KR20230075317A - System and method for monitoring the road conditions using drone - Google Patents

Abstract

A road surface condition monitoring system and method using a drone are disclosed. A road surface condition monitoring system using a drone according to an embodiment of the present invention is installed on an unmanned aerial vehicle or an unmanned aerial vehicle set to fly within a preset detection section, takes a road image within the detection section, and monitors the standby state within the detection section. and generates information for output by receiving information on the road surface from any one of at least one road surface detection device, an unmanned aerial vehicle, and a road surface detection device that determines the road surface condition within the detection section based on the road image and the standby state. and a display device for receiving and displaying information for output from the road monitoring server and the road monitoring server.

Description

Road condition monitoring system and method using drone {SYSTEM AND METHOD FOR MONITORING THE ROAD CONDITIONS USING DRONE}

The present invention relates to a road surface condition monitoring system and method using a drone, and more particularly, to a road surface condition monitoring system and method using a drone for notifying road surface conditions obtained from images taken of a road.

Traffic accidents can occur under the influence of various circumstances. The driver's physical and psychological condition, car management condition, road condition, and climate conditions are good to help safe driving, and conversely, poor conditions can cause traffic accidents.

Looking at the condition of roads, which is one of the causes of traffic accidents, damage to paved roads occurs due to various causes. Damage to roads can be repaired at a low cost if repairs are made in a timely manner, but the reality is that most local governments do not respond immediately for reasons such as lack of budget and manpower.

Looking at the climatic causes among the causes of road damage, local heavy rain that rapidly pours in a short time in summer and heavy snow in winter are the main causes of road damage. In particular, meteorological phenomena such as heavy rain, heavy snow, and hail often occur due to abnormal temperature phenomena, which also cause damage to roads. In addition, as the temperature of the asphalt heated by the urban heat island phenomenon rises, a jungle phenomenon occurs due to heavy vehicles.

Another cause of road damage is aging. Plastic deformation that occurs at the point where automobile wheels come into contact due to the accumulation of deformation in the cross-section of the asphalt pavement due to heavy traffic load, and fatigue cracks that occur in the direction of traffic due to the repeated traffic load mainly occur.

As mentioned earlier, since there is no prompt repair for road damage, serious traffic accidents can occur at the point of damage. In an attempt to avoid a sinkhole caused by the sinking of the ground, a collision with a vehicle in the next lane may occur, and if cracks and jungles occur on the road with bad weather, it may cause a major traffic accident.

In addition to road damage, there are various variables on the road. For example, a vehicle may stop in the middle of the road due to a problem with the vehicle during operation, and there may be a falling object that is left unattended while being transported from a large truck.

As such, in addition to problems that inevitably require the intervention of local governments, such as damage to roads, various factors that hinder traffic flow occur. These problems cause significant safety risks, but since most of the situations are difficult to solve immediately, solutions are required.

Korean Registered Patent No. 10-1977052 (published on May 3, 2019)

In order to solve the above problems, the technical problem to be achieved by the present invention is to output the information obtained by comprehensively reflecting the road image and atmospheric information of the road, especially the dangerous situation on the road, through a display device installed on the road. By doing so, it is to propose a road surface condition monitoring system and method using a drone that can notify the driver of various issues occurring on the road surface in advance.

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

As a means for solving the above-described technical problem, the road surface condition monitoring system using a drone according to an embodiment of the present invention is mounted on an unmanned aerial vehicle or an unmanned aerial vehicle set to fly within a preset detection range, At least one road surface detection device that captures an image, measures the atmospheric condition within the detection zone, and determines the road surface condition within the detection zone based on the road image and the atmospheric condition, the road surface from any one of the unmanned aerial vehicle and the road surface detection apparatus. It includes a road monitoring server that receives information about a state and generates information for output, and a display device that receives and displays information for output from the road monitoring server.

Preferably, the road surface detection device includes a camera for capturing a road image, a temperature/humidity sensor for measuring the atmospheric condition by detecting the temperature and humidity in the air, and a camera for determining the road surface condition based on the captured road image and the measured atmospheric condition. It includes a road surface condition determining unit and a communication unit for transmitting the determined road surface condition to a road monitoring server.

