KR20210039527A - System for providing 2-dimensional water quality map using unmanned ship vehicle (usv) with fluorescence spectroscopy, and method for the same - Google Patents

Abstract

Provided are a three-dimensional water quality map creation system using a movable unmanned ship equipped with a fluorescent sensor and a method thereof. Since a fluorescent sensor for water quality measurement and a water depth sensor are mounted on a movable unmanned ship (USV) capable of autonomous driving to measure water quality and water depth at the same time, a two-dimensional water quality map indicating a spatial distribution range of water pollution can be created with respect to a water specimen such as a river, a lake or the like, and also, since a fluorescent sensor and a depth sensor, which can measure chlorophyll-a, phycocyanin and total organic matter concentrations, are installed as an integrated body in the movable unmanned ship capable of autonomous driving, the total organic matter and algal bloom concentrations of a water specimen area can be measured in various directions, and water depth measurement can be performed to observe an influence conveyed from water depth to water quality. Also, a movable unmanned ship capable of water depth and water quality measurement is used to create a two-dimensional image water quality map in regard to total organic matter and algal bloom changes of the water specimen area.

Description

Two-dimensional water quality map creation system using a mobile unmanned ship equipped with a fluorescent sensor and its method {SYSTEM FOR PROVIDING 2-DIMENSIONAL WATER QUALITY MAP USING UNMANNED SHIP VEHICLE (USV) WITH FLUORESCENCE SPECTROSCOPY, AND METHOD FOR THE SAME}

The present invention relates to a two-dimensional water quality map creation system using a mobile unmanned ship, and more specifically, a fluorescence sensor for water quality measurement (Fluorescence spectroscopy) and a water depth sensor on a mobile unmanned ship (USV) capable of autonomous navigation. By installing and measuring the water quality and depth at the same time, it creates a two-dimensional water quality map indicating the spatial distribution range of water pollution targeting water bodies such as rivers and lakes, and a two-dimensional water quality map using a mobile unmanned ship equipped with a fluorescent sensor. It relates to a system and a method thereof.

In general, as a method of measuring water quality for a water body, there are a method of measuring the water quality for a point by installing an online meter per point, and a method of determining the water quality for a representative point by field sampling.

The water quality measurement method using the former online measuring instrument measures one data per point, and the latter method of water quality determination by field sampling takes a long time to analyze, and only shows the water quality at the sampling point. Has a limitation that it cannot represent the total water quality.

Specifically, the water quality measurement method using an online measuring instrument is inconvenient to receive replacement or repair in the event of a failure of such a measuring instrument, because the measuring instrument is often installed in a place that is difficult to access, and a ship is used to measure the water quality in a place where it is difficult to reach a person. There is a limit of being very inconvenient because it must be done. In addition, there is a limitation that water quality changes frequently change dramatically within a short time due to various environmental factors such as rain and wind.

In addition, in the case of the water quality determination method by field sampling, the water quality must be monitored by field measurement in large areas such as rivers and lakes, so there is a limitation in time and space. In addition, in water bodies such as rivers, the depth of the water has a great influence on the water quality, and in particular, the green algae generated in the rivers are affected by the water depth. Accordingly, in the case of the water quality determination method by field sampling, there is a problem that it is inappropriate to represent the whole water body to monitor the water quality of the water body in the target range at one point.

In order to compensate for the limitations of the method of measuring water quality of the water body according to the prior art described above, recently, there have been increasing cases of technology development for measuring the water quality of the water body using an unmanned ship vehicle (USV). That is, the mobile unmanned aerial vehicle (USV) can be applied to monitor the water quality of water bodies such as rivers, rivers, ponds, lakes, and estuaries.

However, in the case of such a mobile unmanned aerial vehicle (USV), a water quality measurement sensor (or water quality sensor) is required to monitor the water quality of the water body. The development of sensors and monitoring technologies capable of indicating the concentration of organic matter is inadequate, and data work and systems for expressing them as two-dimensional images are also inadequate. In addition, as the organic material index has recently been converted to Total Organic Carbon (TOC) as a standard for the water quality of river water, it is necessary to monitor the organic material index including the total organic carbon (TOC).

Republic of Korea Patent No. 10-883046 (filing date: June 11, 2013), title of invention: "Unmanned remote water quality and meteorological environment monitoring vessel and its operation method" Republic of Korea Patent No. 10-1496083 (filing date: January 24, 2014), title of the invention: "Chlorophyll and algae measuring apparatus and method using a fluorescent black line" Republic of Korea Patent No. 10-1684407 (filing date: December 02, 2016), title of the invention: "Water pollution measuring system and water pollution measuring device using an optical sensor" Republic of Korea Patent No. 10-1406884 (application date: June 5, 2014), title of invention: "On-line water quality measurement system based on multi-wavelength analysis for real-time detection of organic pollutants in water" Republic of Korea Patent No. 10-1338038 (filing date: September 5, 2012), title of invention: "Red tide and green algae outbreak monitoring device using laser" Republic of Korea Patent No. 10-1075561 (filing date: June 10, 2011), title of invention: "Multi water quality measuring device based on wired and wireless Internet" Republic of Korea Patent No. 10-906654 (filing date: July 4, 2008), title of invention: "Small Reservoir and Reclamation Desalination Lake Agricultural Water Remote Water Quality Automatic Observation System and Turbidity Observation Method" Republic of Korea Patent No. 10-522764 (filing date: November 20, 2002), title of invention: "Real-time water quality monitoring device and its control method" Republic of Korea Registered Patent No. 10-1936586 (filing date: February 15, 2017), title of invention: "River green algae map creation system and method using self-driving unmanned aerial vehicle and mobile unmanned aerial vehicle"

The technical problem to be achieved by the present invention for solving the above-described problems is to simultaneously measure water quality and depth by attaching a fluorescent sensor for water quality measurement and a water depth sensor to a mobile unmanned aerial vehicle (USV) capable of autonomous navigation. It is to provide a system and method for creating a 2D water quality map using a mobile unmanned ship equipped with a fluorescent sensor that can create a 2D water quality map representing the spatial distribution range of water pollution for the same water body.

Another technical problem to be achieved by the present invention is to integrate a fluorescent sensor and a depth sensor capable of measuring multiple concentrations of chlorophyll-a, phycocyanin, and total organic matter on a mobile unmanned aerial vehicle capable of autonomous navigation. And to provide a two-dimensional water quality map creation system and method using a mobile unmanned ship equipped with a fluorescent sensor that can measure the concentration of green algae in various directions and observe the effect of the water depth on the water quality. will be.

Another technical problem to be achieved by the present invention is a mobile unmanned aerial vehicle equipped with a fluorescent sensor capable of creating a water quality map of a two-dimensional image of changes in total organic matter and green algae in a water body area using a mobile unmanned aerial vehicle capable of measuring water depth and water quality. It is to provide a system and method for creating a two-dimensional water quality map using lines.

