Device for providing spatial information convergence solution

Abstract

To provide a device for providing a spatial information convergence solution that can provide a solution in a level required by a user through selecting sources of appropriate spatial information data correspondingly to analysis required by the user, and fusing the spatial information data of each selected source.SOLUTION: A device for providing a spatial information convergence solution includes: a data collection module for receiving a plurality of spatial information data and user requirement data; a selection module for selecting needed data required for generating the requirement data from among the plurality of spatial information data; a fusion module for generating a spatial information convergence solution by fusing the needed data; and an output module for providing the spatial information convergence solution to a user terminal corresponding to the user, wherein the plurality of spatial information data may include at least one of CCTV data, drone data, GPS data, and satellite captured data.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a spatial information fusion solution providing device.

[0002] Specifically, the present invention relates to a spatial information fusion solution providing device that can select an appropriate source of spatial information data according to the analysis required by a user, and fuse the spatial information data from each selected source to provide a solution of the level required by the user. [Background technology]

[0003] The content of this section merely provides background information regarding the present invention and may not constitute prior art.

[0004] Spatial information data is generally used to check, monitor, or inspect spaces such as buildings and nature. The most common form of spatial information data is closed-circuit television (CCTV), and in recent years, with technological advances, drones, satellite images, and aerial images are also being used.

[0005] However, existing monitoring platforms, management platforms, etc., use fragmented spatial information, and therefore have the drawback of not being able to combine and utilize the advantages and disadvantages of each piece of spatial information.

[0006] In other words, each spatial information data has its own unique spatial information parameters (e.g., resolution, acquisition cost, shooting area, real-time performance, etc.), and therefore each spatial information data has its own unique advantages and disadvantages. However, there is currently a lack of technology to provide spatial information fusion solutions by integrating and utilizing such various spatial information data.

[0007] Therefore, there is a strong need for a technology that can provide a new level of spatial information fusion solution by combining and utilizing the advantages and disadvantages of each spatial information data. Summary of the Invention [Problem to be solved by the invention]

[0008] The problem to be solved by the present invention is to provide a spatial information fusion solution providing device that can select an appropriate source of spatial information data according to the analysis required by the user, and fuse the spatial information data from each selected source to provide a solution of the level required by the user.

[0009] Specifically, the problem to be solved by the present invention is to provide a spatial information fusion solution providing device that can select appropriate spatial information data according to the user's analytical requirements by integrating and utilizing the advantages and disadvantages of the spatial information parameters possessed by each spatial information data, and by integrating them, can provide a new dimension of spatial information total solutions.

[0010] The objects of the present invention are not limited to the objects mentioned above, and other unmentioned objects and advantages of the present invention can be understood from the following description and will become more clearly understood by the embodiments of the present invention. Furthermore, it is easily apparent that the objects and advantages of the present invention can be realized by the means and combinations thereof set forth in the claims. [Means for solving the problem]

[0011] According to some embodiments of the present invention, a spatial information fusion solution providing device includes a data collection module that receives a plurality of spatial information data and user requested data, a selection module that selects necessary data necessary for generating the requested data from the plurality of spatial information data, a fusion module that fuses the necessary data to generate a spatial information fusion solution, and an output module that provides the spatial information fusion solution to a user terminal corresponding to the user, and the plurality of spatial information data may include at least one of CCTV data, drone data, GPS data, satellite photography data, and aerial data.

[0012] The satellite imaging data may include first satellite imaging data taken from a low-earth orbit satellite and second satellite imaging data taken from a geostationary orbit satellite.

[0013] The request data may also include solution type information related to the type of solution to be provided and priority information related to the priority of the spatial information parameters.

[0014] In addition, the solution type information may include any one of construction site danger notification, urban heat wave warning management, forest fire risk monitoring, and farmland condition monitoring.

[0015] The spatial information parameters may include at least one of resolution, acquisition cost, imaging area, and real-time performance, and the priority information may include the user's selection for at least one of the plurality of spatial information parameters.