Also preferably, the road surface detection device further includes a thermal imaging camera that captures a thermal image within the detection section, and the road surface condition determining unit may also reflect the thermal image when determining the road surface condition.

Also preferably, the road surface detection device may further include a controller controlling the communication unit to transmit the road surface condition determined by the road surface condition determination unit to one of the road monitoring server and the unmanned aerial vehicle according to the current communication status.

Also preferably, the unmanned aerial vehicle may include a drone body, a flight control unit that controls the drone body, a GPS sensor that generates GPS information, and a remote communication module that supports communication with a road monitoring server.

Also preferably, the unmanned aerial vehicle further includes a short-range communication module supporting short-range communication with the road surface sensing device, and the road surface sensing device receives GPS information generated by the GPS sensor through the short-range communication module to obtain location information. can be obtained

Also preferably, the unmanned air vehicle and the road surface detection device are plural in a one-to-one correspondence with each other, and the road monitoring server includes a network interface unit for receiving information on the road surface condition from any one of the plurality of road surface detection devices and the unmanned air vehicle; An information generation unit may be included to generate information for output by collecting information on road surface conditions.

Also preferably, the road monitoring server may further include a deep learning learning unit that learns road surface condition information through deep learning recognition.

On the other hand, in the road surface condition monitoring method using a drone according to another embodiment of the present invention, the step of taking a road image within the detection section in the road surface detection device, the step of measuring the atmospheric condition in the detection section in the road surface detection device , In the road surface detection device, determining the road surface condition in the detection section based on the road image and the atmospheric condition, in the road monitoring server, receiving information on the road surface condition and generating output information, in the road monitoring server, for outputting Transmitting the information to the display device, and receiving and displaying the information for output in the display device.

Preferably, the road surface detection device further includes the step of capturing a thermal image within the detection section, and in the step of determining the road surface condition, the thermal image may also be reflected when determining the road surface condition.

Preferably, the road surface detection device may further include determining the road surface condition and then transmitting information on the road surface condition to one of the road monitoring server and the unmanned aerial vehicle according to the current communication condition.

Preferably, the method may further include transmitting the received road surface condition information to a road monitoring server when information on the road surface condition is received from the road surface detection device in the unmanned aerial vehicle.

Preferably, the road surface detection device may further include obtaining location information by receiving GPS information generated by a GPS sensor of the unmanned aerial vehicle through short-range communication.

Also preferably, the UAV and the road surface detection device are plural in a one-to-one correspondence with each other, and the road monitoring server further comprises receiving information about the road surface condition from any one of the plurality of road surface detection devices and the UAV, and outputting In the step of generating information, information for output may be generated by integrating the received information on the road surface condition.

Also preferably, the road monitoring server may further include learning information about road surface conditions through deep learning recognition.

According to the present invention, the road surface condition using a drone can be judged by reflecting the road image captured using a drone and the atmospheric condition on the road to determine the road surface condition, and inform the driver of information based on the result of the determination in advance. There is an effect of providing a monitoring system and method.

In addition, various accidents that may occur on the road can be prevented in advance by the driver knowing in advance various variables that may occur on the road, in particular, dangerous situations on the road, and there is an effect of inducing safe driving.

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

1 is a network configuration diagram of a road condition monitoring system using a drone according to a preferred embodiment of the present invention;
2 is a block diagram of an unmanned aerial vehicle according to a preferred embodiment of the present invention;
3 is a block diagram of a road surface detection device according to a preferred embodiment of the present invention;
4 is a block diagram of a road monitoring server according to a preferred embodiment of the present invention;
5 is a flowchart for explaining an example of a road surface condition monitoring method according to a preferred embodiment of the present invention, and
6 is a flowchart illustrating an example of a road surface condition monitoring method according to a preferred embodiment of the present invention.

The above objects, other objects, features and advantages of the present invention will be easily understood through the following preferred embodiments in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments described herein and may be embodied in other forms. Rather, the embodiments introduced herein are provided so that the disclosed content will be thorough and complete and the spirit of the present invention will be sufficiently conveyed to those skilled in the art.