As a means for achieving the above-described technical problem, the system for creating a two-dimensional water quality map using a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to the present invention is equipped with a GPS module to enable autonomous navigation. A mobile unmanned aerial vehicle that operates along a preset route by inputting a GPS coordinate point after setting an area and route, and simultaneously measuring the water quality and depth of the river to be measured by mounting a fluorescence sensor and a depth sensor; It is mounted in the mobile unmanned aerial vehicle to control autonomous navigation and collision avoidance of the mobile unmanned aerial vehicle, and collects water quality data and water depth data measured from the fluorescence sensor and the water depth sensor together with the coordinate data of the GPS module and transmits wirelessly in real time. Integrated management module; And a manager terminal for wirelessly receiving water quality data, water depth data, and coordinate data from the integrated management module to create a two-dimensional water quality map in real time, wherein the fluorescence sensor of the mobile unmanned ship is calculated as a fluorescence intensity value. It is characterized in that the concentration, the phycocyanin concentration, and the total organic matter concentration are measured multiplexed, and the depth sensor measures the water depth at the same time.

Here, the fluorescence sensor measures a fluorescence intensity value representing a concentration of chlorophyll-a and a concentration of phycocyanin, but the concentration of chlorophyll-a is an emission wavelength of 650 nm to 700 nm and an excitation wavelength of 400 nm to 450 nm, 675 nm. It represents the fluorescence intensity value measured at the emission wavelength of ~725nm and the excitation wavelength of 650nm~700nm, and the phycocyanin concentration is measured at the emission wavelength of 650nm~720nm and the excitation wavelength of 600nm~630nm. Represents a fluorescence intensity value, and the concentration of chlorophyll-a is given as Chlorophyll-a(㎍/L) = [(Intensity, 425nm, 675nm) + b] / a, where a = 0.0014, b = 0.0085 However, the a and b values can be changed according to the fluorescence intensity value, and the phycocyanin concentration is given as Blue Green Algae(㎍/L) = [(Intensity, 610 nm) + b] / a, In this case, a = 0.0006 and b = 0.0076 are given, but the a and b values may be changed according to the fluorescence intensity value.

Here, the fluorescence sensor measures a fluorescence intensity value representing a total organic concentration according to the first, second, and third matrices (C1, C2, C3) extracted for organic substance concentration analysis, and the second matrix (C2) Represents a fluorescence intensity value measured at an emission wavelength of 350 nm to 450 nm and an excitation wavelength of 300 nm to 350 nm, and the first matrix C1 has an emission wavelength of 400 nm to 500 nm and an emission wavelength of 250 nm to 300 nm. A fluorescence intensity value measured at an excitation wavelength is indicated, and the third matrix C3 indicates a fluorescence intensity value measured at an emission wavelength of 300 nm and an excitation wavelength of 275 nm, and the total organic concentration (TOC) is TOC (Mg/L) = [(C2 x C1/C3) + b] / a is given, in this case, a = 52.305, b = 37.687, but the a and b values can be changed according to the fluorescence intensity value. .

Here, the first matrix (C1) represents the concentration of humic acid among the total organic substance concentration, the second matrix (C2) represents the concentration of humic acid and fulvic acid among the total organic substance concentration, and the third matrix (C3) represents the total organic substance concentration. Characterized in that it shows the protein concentration.

Here, each fluorescence intensity value measured by the fluorescence sensor is converted to a concentration in the data processing unit of the manager terminal, and the data converted to the concentration is organized by a statistical technique and matched with the coordinate data, and then the two-dimensional water quality It is characterized by being mapped to a map.

Here, the mobile unmanned aerial vehicle may include a mobile unmanned aerial vehicle body; A water quality sensor, comprising: a fluorescence sensor mounted on the mobile unmanned aerial vehicle body to measure multiple concentrations of chlorophyll-a, phycocyanin concentrations, and total organic matters calculated as fluorescence intensity values; A depth sensor installed on the mobile unmanned aerial vehicle body to measure the depth of a target river in real time; An automatic navigation device, comprising: a GPS module mounted on the main body of the mobile unmanned aerial vehicle to generate coordinate data representing the location of the mobile unmanned aerial vehicle; And an autonomous navigation driving unit for driving the mobile unmanned aerial vehicle main body to autonomously navigate along a preset navigation route in which a GPS coordinate point is input.

Here, the mobile unmanned aerial vehicle includes: a camera installed on an upper front surface of the mobile unmanned aerial vehicle body to photograph an obstacle in front of the autonomous navigation route; And a lidar sensor installed on the side of the camera and measuring a distance to the obstacle by radiating a laser pulse and measuring a return from the obstacle, wherein the mobile unmanned aerial vehicle includes the camera and the lidar sensor It is characterized in that it is controlled to avoid a collision when unexpected obstacles are found during autonomous navigation at the top of the water body.

Here, the integrated management module includes: a data collection unit for collecting water quality data measured by the fluorescence sensor and water depth data measured by the water depth sensor; An integrated management unit that converts the water quality and depth data collected by the data collection unit and coordinate data of the GPS module to enable wireless transmission, and integrates and manages the autonomous navigation of the mobile unmanned aerial vehicle; A wireless communication module, comprising: a data transmission unit for wirelessly transmitting water quality, water depth and coordinate data of the integrated management unit; And an autonomous navigation control unit that controls the driving of the autonomous navigation driving unit of the mobile unmanned aerial vehicle.

Here, the integrated management module may further include a collision avoidance control unit that controls the driving of the autonomous navigation driving unit to avoid a collision when an unexpected obstacle is found during autonomous navigation of the mobile unmanned aerial vehicle.

Here, the manager terminal, as a wireless communication module, the data receiving unit for wirelessly receiving water quality, water depth and coordinate data from the data transmission unit of the integrated management module; A data processing unit processing the received water quality, depth and coordinate data to derive effective values according to a data mining technique to which a statistical numerical analysis algorithm is applied; A data analysis and mapping unit that analyzes the data processed by the data processing unit and maps the point-based data, which is arranged as an effective value, into a cell-based map using an interpolation method; And a two-dimensional water quality map creation unit that creates a two-dimensional water quality map for the concentration of green algae and total organic matter in a water body in response to the map mapping of the data analysis and mapping unit.

Here, the manager terminal may further include an image editing unit for editing and changing an image according to a water depth and a type of water when there is a change in the 2D water quality map created by the 2D water quality map creation unit.

Here, the data processing unit is characterized in that firstly, the measurement error value is excluded, and secondly, the data is arranged based on a coordinate value representing a space.

Here, the data analysis and mapping unit may perform interpolation by selecting an inverse distance weighting method or a kriging interpolation method.

