conduct timely and accurate monitoring of reservoir pollution.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent monitoring, and in particular to a reservoir monitoring system based on the Internet of Things. Background Art

[0002] A reservoir is a man-made lake. It is usually formed by building a dam in the middle and upper reaches of a river. When the river water floods the river valley, a reservoir can be formed. A comprehensive utilization reservoir that can regulate and store flood water is built at an appropriate location in the upstream river channel of the flood control area. The reservoir capacity is used to intercept and store flood water, reduce the peak flow entering the downstream river channel, and achieve the purpose of reducing flood disasters. There are two different ways for reservoirs to regulate floods. One is to retain flood water, and the other is to store flood water.

[0003] In recent years, there has been an increase in domestic waste, and major reservoirs are also facing serious pollution problems. As the source of our daily water, reservoirs are extremely polluted. Organic pollution and phosphorus pollution can cause algae to grow wildly, fish to die, and even cause harm to the human body. This process is difficult to monitor in time with the original detection method, and it is impossible to respond effectively. Therefore, a new monitoring method is needed to enable rapid, accurate, and all-weather monitoring of the reservoir environment.

[0004] The existing detection method for reservoir pollution is to set up manual monitoring points in the reservoir, which is often not timely and accurate, and has little effect on garbage monitoring of domestic water sources. Therefore, how to monitor and detect reservoir pollution in a timely and accurate manner is an urgent problem to be solved. Summary of the invention

[0005] The technical problem solved by the present invention is to provide a reservoir monitoring system based on the Internet of Things, which can monitor reservoir pollution in a timely and accurate manner.

[0006] The basic solution provided by the present invention is: a reservoir monitoring system based on the Internet of Things, including a drone, a server and a user terminal, wherein the server includes an inspection planning module, an image acquisition module, an image recognition module, a floating object recognition module, a water body sampling module, a sample analysis module and a floating object management module;

[0007] Inspection planning module, which has a pre-made GIS map of the reservoir area for planning the inspection route of drones;

[0008] An image acquisition module is used to obtain the aerial images of the water surface taken by the drone;

[0009] An image recognition module is used to recognize aerial images and identify floating objects on the water surface based on the aerial image. When there are floating objects, the location of the floating objects is identified based on the drone data and the location of the abnormal area in the aerial image. The drone data includes the drone positioning coordinates and the drone flight altitude.

[0010] The floating object recognition module is used to identify the type of floating objects based on aerial images and whether they are floating objects that affect water quality;

[0011] The water sampling module is used to generate sampling instructions when the floating objects affect the water quality, so that the drone can take water samples in the water area where the floating objects exist, and use the drone's built-in water quality rapid detector to test the water quality, and accept the test results uploaded by the rapid detector;

[0012] The sample analysis module is used to identify whether the test results of the rapid detector meet the pollution standards. If the pollution standards are met, a sampling instruction is generated to enable the drone to take samples and bind the water samples to the location of the floating objects and bring them back for testing by the precision detector.

[0013] The floating object management module is used to package the floating object location, floating object type, and detection results of the rapid detector to generate a salvage instruction when the floating object does not affect the water quality, or the rapid detector does not meet the pollution standard, and send the salvage instruction to the user terminal.

[0014] The principle and advantage of the present invention are: by formulating the inspection route of the drone, the drone can be used to inspect the water surface of the reservoir by aerial photography to identify whether there are floating pollutants on the water surface. When there are floating pollutants, the type of floating objects is first identified through images to determine whether it will affect the water quality. One type of common floating objects on the water surface is suspended floating objects, such as algae, bacteria, clay, domestic pollution excrement, microorganisms, etc., which are suspended on the water surface. Such floating objects will have a greater impact on water quality, such as COD, nitrogen content, and phosphorus content. Another type is floating objects, such as fallen leaves, plastic bags, plastic bottles, and foam. When such floating objects first appear on the water surface, they will not have a greater impact on water quality. It is only necessary to salvage such floating objects. After identifying whether it is a floating object that affects water quality, if it does not affect water quality, directly record the location of the floating object, generate a salvage instruction for the location and type of the floating object, send it to the user terminal, and arrange staff to salvage it. If there are floating objects that affect water quality, the first choice is to use the drone's built-in rapid detector to conduct preliminary sampling of the water quality to identify whether it has reached the preset standard. If it has reached the preset standard, it means that such floating objects have already affected the water quality and further measurement of the water quality is needed so that corresponding measures can be taken for the cause of the pollution. If it has not reached the preset pollution standard, it means that the floating objects have not yet had a significant impact on the water quality. Just like the floating objects that do not affect the water quality, staff can be arranged to salvage them.

