KR102515112B1 - Black ice detecting system using drone - Google Patents

Abstract

A black ice detection system using a drone is disclosed. A black ice detection system using a drone according to an embodiment of the present invention includes a control server holding geographic data of a geographic information system (GIS); A drone equipped with a thermal imaging camera, flying in a flight area set through the geospatial information from the control server, and photographing the road surface set through the geospatial information; wherein the control server includes an ID of the drone ( ID) device-specific information, a photograph taken, a photographed angle, and photographing information including geospatial information at the time of photographing are received from the drone, and after determining a black ice risk area from the photographing information, it is determined whether there is black ice, If it is determined to be ice, the captured photos are mapped on a map through Ground Control Point (GCP) correction, and then map data is transmitted to related organizations. According to the present invention, the road surface is photographed using a thermal imaging camera using a drone, but the road surface is photographed at an accurate location using GIS, black ice is detected from the photographed information, and mapping is performed to have accurate location information through GCP. A black ice detection system using a drone provided to a user is provided.

Description

Black ice detection system using drone {BLACK ICE DETECTING SYSTEM USING DRONE}

The present invention relates to a system for detecting black ice using a drone, and more particularly, a road surface is photographed through a thermal imaging camera using a drone, the road surface is photographed at an accurate location using a GIS, and black ice is obtained from photographing information. It relates to a black ice detection system using a drone that detects whether there is a black ice, maps it to have accurate location information through GCP, and provides it to the user.

Black ice refers to snow or rain that fell during the day that seeps into the cracks of the asphalt road and mixes with oil and dust on the road overnight and freezes thinly on the road, and is also called 'road icing'.

When the outside temperature is above zero and the road surface is below freezing, black ice that occurs when moisture or freezing rain in the air comes into contact with the road surface cannot be prevented, causing the driver to experience an optical illusion, causing the vehicle to slip and collide. There was a problem of not being able to prevent accidents such as overturning, overturning, and crossing the center line.

Drivers are not easily seen when driving on the road and it is easy to think that the road is simply a little wet, so accidents caused by black ice are increasing every year. There is a problem with

Conventional anti-icing devices on the road prevent freezing of the road surface by burying a heat wire on the road surface and supplying power when it snows to generate heat, or measures the environment such as temperature, humidity, and illumination of the road. It predicts icing of the road by the measured environmental information, alerts vehicles entering the section, and notifies the road manager. However, these anti-icing devices do not determine black ice and do not perform accident prevention functions.

Therefore, there is a need to develop a black ice detection system capable of detecting black ice on a road surface and notifying the user in real time without requiring a lot of equipment.

Korean Patent Publication No. 10-2020-0086492 (published on July 17, 2020) “Black ice detection device for detecting black ice on roads in winter” Republic of Korea Patent Publication No. 10-2019-0140272 (2019.12.19. Publication) “Black ice detection device and method” Korean Patent Registration No. 10-2158841 (2020.09.16. Registration) “Black Ice Detection System”

The black ice detection system using a drone according to the present invention photographs the road surface using a thermal imaging camera using a drone, but photographs the road surface at an accurate location using GIS, detects black ice from the photographing information, and GCP It is an object of the present invention to provide a black ice detection system using a drone that is mapped to have accurate location information through and provided to the user.

In addition, the black ice detection system using a drone according to the present invention is aimed at providing a black ice detection system using a drone that can determine black ice with a minimum error and notify the user of the determined black ice in real time. to be

The tasks of the present invention are not limited to the technical tasks mentioned above, and other technical tasks not mentioned will be clearly understood by those skilled in the art from the following description.

A black ice detection system using a drone according to an embodiment of the present invention includes a control server holding geographic data of a geographic information system (GIS); A drone equipped with a thermal imaging camera, flying in a flight area set through the geospatial information from the control server, and photographing the road surface set through the geospatial information; wherein the control server includes an ID of the drone ( ID) device-specific information, a photograph taken, a photographing angle, and photographing information including geospatial information at the time of photographing are received from the drone, a black ice risk area is determined from the photographing information, and black ice is determined. If it is determined to be ice, the captured photo is mapped on a map through Ground Control Point (GCP) correction, and then the map data is transmitted to the relevant organization, and the frame of the captured photo of the captured information received from the first drone. extracts a temperature value for each pixel included in , determines whether the temperature is within a preset temperature range, determines a black ice risk area, and when determined to be a black ice risk area, flies in an area adjacent to the first drone Instructs shooting by calling the second drone to shoot.

