KR20200080379A - Safety flight path creation system and method for big data based drone - Google Patents

Abstract

According to one embodiment of the present invention, a system for generating a safe flight path of a drone based on big data comprises a ground control system, a drone IoT server, and an AI big data server. The AI big data server includes a database management unit managing reference information for generating a safe flight path by interlocking with a database storing spatial information big data; a real-time information collection unit receiving destination information inputted to the ground control system and drone flight information collected by a smart drone flying according to a remote control command received from the ground control system through the drone IoT server through the drone IoT server; and a safety flight path generation unit generating at least one safe flight path based on the reference information, the destination information, and the drone flight information and providing the generated safe flight path to the ground control system through the drone IoT server. The system may provide a safe flight path of a drone.

Description

Safe flight path generation system and method for big data-based drones{SAFETY FLIGHT PATH CREATION SYSTEM AND METHOD FOR BIG DATA BASED DRONE}

Embodiments of the present invention relate to a system and method for safe flight path generation of a big data-based drone.

Since drones can move freely in the air and quickly reach their destinations, they have high potential for courier delivery, reconnaissance, and tracking, and related studies have been actively conducted. Studies have reached the stage of testing for commercialization purposes, with the necessary flight path generation and planned flight or autonomous flight skills required to fulfill the mission. However, it is often the case that the test fails due to a loss of communication during flight or a crash due to an obstacle on the flight path.

In general, the drone's flight algorithm uses GPS information to generate a waypoint to follow the waypoints. Therefore, if there is an incommunicable area on the designated path, communication may be lost. In addition, the pre-determined holding altitude during flight can cause collisions with high-rise facilities or other obstacles such as drones. When these situations occur, drones can fall at high altitudes and cause serious safety accidents.

In other words, it is most important to create a safe flight path to the destination because most drone flight path creation methods do not guarantee safety. In order to create a safe flight path, a lot of accumulated information related to the environment in which the drone is actually operated, such as building location information, a no-fly zone, and an incommunicable area is required.

Related prior art is Republic of Korea Patent Publication No. 10-2017-0014817 (name of invention: drone control method and apparatus and system for performing the same, and drone control server, publication date: 2017.02.08).

An embodiment of the present invention is a system and method for generating a safe flight path for a big data-based drone that can provide a safe flight path for a drone by generating an optimal path to a destination based on big data such as a no-fly zone and a building location Gives

An exemplary embodiment of the present invention continuously collects real-time information from a drone and periodically performs an updater of the information to update a safe flight path that reflects the latest information and applies a safe flight path of a big data-based drone that can be applied to a drone in flight Provide a production system and method.

The problem to be solved by the present invention is not limited to the problem(s) mentioned above, and another problem(s) not mentioned will be clearly understood by those skilled in the art from the following description.

A safe flight path generation system for a big data-based drone according to an embodiment of the present invention includes a ground control system, a drone IoT server, and an AI big data server, and the AI big data server is a database for storing spatial information big data Database management unit to manage the reference information for the creation of a safe flight path in conjunction with; Real-time information that receives drone flight information collected by a smart drone flying according to the destination information input to the ground control system and a remote control command received from the ground control system through the drone IoT server through the drone IoT server Collection unit; And generating a safe flight path based on the reference information, the destination information and the drone flight information, and providing the generated safe flight path to the ground control system through the drone IoT server. Includes wealth.

The real-time information collecting unit receives real-time information including the drone flight information and the camera image in real time from the smart drone through the drone IoT server, and the database manager determines whether there is any change in the reference information based on the real-time information If there is a change in the result of the determination, it is possible to update the reference information and the spatial information big data related to the reference information in conjunction with the database.

The safe flight path generation unit generates a new safe flight path based on the updated reference information, and provides the generated new safe flight path to the ground control system through the drone IoT server, thereby providing the new safe flight path. The flight path of the smart drone may be updated in real time according to the included remote control command.