[0016] In addition, when the solution type information is the construction site danger notification, the selection module selects the CCTV data, the drone data, and the GPS data as the required data, the fusion module determines a danger area in a predetermined area based on the drone data, and generates a danger notification as the spatial information fusion solution based on the CCTV data and the GPS data when a worker enters the danger area, and the output module can provide the danger notification to the user terminal corresponding to the worker.

[0017] In addition, when the priority information is acquisition cost, the selection module may select the second drone data as the necessary data from among first drone data captured in a first shooting cycle and second drone data captured in a second shooting cycle having a shooting cycle longer than the first shooting cycle.

[0018] In addition, when the solution type information is the urban extreme heat warning management, the data collection module further receives weather data including temperature information and humidity information, the selection module selects the satellite photography data and the GPS data as the necessary data, the fusion module determines the location-specific perceived temperature in a predetermined area based on the weather data and the satellite photography data, and generates an extreme heat notification for passersby as the spatial information fusion solution based on the location-specific perceived temperature and the GPS data, and the output module provides the extreme heat notification to the user terminal corresponding to the passersby, and the extreme heat notification may include at least one of a notification regarding areas where extreme heat is expected and a notification regarding areas where evacuation is possible.

[0019] In addition, when the solution type information is wildfire risk monitoring, the selection module selects the drone data and the satellite photography data as the required data, the fusion module generates wildfire parameters by inputting the drone data and the satellite photography data into a pre-trained wildfire management algorithm, and determines the generated wildfire parameters as the spatial information fusion solution, and the output module provides the wildfire parameters to the user terminal, and the wildfire parameters may include at least one of a wildfire damage area and a wildfire spread rate.

[0020] In addition, when the solution type information is the farmland condition monitoring, the selection module selects the first satellite photography data and the second satellite photography data as the required data, the fusion module combines the first satellite photography data and the second satellite photography data to determine a Normalized Difference Vegetation Index (NDVI), and determines the determined NDVI as the spatial information fusion solution, and the output module provides the NDVI to the user terminal. [Effects of the Invention]

[0021] The spatial information fusion solution providing device according to some embodiments of the present invention has the novel effect of being able to provide a solution of the level required by the user by selecting an appropriate source of spatial information data according to the analysis required by the user and fusing the spatial information data from each selected source.

[0022] Specifically, the spatial information fusion solution providing device according to some embodiments of the present invention can select appropriate spatial information data according to the user's analytical requirements by integrating and utilizing the advantages and disadvantages of the spatial information parameters of each spatial information data, and by integrating them, can provide a new dimension of spatial information total solutions.

[0023] That is, each spatial information data has its own spatial information parameters (e.g., resolution, acquisition cost, shooting area, real-timeness, etc.), and accordingly each spatial information data has its own advantages and disadvantages. However, the spatial information fusion solution providing device according to some embodiments of the present invention can ensure the completeness of the user's requirements and solutions by integrating and utilizing the advantages and disadvantages of each spatial information data.

[0024] The above-mentioned contents and specific effects of some embodiments of the present invention will be described together with the following detailed description of the implementation of the invention. [Brief explanation of the drawings]

[0025] [Figure 1] 1 illustrates a spatial information fusion solution providing system according to some embodiments of the present invention. [Figure 2] 1 is a block diagram of a spatial information fusion solution providing apparatus according to some embodiments of the present invention; [Figure 3A] FIG. 2 is a diagram illustrating spatial information data according to some embodiments of the present invention. [Figure 3B] FIG. 2 is a diagram illustrating spatial information data according to some embodiments of the present invention. [Figure 3C] FIG. 2 is a diagram illustrating spatial information data according to some embodiments of the present invention. [Figure 4] FIG. 10 is a diagram illustrating request data according to some embodiments of the present invention. [Figure 5A] 10 is a diagram illustrating a process of providing a spatial information fusion solution when the solution type information is a construction site danger notification. [Figure 5B] 10 is a diagram illustrating a process of providing a spatial information fusion solution when the solution type information is a construction site danger notification. [Figure 6A]10 is a diagram illustrating a process of providing a spatial information fusion solution when the solution type information is urban heat wave warning management. [Figure 6B] 10 is a diagram illustrating a process of providing a spatial information fusion solution when the solution type information is urban heat wave warning management. [Figure 7A] 10 is a diagram illustrating a process of providing a spatial information fusion solution when the solution type information is forest fire risk monitoring. [Figure 7B] 10 is a diagram illustrating a process of providing a spatial information fusion solution when the solution type information is forest fire risk monitoring. [Figure 8A] 10 is a diagram illustrating a process of providing a spatial information fusion solution when solution type information is farmland condition monitoring. [Figure 8B] 10 is a diagram illustrating a process of providing a spatial information fusion solution when solution type information is farmland condition monitoring. DETAILED DESCRIPTION OF THE INVENTION