In this specification, when an element is referred to as being on another element, it means that it may be directly formed on the other element or a third element may be interposed therebetween. Also, in the drawings, the thickness of components is exaggerated for effective description of technical content.

Where an element, component, device, or system is referred to as including a component consisting of a program or software, even if not explicitly stated otherwise, that element, component, device, or system means that the program or software executes or operates. It should be understood that it includes hardware (eg, memory, CPU, etc.) or other programs or software (eg, operating system or driver required to drive hardware) required to do so.

In addition, it should be understood that, unless otherwise specified, the element (or component) may be implemented in any form of software, hardware, or both software and hardware.

In addition, terms used in this specification are for describing embodiments and are not intended to limit the present invention. In this specification, singular forms also include plural forms unless specifically stated otherwise in a phrase. The terms 'comprises' and/or 'comprising' used in the specification do not exclude the presence or addition of one or more other elements.

1 is a network configuration diagram of a road condition monitoring system using a drone according to a preferred embodiment of the present invention.

Referring to FIG. 1, the road surface condition monitoring system using a drone according to a preferred embodiment of the present invention includes an unmanned aerial vehicle 100, a road surface detection device 200, a display device 300, and a road monitoring server 400. It is done.

The unmanned air vehicle 100 refers to an air vehicle that flies automatically or semi-automatically according to a pre-programmed path on the ground without a pilot directly boarding, and may be a conventional drone.

The unmanned aerial vehicle 100 flies within a predetermined detection range. The road surface condition monitoring system using the present drone includes a plurality of unmanned aerial vehicles 100, and each detection section may be set as a flight section so as not to overlap for each unmanned aerial vehicle 100. In particular, flight sections must be set so that the plurality of unmanned aerial vehicles 100 do not collide with each other.

In addition, the unmanned aerial vehicle 100 may provide location information of a place currently flying by using a Global Positioning System (GPS). In this embodiment, only one unmanned aerial vehicle 100 is shown for convenience of explanation, and it is obvious that it is not limited thereto. The unmanned aerial vehicle 100 will be described in more detail in FIG. 2 to be described later.

The road surface detection device 200 is mounted on the unmanned aerial vehicle 100 and flies along with the unmanned aerial vehicle 100 as it flies. The road surface detection device 200 captures a road image, measures an atmospheric condition, and determines a road surface condition based on the road image and atmospheric condition. The road surface detection device 200 will be described in more detail in FIG. 3 to be described later.

The road surface detection device 200 and the unmanned aerial vehicle 100 correspond one-to-one. That is, one road surface detection device 200 is mounted on one unmanned aerial vehicle 100 . In addition, the road surface monitoring system using this drone is provided with a plurality of road surface detection devices 200 and unmanned aerial vehicles 100 corresponding one-to-one, and each flight section is set.

The display device 300 is a display installed on the road and displays information transmitted from the road monitoring server 400, for example, output information. In this embodiment, a state in which one display device 300 is installed on a road has been exemplified, but this is only for convenience of description and is not limited thereto.

That is, a plurality of display devices 300 may be installed on the road at predetermined intervals, and may also be installed on the ascending line and the descending line, respectively. In addition, the display devices 300 respectively installed on the ascending line and the descending line may receive different information from the road monitoring server 400, and in this case, may display different information.

The road monitoring server 400 receives information about the road surface condition from any one of the unmanned aerial vehicle 100 and the road surface detection device 200 and generates information for output. More specifically, the road monitoring server 400 generates information for output by collecting information on a plurality of road surface conditions by receiving information on each road surface condition from a plurality of road surface detection devices 200 .

In some cases, the road monitoring server 400 may determine a dangerous area after receiving information on road surface conditions. Through this, the road monitoring server 400 may not display any information or display a daily guide phrase when a particularly dangerous area is not found on the road. In addition, when a dangerous area is found on the road, the road monitoring server 400 may generate output information for notifying the dangerous situation on the display device 300 installed near the corresponding area. The road monitoring server 400 will be described in detail in FIG. 4 to be described later.

2 is a block diagram of an unmanned aerial vehicle according to a preferred embodiment of the present invention.