On the other hand, as another means for achieving the above-described technical problem, the method for creating a two-dimensional water quality map using a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to the present invention comprises the steps of: a) autonomously operating a mobile unmanned aerial vehicle within a water body; b) measuring the water quality using a fluorescent sensor mounted on the mobile unmanned ship, and measuring the water depth using a water depth sensor at the same time; c) collecting the measured water quality and depth data by an integrated management module mounted on the mobile unmanned aerial vehicle; d) transmitting, by the integrated management module, the collected water quality and depth data together with coordinate data to a manager terminal in real time; e) the manager terminal processing the transmitted water quality and depth data to derive an effective value; f) the manager terminal analyzing the processed data and mapping it to a map; And g) the manager terminal creating a two-dimensional water quality map for the green algae concentration and total organic matter concentration in the water body, wherein the fluorescence sensor of step b) is a water quality sensor, chlorophyll-a concentration, phycocyanin concentration And multiple measurements of the water quality of the water body with respect to the total organic carbon concentration.

According to the present invention, the spatial distribution range of water pollution in water bodies such as rivers and lakes by simultaneously measuring water quality and depth by attaching a fluorescent sensor for water quality measurement and a water depth sensor to a mobile unmanned aerial vehicle (USV) capable of autonomous navigation. You can create a two-dimensional water quality map showing

According to the present invention, by integrating a fluorescence sensor and a depth sensor capable of measuring multiple concentrations of chlorophyll-a, phycocyanin and total organic matter on a mobile unmanned aerial vehicle capable of autonomous navigation, the total organic concentration and algal concentration in the water body area can be varied. It can be measured in a direction and the depth of water can be measured, so that the effect of water depth on the water quality can be observed. In other words, by integrating a depth sensor and a fluorescent sensor on an autonomous mobile unmanned ship, the total organic matter and green algae concentration in water bodies such as rivers, lakes, reservoirs, and sea areas can be constructed as an integrated monitoring device. Accordingly, the behavior of the water depth on the water quality can be analyzed.

According to the present invention, it is possible to create a water quality map of a two-dimensional image of changes in total organic matter and green algae in a water body area using a mobile unmanned aerial vehicle capable of measuring water depth and water quality.

According to the present invention, changes in total organic matter and green algae in the water body area can be quickly analyzed in two dimensions for all water bodies.

According to the present invention, since it is possible to know the change in water quality and the depth of the water body without inconvenient field sampling that has to go out by boat from the ground, the total organic matter and green algae of the total area of the water body requested are not monitored by a single point in the water body. Changes can be expressed in two-dimensional visual images.

1 is a diagram illustrating a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to an embodiment of the present invention.
2 is a schematic configuration diagram of a system for creating a two-dimensional water quality map using a mobile unmanned ship equipped with a fluorescent sensor according to an embodiment of the present invention.
3 is a detailed configuration diagram of a manager terminal in a system for creating a two-dimensional water quality map using a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to an embodiment of the present invention.
4 is a diagram showing a matrix of wavelengths indicating the concentration of chlorophyll-a and the concentration of phycocyanin detected by fluorescence analysis.
5 is a diagram showing fluorescence intensity values indicating the concentration of chlorophyll-a and the concentration of phycocyanin detected by fluorescence analysis.
6 is a diagram showing the correlation between the concentration of chlorophyll-a and the wavelength value.
7A to 7C are diagrams showing matrices extracted for organic substance concentration analysis, respectively.
8 is a diagram showing the correlation between the matrix (C1, C2, C3) and the total organic concentration (TOC).
9 is an operation flow diagram of a method for creating a two-dimensional water quality map using a mobile unmanned ship equipped with a fluorescent sensor according to an embodiment of the present invention.
10 is an operation flow diagram specifically showing the creation of a 2D water quality map by a manager terminal in the method of creating a 2D water quality map using a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to an embodiment of the present invention.
11 is a view showing a two-dimensional image of total organic matter and green algae concentration in a water body in a method for creating a two-dimensional water quality map using a mobile unmanned ship equipped with a fluorescent sensor according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art can easily implement the present invention. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part "includes" a certain component, it means that other components may be further included rather than excluding other components unless specifically stated to the contrary. In addition, terms such as "... unit" described in the specification mean a unit that processes at least one function or operation, which may be implemented by hardware or software, or a combination of hardware and software.

Hereinafter, a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to an embodiment of the present invention will be described with reference to FIG. 1, and a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to an embodiment of the present invention will be described with reference to FIGS. A system for creating a two-dimensional water quality map using lines will be described, and a method for creating a two-dimensional water quality map using a mobile unmanned ship equipped with a fluorescent sensor according to an embodiment of the present invention will be described with reference to FIGS. 9 to 11. .

[2D water quality map creation system using a mobile unmanned ship equipped with a fluorescent sensor]

1 is a diagram illustrating a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to an embodiment of the present invention.

As shown in Fig. 1, the mobile unmanned aerial vehicle 100 equipped with a fluorescence sensor according to an embodiment of the present invention includes a depth sensor 120, a fluorescence sensor 130, and a GPS module on the unmanned vehicle body 110. (140), a camera 160 and a Lidar sensor 170 are mounted.

Here, the fluorescence sensor 130 is a water quality sensor, and the fluorescence intensity value measured by the fluorescence sensor 130 is transmitted in real time to the integrated management module, and at this time, the measurement value measured by the fluorescence sensor 130 is It consists of one or more data per second. For example, the fluorescence sensor 130 is installed in the middle of the mobile unmanned aerial vehicle 100 to measure the total organic matter and green algae concentration on the measuring body.

In addition, the Lidar (LIght Detection And Ranging) sensor is a device that accurately draws the surroundings by emitting a laser pulse and measuring the distance to the object by receiving the light reflected back from the surrounding target object. These Lidar sensors are used not only for distance to a target object, but also for moving speed and direction, temperature, analysis of ambient air substances, and concentration measurement.

In addition, the movable unmanned aerial vehicle 100 equipped with a fluorescence sensor according to an embodiment of the present invention includes the mobile unmanned aerial vehicle 100 from the upper part of the water body by the camera 160 and the lidar sensor 170 shown in FIG. 1. It is controlled to avoid collision when unexpected obstacles are found during autonomous navigation.

Meanwhile, FIG. 2 is a schematic configuration diagram of a system for creating a two-dimensional water quality map using a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to an embodiment of the present invention. This is a detailed configuration diagram of a manager terminal in a two-dimensional water quality map creation system using a mobile unmanned ship.