[0026] The terms and words used in this specification and claims should not be interpreted as being limited to their general or dictionary meanings. They should be interpreted in a way that is consistent with the technical idea of ​​the present invention, based on the principle that the inventors themselves can define the concepts of terms and words to best describe the invention. Furthermore, the embodiments described in this specification and the configurations shown in the drawings are merely one embodiment for realizing the present invention and do not represent the entire technical idea of ​​the present invention. It should be understood that at the time of this application, there may be various equivalents, modifications, and applicable examples that replace them.

[0027] Terms such as "first," "second," "A," and "B" used in this specification and claims may be used to describe various components, but the components should not be limited by these terms. These terms are used only to distinguish one component from another. For example, a first component may be designated a second component, and similarly, a second component may be designated a first component, without departing from the scope of the present invention.

[0028] The terms used in the present specification and claims are merely used to describe specific embodiments and are not intended to limit the present invention. The singular expressions include the plural expressions unless the context clearly indicates otherwise. In this application, terms such as "comprise" or "have" should be understood as not precluding the possibility of the presence or addition of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification.

[0029] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0030] Terms defined in commonly used dictionaries should be interpreted to have a meaning consistent with the contextual meaning of the relevant art, and should not be interpreted in an idealized or overly formal sense unless expressly defined in this application.

[0031] Furthermore, the configurations, processes, steps, or methods included in the embodiments of the present invention may be shared within the scope of not being technically inconsistent with each other.

[0032] Hereinafter, an apparatus for providing a spatial information fusion solution according to some embodiments of the present invention will be described with reference to FIGS. 1 to 8B.

[0033] FIG. 1 is a diagram illustrating a spatial information fusion solution providing system according to some embodiments of the present invention.

[0034] Referring to FIG. 1, a spatial information fusion solution providing system 1 according to some embodiments of the present invention may include a user terminal 100, an external database 200, a spatial information fusion solution providing device (300, hereinafter referred to as the “device”), and a communication network 400.

[0035] The user terminal 100 is a terminal related to a user who requests a spatial information fusion solution from the device 300 .

[0036] In some examples, the user terminal 100 transmits request data to the device 300. In other words, the user terminal 100 transmits request data, which is data requesting the device 300 for a spatial information fusion solution.

[0037] In this case, the request data may include solution type information and priority information, although the embodiment of the present invention is not limited thereto, and the priority information may be omitted from the request data.

[0038] The solution type information may be information related to the type of solution that the user wishes to receive. For example, the solution type information may include construction site danger notification, urban heat wave warning management, wildfire risk monitoring, farmland condition monitoring, etc. That is, the solution type information may include a user's selection of any one of construction site danger notification, urban heat wave warning management, wildfire risk monitoring, and farmland condition monitoring. However, the present invention is not limited thereto.

[0039] The priority information may include information related to the priority of a plurality of spatial information parameters for the spatial information data. In this case, the spatial information parameters may include resolution, acquisition cost, imaging area, real-time performance, etc. That is, the priority information may include a selection of a spatial information parameter that a user preferentially considers among a plurality of spatial information parameters. In other words, the priority information may include a user selection of at least one of resolution, acquisition cost, imaging area, and real-time performance. However, embodiments of the present invention are not limited thereto, and examples of spatial information parameters may be freely changed and implemented.

[0040] The user terminal 100 may be in the form of various electronic devices such as a smartphone, a computer, a notebook computer (PC), a wearable device, a workstation, a data center, an internet data center (IDC), a DAS (direct attached storage) system, a SAN (storage area network) system, a NAS (network attached storage) system, and a RAID (redundant array of inexpensive disks, or redundant array of independent disks) system, but embodiments of the present invention are not limited thereto.