Referring to FIG. 2, an unmanned air vehicle 100 according to a preferred embodiment of the present invention includes a drone body 110, a flight control unit (FCU) 120, a GPS sensor 130, a short-range communication module 140, and A remote communication module 150 is included.

The drone body 110 is a hardware flight device that allows the unmanned aerial vehicle 100 to fly, and flies within a preset detection range under the control of the FCU 120. A geomagnetic sensor for estimating a flight direction and a barometer for measuring altitude may be embedded in the drone body 110 .

The FCU 120 is for controlling the flight of the unmanned aerial vehicle 100, and controls a motor (not shown) using sensing data and adjustment commands by various sensors mounted on the unmanned aerial vehicle 100. For example, the FCU 120 may control a motor using sensing data obtained from a geomagnetic sensor and a barometer and an adjustment command.

The GPS sensor 130 is a sensor that uses a global positioning system (GPS) and plays a very important role in autonomous flight of the unmanned aerial vehicle 100 . It is recommended that the unmanned aerial vehicle 100 receive as many radio waves as possible from satellites in order to obtain information for deriving a location.

In this embodiment, the GPS sensor 130 is also used for autonomous flight of the unmanned aerial vehicle 100, but may also be used for the purpose of adding location information to a road image captured by the road surface detection device 200.

The short-range communication module 140 supports short-range communication between the unmanned aerial vehicle 100 and the road surface detection device 200 . The short-distance communication module 140 may apply one of wireless communication standards such as Bluetooth and ZigBee.

In this embodiment, wireless short-range communication is exemplified in the communication between the unmanned aerial vehicle 100 and the road surface detection device 200, but considering that the road surface detection device 200 is mounted on the unmanned air vehicle 100 in some cases, the road surface The sensing device 200 and the unmanned aerial vehicle 100 may be connected to each other through a wired cable to transmit/receive GPS information or road conditions.

The remote communication module 150 supports remote communication between the unmanned aerial vehicle 100 and the road monitoring server 400 . The remote communication module 150 does not necessarily have to be provided in the unmanned aerial vehicle 100 . For example, when the road surface detection device 200 is configured to directly communicate with the road monitoring server 400, it is irrelevant that the unmanned aerial vehicle 100 does not have the remote communication module 150. However, even when the road surface detection device 200 and the road monitoring server 400 communicate directly, it may be provided for reserve use when communication between the road surface detection device 200 is not smooth.

The remote communication module 150 operates when the road surface detection device 200 transmits information on the road surface condition to the unmanned aerial vehicle 100, and transmits information about the road surface condition received from the road surface detection device 200 to the road. It performs a function of transmitting back to the monitoring server 400.

3 is a block diagram of a road surface detection device according to a preferred embodiment of the present invention.

Referring to FIG. 3 , the road surface detection device 200 according to a preferred embodiment of the present invention includes a camera 210, a temperature/humidity sensor 220, a thermal imaging camera 230, a road condition determining unit 240, and a communication unit. (250), and a controller (260). As mentioned above, the road surface detection device 200 is mounted on the unmanned aerial vehicle 100.

The camera 210 captures a road image while the unmanned aerial vehicle 100 flies within the detection area. The camera 210 may take a moving image of the road while flying within the detection section according to a preset condition, or may take a still image according to a predetermined time interval.

The temperature/humidity sensor 220 is a sensor that detects temperature and humidity within a sensing section. Temperature and humidity are important factors in predicting road conditions. Since temperature is higher or lower than average and humidity is higher or lower than average, these are factors that can greatly affect the road surface, so in this embodiment, the sensing data of the temperature/humidity sensor is used to judge

The thermal imaging camera 230 takes a thermal image within the detection period. In general, the thermal imaging camera 230 utilizes the fact that the wavelength of infrared rays decreases as the temperature of an object increases. Instead of an image sensor, a microbolometer that responds to infrared rays is mounted, and the infrared energy passing through the lens is reflected in the infrared rays. A thermal image is taken by a structure that is converted into an electrical signal through a sensor.