The ground control system generates a remote control command including the safe flight path received from the AI big data server through the drone IoT server, and the generated remote control command is waiting for a mission through the drone IoT server or The smart drone can be controlled from a remote location by delivering it to the flying smart drone.

The reference information may include at least one of a no-fly zone, airport control zone, incommunicable area, densely populated area, restricted altitude, building location information, and drone location information.

When the variability is lower than the reference, the reference information is periodically checked and updated to be utilized in the creation of the safe flight path. When the variability is higher than the reference, the information is continuously updated with the latest information to ensure safety. It can be used to create flight routes.

For the densely populated areas, the volatility is normal (standard), the no-fly zone, the airport control area, the incommunicable area, the restricted altitude, and the variability is lower than the standard for the building location information, and the drone position In the case of information, volatility may be higher than the standard.

In a method of generating a safe flight path for a big data-based drone according to an embodiment of the present invention, the database management unit of the AI big data server manages reference information for generating a safe flight path in conjunction with a database storing spatial information big data To do; The real-time information collecting unit of the AI big data server collects the drone flight information collected by the smart drone flying according to the destination information input to the ground control system and the remote control command received from the ground control system through the drone IoT server. Receiving through the drone IoT server; A safe flight path generation unit of the AI big data server generating at least one safe flight path based on the reference information, the destination information, and the drone flight information; And providing the generated safe flight path to the ground control system through the drone IoT server.

In a method of generating a safe flight path for a big data-based drone according to an embodiment of the present invention, the real-time information collection unit receives real-time information including the drone flight information and a camera image in real time from the smart drone through the drone IoT server. step; Determining whether there is a change in the reference information based on the real-time information by the database manager; And when there is a change as a result of the determination, the database management unit may further include updating the reference information and spatial information big data related to the reference information in cooperation with the database.

A method for generating a safe flight path of a big data-based drone according to an embodiment of the present invention includes the steps of the safe flight path generation unit generating a new safe flight path based on the updated reference information; And the safe flight path generation unit provides the generated new safe flight path to the ground control system through the drone IoT server, real-time the flight path of the smart drone according to a remote control command including the new safe flight path. It may further include the step of updating.

Details of other embodiments are included in the detailed description and accompanying drawings.

According to an embodiment of the present invention, it is possible to provide a safe flight path of a drone by generating an optimal path to a destination based on big data such as a no-fly zone and a building location.

According to an embodiment of the present invention, it is possible to continuously collect real-time information from a drone and periodically perform an updater of the information to update a safe flight path reflecting the latest information and apply it to a drone in flight.

1 is a system configuration diagram illustrating a safe flight path generation system of a big data-based drone according to an embodiment of the present invention.
FIG. 2 is a block diagram showing a detailed configuration of the AI big data server of FIG. 1.
3 shows a method of generating a safe flight path according to an embodiment of the present invention.
FIG. 4 is a diagram illustrating a route newly updated by creating a safety flight route based on big data and updating information.
5 is a flowchart illustrating a method for generating a safe flight path of a big data-based drone according to an embodiment of the present invention.
6 is a flowchart illustrating a method for generating a safe flight path of a big data-based drone according to another embodiment of the present invention.

Advantages and/or features of the present invention and methods for achieving them will become apparent by referring to embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but will be implemented in various different forms, and only the present embodiments allow the disclosure of the present invention to be complete, and common knowledge in the art to which the present invention pertains. It is provided to fully inform the person having the scope of the invention, and the present invention is only defined by the scope of the claims. The same reference numerals refer to the same components throughout the specification.

In addition, a preferred embodiment of the present invention to be carried out below is provided in each system functional configuration to effectively describe the technical components constituting the present invention, or a system function commonly provided in the technical field to which the present invention pertains. The configuration is omitted as much as possible, and the functional configuration that should be additionally provided for the present invention will be mainly described. If a person having ordinary knowledge in the technical field to which the present invention pertains, it will be possible to easily understand the functions of components that have been used in the prior art among the omitted functional configurations not shown below, and also the omitted components as described above. It will also be clearly understood the relationship between the elements and the components added for the present invention.