[0041] The external database 200 may be a database that stores, manages, and / or transmits a plurality of spatial information data that is the basis for providing a spatial information fusion solution.

[0042] In some examples, spatial information data may include CCTV data, drone data, GPS data, satellite imagery data, aerial data, etc., although embodiments of the present invention are not limited thereto.

[0043] CCTV data may include images, videos, and other data captured by CCTV cameras installed in buildings, roads, and the like.

[0044] The drone data may include images, videos, and other data captured by a camera attached to a drone. In this case, the drone may include a ground drone, an aerial drone, an underwater drone, and the like, but the type of drone is not limited thereto.

[0045] The GPS data may include data collected via a Global Positioning System (GPS). The GPS system may receive signals from satellites and provide information about the location of a GPS receiver. As an example, the GPS data may include information about the current location of each user terminal 100, although embodiments of the present invention are not limited thereto.

[0046] The satellite imaging data may include data captured by a satellite located at a predetermined height above the ground. In this case, the satellite may include a geostationary orbit satellite located in a relatively high orbit and a low-orbit satellite located in a relatively low orbit. In other words, the satellite imaging data may include first satellite imaging data captured by a geostationary orbit satellite and second satellite imaging data captured by a low-orbit satellite. In this case, the types of satellite imaging data may include visible light images, multispectral images, etc.

[0047] The aerial data may include data such as images and videos taken by a camera mounted on an aircraft flying at a predetermined height (e.g., 2000 m to 4000 m) above the ground. In this case, the camera mounted on the aircraft may include a digital camera for aerial photography, but the embodiment of the present invention is not limited thereto.

[0048] The external database 200 may be in the form of various types of electronic devices such as a computer, a laptop, a mobile device, a wearable device, a workstation, a data center, an internet data center (IDC), a DAS (direct attached storage) system, a SAN (storage area network) system, a NAS (network attached storage) system, and a RAID (redundant array of inexpensive disks, or redundant array of independent disks) system, but the embodiment of the present invention is not limited thereto.

[0049] The device 300 generates a spatial information fusion solution based on the spatial information data and the request data, and provides the generated spatial information fusion solution to the user terminal 100.

[0050] In some examples, the device 300 may select necessary data necessary for generating the requested data from among the plurality of spatial information data, and then fuse the selected necessary data to generate a spatial information fusion solution. A specific process by which the device 300 generates a spatial information fusion solution will be described later.

[0051] By way of example, the device 300 may be in the form of a workstation, a data center, an internet data center (IDC), a direct attached storage (DAS) system, a storage area network (SAN) system, a network attached storage (NAS) system, a redundant array of inexpensive disks, or redundant array of independent disks (RAID) system, or the like, but embodiments of the present invention are not limited thereto.

[0052] The communication network 400 serves to connect the user terminal 100 and the external database 200 to the device 300. In other words, the communication network 400 refers to a communication network that provides a connection path so that the device 300 can send and receive data from the user terminal 100 and the external database 200. The communication network 400 may include, for example, wired networks such as LANs (Local Area Networks), WANs (Wide Area Networks), MANs (Metro Area Networks), and ISDNs (Integrated Service Digital Networks), and wireless networks such as wireless LANs, CDMA, Bluetooth, and satellite communications, but the scope of the present invention is not limited thereto.

[0053] The operation of the device 300 will now be described in more detail with reference to FIG.

[0054] FIG. 2 is a block diagram of an apparatus for providing a spatial information fusion solution according to some embodiments of the present invention.

[0055] 1 and 2, the device 300 is a device that provides a spatial information confusion solution (hereinafter referred to as "SICS") based on spatial information data (hereinafter referred to as "SID") and requirement data (hereinafter referred to as "RD"), and specifically may include a data collection module 310, a selection module 320, a fusion module 330, and an output module 340. However, embodiments of the present invention are not limited thereto, and according to some embodiments, the device 300 according to some embodiments of the present invention may omit some components or may add other components not shown.