Referring to FIG. 2, a system for creating a two-dimensional water quality map using a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to an embodiment of the present invention includes a mobile unmanned aerial vehicle 100, an integrated management module 200, and a manager terminal ( 300). Here, the mobile unmanned aerial vehicle 100 includes a mobile unmanned aerial vehicle body 110, a depth sensor 120, a fluorescence sensor 130, a GPS module 140, and an autonomous navigation driver 150, and further, the mobile The unmanned aerial vehicle 100 includes a camera 160 and a Lidar sensor 170, as shown in FIG. 1. In addition, the integrated management module 200 includes a data collection unit 210, an integrated management unit 220, a data transmission unit 230, an autonomous navigation control unit 240, and a collision avoidance control unit 250.

The mobile unmanned ship 100 is equipped with a GPS module 140 to enable autonomous navigation, and operates according to a preset route by inputting a GPS coordinate point after setting the area and route of the river to be measured in advance. ) And a depth sensor 120 to measure the water quality and depth of the river to be measured at the same time. Here, the fluorescence sensor 130 of the mobile unmanned aerial vehicle 100 multi-measures the chlorophyll-a concentration, the phycocyanin concentration, and the total organic concentration calculated as the fluorescence intensity value, and at the same time, the depth sensor 120 Measure.

Specifically, the fluorescence sensor 130 of the mobile unmanned ship 100 is a water quality sensor, and is mounted on the mobile unmanned ship body 110 to calculate the fluorescence intensity value of the chlorophyll-a concentration, the phycocyanin concentration, and the total organic matter concentration. Is measured multiple times. In other words, each fluorescence intensity value measured by the fluorescence sensor 130 is converted into concentration by the data processing unit 320 of the manager terminal 300, as described later, and data converted into the concentration May be summarized using a statistical technique, matched with the coordinate data, and then mapped to a two-dimensional water quality map. In addition, the depth sensor 120 of the mobile unmanned aerial vehicle 100 is installed in the mobile unmanned aerial vehicle body 110 to measure the depth of the target river in real time.

In addition, the GPS module 140 of the mobile unmanned aerial vehicle 100 is an automatic navigation device and is mounted on the mobile unmanned aerial vehicle body 110 to generate coordinate data indicating the location of the mobile unmanned aerial vehicle 100.

The autonomous navigation driving unit 150 of the mobile unmanned aerial vehicle 100 drives the mobile unmanned aerial vehicle body 110 to operate autonomously along a preset navigation route in which a GPS coordinate point is input. That is, the autonomous navigation driving unit 150 operates autonomously according to the movement route according to the route arbitrarily set by the user based on GPS along the navigation route automatically set by the mobile unmanned aerial vehicle 100. At this time, the mobile unmanned aerial vehicle 100 grasps a location using a GPS signal along a set navigation route, records the location, and transmits it to the manager terminal 300 in real time.

In addition, the camera 160 of the mobile unmanned aerial vehicle 100 is installed on the upper front of the mobile unmanned aerial vehicle body 110 to photograph an obstacle in front of the autonomous navigation route, and a lidar sensor of the mobile unmanned aerial vehicle 100 ( 170) is installed on the side of the camera 160 and measures the distance to the obstacle by measuring the reflected return from the obstacle by emitting a laser pulse, and accordingly, the mobile unmanned ship 100 It is controlled by the camera 160 and the lidar sensor 170 to avoid a collision when an unexpected obstacle is found during autonomous navigation in the upper part of the water body.

Referring again to FIG. 2, the integrated management module 200 is an integrated monitoring unit that manages the mobile unmanned aerial vehicle 100 capable of autonomous navigation, and comprehensively leads the navigation and data management of the mobile unmanned aerial vehicle 100. do. That is, the integrated management module 200 is mounted in the mobile unmanned aerial vehicle 100 to control autonomous navigation and collision avoidance of the mobile unmanned aerial vehicle 100, and together with the coordinate data of the GPS module 140 Water quality data and water depth data measured from the sensor 130 and the depth sensor 120 are collected and wirelessly transmitted in real time.

Specifically, as shown in Figure 2, the data collection unit 210 of the integrated management module 200 is the water quality data measured by the fluorescence sensor 130 and the depth data measured by the depth sensor 120 To collect.

The integrated management unit 220 of the integrated management module 200 converts the water quality and depth data collected by the data collection unit 210 and the coordinate data of the GPS module 140 to enable wireless transmission, and the mobile unmanned The autonomous operation of the ship 100 is integrated and managed. That is, chlorophyll-a intensity transmitted from the fluorescence sensor 130, phycocyanin intensity, total organic matter intensity, depth data transmitted from the depth sensor 120, and GPS coordinates transmitted from the GPS module 140 are integrated in real time. It may be transmitted to the manager terminal 300 via the management unit 220.

The data transmission unit 230 of the integrated management module 200 is a wireless communication module and wirelessly transmits the water quality, water depth and coordinate data of the integrated management unit 220.

The autonomous navigation control unit 240 of the integrated management module 200 controls the driving of the autonomous navigation driving unit 150 of the mobile unmanned aerial vehicle 100.

The collision avoidance control unit 250 of the integrated management module 200 controls the driving of the autonomous navigation driving unit 150 to avoid a collision when an unexpected obstacle is found during autonomous navigation of the mobile unmanned aerial vehicle 100.

Referring back to FIG. 3, the manager terminal 300 wirelessly receives water quality data, water depth data, and coordinate data from the integrated management module 200, and creates a two-dimensional water quality map in real time.

Specifically, as shown in FIG. 3, the manager terminal 300 includes a data receiving unit 310, a data processing unit 320, a data analysis and mapping unit 330, and a two-dimensional water quality map creation unit 340. And an image editing unit 350.

The data receiving unit 310 of the manager terminal 300 is a wireless communication module and wirelessly receives water quality, water depth, and coordinate data from the data transmission unit 230 of the integrated management module 200.

The data processing unit 320 of the manager terminal 300 processes the received water quality, depth and coordinate data to derive valid values according to a data mining technique to which a statistical numerical analysis algorithm is applied.

The data analysis and mapping unit 330 of the manager terminal 300 analyzes the data processed by the data processing unit 320 and calculates the point-based data organized into an effective value by using an interpolation method. ) Based map. Here, as described later, the data analysis and mapping unit 330 may perform interpolation by selecting an Inverse Distance Weighted (IDW) method or a Kriging Interpolation method.

The two-dimensional water quality map creation unit 340 of the manager terminal 300 creates a two-dimensional water quality map for the green algae concentration and total organic matter concentration in the water body in response to the map mapping of the data analysis and mapping unit 330.

When there is a change in the 2D water quality map created by the 2D water quality map creation unit 340, the image editing unit 350 of the manager terminal 300 edits and changes the image according to the water depth and water quality type.

In other words, in the case of a two-dimensional water quality map creation system using a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to an embodiment of the present invention, the chlorophyll-a by an algorithm through the data processing unit 320 of the manager terminal 300 Calculate concentration, phycocyanin concentration, and total organic matter concentration, process data by statistical technique by matching with coordinates, and create a two-dimensional water quality map expressing water depth and water quality in the two-dimensional water quality map creation unit 340 And, when there is a change in the map created by the image editing unit 350, the water quality map is edited.