In addition, in the following description, the terms "transmission", "communication", "transmission", "reception" of a signal or information, or similar terms mean that a signal or information is directly transmitted from one component to another. Not only that, it also includes passing through other components. In particular, "sending" or "transmitting" a signal or information to a component indicates the final destination of the signal or information and does not mean a direct destination. The same is true for the "reception" of a signal or information.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a system configuration diagram illustrating a safe flight path generation system of a big data-based drone according to an embodiment of the present invention, and FIG. 2 is a block diagram illustrating detailed configuration of the AI big data server of FIG. 1. to be.

Referring to FIG. 1, a safe flight path generation system 100 for a big data-based drone according to an embodiment of the present invention includes a smart drone 110, a ground control system 120, a drone IoT server 130, and an AI big It may be configured to include a data server 140 and the database 150.

The smart drone 110 communicates with the drone IoT server 130 to indirectly receive a remote control command for flight control of the smart drone 110 from the ground control system 120, and the remote control command You can fly a safe flight path according to. Here, the safe flight path means an optimal flight path to a destination based on big data such as a no-fly zone, a building location, and the like.

The smart drone 110 communicates with the drone IoT server 130 in various wireless communication methods, for example, communication using radio frequency, Bluetooth ( ^TM ), Wireless LAN (WLAN), Radio Frequency Identification (RFID), infrared communication ( You can use at least one of Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee, Near Field Communication (NFC), WirelessFidelity (Wi-Fi), Wi-Fi Direct, and Wireless Universal Serial Bus (USB) technology. .

However, since the existing wireless communication method is a short-range wireless communication method, there is no problem in the smart drone 110 performing a short-range task, but there is a problem that it is not suitable for performing a long-range task.

Accordingly, in one embodiment of the present invention, the smart drone 110 communicates with the drone IoT server 130 through interactive communication based on a Long Term Evolution (LTE) mobile communication network, which is a wireless communication method suitable for performing long-distance missions. Can send and receive. Through this, the smart drone 110 can perform situation analysis and object recognition (AI), real-time sharing of flight situation information (Telemetry), and autonomous flight according to the generation of a safe flight path based on big data.

The user (controller) transmits a flight-related remote control command to the smart drone 110 through a ground control system (GCS) and receives camera images or route camera images from the smart drone 110. Can.

The smart drone 110 may be dispatched to a mission site to perform initial observation or forestry, and may capture an image of the environment around the flight path and the mission site with a camera or collect mission related information through a sensor or the like. In other words, the smart drone 110 first dispatches to the field before the on-site worker arrives at the site where the mission is required or an accident occurs, and then shoots a video related to the mission or information necessary for performing the mission (mission-related information ).

In this case, the smart drone 110 may capture an image of the environment around the flight path and the mission site or collect the mission-related information from the time of dispatch to the mission site to arrival and return. The smart drone 110 may transmit a real-time shooting image and information related to the mission to the ground control system 120 through the drone IoT server 130.

For example, if the task to be performed by the smart drone 110 is fire suppression or fire monitoring, the smart drone 110 first goes to the fire site before the firefighter, a field worker, arrives at the scene and fire scene Alternatively, a real-time image of a fire scene may be captured, and the captured image may be transmitted in real time to the ground control system 120 through the drone IoT server 130. In addition, the smart drone 110 collects mission-related information including weather information such as temperature, humidity, wind speed, and wind direction of the environment around the flight path or a mission site through various sensors and uses the drone IoT server 130. It can be transmitted to the ground control system 120 in real time.

To this end, the smart drone 110 receives a remote control command including location information (destination information) and flight route information regarding the site from the ground control system 120 through the drone IoT server 130 and In addition, it is possible to reach the site by performing flight control in a corresponding flight path according to the received remote control command.