[0056] The data collection module 310 receives the spatial information data SID and the request data RD. In other words, the data collection module 310 can receive the request data RD from the user terminal 100 and can receive the spatial information data SID from the external database 200. However, the embodiment of the present invention is not limited thereto, and the spatial information data SID can be stored in advance in a database module within the device 300. For convenience of explanation, the following description will be given assuming that the data collection module 310 receives the spatial information data SID from the external database 200.

[0057] Spatial information data SID refers to data collected about a specific point or area based on the geographic location (e.g., height, angle, etc.) of a data collector (e.g., CCTV, drone, satellite, aircraft, etc.). In some examples, spatial information data SID may include CCTV data, drone data, GPS data, satellite photography data, aerial data, etc. However, embodiments of the present invention are not limited thereto.

[0058] The request data RD may include solution type information and priority information. However, the embodiment of the present invention is not limited thereto, and the priority information may be omitted from the request data RD. The solution type information may be information related to the type of solution that the user wishes to receive. The priority information may include information related to the priority of a plurality of spatial information parameters corresponding to the spatial information data SID.

[0059] Hereinafter, spatial information data SID according to some embodiments of the present invention will be described with reference to FIGS. 3A to 3C, and request data RD according to some embodiments of the present invention will be described with reference to FIG.

[0060] 3A to 3C are diagrams illustrating spatial information data according to some embodiments of the present invention. Specifically, FIG. 3A is a diagram illustrating an example of spatial information data, FIG. 3B is a diagram illustrating an example of spatial information parameters, and FIG. 3C is a diagram illustrating an exemplary relationship between the spatial information data and the spatial information parameters.

[0061] 3A to 3C, the spatial information data SID may include CCTV data SID1, drone data SID2, GPS data SID3, satellite photography data SID4, and aerial data SID5. However, the embodiment of the present invention is not limited thereto, and it goes without saying that the spatial information data SID may include more types of examples.

[0062] The CCTV data SID1 may include data such as images and videos taken from CCTVs installed in buildings, roads, etc. In other words, the CCTV data SID1 may include visual information monitored and recorded via CCTVs installed in specific buildings, roads, etc.

[0063] The drone data SID2 may include data such as images and videos captured by a camera attached to a drone. In this case, the drone may include a ground drone, an aerial drone, an underwater drone, etc., but the type of drone is not limited thereto. In this case, navigation control of the drone that collects the drone data SID2 may be performed by the device (300 in FIGS. 1 and 2) itself or its administrator.

[0064] The GPS data SID3 may include data collected via a GPS system. The GPS system may receive signals from satellites and provide information about the location of a GPS receiver. In other words, the GPS data SID3 may include data indicating the geographic location of each device collected via GPS satellite signals. As an example, the GPS data SID3 may include information about the current location of each user terminal (100 in FIG. 1), but the embodiment of the present invention is not limited thereto. In this case, the GPS data SID3 may not be classified as spatial information data SID but may be defined as separate data.

[0065] The satellite image data SID4 may include data captured by a satellite located at a predetermined height above the ground. In this case, the satellite may include a geostationary satellite located in a relatively high orbit and a low-earth orbit satellite located in a relatively low orbit. In other words, the satellite image data SID4 may include first satellite image data SID4_1 captured by a geostationary satellite and second satellite image data SID4_2 captured by a low-earth orbit satellite. In this case, the types of satellite image data SID4 may include visible light images, multispectral images, radar images, etc.

[0066] The aerial data SID5 may include data such as images and videos taken by a camera mounted on an aircraft flying at a predetermined height (e.g., 2000 m to 4000 m) above the ground. In this case, the camera mounted on the aircraft may include a digital camera for aerial photography, but the embodiment of the present invention is not limited thereto.

[0067] Each of the plurality of spatial information data SID1 to SID5 can have a spatial information parameter (hereinafter referred to as "SIPA"). In other words, each of the CCTV data SID1, the drone data SID2, the GPS data SID3, the satellite photography data SID4, and the aeronautical data SID5 can have a unique value of the spatial information parameter SIPA.

[0068] In this case, the spatial information parameter SIPA means data characteristics corresponding to each of the spatial information data SID1 to SID5. In other words, the spatial information parameter SIPA may include an index that quantifies the attribute of each of the spatial information data SID1 to SID5.