Since the thermal imaging camera 230 expresses the temperature as an image, a manager can intuitively check the temperature state based on the thermal image captured by the thermal imaging camera 230 . In other words, you can quickly analyze the temperature through the image, and check the overall temperature distribution to identify the point with the highest temperature at a glance. In addition, the temperature changing in real time by the thermal imaging camera 230 can be checked.

The road surface condition determination unit 240 determines the road image captured by the camera 210, the air temperature and humidity measured by the temperature/humidity sensor 220, and the thermal image captured by the thermal imaging camera 230. Integrating, the road surface condition is comprehensively judged by these information.

The communication unit 250 supports network communication of the road surface detection device 200 . Through the communication unit 250, the road surface detection device 200 may transmit information on the road surface condition to the road monitoring server 400. In this embodiment, the communication unit 250 includes both a short-range communication function with the unmanned aerial vehicle 100 and a long-distance communication function with the road monitoring server 400 .

The controller 260 controls overall functions of the road surface detection device 200 . That is, the controller 260 controls signal input/output between the camera 210, the temperature/humidity sensor 220, the thermal imaging camera 230, the road condition determining unit 240, and the communication unit 250.

The controller 260 controls the communication unit 250 to transmit the road surface condition determined by the road surface condition determining unit 240 to the road monitoring server 400 or the unmanned aerial vehicle 100 according to the current communication status.

4 is a block diagram of a road monitoring server according to a preferred embodiment of the present invention.

Referring to FIG. 4, the road monitoring server 400 according to a preferred embodiment of the present invention includes a network interface unit 410, an information generator 420, a deep learning learning unit 430, a storage unit 440, and A control unit 450 is included.

The network interface unit 410 supports the network interface of the road monitoring server 400 . For example, the network interface unit 410 may support communication for transmitting and receiving information with the unmanned aerial vehicle 100 , the road surface detection device 200 , and the display devices 300 .

The information generation unit 420 generates information for output using information about road surface conditions transmitted from the road surface detection device 200 or the unmanned aerial vehicle 100 . The information for output output by the information generating unit 430 is information for notifying the driver of road surface conditions.

When information on the road surface condition transmitted from the plurality of road surface detection devices 200 or the plurality of unmanned aerial vehicles 100 is received, the information generating unit 420 collects the information on the plurality of road surface conditions and risks the road. It determines the situation and generates information for output so that the driver can be notified of the dangerous situation on the road.

For example, when the road surface condition is normal, information informing that the road condition is good may be generated, and when the road surface condition is abnormal, information for notifying the driver of the poor road condition while notifying the current road condition may be generated. information can be created.

The deep learning learning unit 430 learns information about road surface conditions through deep learning recognition. The deep learning learning unit 440 continuously learns the road surface condition whenever information on the road surface condition is received using a conventional deep learning technology, so that the information generating unit 420 determines the dangerous situation of the road. You can keep evolving.

The storage unit 440 stores all information necessary for the operation of the road monitoring server 400. For example, the storage unit 440 may store information about a preset sensing section in which the unmanned aerial vehicle 100 will fly. Also, the storage unit 440 may store information about the road surface condition received through the network interface unit 410 so that the road surface condition can be learned by the deep learning learning unit 430 .

The controller 450 controls the overall operation of the road monitoring server 400 . That is, the control unit 450 controls signal input/output between the network interface unit 410, the information generation unit 420, the deep learning learning unit 430, and the storage unit 440.

5 is a flowchart illustrating an example of a road surface condition monitoring method according to a preferred embodiment of the present invention.

Here, an example of a road surface condition monitoring method according to a preferred embodiment of the present invention will be described with reference to FIGS. 1 to 5 .

When the flight of the unmanned aerial vehicle 100 is started by the manager, the unmanned aerial vehicle 100 flies within a preset detection range, and the camera 210 of the road surface detection device 200 captures a road image (S501). In this case, the road image may be a moving image during flight or a still image captured at predetermined time intervals.

The road surface detection device 200 measures the atmospheric condition (S503). More specifically, the temperature/humidity sensor 220 senses the temperature and humidity of the road, and the thermal imaging camera 230 takes a thermal image of the road.

The road surface condition determining unit 240 comprehensively judges the measured atmospheric condition and the previously photographed road image to determine the road surface condition (S505).