[0015] Through the technical solution of this application, drone inspections are used to monitor floating objects and determine the type of floating objects to determine whether they can be directly salvaged or whether water quality needs to be measured and targeted rectification is made, thereby responding to reservoir pollution in a timely and accurate manner.

[0016] Furthermore, the floating object identification module includes a floating object marking module, a multi-directional identification module, a height identification module and a floating object determination module;

[0017] A floating object marking module is used to mark floating objects in the aerial image when floating objects are identified on the water surface;

[0018] The multi-directional identification module controls the drone to obtain aerial images of the floating object from multiple directions;

[0019] The height recognition module recognizes the height of the floating object protruding from the water surface in the aerial images of each direction. When the heights of the protruding from the water surface in different directions are similar and are lower than the preset height threshold, the floating object is judged to be a suspended floating object, otherwise it is an object floating object;

[0020] The floating object determination module determines that when floating objects are suspended in the floating position, they are determined to be floating objects that affect water quality.

[0021] Since algae, bacteria, clay, domestic waste, microorganisms, etc., most of the suspended floating objects are evenly suspended on the surface of the water, so from all angles, they are close to the water surface, not protruding too high, and the height is relatively uniform. As for floating objects, because of the existence of buoyancy, when objects float on the water surface, they usually protrude a certain height from the water surface, and some floating objects, due to different directions and different perspectives, protrude inconsistently from the water surface in different directions. Therefore, the type of floating objects can be judged by the height of the floating objects protruding from the water surface in different directions.

[0022] Further, the floating object identification module also includes a water immersion identification module;

[0023] A water immersion identification module is used to perform image recognition according to the aerial image when the floating object is an object floating object, and identify the object type of the object floating object. The water immersion identification module has a built-in model library, and the model library is pre-set with object models of various object floating objects. The object floating object in the aerial image is compared with the object model in the model library to obtain the object type of the object floating object, and according to its object type and the object state of the floating object appearing in the aerial image, the immersion time of the floating object is identified, and the object state includes the object color and the degree of fragmentation;

[0024] The floating object determination module is also used to determine that the floating object is a floating object that affects water quality when the immersion time of the floating object is higher than the time threshold corresponding to the floating object.

[0025] Most floating objects will not have a significant impact on water quality when they first enter the water, but they may rot or dissolve as the soaking time increases, which will affect the water quality. By identifying the state of floating objects and their soaking time, if the soaking time is long, they will also be listed as floating objects that affect water quality.

[0026] Further, the water immersion recognition module includes a chromaticity recognition module;

[0027] The chromaticity recognition module is used to identify the original chromaticity of the floating object according to the object type, and to identify the current chromaticity of the floating object according to the aerial image, to identify the difference between the original chromaticity and the current chromaticity, and to determine the immersion time of the floating object;

[0028] The fragmentation recognition module is used to identify the original shape of the floating object according to the type of floating object, and to identify the current shape of the floating object according to the aerial image, to identify the degree of fragmentation of the floating object according to the original shape and the current shape, and to identify the duration of immersion of the floating object according to the degree of fragmentation.

[0029] For soluble floating objects, as the soaking time increases, their fragmentation gradually increases. By identifying the difference between the original shape and the current shape of the floating object, its fragmentation degree can be determined, and then the soaking time of the floating object can be estimated. For insoluble floating objects, most of them will also change color with the soaking time. For example, leaves and branches will become darker with the soaking time. For example, some domestic garbage will fade with the soaking time, and the color will become lighter. Therefore, by identifying the difference between the initial color and the current color of the floating object, the soaking time of the floating object can be estimated.