[0069] 3B and 3C, in some examples, the spatial information parameters SIPA may include a resolution SIPA1, an acquisition cost SIPA2, a shooting area SIPA3, and real-time performance SIPA4. However, the embodiments of the present invention are not limited thereto, and it goes without saying that the spatial information parameters SIPA may include many more types of examples.

[0070] The resolution SIPA1 refers to the smallest size of an object observed in the spatial information data SID or the smallest spatial distance that can be distinguished on the spatial information data SID. The higher the resolution SIPA1, the smaller objects and details can be distinguished.

[0071] Acquisition cost SIPA2 refers to the cost required to acquire the corresponding spatial information data SID. In this case, acquisition cost SIPA2 may include all costs such as the purchase, operation, and maintenance of data collection entities (e.g., CCTV, drones, satellites, etc.) and the costs incurred in the process of acquiring the corresponding spatial information data SID. The higher the acquisition cost SIPA2, the higher the cost incurred in using the corresponding spatial information data SID.

[0072] The photographing area SIPA3 means a geographical range or area that can be covered by the spatial information data SID. The larger the photographing area SIPA3, the larger the area that the corresponding spatial information data SID covers.

[0073] The real-time property SIPA4 means the time it takes for spatial information data SID to be collected and provided to the user terminal (100 in FIG. 1). The higher the real-time property SIPA4, the smaller the delay that occurs when providing data to the user terminal (100 in FIG. 1).

[0074] In this case, as shown in Figure 3C, the spatial information parameter SIPA of the spatial information data SID is quantified in advance within a general range. For example, drone data SID2 acquired by a drone has a relatively high resolution SIPA1 and acquisition cost SIPA2, but a low image area SIPA3 and real-time performance SIPA4. In contrast, first satellite image data SID4_1 acquired by a low-earth-orbit satellite has average values ​​for resolution SIPA1, acquisition cost SIPA2, image area SIPA3, and real-time performance SIPA4. In contrast, second satellite image data SID4_2 acquired by a geostationary-orbit satellite has a relatively low resolution SIPA1 and acquisition cost SIPA2, but a high image area SIPA3 and real-time performance SIPA4.

[0075] The apparatus (300 in FIGS. 1 and 2) of the present invention provides a spatial information fusion solution SICS by taking into consideration the characteristics of the spatial information parameter SIPA of each of the spatial information data SID1 to SID5. This provides a novel effect of selecting an appropriate source of spatial information data SID according to the analysis requested by the user and fusing the spatial information data SID from each selected source to provide a solution at a level desired by the user. Specifically, the apparatus (300 in FIGS. 1 and 2) combines and utilizes the advantages and disadvantages of the spatial information parameter SIPA of each of the spatial information data SID, thereby selecting appropriate spatial information data SID according to the level of analysis requested by the user, and fusing them to provide a spatial information total solution of a new dimension. That is, each spatial information data SID has its own unique spatial information parameter SIPA, and therefore each spatial information data SID has its own unique advantages and disadvantages. However, the apparatus (300) of the present invention combines and utilizes the advantages and disadvantages of each of the spatial information data SID to ensure the completeness of both the user's requirements and the solution.

[0076] FIG. 4 is a diagram illustrating request data according to some embodiments of the present invention.

[0077] 3A to 4, the request data RD may include solution type information (hereinafter referred to as "STI") and priority information (hereinafter referred to as "PI"). However, the embodiment of the present invention is not limited thereto, and the priority information PI may be omitted from the request data RD.

[0078] The solution type information STI may be information related to the type of solution that the user wishes to receive. For example, the solution type information STI may include construction site danger notification, urban heat wave warning management, wildfire risk monitoring, farmland condition monitoring, etc. That is, the solution type information STI may include a user's selection of any one of construction site danger notification, urban heat wave warning management, wildfire risk monitoring, and farmland condition monitoring. However, the embodiment of the present invention is not limited thereto.