Specifically, the smart drone 110 receives the remote control command through wireless communication based on the drone IoT server 130 and the LTE mobile communication network, and the smart drone 110 receives the remote control command according to the received remote control command. The flight can be controlled in an autonomous flight mode. Here, the flight path information included in the remote control command may include a safe flight path generated by the AI big data server 140 to be described later, and when the safe flight paths are multiple, multiple safe flight paths The user may point to a flight path selected by the user through input manipulation of the ground control system 120.

When receiving the remote control command from the ground control system 120 through the drone IoT server 130, the smart drone 110 is located within a certain distance based on the current location of the smart drone 110. The remote control command may be shared by communicating with at least one other drone. As a result, the smart drone 110 may perform a group flight with at least one other drone according to the remote control command. At this time, communication between each drone may be achieved by an LTE mobile communication method, and the distance (interval) between each drone may be set such that the viewing angles of each drone overlap each other.

In addition, the smart drone 110, the flight route, flight altitude, the drone flight information obtained in the course of flight, such as location information with other drones to the AI big data server 140 through the drone IoT server 130 It can be transmitted in real time.

For reference, real-time information, which is a term continuously referred to in the following embodiments, is collected by the smart drone 110 and the AI big data server 140 or the ground control system through the drone IoT server 130. It may be understood as a concept including camera images, mission-related information, and drone flight information, which are information transmitted in real time to the 120.

The ground control system 120 may receive information regarding a destination or flight route according to a manual operation of a user (control worker). The ground control system 120 may transmit information on the destination and information on the current location of the smart drone 110 to the AI big data server 140. Here, the information about the current location of the smart drone 110 may initially indicate predetermined location information, but thereafter, the drone delivered in real time from the smart drone 110 through the drone IoT server 130 It may indicate current location information included in flight information.

The ground control system 120 generates a remote control command including the safe flight path received through the drone IoT server 130 from the AI big data server 140, and the generated remote control command Through the drone IoT server 130, the smart drone 110 can be controlled from a remote location by delivering it to the smart drone 110 that is on standby or in flight.

The drone IoT server 130 may operate as a relay server for communication connection between the smart drone 110 and the ground control system 120. That is, the drone IoT server 130 receives the remote control command from the ground control system 120 and transmits it to the smart drone 110, and receives the camera image from the smart drone 110 to control the ground. System 120. In addition, the drone IoT server 130 may receive real-time information including camera images and drone flight information from the smart drone 110 and transmit it to the AI big data server 140.

To this end, the drone IoT server 130 may perform two-way communication based on the smart drone 110 and the LTE mobile communication network. In other words, the drone IoT server 130 receives the remote control command from the ground control system 120 through the smart drone 110 and the LTE mobile communication network-based two-way communication to the smart drone 110. The real-time information collected from the smart drone 110 may be transmitted to the AI big data server 140.

The AI big data server 140 may manage reference information for generating a safe flight path. In addition, the AI big data server 140 may receive real-time information collected by the smart drone 110 from the drone IoT server 130 and update information having a change. The AI big data server 140 may generate a safe flight path from information managed with the latest information and transmit it to the ground control system 120.

The ground control system 120 is a system that controls the smart drone 110 by sending a remote control command from a remote location to the drone IoT server 130, and a drone waiting for a mission or in flight includes a safe flight path. Control commands may be sent to allow the smart drone 110 to perform a task. If a new safe flight path is generated due to a change in information update, the flight path of the smart drone 110 is updated by transmitting the path information in real time.

The smart drone 110 flies along a safe flight path received from the drone IoT server 130 and continuously collects reference information for generating a safe flight path that can be collected during flight, and then the drone IoT server 130 Can be delivered to.

The AI big data server 140 uses space information big data to avoid (Avoid) a military area, a population dense area, or a no-fly zone, or raise the altitude in a high-rise building to create an optimal safe flight path. can do. In other words, the AI big data server 140 may generate an optimal safe flight path for providing an active autonomous flight technology utilizing the spatial information big data. Accordingly, according to an embodiment of the present invention, it is possible to provide a flight technology that actively generates an optimal safe flight path according to a mission, and information on a location, height, etc. of a building existing on the generated optimal safe flight path It can provide ideal altitude flight technology using (building location information).