The GPS sensor 130 of the unmanned aerial vehicle 100 provides GPS information to the road surface detection device 200 (S507). Accordingly, the road surface detection device 200 transmits the road surface condition determined by the road surface condition determination unit 240 and the GPS information to the road monitoring server 400 (S509).

The road monitoring server 400 collects information on road surface conditions transmitted from the plurality of unmanned aerial vehicles 100 (S511) and generates output information for display on the display device 300 (S513).

Thereafter, the road monitoring server 400 generates output information, transmits the generated output information to the display device 300 (S515), and displays the output information in the display device 300 (S517).

In this embodiment, an example of directly transmitting information on road surface conditions from the road surface detection device 200 to the road monitoring server 400 without passing through the unmanned aerial vehicle 100 has been described. In this case, the unmanned aerial vehicle 100 may perform only a role of providing GPS information while flying.

6 is a flowchart illustrating an example of a road surface condition monitoring method according to a preferred embodiment of the present invention.

Here, an example of a road surface condition monitoring method according to a preferred embodiment of the present invention will be described with reference to FIGS. 1 to 4 and 6 .

The road surface detection device 200 measures road images and atmospheric conditions. More specifically, a road image is photographed through the camera 210 (S601), and temperature and humidity are measured by the temperature/humidity sensor 220 (S603).

The road surface condition determining unit 240 comprehensively judges the measured atmospheric condition and the previously photographed road image to determine the road surface condition (S605), and transmits information on the determined road surface condition to the unmanned aerial vehicle 100 (S605). S607).

After receiving information on the road surface condition from the road surface detection device 200, the unmanned aerial vehicle 100 transmits information on the road surface condition and GPS information by the GPS sensor 130 to the road monitoring server 400 (S609). ).

The road monitoring server 400 collects information on road surface conditions received from the plurality of unmanned aerial vehicles 100 (S611) and generates output information for display on the display device 300 (S613).

After the road monitoring server 400 generates information for output, it transmits the generated information for output to the display device 300 (S615), and displays the information for output in the display device 300 (S617).

Thereafter, the deep learning learning unit 430 of the road surface detection device 200 proceeds with deep learning learning using the information on the road surface condition (S619). Through deep learning learning, the information generation unit 420 of the road monitoring server 400 continuously evolves when generating information for output, so that a dangerous situation can be identified more accurately.

There are various variables on the road. While there are weather conditions that the driver can visually check, such as heavy rain, heavy snow, and thick fog, there are also situations that are difficult for users to predict, such as black ice. In addition, potholes caused by aging of roads, regardless of climate, may cause a situation that is difficult for drivers to avoid. In addition, falling objects from a large cargo vehicle can cause a very dangerous situation to vehicles following, and depending on the type of falling object, if a sharp falling object is left on the road, it may affect the wheels of the vehicle and lead to a serious accident.

That is, a wide variety of unpredictable dangerous situations occur on the road. Therefore, many existing fixed CCTVs have limitations in determining dangerous situations on the road.

Therefore, by taking an image of the road by a flexible and maneuverable drone and determining the road surface condition by reflecting the image of the road, a great effect can be expected at a low cost. In particular, by using temperature/humidity and thermal images together with drones, even situations that are difficult to judge with only road images can be reflected.

Those skilled in the art to which the present invention pertains will understand that the present invention may be embodied in other specific forms without changing its technical spirit or essential features. Therefore, the embodiments described above should be understood as illustrative in all respects and not limiting. The scope of the present invention is indicated by the following claims rather than the detailed description above, and all changes or modifications derived from the meaning and scope of the claims and equivalent concepts should be construed as being included in the scope of the present invention. do.