[0030] Further, the floating object management module includes a location prediction module;

[0031] The position prediction module is used to obtain the current water flow velocity in the reservoir and identify the average response time of the user terminal based on historical data. The average response time is the time from sending the salvage instruction to the user terminal to the user terminal reporting the salvage result. According to the water flow velocity, the average response time and the current position of the float, the position of the floating object when the user terminal responds is inferred. According to the water flow velocity during the average response time, the moving distance of the floating object is calculated. According to the current position of the floating object and the moving distance of the floating object, the inferred position of the floating object is obtained, and the inferred position of the floating object is sent to the user terminal.

[0032] For the same water area, the water flow speed is almost the same. Therefore, based on the response time to the salvage command in the historical data and the water flow speed of the water area, the moving distance of the floating object at the time of response is obtained, and combined with the current position of the floating object, the estimated position of the floating object is obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a schematic diagram of an embodiment of a reservoir monitoring system based on the Internet of Things of the present invention. DETAILED DESCRIPTION

[0034] The following is further described in detail through specific implementation methods:

[0035] The embodiment is basically as shown in the attached Figure 1 As shown:

[0036] A reservoir monitoring system based on the Internet of Things, comprising a drone, a server and a user terminal, wherein the server comprises an inspection planning module, an image acquisition module, an image recognition module, a floating object recognition module, a water body sampling module, a sample analysis module and a floating object management module;

[0037] Inspection planning module, which has a pre-made GIS map of the reservoir area for planning the inspection route of drones;

[0038] An image acquisition module is used to obtain the aerial images of the water surface taken by the drone;

[0039] An image recognition module is used to recognize aerial images and identify floating objects on the water surface based on the aerial image. When there are floating objects, the location of the floating objects is identified based on the drone data and the location of the abnormal area in the aerial image. The drone data includes the drone positioning coordinates and the drone flight altitude.

[0040] The floating object recognition module is used to identify the type of floating objects based on aerial images and whether they are floating objects that affect water quality;

[0041] The water sampling module is used to generate sampling instructions when the floating objects affect the water quality, so that the drone can take water samples in the water area where the floating objects exist, and use the drone's built-in water quality rapid detector to test the water quality, and accept the test results uploaded by the rapid detector;

[0042] The sample analysis module is used to identify whether the test results of the rapid detector meet the pollution standards. If the pollution standards are met, a sampling instruction is generated to enable the drone to take samples and bind the water samples to the location of the floating objects and bring them back for testing by the precision detector.

[0043] The floating object management module is used to package the floating object location, floating object type, and detection results of the rapid detector to generate a salvage instruction when the floating object does not affect the water quality, or the rapid detector does not meet the pollution standard, and send the salvage instruction to the user terminal.

[0044] By developing a drone inspection route, the drone can be used to inspect the surface of the reservoir and identify whether there are floating pollutants on the water surface. When there are floating pollutants, the type of floating objects is first identified through images to determine whether they will affect the water quality. One type of common floating objects on the water surface is suspended floating objects, such as algae, bacteria, clay, domestic pollution excrement, microorganisms, etc., which are suspended on the water surface. This type of floating object will have a greater impact on water quality, such as COD, nitrogen content, and phosphorus content. Another type is floating objects, such as fallen leaves, plastic bags, plastic bottles, and foam. When these floating objects first appear on the water surface, they will not have a greater impact on water quality. They only need to be salvaged. After identifying whether it is a floating object that affects water quality, if it does not affect water quality, directly record the location of the floating object, generate a salvage instruction for the location and type of the floating object, send it to the user terminal, and arrange staff to salvage it. If there are floating objects that affect water quality, the first choice is to use the drone's built-in rapid detector to conduct preliminary sampling of the water quality to identify whether it has reached the preset standard. If it has reached the preset standard, it means that such floating objects have already affected the water quality and further measurement of the water quality is needed so that corresponding measures can be taken for the cause of the pollution. If it has not reached the preset pollution standard, it means that the floating objects have not yet had a significant impact on the water quality. Just like the floating objects that do not affect the water quality, staff can be arranged to salvage them.

[0045] Through the technical solution of this application, drone inspections are used to monitor floating objects and determine the type of floating objects to determine whether they can be directly salvaged or whether water quality needs to be measured and targeted rectification is made, thereby responding to reservoir pollution in a timely and accurate manner.