To this end, the AI big data server 140 analyzes a flight path from a departure location to a destination, which is the current location of the smart drone 110, through digitization of spatial information based on the spatial information big data. It is possible to determine whether a non-flying area or an LTE deterioration area is included.

Specifically, the AI big data server 140 divides the map including the flight path of the analysis target into a plurality of grid-shaped areas, and assigns a unique number to each of the plurality of areas to determine the actual coordinate values of the area. After matching, through the analysis of the coordinates of the flight path using the spatial information big data, a unique number of the area determined as the non-flyable area may be output, and the area of the unique number may be determined as the non-flyable area. Here, the non-flyable area is a concept including an unexpectedly populated area (for example, a gathering area, etc.) or an area where unexpected buildings are included in a flight path included in a previous remote control command. .

The AI big data server 140 as described above includes a database management unit 210, a real-time information collection unit 220, a safe flight path generation unit 230, and a control unit 240 as shown in FIG. Can be.

The database manager 210 may manage reference information for the creation of a safe flight path in conjunction with a database 150 that stores spatial information big data. The above reference information is necessary to create a safe flight path so that a drone can minimize damage even if a crash occurs due to an accident during a flight. The reference information may include a no-fly zone, airport control zone, incommunicable area, densely populated area, restricted altitude, building location information, and drone location information as shown in Table 1 below.

[Table 1]

Referring to Table 1, in the densely populated area of the reference information, the volatility is normal (reference) level, and among the reference information, the non-fly zone, the airport control area, the incommunicable area, the restricted altitude, and the building location information In the case, the variability is lower than the reference, and in the case of the drone position information among the reference information, the variability may be higher than the reference. When the variability is lower than the reference, the reference information is periodically checked and updated to be utilized in the creation of the safe flight path. When the variability is higher than the reference, the information is continuously updated with the latest information to ensure safety. It can be used to create flight routes.

In general, airport control zones that are in danger of collision with aircraft taking off and landing near borders or military units are designated as no-fly zones. The no-fly zone is a necessary criterion because the drone must be avoided. In addition, in areas where communication is not possible or where signal is weaker than other areas, and densely populated areas, such as residential areas or event areas, are places where damage from a drone crash can occur, which is a necessary criterion for creating a safe route.

In addition, in the airspace where aircraft flight routes are installed, there is a risk of collision with the aircraft, so most areas have limited altitudes, so you must fly accordingly. In addition, if you know the location information of buildings that are as high as the altitude of the drone flying and the location information of drones flying nearby, it is a standard that can be used to avoid unexpected collisions. Standards other than those that must be followed can be added depending on the availability.

The real-time information collecting unit 220 is a smart drone flying according to the destination information input to the ground control system 120 and a remote control command received from the ground control system 120 through the drone IoT server 130. The drone flight information collected by 110 may be received through the drone IoT server 130.

The real-time information collection unit 220 may receive real-time information including the drone flight information and camera images from the smart drone 110 through the drone IoT server 130 in real time. Accordingly, the database management unit 210 determines whether there is a change in the reference information based on the real-time information, and if there is a change as a result of the determination, the reference information and the reference in conjunction with the database 150 Spatial information big data related to information can be updated.

The safe flight path generation unit 230 generates at least one safe flight path based on the reference information, the destination information, and the drone flight information, and the drone IoT server 130 generates the safe flight path. It can be provided to the ground control system 120 through.

The safe flight path generation unit 230 generates a new safe flight path based on the updated reference information, and the ground safety control system 120 generates the new safe flight path through the drone IoT server 130. Provided to, it is possible to update the flight path of the smart drone 110 in real time according to a remote control command including the new safe flight path.