Meanwhile, FIG. 4 is a diagram showing a matrix of wavelengths indicating chlorophyll-a concentration and phycocyanin concentration detected by fluorescence analysis, and FIG. 5 is a diagram showing chlorophyll-a concentration and phycocyanin concentration detected by fluorescence analysis. It is a diagram showing a fluorescence intensity value, and FIG. 6 is a diagram showing a correlation between a concentration of chlorophyll-a and a wavelength value.

4 and 5, the fluorescence sensor 130 measures a fluorescence intensity value representing a chlorophyll-a concentration and a phycocyanin concentration, but the chlorophyll-a concentration is an emission wavelength of 650 nm to 700 nm. And an excitation wavelength of 400 nm to 450 nm, an emission wavelength of 675 nm to 725 nm, and fluorescence intensity values measured at an excitation wavelength of 650 nm to 700 nm, and the phycocyanin concentration is an emission wavelength of 650 nm to 720 nm. And the fluorescence intensity values measured at an excitation wavelength of 600 nm to 630 nm.

Here, the concentration of chlorophyll-a is given by Chlorophyll-a(㎍/L) = [(Intensity, 425nm, 675nm) + b] / a, where a = 0.0014, b = 0.0085, The values a and b may be changed according to the fluorescence intensity value.

In addition, the phycocyanin concentration is given by Blue Green Algae (㎍/L) = [(Intensity, 610 ㎚) + b] / a, in which case, a = 0.0006, b = 0.0076, but the a and b The value can be changed according to the fluorescence intensity value.

On the other hand, FIGS. 7A to 7C are diagrams each showing a matrix extracted for analysis of organic matter concentration, and FIG. 8 is a diagram showing a correlation between the matrices C1, C2, and C3 and the total organic matter concentration (TOC).

7A to 7C, the fluorescence sensor 130 calculates a fluorescence intensity value representing the total organic concentration according to the first, second, and third matrices C1, C2, and C3 extracted for organic substance concentration analysis. However, the second matrix C2 represents a fluorescence intensity value measured at an emission wavelength of 350 nm to 450 nm and an excitation wavelength of 300 nm to 350 nm, and the first matrix C1 is 400 nm to 500 nm. The fluorescence intensity values measured at the emission wavelength of and the excitation wavelength of 250 nm to 300 nm are shown, and the third matrix C3 represents the fluorescence intensity values measured at the emission wavelength of 300 nm and the excitation wavelength of 275 nm.

At this time, the total organic concentration (TOC) is given by TOC (mg/L) = [(C2 x C1/C3) + b] / a, where a = 52.305, b = 37.687, but the a The values of and b can be changed according to the fluorescence intensity value.

Here, the first matrix (C1) of FIG. 7A represents the concentration of humic acid among the total organic substances concentration, and the second matrix (C2) of FIG. 7B represents the humic acid and fulvic acid (Fulvic acid) of the total organic substance concentration. Acid) concentration, and the third matrix (C3) of FIG. 7C represents the protein (Tryptophan-like) concentration of the total organic matter concentration.

)를 산출할 수 있다.In addition, as shown in Fig. 8, a multi-directional analysis of the data mining technique is used, and the total organic concentration (

) Can be calculated.

는 차원

샘플에서 측정된 방출 파장

, 여기파장

의 형광강도값이다.

,

및

는 모델에 의해 생성된 매개변수이다. 즉, 도 8은 모델링에 의해 산출된 값과 C1, C2, C3의 관계와 총유기탄소(TOC) 농도와의 상관성을 나타낸 것이다.here,

Is the dimension

Emission wavelength measured in the sample

, Excitation wavelength

Is the fluorescence intensity value of.

,

And

Is the parameter generated by the model. That is, FIG. 8 shows the relationship between the values calculated by modeling and C1, C2, and C3, and the correlation between the total organic carbon (TOC) concentration.

In the end, according to the two-dimensional water quality map creation system using a mobile unmanned aerial vehicle equipped with a fluorescence sensor according to an embodiment of the present invention, a water quality measurement fluorescence sensor and a water depth sensor are mounted on a mobile unmanned vehicle (USV) capable of autonomous navigation. By measuring the water quality and depth at the same time, it is possible to create a two-dimensional water quality map showing the spatial distribution range of water pollution for water bodies such as rivers and lakes.

[How to create a two-dimensional water quality map using a mobile unmanned ship equipped with a fluorescent sensor]

9 is an operation flow diagram of a method for creating a two-dimensional water quality map using a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to an embodiment of the present invention, and FIG. 10 is a mobile unmanned aerial vehicle equipped with a fluorescence sensor according to an embodiment of the present invention. In the method of creating a two-dimensional water quality map using, an operation flow chart specifically showing the creation of a two-dimensional water quality map of a manager terminal, and FIG. 11 is a method of creating a two-dimensional water quality map using a mobile unmanned ship equipped with a fluorescent sensor according to an embodiment of the present invention Is a diagram showing a two-dimensional image of the concentration of total organic matter and green algae in the water body.

9 and 10, in the method of creating a two-dimensional water quality map using a mobile unmanned aerial vehicle equipped with a fluorescent sensor according to an embodiment of the present invention, first, the mobile unmanned aerial vehicle 100 is autonomously operated in the water body ( S110).

Next, the water quality is measured using the fluorescent sensor 130 mounted on the mobile unmanned ship 100, and at the same time, the water depth is measured using the water depth sensor 120 (S120). Here, the fluorescence sensor 130 is a water quality sensor, and measures the water quality of the water body with respect to the chlorophyll-a concentration, the phycocyanin concentration, and the total organic carbon concentration (TOC).

Next, the integrated management module 200 mounted on the mobile unmanned ship collects the measured water quality and depth data (S130).

Next, the integrated management module 200 transmits the collected water quality and depth data together with coordinate data to the manager terminal 300 in real time (S140).

Next, the data processing unit 320 of the manager terminal 300 processes the transmitted water quality and depth data to derive an effective value (S150). Specifically, the data processing unit 320 of the manager terminal 300 edits and processes the data received from the data receiving unit 310 in real time. At this time, it is preferable that the number of data received in real time is at least one per second, but less than that is fine. Therefore, each fluorescence intensity value measured by the fluorescence sensor 130 is converted to a concentration by the data processing unit 320 of the manager terminal 300, and subsequently, the data converted to the concentration is converted into a statistical technique. After being organized and matched with the coordinate data, it can be mapped to a two-dimensional water quality map.