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In addition, the second drone may photograph the same road surface area as the first drone, but at a different angle from that of the first drone.

In addition, the control server receives the photographing information from the second drone, extracts a temperature value for each pixel included in the frame of the photographed photograph, and if the temperature is within a preset temperature range, it is determined as a black ice area. can

In addition, the related organization may display the black ice area on the navigation in real time through the received map data.

According to embodiments of the present invention, at least the following effects are provided.

According to the black ice detection system according to the present invention, the road surface is photographed using a thermal imaging camera using a drone, but the road surface is photographed at an accurate location using GIS, black ice is detected from the photographing information, and through GCP A black ice detection system using a drone that is mapped to have accurate location information and provided to a user is provided.

In addition, whether or not there is black ice is determined based on whether or not the temperature value of each pixel included in the frame of the photograph falls within the range between the temperature value and the preset temperature value, thereby providing excellent accuracy.

In addition, when it is determined that the black ice risk area is determined by the first drone, the second drone is introduced into the area and photographed from a different angle than the first drone, so the accuracy is excellent.

In addition, the photographing information taken by the drone is transmitted to the control server, and when the control server determines that it is black ice, it can be transmitted to the related agency in real time to notify the user of the black ice determined in real time.

Effects according to the present invention are not limited by the contents exemplified above, and more various effects are included in the present specification.

1 is a schematic device diagram of a black ice detection system using a drone according to an embodiment of the present invention.
2 is a diagram of the relationship between a drone and a control server in a black ice detection system using a drone according to an embodiment of the present invention.
3 is a black ice detection algorithm of a black ice detection system using a drone according to an embodiment of the present invention
4 is a map picture of a black ice detection system using a drone according to an embodiment of the present invention.

Since the present invention can apply various transformations and have various embodiments, specific embodiments are illustrated in the drawings and described in detail in the detailed description. Effects and features of the present invention, and methods for achieving them will become clear with reference to the embodiments described later in detail together with the drawings. However, it should be understood that the present invention is not limited to the embodiments disclosed below, but may be implemented in various forms, and includes all modifications, equivalents, and substitutes included in the spirit and technical scope of the present invention.

Prior to the description, the terms described in the detailed description will be described. In the following embodiments, terms such as first and second are used for the purpose of distinguishing one component from another component without limiting meaning. Accordingly, it goes without saying that the first element mentioned below may also be the second element within the technical spirit of the present invention. Also, expressions in the singular number include plural expressions unless the context clearly dictates otherwise. In addition, terms such as 'include' or 'have' mean that features, numbers, steps, operations, components, parts, or combinations thereof described in the specification exist, and that one or more other features or components are present. It does not preclude the possibility of being added.

In addition, in the drawings, the size of components may be exaggerated or reduced for convenience of explanation. For example, since the size and thickness of each component shown in the drawings are arbitrarily shown for convenience of description, the present invention is not necessarily limited to the illustrated bar.

Hereinafter, embodiments according to the present invention will be described in detail with reference to the accompanying drawings. In the description with reference to the accompanying drawings, the same or corresponding components are assigned the same reference numerals, and overlapping descriptions thereof will be omitted.

1 is a schematic device diagram of a black ice detection system using a drone according to an embodiment of the present invention, and FIG. 2 is a relationship between a drone and a control server in a black ice detection system using a drone according to an embodiment of the present invention. 3 is a black ice detection algorithm of a black ice detection system using a drone according to an embodiment of the present invention, and FIG. 4 is a mapped map of a black ice detection system using a drone according to an embodiment of the present invention. It is a picture.

In the black ice detection system 1000 using the drone 100 according to the present invention, the road surface is photographed using a thermal imaging camera using the drone 100, and the road surface is photographed at an accurate location using GIS, and the photographing information It is to detect whether or not there is black ice from , and map it to have accurate location information through GCP and provide it to the user.