100: unmanned aerial vehicle 200: road surface detection device
300: display device 400: road monitoring server

Claims (15)

An unmanned aerial vehicle set to fly within a preset detection range;
At least one mounted on the unmanned aerial vehicle, photographing a road image within the detection section, measuring an atmospheric state within the detection region, and determining a road surface condition within the detection region based on the road image and the atmospheric state road surface detection device;
a road monitoring server generating information for output by receiving information on the road surface condition from any one of the unmanned aerial vehicle and the road surface detection device; and
A road surface condition monitoring system using a drone, characterized in that it includes a display device for receiving and displaying the information for output from the road monitoring server. According to claim 1,
The road surface detection device,
a camera for capturing the road image;
a temperature/humidity sensor for measuring the air condition by sensing temperature and humidity in the air;
a road surface condition determination unit determining the road surface condition based on the captured road image and the measured atmospheric condition; and
A road surface condition monitoring system using a drone comprising a; communication unit for transmitting the determined road surface condition to the road monitoring server. According to claim 2,
The road surface detection device,
Further comprising a thermal imaging camera for taking a thermal image within the detection section,
The road surface condition monitoring system using a drone, characterized in that the road surface condition determining unit also reflects the thermal image when determining the road surface condition. According to claim 2,
The road surface detection device,
and a controller controlling the communication unit to transmit the road surface condition determined by the road surface condition determining unit to one of the road monitoring server and the unmanned aerial vehicle according to a current communication state. surveillance system. According to claim 1,
The unmanned aerial vehicle,
drone aircraft;
Flight control unit that controls the drone body
a GPS sensor that generates GPS information; and
A road surface condition monitoring system using a drone, characterized in that it includes a; remote communication module supporting communication with the road monitoring server. According to claim 5,
The unmanned aerial vehicle,
It further includes a short-range communication module supporting short-range communication with the road surface detection device,
The road surface monitoring system using a drone, characterized in that the road surface detection device acquires location information by receiving the GPS information generated by the GPS sensor through the short-range communication module. According to claim 1,
The unmanned aerial vehicle and the road surface detection device are plural in a one-to-one correspondence with each other,
The road monitoring server,
a network interface unit receiving information on the road surface condition from one of a plurality of road surface detection devices and the unmanned aerial vehicle; and
A road surface condition monitoring system using a drone, characterized in that it comprises a; information generation unit for generating information for output by integrating the received information on the road surface condition. According to claim 7,
The road monitoring server,
The road surface condition monitoring system using a drone, characterized in that it further comprises; a deep learning learning unit that learns the information on the road surface condition through deep learning recognition. A road surface monitoring method for a system comprising a road surface detection device mounted on an unmanned aerial vehicle set to fly within a preset detection section, a road monitoring server communicating with the road surface detection device, and a display device communicating with the road monitoring server,
In the road surface detection device, photographing a road image within the detection section;
In the road surface detection device, measuring a standby state within the detection section;
determining a road surface condition within the sensing section based on the road image and the waiting condition, in the road surface detection device;
generating information for output by receiving the information on the road surface condition in the road monitoring server;
Transmitting, in the road monitoring server, the information for output to a display device; and
The method for monitoring road surface conditions using a drone, characterized in that it comprises a; step of receiving and displaying the information for output in the display device. According to claim 9,
In the road surface detection device, photographing a thermal image within the detection section; further comprising,
In the step of determining the road surface condition, the road surface condition monitoring method using a drone, characterized in that the thermal image is also reflected when the road surface condition is determined. According to claim 9,
In the road surface detection device, after determining the road surface condition, transmitting information on the road surface condition to one of the road monitoring server and the unmanned aerial vehicle according to the current communication state; Road surface condition monitoring method used. According to claim 11,
In the unmanned air vehicle, when the information on the road surface condition is received from the road surface detection device, transmitting the received information on the road surface condition to the road monitoring server; State monitoring method. According to claim 9,
In the road surface detection device, receiving GPS information generated by the GPS sensor of the unmanned aerial vehicle through short-range communication and acquiring location information; road surface monitoring method using a drone, characterized in that it further comprises. According to claim 13,
The unmanned aerial vehicle and the road surface detection device are plural in a one-to-one correspondence with each other,
In the road monitoring server, receiving information on the road surface condition from any one of a plurality of road surface detection devices and the unmanned aerial vehicle; further comprising,
In the step of generating the information for output, the information for output is generated by collecting the received information on the road surface condition. According to claim 9,
The road surface condition monitoring method using a drone, characterized in that it further comprises; learning the information on the road surface condition through deep learning recognition in the road monitoring server.

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