[0046] The floating object identification module includes a floating object marking module, a multi-directional identification module, a height identification module and a floating object determination module;

[0047] A floating object marking module is used to mark floating objects in the aerial image when floating objects are identified on the water surface;

[0048] The multi-directional identification module controls the drone to obtain aerial images of the floating object from multiple directions;

[0049] The height recognition module recognizes the height of the floating object protruding from the water surface in the aerial images of each direction. When the heights of the protruding from the water surface in different directions are similar and are lower than the preset height threshold, the floating object is judged to be a suspended floating object, otherwise it is an object floating object;

[0050] The floating object determination module determines that when the floating objects are suspended floating objects, they are determined to be floating objects that affect water quality.

[0051] Since algae, bacteria, clay, domestic waste, microorganisms, etc., most of the suspended floating objects are evenly suspended on the surface of the water, so from all angles, they are close to the water surface, not protruding too high, and the height is relatively uniform. As for floating objects, because of the existence of buoyancy, when objects float on the water surface, they usually protrude a certain height from the water surface, and some floating objects, due to different directions and different perspectives, protrude inconsistently from the water surface in different directions. Therefore, the type of floating objects can be judged by the height of the floating objects protruding from the water surface in different directions.

[0052] The floating object identification module also includes a water immersion identification module;

[0053] A water immersion identification module is used to perform image recognition according to the aerial image when the floating object is an object floating object, and identify the object type of the object floating object. The water immersion identification module has a built-in model library, and the model library is pre-set with object models of various object floating objects. The object floating object in the aerial image is compared with the object model in the model library to obtain the object type of the object floating object, and according to its object type and the object state of the floating object appearing in the aerial image, the immersion time of the floating object is identified, and the object state includes the object color and the degree of fragmentation;

[0054] The floating object determination module is also used to determine that the floating object is a floating object that affects water quality when the immersion time of the floating object is higher than the time threshold corresponding to the floating object.

[0055] Most floating objects will not have a significant impact on water quality when they first enter the water, but they may rot or dissolve as the soaking time increases, which will affect the water quality. By identifying the state of floating objects and their soaking time, if the soaking time is long, they will also be listed as floating objects that affect water quality.

[0056] The water immersion recognition module includes a chromaticity recognition module;

[0057] The chromaticity recognition module is used to identify the original chromaticity of the floating object according to the object type, and to identify the current chromaticity of the floating object according to the aerial image, to identify the difference between the original chromaticity and the current chromaticity, and to determine the immersion time of the floating object;

[0058] The fragmentation recognition module is used to identify the original shape of the floating object according to the type of floating object, and to identify the current shape of the floating object according to the aerial image, to identify the degree of fragmentation of the floating object according to the original shape and the current shape, and to identify the duration of immersion of the floating object according to the degree of fragmentation.

[0059] For soluble floating objects, as the soaking time increases, their fragmentation gradually increases. By identifying the difference between the original shape and the current shape of the floating object, its fragmentation degree can be determined, and then the soaking time of the floating object can be estimated. For insoluble floating objects, most of them will also change color with the soaking time. For example, leaves and branches will become darker with the soaking time. For example, some domestic garbage will fade with the soaking time, and the color will become lighter. Therefore, by identifying the difference between the initial color and the current color of the floating object, the soaking time of the floating object can be estimated.

[0060] The floating object management module includes a location prediction module;

[0061] The position prediction module is used to obtain the current water flow velocity in the reservoir and identify the average response time of the user terminal based on historical data. The average response time is the time from sending the salvage instruction to the user terminal to the user terminal reporting the salvage result. According to the water flow velocity, the average response time and the current position of the float, the position of the floating object when the user terminal responds is inferred. According to the water flow velocity during the average response time, the moving distance of the floating object is calculated. According to the current position of the floating object and the moving distance of the floating object, the inferred position of the floating object is obtained, and the inferred position of the floating object is sent to the user terminal.

[0062] For the same water area, the water flow speed is almost the same. Therefore, based on the response time to the salvage command in the historical data and the water flow speed of the water area, the moving distance of the floating object at the time of response is obtained, and combined with the current position of the floating object, the estimated position of the floating object is obtained.