Referring to Table 2 with reference to the creation of the safe flight path in detail as follows. The drone's route is generally created by using GPS information to create stop points that make up the route. Table 2 shows the waypoint information configuring the route.

[Table 2]

The drone arrives at the destination by sequentially flying from the starting point to the waypoints. Therefore, as shown in Table 2, the sequence information for each point must be known, and the latitude and longitude, which is the coordinate information of the point to be moved, the flight altitude information to be maintained while moving to the point, and the distance for each point constitute the flight path. Branch configuration information.

Although there are various flight path generation algorithms, the present invention proposes a path generation method that can be easily generated from spatial information to which big data is applied.

For reference, the spatial information is information necessary for location information on natural or artificial objects existing in space, such as ground, underground, water, and underwater, and spatial recognition and decision related thereto. In the present invention, location information on natural or artificial objects existing on the ground and information necessary for spatial recognition and decision-making related thereto may be used as spatial information.

The control unit 240 may control the AI big data server 140, that is, the database management unit 210, the real-time information collection unit 220, the safety flight path generation unit 230, and the like.

Referring to FIG. 1 again, the database 150 may store spatial information big data related to autonomous flight control of the smart drone 110. That is, the database 150 includes a drone location information DB storing drone location information (latitude, longitude, height, etc.), a building location information DB storing location information of buildings (latitude, longitude, height, etc.), military area Includes non-fly zone DB that stores information about non-fly zones, densely populated area DB that stores information about densely populated areas such as downtown areas, and non-communication area DB that stores information about LTE-degraded areas, etc. can do.

3 shows a method of generating a safe flight path according to an embodiment of the present invention.

Referring to FIG. 3, all of the reference information for generating a safe flight path is given as GPS information indicating an area. And to avoid GPS information errors and flight at the boundary of the area, the boundary of all areas has a safe distance between them. The flight route basically creates a waypoint at a certain distance and a straight line toward the destination. If the location to create a waypoint belongs to a region that cannot be created, it is changed to a location that leaves the region in the direction of a close boundary. If the non-creation area is a building or other drone, only the flight altitude is changed to avoid the risk of collision. This process is repeated to create a safe flight path for the drone.

FIG. 4 is a diagram illustrating a route newly updated by creating a safety flight route based on big data and updating information.

1 and 4, the AI big data server 140 of the safe flight path generation system 100 continuously updates the latest information collected from the smart drone 110. In addition, if an existing safety path cannot be used due to information changes, drones can continue to fly because a new safety path is created and updated.

The AI big data server 140 collects crowd information on the route from drones flying along the existing route generated according to the reference information for the creation of a safe flight route and immediately updates the information when a new population-dense area where crowds gather is generated. do. Then, based on the updated information, a new safe flight path is created and applied. The updated information is applied not only to drones waiting to be flying, but also to drones in flight, so that the drones reach the destination by avoiding the newly generated area.

As described above, in the present invention, a structure of a system for generating a safe flight path of a drone using big data is proposed. The proposed safe flight path generation system creates a safe flight path through safety flight path generation reference information defined as additional information to avoid the danger of accidents and places where flight is prohibited under the Aviation Safety Law. Safe flight path creation reference information is managed from the AI big data server 140 and is continuously updated by receiving new information from drones in flight, so if a change occurs, a new path can be created and applied to drones immediately. have.

The device described above may be implemented with hardware components, software components, and/or combinations of hardware components and software components. For example, the devices and components described in the embodiments include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor (micro signal processor), a microcomputer, a field programmable array (FPA), It may be implemented using one or more general purpose computers or special purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. The processing device may run an operating system (OS) and one or more software applications running on the operating system. In addition, the processing device may access, store, manipulate, process, and generate data in response to the execution of the software. For convenience of understanding, a processing device may be described as one being used, but a person having ordinary skill in the art, the processing device may include a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that may include. For example, the processing device may include a plurality of processors or a processor and a controller. In addition, other processing configurations, such as parallel processors, are possible.