Specifically, it is necessary to process the data in order to map the point source-based data acquired by the fluorescence sensor 130 into a cell-based two-dimensional planar water pollution status map. The mobile unmanned aerial vehicle 100 that operates along a preset navigation route through automatic route setting acquires a number of point-based data only in the direction of travel according to the operation width, and thus, through statistical numerical analysis in the data processing unit 320 You should organize your data with valid values. In addition, to convert point source-based data into a cell-based map, a spatial interpolation method (Geographic information system interpolation) is used. The interpolation method is to obtain a value between data by applying an interpolation algorithm to an already acquired point.

)으로부터 선형으로 결합된 가중치를 사용하는 것으로, 가까울수록 가중치가 크게 적용되며, 다음의 수학식 2와 같이 주어진다.For example, spatial interpolation methods used to create a 2D water quality map include Inverse Distance Weighted (IDW) and Kriging Interpolation. That's the way. Specifically, the inverse distance weighting method (IDW) is a near point (

) To use a weight that is linearly combined, and the closer the weight is, the larger the weight is applied, and is given by Equation 2 below.

로 주어지고, 이때,

를 예측하기 위해서 n에 대한 샘플인

를 기반으로 주어진 점(

)에서 보간한다. 이때,

는 두 점사이의 거리이고,

는 데이터 포인트, d는 데이터 포인트(

)에서 알려지지 않은 보간 포인트(

)까지의 거리, n은 보간에 사용된 데이터 포인트의 총 수를 각각 나타낸다. here,

Given by, where,

To predict n, which is a sample for n

Based on the given point(

) To interpolate. At this time,

Is the distance between two points,

Is the data point, d is the data point (

) At an unknown interpolation point (

), n represents the total number of data points used for interpolation, respectively.

In addition, the Kriging Interpolation method estimates a value using a statistical method. As an interpolation method for predicting a value of a desired point by a linear combination of data, it is given as Equations 3 and 4 below.

는 특정 거리(

) 내의 샘플 쌍의 수를 나타낸다.here,

Is a specific distance (

) Represents the number of pairs of samples in.

Next, the data analysis and map mapping unit 330 of the manager terminal 300 analyzes the processed data and maps it to a map (S160). Specifically, the data analysis and map mapping unit 330 matches depth data, water quality data, and coordinate data, and processes the data using a data statistical technique. In this case, the data analysis and map mapping unit 330 must first exclude measurement error values, and secondly, organize the data based on coordinate values representing space.

Next, as shown in FIG. 11, the two-dimensional water quality map creation unit 340 of the manager terminal 300 creates a two-dimensional water quality map for the green algae concentration and total organic matter concentration in the water body (S170). The 2D water quality map creation unit 340 selectively utilizes the above-described interpolation method to map the total organic concentration and the green algae map into a 2D image.

Here, the image editing unit 350 of the manager terminal 300 may modify and change a previously prepared 2D water quality map according to a desired condition according to a manager's selection such as water quality and depth.

The concrete 2D water quality map creation algorithm of the manager terminal 300 may go through a process as shown in FIG. 10. First, the water quality, depth, and coordinate data are wirelessly received from the integrated management module in real time (S210), and then, the water quality and depth data are processed to derive an effective value (S220). Next, the vector is mapped first (S230), and then, data attributes and patterns are checked (S240), and then, IDW interpolation or kriging interpolation is selectively applied (S250). Next, after the registers are secondarily mapped (S260), a two-dimensional water quality map is output (S270).

After all, according to an embodiment of the present invention, the total organic concentration in the water body area is integrated by installing a fluorescent sensor and a depth sensor that can measure multiple concentrations of chlorophyll-a, phycocyanin, and total organic matter on a mobile unmanned aerial vehicle capable of autonomous navigation. And green algae concentration in various directions, depth measurement is possible, and the effect of water depth on water quality can be observed. In addition, total organic matter and green algae changes in the water body area can be monitored using a mobile unmanned ship capable of measuring depth and water quality. You can create a water quality map of a two-dimensional image.

The above description of the present invention is for illustrative purposes only, and those of ordinary skill in the art to which the present invention pertains will be able to understand that other specific forms can be easily modified without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and are not limiting. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as being distributed may also be implemented in a combined form.

The scope of the present invention is indicated by the claims to be described later rather than the detailed description, and all changes or modified forms derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present invention. do.

100: Unmanned Ship Vehicle (USV)
200: integrated management module
300: manager terminal
110: mobile unmanned ship body 120: depth sensor
130: fluorescence sensor (water quality sensor) 140: GPS module (automatic navigation device)
150: autonomous navigation driving unit 160: camera
170: Lidar sensor
210: data collection unit 220: integrated management unit
230: data transmission unit (wireless communication module) 240: autonomous navigation control unit
250: collision avoidance control unit
310: data receiving unit (wireless communication module) 320: data processing unit
330: data analysis and map mapping unit 340: two-dimensional water quality map creation unit
350: video editing department

Claims (20)