The black ice detection system 1000 using the drone 100 according to an embodiment of the present invention includes the drone 100 and a control server.

The drone 100 is equipped with a thermal imaging camera, and is configured to photograph the road surface and transmit photographic information to a control server.

The control server holds geospatial information (Geographic Data) of a Geographic Information System (GIS). The drone 100 receives the flight area and road area set by the control server using GIS, and photographs the road surface of the road area while continuously flying within the flight area. Here, GIS refers to a system that stores, manages, analyzes, and processes the spatial data of an object and can utilize it as meaningful spatial information. It is possible to know the flight area and road area with very high accuracy through GIS, and the drone 100 can accurately photograph the road surface location while flying in the flight area.

The drone 100 photographs the road surface through a thermal imaging camera. Specifically, an infrared image is photographed through an infrared camera, converted into a thermal image, and then output as a temperature distribution diagram.

When the drone 100 photographs the road surface, it transmits photographing information including device-specific information, photographed pictures, photographing angle, and geospatial information at the time of photographing to the control server. Device-specific information may be an ID for distinguishing each drone 100 flying in a plurality of flight areas from each other. The geospatial information at the time of shooting means the exact location information of the drone 100 at the time of shooting, and the shooting angle means the angle between the road surface and the drone 100 when shooting the corresponding road surface.

The control server receives and analyzes the above-described photographing information from the drone 100 to determine a black ice risk area.

Specifically, for each pixel included in the frame of the photographed picture of photographing information received from the first drone 110, which is the drone 100 that photographs the road surface of the road area within the corresponding flight region while flying in an arbitrary flight region. Extract the temperature value. For example, assuming that the frame of a photograph taken by a thermal imaging camera mounted on the drone 100 is 640X480, there are 640 pixels on a horizontal side and 480 pixels on a vertical side, Extract the temperature value.

Temperature values for pixels corresponding to black ice are preset in the control server. A lower limit and an upper limit are set to the first reference value and the second reference value, and it is determined whether the temperature value is between the first reference value and the second reference value.

If the temperature value for each pixel value is between the first reference value and the second reference value, it is determined as a black ice risk area.

The control server calls the second drone 120 flying in an area adjacent to the first drone 110 when it is determined that the corresponding road area is a black ice risk area from the photographing information taken by the first drone 110 .

The second drone 120 receives geospatial information on which the first drone 110 flies from the control server and is introduced to the corresponding area. The second drone 120 also receives geospatial information of the road area photographed by the first drone 110 and photographs the corresponding area through a thermal imaging camera.

At this time, the second drone 120 photographs the corresponding area at a different angle from that of the first drone 110 . Accuracy is improved through various angles of the road area, and even when the thermal imaging camera mounted on the first drone 110 is in an error state, the accuracy is improved by shooting through a different thermal imaging camera it gets done

When the second drone 120 also photographs the road surface, it transmits photographing information including device-specific information, photographed pictures, photographing angle, and geospatial information at the time of photographing to the control server. The control server receives and analyzes the above-described photographing information from the drone 100 to determine a black ice risk area. The control server extracts a temperature value for each pixel included in the frame of the photographed picture of the photographing information received from the second drone 120, and determines whether the value is between a first reference value and a second reference value. .

If the temperature value analyzed from the photographing information received from the second drone 120 falls between the first reference value and the second reference value, the control server determines the black ice area.

If the temperature value analyzed from the photographing information received from the second drone 100 is not between the first reference value and the second reference value, it is not determined as a black ice area, but determined as a black ice risk area, and the first drone ( 110) and the second drone 120 continuously photograph and monitor the corresponding area.

On the other hand, the information communication network for data communication between the drone 100 and the control server means a connection structure capable of exchanging information between nodes such as a plurality of terminals and servers. An example of such an information communication network is RF , 3GPP (3rd Generation Partnership Project) network, LTE (Long Term Evolution) network, 5GPP (5rd Generation Partnership Project) network, WIMAX (World Interoperability for Microwave Access) network, Internet, LAN (Local Area Network), Wireless A wireless local area network (LAN), a wide area network (WAN), a personal area network (PAN), a Bluetooth network, an NFC network, a satellite broadcasting network, and an analog broadcasting network may be included, but are not limited to a specific network.