The software may include a computer program, code, instruction, or a combination of one or more of these, and configure the processing device to operate as desired, or process independently or collectively You can command the device. Software and/or data may be interpreted by a processing device or to provide instructions or data to a processing device, of any type of machine, component, physical device, virtual equipment, computer storage medium or device. , Or may be permanently or temporarily embodied in the transmitted signal wave. The software may be distributed over networked computer systems, and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

5 is a flowchart illustrating a method for generating a safe flight path of a big data-based drone according to an embodiment of the present invention.

The method for generating a safe flight path of a big data-based drone described here is only one embodiment of the present invention, and various other steps may be added as necessary, and the following steps may also be performed by changing the order. Therefore, the present invention is not limited to each step and order described below. This may also be applied to other embodiments below.

1, 2 and 5, in step 510, the database management unit 210 of the AI big data server 140 interlocks with a database 150 that stores spatial information big data, and Reference information for creation can be managed.

Next, in step 520, the real-time information collection unit 220 of the AI big data server 140 controls the ground through the destination information input to the ground control system 120 and the drone IoT server 130. The drone flight information collected by the smart drone 110 flying according to the remote control command received from the system 120 may be received through the drone IoT server 130.

Next, in step 530, the safe flight path generation unit 230 of the AI big data server 140 generates at least one safe flight path based on the reference information, the destination information, and the drone flight information. Can.

Next, in step 540, the safe flight path generation unit 230 may provide the generated safe flight path to the ground control system 120 through the drone IoT server 130.

6 is a flowchart illustrating a method for generating a safe flight path of a big data-based drone according to another embodiment of the present invention.

1, 2 and 6, in step 610, the database management unit 210 of the AI big data server 140 interlocks with a database 150 that stores spatial information big data, and Reference information for creation can be managed.

Next, in step 620, the real-time information collection unit 220 of the AI big data server 140 controls the ground through the destination information input to the ground control system 120 and the drone IoT server 130. The drone flight information collected by the smart drone 110 flying according to the remote control command received from the system 120 may be received through the drone IoT server 130.

Next, in step 630, the safe flight path generation unit 230 of the AI big data server 140 generates at least one safe flight path based on the reference information, the destination information, and the drone flight information. Can.

Next, in step 640, the safe flight path generation unit 230 may provide the generated safe flight path to the ground control system 120 through the drone IoT server 130.

Next, in step 650, the real-time information collecting unit 220 can receive real-time information including the drone flight information and camera image in real time from the smart drone 110 through the drone IoT server 130. have.

Next, in step 660, the database management unit 210 may determine whether there is a change in the reference information based on the real-time information.

If there is a change as a result of the determination ("Yes" direction of 660), in step 670, the database manager 210 interlocks with the database 150 to generate the reference information and spatial information related to the reference information big data Can be updated. On the other hand, if there is no change as a result of the determination ("No" direction of 660), it may return to step 650.

Next, in step 680, the safe flight path generation unit 230 may generate a new safe flight path based on the updated reference information.

Next, in step 690, the safe flight path generation unit 230 provides the generated new safe flight path to the ground control system 120 through the drone IoT server 130, so that the new safe flight The flight path of the smart drone 110 may be updated in real time according to a remote control command including a path.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, or the like alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiment or may be known and usable by those skilled in computer software. Examples of computer readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CDROMs, DVDs, and magneto-opticals such as floptical disks. And hardware devices specially configured to store and execute program instructions such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language code that can be executed by a computer using an interpreter, etc., as well as machine language codes made by a compiler. The hardware device described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

As described above, although the embodiments have been described by the limited embodiments and drawings, those skilled in the art can make various modifications and variations from the above description. For example, the described techniques are performed in a different order than the described method, and/or the components of the described system, structure, device, circuit, etc. are combined or combined in a different form from the described method, or other components Alternatively, even if replaced or substituted by equivalents, appropriate results can be achieved.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