[0063] The above are only embodiments of the present invention. Common knowledge such as the known specific structures and characteristics in the scheme is not described in detail here. Ordinary technicians in the relevant field know all the common technical knowledge in the technical field to which the invention belongs before the application date or priority date, can obtain all the existing technologies in the field, and have the ability to apply conventional experimental means before that date. Ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the scope of protection of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A reservoir monitoring system based on the Internet of Things, characterized by: It includes a drone, a server and a user terminal, wherein the server includes an inspection planning module, an image acquisition module, an image recognition module, a floating object recognition module, a water body sampling module, a sample analysis module and a floating object management module; Inspection planning module, which has a pre-made GIS map of the reservoir area for planning the inspection route of drones; An image acquisition module is used to obtain the aerial images of the water surface taken by the drone; An image recognition module is used to recognize aerial images and identify floating objects on the water surface based on the aerial image. When there are floating objects, the location of the floating objects is identified based on the drone data and the location of the abnormal area in the aerial image. The drone data includes the drone positioning coordinates and the drone flight altitude. The floating object recognition module is used to identify the type of floating objects based on aerial images and whether they are floating objects that affect water quality; The water sampling module is used to generate sampling instructions when the floating objects affect the water quality, so that the drone can take water samples in the water area where the floating objects exist, and use the drone's built-in water quality rapid detector to test the water quality, and accept the test results uploaded by the rapid detector; The sample analysis module is used to identify whether the test results of the rapid detector meet the pollution standards. If the pollution standards are met, a sampling instruction is generated to enable the drone to take samples and bind the water samples to the location of the floating objects and bring them back for testing by the precision detector. The floating object management module is used to package the floating object location, floating object type, and detection results of the rapid detector to generate a salvage instruction when the floating object is not a floating object that affects water quality, or the rapid detector does not meet the pollution standard, and send the salvage instruction to the user terminal; the floating object identification module includes a floating object marking module, a multi-directional identification module, a height identification module, and a floating object determination module; A floating object marking module is used to mark floating objects in the aerial image when floating objects are identified on the water surface; The multi-directional identification module controls the drone to obtain aerial images of the floating object from multiple directions; The height recognition module recognizes the height of the floating object protruding from the water surface in the aerial images of each direction. When the heights of the protruding from the water surface in different directions are similar and are lower than the preset height threshold, the floating object is judged to be a suspended floating object, otherwise it is an object floating object; A floating object determination module determines that the floating object is a floating object that affects water quality when the floating object is a suspended floating object; the floating object identification module also includes a water immersion identification module; A water immersion identification module is used to perform image recognition according to the aerial image when the floating object is an object floating object, and identify the object type of the object floating object. The water immersion identification module has a built-in model library, and the model library is pre-set with object models of various object floating objects. The object floating object in the aerial image is compared with the object model in the model library to obtain the object type of the object floating object, and according to its object type and the object state of the floating object appearing in the aerial image, the immersion time of the floating object is identified, and the object state includes the object color and the degree of fragmentation; The floating object determination module is also used to determine that the floating object is a floating object that affects water quality when the immersion time of the floating object is higher than the time threshold corresponding to the floating object.

2. The reservoir monitoring system based on the Internet of Things according to claim 1 is characterized in that: The water immersion recognition module includes a chromaticity recognition module; The chromaticity recognition module is used to identify the original chromaticity of the floating object according to the object type, and to identify the current chromaticity of the floating object according to the aerial image, to identify the difference between the original chromaticity and the current chromaticity, and to determine the immersion time of the floating object; The fragmentation recognition module is used to identify the original shape of the floating object according to the type of floating object, and to identify the current shape of the floating object according to the aerial image, to identify the degree of fragmentation of the floating object according to the original shape and the current shape, and to identify the length of time the floating object has been submerged in water according to the degree of fragmentation.

3. A reservoir monitoring system based on the Internet of Things according to claim 2, characterized in that: The floating object management module includes a location prediction module; The position prediction module is used to obtain the current water flow velocity in the reservoir and identify the average response time of the user terminal based on historical data. The average response time is the time from sending the salvage instruction to the user terminal to the user terminal reporting the salvage result. According to the water flow velocity, the average response time and the current position of the float, the position of the floating object when the user terminal responds is inferred. According to the water flow velocity during the average response time, the moving distance of the floating object is calculated. According to the current position of the floating object and the moving distance of the floating object, the inferred position of the floating object is obtained, and the inferred position of the floating object is sent to the user terminal.

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