The control server maps the photograph received from the drone 100 on a map when it is determined to be a black ice risk area. At this time, ground control point (GCP) correction is performed to minimize the error.

Ground control point correction is a method of correcting image distortion by analyzing only the degree of distortion without considering the cause of the distortion, and obtaining a correction equation that can connect the collected images and the reference map.

First, select GCP. At this time, if there is a well-known place or clearly identifiable entity within the mapping area, GCP preferably selects a point of the corresponding place or entity. The most important point in selecting a ground control point (GCP) is, above all, whether the point is qualified as a control point. Since the ground control point (GCP) is a reference point for conversion between image coordinates and map coordinates, its location must always remain unchanged over time. For these points, road intersections, embankment ends, artificial structures, and large buildings are used. At this time, the resolution of the sensor must be considered. When the coordinates of the ground control point (GCP) on the map are (x,y) and the coordinates on the photograph are (u,v), the relational expression between them is obtained by connecting the two coordinates.

Errors can be reduced to a minimum through accurate selection of ground control points, and errors occurring during calibration can be reduced to a minimum by selecting a plurality of ground control points, and accurate conversion is possible by evenly distributing them over a wide area. .

Terrain correction can be performed from the above relationship, pixels in the correct position can be obtained from this, and data with very high accuracy can finally be obtained by resampling these pixels into a new picture.

When the map mapping is completed, the control server transmits it to related organizations. Relevant organizations may be navigation service companies, Korea Expressway Corporation, and the like.

By delivering an accurate map to a navigation service provider, the navigation service provider can display the black ice area in real time through a map mapped to a navigation device installed in a user's vehicle.

In addition, Korea Expressway Corporation, etc., can put in manpower to install black ice warning signs in the area.

Therefore, according to the present invention, the road surface is photographed using a thermal imaging camera using the drone 100, but the road surface is photographed at an accurate location using GIS, black ice is detected from the photographing information, and accurate through GCP is used. A black ice detection system 1000 using a drone 100 that is mapped to have location information and provided to a user is provided.

The use of all examples or exemplary terms (eg, etc.) in the present invention is simply to explain the present invention in detail, and the scope of the present invention due to the examples or exemplary terms is not limited unless it is limited by the claims. It is not limited. In addition, those skilled in the art can recognize that various modifications, combinations, and changes can be made according to design conditions and factors within the scope of the appended claims or equivalents thereof.

Therefore, the spirit of the present invention should not be limited to the above-described embodiments and should not be determined, and not only the claims to be described later, but also all ranges equivalent to or equivalently changed from these claims fall within the spirit of the present invention. would be considered to be in the category.

1000: Black ice detection system using drones
100: drone 110: first drone
120: second drone 200: control server

Claims (5)

A control server that holds geospatial information (Geographic Data) of a Geographic Information System (GIS);
A drone equipped with a thermal imaging camera, flying over a flight area set through the geospatial information from the control server, and photographing a road surface set through the geospatial information;
The control server,
By receiving photographing information, including device-specific information, which is the ID of the drone, photographing picture, photographing angle, and geospatial information at the time of photographing, from the drone,
After determining the black ice risk area from the above photographing information, it is determined whether there is black ice, and if it is determined to be black ice, the photographed picture is mapped on a map through ground control point (GCP) correction, and the map data is transferred to the relevant institutions. send to,
The temperature is extracted for each pixel included in the frame of the photographed picture of the photographing information received from the first drone, and a black ice risk area is determined by determining whether the temperature is within a preset temperature range. A black ice detection system using a drone that calls a second drone flying in an area adjacent to the first drone and instructs shooting when it is determined that the area is dangerous.
delete According to claim 1,
The black ice detection system using a drone in which the second drone photographs the same road surface area as the first drone, but photographs at a different angle from that of the first drone.
According to claim 1,
The control server,
A black ice detection system using a drone that receives photographing information from the second drone, extracts a temperature value for each pixel included in a frame of a photograph, and determines that the area is black ice if the temperature is within a preset temperature range. .
According to claim 1,
The black ice detection system using a drone, wherein the related institution displays a black ice area in real time on the navigation through the received map data.

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