110: smart drone
120: ground control system
130: drone IoT server
140: AI big data server
150: database
210: database management
220: real-time information collection unit
230: safe flight path generation unit
240: control unit

Claims (10)

Includes ground control system, drone IoT server, and AI big data server,
The AI big data server
A database management unit that manages reference information for generating a safe flight path in conjunction with a database that stores spatial information big data;
Real-time information that receives drone flight information collected by a smart drone flying according to the destination information input to the ground control system and a remote control command received from the ground control system through the drone IoT server through the drone IoT server Collection unit; And
A safety flight path generation unit that generates at least one safe flight path based on the reference information, the destination information, and the drone flight information, and provides the generated safe flight path to the ground control system through the drone IoT server.
Safe flight path generation system of a big data-based drone, characterized in that it comprises a.
According to claim 1,
The real-time information collection unit
Real-time information including the drone flight information and camera image is received in real time from the smart drone through the drone IoT server,
The database management unit
It is characterized by determining whether there is a change in the reference information based on the real-time information, and updating the reference information and spatial information big data related to the reference information by interworking with the database when there is a change as a result of the determination. Safe flight path generation system for big data-based drones.
According to claim 2,
The safe flight path generation unit
Create a new safe flight path based on the updated reference information, and provide the generated new safe flight path to the ground control system through the drone IoT server, to a remote control command including the new safe flight path In accordance with the system, the flight path of the smart drone is updated in real time.
According to claim 1,
The ground control system
The AI drone IoT server generates a remote control command including the safe flight path received through the drone IoT server, and the smart drone waiting for a mission or flying the generated remote control command through the drone IoT server. A safe flight path generation system of a big data-based drone, characterized by controlling the smart drone from a remote location by delivering it to a remote location.
According to claim 1,
The above reference information
A safe flight path generation system for a big data-based drone, comprising at least one of a no-fly zone, airport control zone, incommunicable area, densely populated area, restricted altitude, building location information, and drone location information.
The method of claim 5,
The above reference information
When the volatility is lower than the standard, it is periodically checked and updated to be used for the creation of the safe flight path. When the volatility is higher than the standard, it is continuously updated with the latest information to create a safe flight path to which the latest information is applied. Safe flight path generation system of a big data-based drone, characterized in that utilized in.
The method of claim 6,
For the densely populated areas, the volatility is normal (standard), the no-fly zone, the airport control area, the incommunicable area, the restricted altitude, and the variability is lower than the standard for the building location information, and the drone position In the case of information, the variability is higher than the standard.
In the method of generating a safe flight path using a safe flight path generation system of a big data-based drone including a ground control system, a drone IoT server, and an AI big data server,
The database management unit of the AI big data server manages the reference information for the creation of a safe flight path in conjunction with a database storing spatial information big data;
The real-time information collection unit of the AI big data server collects the drone flight information collected by the smart drone flying according to the destination information input to the ground control system and the remote control command received from the ground control system through the drone IoT server. Receiving through the drone IoT server;
A safe flight path generation unit of the AI big data server generating at least one safe flight path based on the reference information, the destination information, and the drone flight information; And
The safe flight path generation unit providing the generated safe flight path to the ground control system through the drone IoT server.
A method of generating a safe flight path for a big data-based drone, comprising:
The method of claim 8,
Receiving, by the real-time information collecting unit, real-time information including the drone flight information and a camera image in real time from the smart drone through the drone IoT server;
Determining whether there is a change in the reference information based on the real-time information by the database manager; And
If there is a change as a result of the determination, the database management unit updates the reference information and spatial information big data related to the reference information in cooperation with the database.
A method of generating a safe flight path for a big data-based drone, further comprising a.
The method of claim 9,
The safe flight path generation unit generating a new safe flight path based on the updated reference information; And
The safe flight path generation unit provides the generated new safe flight path to the ground control system through the drone IoT server, so that the flight path of the smart drone in real time according to a remote control command including the new safe flight path. Steps to update
A method of generating a safe flight path for a big data-based drone, further comprising a.

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