A GPS module 140 is mounted to enable autonomous navigation, and after setting the area and route of the river to be measured in advance, it navigates along a preset route by inputting a GPS coordinate point, and a fluorescence sensor 130 and a depth sensor 120 A mobile unmanned ship 100 that measures the water quality and depth of the river to be measured by installing it at the same time;
It is mounted in the mobile unmanned aerial vehicle 100 to control autonomous navigation and collision avoidance of the mobile unmanned aerial vehicle 100, and the fluorescence sensor 130 and the water depth sensor 120 together with the coordinate data of the GPS module 140 An integrated management module 200 for collecting water quality data and water depth data measured from and transmitting in real time wirelessly; And
A manager terminal 300 that wirelessly receives water quality data, water depth data, and coordinate data from the integrated management module 200 to create a two-dimensional water quality map in real time
Including,
The fluorescence sensor 130 of the mobile unmanned aerial vehicle 100 multi-measures the chlorophyll-a concentration, the phycocyanin concentration, and the total organic concentration calculated as a fluorescence intensity value, and at the same time, the depth sensor 120 measures the water depth. A two-dimensional water quality map creation system using a mobile unmanned ship equipped with a fluorescent sensor, characterized in that. The method of claim 1,
The fluorescence sensor 130 measures a fluorescence intensity value representing a concentration of chlorophyll-a and a concentration of phycocyanin, but the chlorophyll-a concentration has an emission wavelength of 650 nm to 700 nm and an excitation wavelength of 400 nm to 450 nm, 675 It represents the fluorescence intensity value measured at the emission wavelength of ㎚~725nm and the excitation wavelength of 650nm~700nm, and the phycocyanin concentration is measured at the emission wavelength of 650nm~720nm and the excitation wavelength of 600nm~630nm. Indicates the fluorescence intensity value,
The concentration of chlorophyll-a is given by Chlorophyll-a(㎍/L) = [(Intensity, 425nm, 675nm) + b] / a, where a = 0.0014, b = 0.0085, but the a And b values can be changed according to the fluorescence intensity value,
The phycocyanin concentration is given by Blue Green Algae (㎍/L) = [(Intensity, 610 ㎚) + b] / a, where a = 0.0006, b = 0.0076, but the a and b values are A two-dimensional water quality map creation system using a mobile unmanned ship equipped with a fluorescent sensor, characterized in that it can be changed according to the fluorescence intensity value. The method of claim 1,
The fluorescence sensor 130 measures a fluorescence intensity value representing a total organic concentration according to the first, second and third matrices C1, C2, C3 extracted for analysis of the organic material concentration, and the second matrix C2 ) Represents a fluorescence intensity value measured at an emission wavelength of 350 nm to 450 nm and an excitation wavelength of 300 nm to 350 nm, and the first matrix (C1) has an emission wavelength of 400 nm to 500 nm and an emission wavelength of 250 nm to 300 nm. Represents the fluorescence intensity value measured at the excitation wavelength of, and the third matrix (C3) represents the fluorescence intensity value measured at an emission wavelength of 300 nm and an excitation wavelength of 275 nm,
The total organic concentration (TOC) is given by TOC (mg/L) = [(C2 x C1/C3) + b] / a, where a = 52.305, b = 37.687 are given as a and b. A two-dimensional water quality map creation system using a mobile unmanned ship equipped with a fluorescent sensor, characterized in that the value can be changed according to the fluorescence intensity value. The method of claim 3,
The first matrix (C1) represents the concentration of humic acid in the total organic concentration, the second matrix (C2) represents the concentration of humic acid and fulvic acid in the total organic concentration, the The third matrix (C3) is a two-dimensional water quality mapping system using a mobile unmanned aerial vehicle equipped with a fluorescence sensor, characterized in that it represents the protein (Tryptophan-like) concentration of the total organic concentration. The method of claim 1,
Each fluorescence intensity value measured by the fluorescence sensor 130 is converted to a concentration by the data processing unit 320 of the manager terminal 300, and the data converted to the concentration is summarized by a statistical method and the coordinate data A two-dimensional water quality map creation system using a mobile unmanned aerial vehicle equipped with a fluorescent sensor, characterized in that the map is mapped to a two-dimensional water quality map after being matched with. The method of claim 1, wherein the mobile unmanned ship (100),
A mobile unmanned aerial vehicle body 110;
A water quality sensor, comprising: a fluorescence sensor 130 mounted on the mobile unmanned aerial vehicle body 110 to multiply measure a chlorophyll-a concentration, a phycocyanin concentration, and a total organic concentration calculated as a fluorescence intensity value;
A depth sensor 120 installed on the mobile unmanned aerial vehicle body 110 to measure the depth of a target river in real time;
An automatic navigation device, comprising: a GPS module 140 mounted on the mobile unmanned aerial vehicle body 110 to generate coordinate data representing the location of the mobile unmanned aerial vehicle 100; And
Creating a two-dimensional water quality map using a mobile unmanned aerial vehicle equipped with a fluorescent sensor including an autonomous navigation driving unit 150 that drives the mobile unmanned aerial vehicle body 110 to autonomously navigate along a preset navigation route in which a GPS coordinate point is input. system. The method of claim 6, wherein the mobile unmanned ship (100),
A camera 160 installed on the upper front surface of the mobile unmanned aerial vehicle body 110 to photograph obstacles in front of the autonomous navigation route; And
It is installed on the side of the camera 160, further comprises a Lidar sensor 170 for measuring the distance to the obstacle by measuring the return reflected from the obstacle by emitting a laser pulse,
The mobile unmanned aerial vehicle 100 is controlled by the camera 160 and the lidar sensor 170 to avoid a collision when an unexpected obstacle is found during autonomous navigation on the water body. A two-dimensional water quality map creation system using an unmanned ship. The method of claim 6, wherein the integrated management module 200,
A data collection unit 210 for collecting water quality data measured by the fluorescence sensor 130 and water depth data measured by the depth sensor 120;
An integrated management unit that converts the water quality and depth data collected by the data collection unit 210 and the coordinate data of the GPS module 140 to enable wireless transmission, and integrates and manages the autonomous operation of the mobile unmanned aerial vehicle 100 ( 220);
A wireless communication module, comprising: a data transmission unit 230 for wirelessly transmitting water quality, water depth and coordinate data of the integrated management unit 220; And
A system for creating a two-dimensional water quality map using a mobile unmanned aerial vehicle equipped with a fluorescent sensor including an autonomous navigation controller 240 that controls the driving of the autonomous navigation driver 150 of the mobile unmanned aerial vehicle 100. The method of claim 8,
The integrated management module 200 includes a collision avoidance control unit 250 that controls the driving of the autonomous navigation driving unit 150 to avoid a collision when an unexpected obstacle is found during autonomous navigation of the mobile unmanned aerial vehicle 100. A two-dimensional water quality map creation system using a mobile unmanned ship equipped with an additional fluorescent sensor. The method of claim 8, wherein the manager terminal 300,
A wireless communication module, comprising: a data receiving unit 310 for wirelessly receiving water quality, water depth and coordinate data from the data transmitting unit 230 of the integrated management module 200;
A data processing unit 320 for processing to derive effective values for the received water quality, depth, and coordinate data according to a data mining technique to which a statistical numerical analysis algorithm is applied;
A data analysis and mapping unit that analyzes the data processed by the data processing unit 320 and maps the point-based data, which is arranged as an effective value, into a cell-based map using an interpolation method ( 330); And
A portable type equipped with a fluorescence sensor including a two-dimensional water quality map creation unit 340 that creates a two-dimensional water quality map for the green algae concentration and total organic matter concentration in the water body in response to the data analysis and map mapping of the mapping unit 330 A two-dimensional water quality map creation system using an unmanned ship. The method of claim 10,
The data processing unit 320 primarily excludes measurement error values, and secondarily organizes data based on coordinate values representing space. Dimensional water quality mapping system. The method of claim 10,
When there is a change in the 2D water quality map created by the 2D water quality map creation unit 340, the manager terminal 300 adds an image editing unit 350 that edits and changes the image according to the water depth and water quality type. A two-dimensional water quality map creation system using a mobile unmanned ship equipped with a fluorescent sensor including as. The method of claim 10,
The data analysis and mapping unit 330 performs interpolation by selecting an inverse distance weighted method (IDW) or a kriging interpolation method. Dimensional water quality mapping system. a) autonomously operating the mobile unmanned aerial vehicle 100 in the water body;
b) measuring water quality using the fluorescent sensor 130 mounted on the mobile unmanned aerial vehicle 100 and measuring the water depth using the water depth sensor 120 at the same time;
c) collecting the measured water quality and depth data by the integrated management module 200 mounted on the mobile unmanned aerial vehicle 100;
d) transmitting, by the integrated management module 200, the collected water quality and depth data together with coordinate data to the manager terminal 300 in real time;
e) the manager terminal 300 processing the transmitted water quality and depth data to derive an effective value;
f) the manager terminal 300 analyzing the processed data and mapping it to a map; And
g) including the step of creating a two-dimensional water quality map for the concentration of green algae and total organic matter in the water body by the manager terminal 300,
The fluorescence sensor 130 of the step b) is a water quality sensor, equipped with a fluorescence sensor, characterized in that multiple measurements of the water quality of the water body for chlorophyll-a concentration, phycocyanin concentration, and total organic carbon concentration (TOC) A method of creating a two-dimensional water quality map using a mobile unmanned ship. The method of claim 14,
The fluorescence sensor 130 measures a fluorescence intensity value representing a concentration of chlorophyll-a and a concentration of phycocyanin, but the chlorophyll-a concentration has an emission wavelength of 650 nm to 700 nm and an excitation wavelength of 400 nm to 450 nm, 675 It represents the fluorescence intensity value measured at the emission wavelength of ㎚~725nm and the excitation wavelength of 650nm~700nm, and the phycocyanin concentration is measured at the emission wavelength of 650nm~720nm and the excitation wavelength of 600nm~630nm. Indicates the fluorescence intensity value,
The concentration of chlorophyll-a is given by Chlorophyll-a(㎍/L) = [(Intensity, 425nm, 675nm) + b] / a, where a = 0.0014, b = 0.0085, but the a And b values can be changed according to the fluorescence intensity value,
The phycocyanin concentration is given by Blue Green Algae (㎍/L) = [(Intensity, 610 ㎚) + b] / a, where a = 0.0006, b = 0.0076, but the a and b values are A two-dimensional water quality map creation system using a mobile unmanned ship equipped with a fluorescent sensor, characterized in that it can be changed according to the fluorescence intensity value. The method of claim 14,
The fluorescence sensor 130 measures a fluorescence intensity value representing a total organic concentration according to the first, second and third matrices C1, C2, C3 extracted for analysis of the organic material concentration, and the second matrix C2 ) Represents a fluorescence intensity value measured at an emission wavelength of 350 nm to 450 nm and an excitation wavelength of 300 nm to 350 nm, and the first matrix (C1) has an emission wavelength of 400 nm to 500 nm and an emission wavelength of 250 nm to 300 nm. Represents the fluorescence intensity value measured at the excitation wavelength of, and the third matrix (C3) represents the fluorescence intensity value measured at an emission wavelength of 300 nm and an excitation wavelength of 275 nm,
The total organic concentration (TOC) is given by TOC (mg/L) = [(C2 x C1/C3) + b] / a, where a = 52.305, b = 37.687 are given as a and b. The value can be changed according to the fluorescence intensity value, wherein the first matrix (C1) represents the concentration of humic acid in the total organic concentration, and the second matrix (C2) represents the concentration of humic acid in the total organic substance concentration. ) And Fulvic Acid concentration, and the third matrix (C3) represents the protein (Tryptophan-like) concentration among the total organic matter concentration. How to create a map. The method of claim 14,
Each fluorescence intensity value measured by the fluorescence sensor 130 is converted to a concentration by the data processing unit 320 of the manager terminal 300, and the data converted to the concentration is summarized by a statistical method and the coordinate data A method of creating a two-dimensional water quality map using a mobile unmanned aerial vehicle equipped with a fluorescent sensor, characterized in that the map is mapped to a two-dimensional water quality map after matching with The method of claim 14, wherein the mobile unmanned ship (100),
A mobile unmanned aerial vehicle body 110;
A water quality sensor, comprising: a fluorescence sensor 130 mounted on the mobile unmanned aerial vehicle body 110 to multiply measure a chlorophyll-a concentration, a phycocyanin concentration, and a total organic concentration calculated as a fluorescence intensity value;
A depth sensor 120 installed on the mobile unmanned aerial vehicle body 110 to measure the depth of a target river in real time;
An automatic navigation device, comprising: a GPS module 140 mounted on the mobile unmanned aerial vehicle body 110 to generate coordinate data representing the location of the mobile unmanned aerial vehicle 100;
An autonomous navigation driving unit 150 for driving the mobile unmanned aerial vehicle body 110 to autonomously navigate along a preset navigation route in which a GPS coordinate point is input;
A camera 160 installed on the upper front surface of the mobile unmanned aerial vehicle body 110 to photograph obstacles in front of the autonomous navigation route; And
It includes a lidar sensor 170 installed on the side of the camera 160 and measuring a distance to the obstacle by measuring a return reflected from the obstacle by emitting a laser pulse,
The mobile unmanned aerial vehicle 100 is controlled by the camera 160 and the lidar sensor 170 to avoid a collision when an unexpected obstacle is found during autonomous navigation on the water body. A method of creating a two-dimensional water quality map using an unmanned ship. The method of claim 18, wherein the integrated management module 200,
A data collection unit 210 for collecting water quality data measured by the fluorescence sensor 130 and water depth data measured by the depth sensor 120;
An integrated management unit that converts the water quality and depth data collected by the data collection unit 210 and the coordinate data of the GPS module 140 to enable wireless transmission, and integrates and manages the autonomous operation of the mobile unmanned aerial vehicle 100 ( 220);
A wireless communication module, comprising: a data transmission unit 230 for wirelessly transmitting water quality, water depth and coordinate data of the integrated management unit 220;
An autonomous navigation control unit 240 for controlling the driving of the autonomous navigation driving unit 150 of the mobile unmanned aerial vehicle 100; And
A mobile unmanned aerial vehicle equipped with a fluorescent sensor including a collision avoidance controller 250 that controls the driving of the autonomous navigation driving unit 150 to avoid a collision when an unexpected obstacle is found during autonomous navigation of the mobile unmanned aerial vehicle 100 A method of creating a two-dimensional water quality map using lines. The method of claim 19, wherein the manager terminal 300,
A wireless communication module, comprising: a data receiving unit 310 for wirelessly receiving water quality, water depth and coordinate data from the data transmitting unit 230 of the integrated management module 200;
A data processing unit 320 for processing to derive effective values for the received water quality, depth, and coordinate data according to a data mining technique to which a statistical numerical analysis algorithm is applied;
A data analysis and mapping unit 330 that analyzes the data processed by the data processing unit 320 and maps the point-based data, which is arranged as an effective value, into a cell-based map using an interpolation method;
A two-dimensional water quality map creation unit 340 for creating a two-dimensional water quality map for the green algae concentration and total organic matter concentration in the water body in response to the data analysis and mapping unit 330's map mapping; And
When there is a change in the 2D water quality map created by the 2D water quality map creation unit 340, a mobile unmanned aerial vehicle equipped with a fluorescence sensor including an image editing unit 350 that edits and changes the image according to the water depth and water quality type A method of creating a two-dimensional water quality map using lines.

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