[0079] The priority information PI may include information related to the priority of the plurality of spatial information parameters SIPA for the spatial information data SID. That is, the priority information PI may include a selection of a spatial information parameter SIPA that the user intends to prioritize among the plurality of spatial information parameters SIPA. In other words, the priority information PI may include a user's selection of at least one of the resolution SIPA1, the acquisition cost SIPA2, the photographing area SIPA3, and the real-time performance SIPA4.

[0080] 1 and 2, the data collection module 310 transmits the received spatial information data SID and request data RD to other components within the device 300. For example, the data collection module 310 may transmit the spatial information data SID and request data RD to the selection module 320, but the present invention is not limited thereto. The data collection module 310 uses various communication modules to exchange data between the user terminal 100 and the external database 200 and the device 300 via the communication network 400.

[0081] The selection module 320 selects needed data (hereinafter referred to as "ND") based on the spatial information data SID and the request data RD.

[0082] In some examples, the selection module 320 selects, from the plurality of spatial information data SID, the necessary data ND required for generating the request data RD. In other words, the necessary data ND may include data selected from the plurality of spatial information data SID as data required for generating the request data RD. For example, the selection module 320 may select at least one of the plurality of spatial information data SID based on the solution type information STI and the priority information PI included in the request data RD.

[0083] The fusion module 330 fuses the necessary data ND to generate the spatial information fusion solution SICS. For example, the fusion module 330 combines the necessary data ND according to a predefined scheme to generate the spatial information fusion solution SICS.

[0084] The output module 340 provides the generated spatial information fusion solution SICS to the user terminal 100. In other words, the output module 340 transmits the spatial information fusion solution SICS generated from the fusion module 330 to the user terminal 100.

[0085] Hereinafter, the process of selecting necessary data ND by the selection module 320 according to the solution type information STI and the priority information PI and the process of generating a spatial information fusion solution SICS by the fusion module 330 will be described with reference to FIGS. 5A to 8B.

[0086] 5A and 5B are diagrams illustrating a process of providing a spatial information fusion solution when the solution type information is a construction site danger notification. Specifically, Fig. 5A illustrates a case where the solution type information is a construction site danger notification and priority information is not set, and Fig. 5B illustrates a case where the solution type information is a construction site danger notification and priority information is set.

[0087] Referring to Figures 3A to 3C, 4 and 5A, if the solution type information STI included in the request data RD is a construction site hazard notification STI1, the fusion module 330 generates a hazard notification (hereinafter referred to as "HN") as the spatial information fusion solution SICS, and the output module 340 outputs the generated hazard notification HN.

[0088] Specifically, first, when the solution type information STI is construction site danger notification STI1, the selection module 320 selects CCTV data SID1, drone data SID2, and GPS data SID3 as the required data ND from the plurality of spatial information data SID1 to SID5. That is, when the type of solution the user wishes to receive is construction site danger notification STI1, the selection module 320 can select CCTV data SID1, drone data SID2, and GPS data SID3 from the plurality of spatial information data SID1 to SID5 and determine them as the required data ND.

[0089] Next, the fusion module 330 generates a danger notification HN based on the CCTV data SID1, the drone data SID2 and the GPS data SID3 selected as the required data ND.

[0090] More specifically, the fusion module 330 first determines a dangerous area within a predetermined area (construction site area) based on the drone data SID2. For example, the fusion module 330 may recognize a dangerous object from the drone data SID2 using a predetermined object recognition algorithm and then determine an area a predetermined distance away from the dangerous object as the dangerous area. In this case, the dangerous object may include a tower crane, rebar, a sedimentation basin, etc., and the object recognition algorithm may be an algorithm pre-trained to recognize a dangerous object from the drone data SID2 when the drone data SID2 is input. For example, the object recognition algorithm may be an algorithm based on a Single Shot Multibox Detector (SSD) algorithm, a You Only Look Once (YOLO) algorithm, etc., but the present invention is not limited thereto. Next, the fusion module 330 generates a danger notification (HN) when a worker located in the construction site area enters the dangerous area based on the CCTV data SID1 and the GPS data SID3. As an example, the fusion module 330 confirms that a worker is entering a corresponding danger area on the CCTV data SID1, and if the GPS data SID3 of each worker's user terminal (100 in Figure 1) is also included within the danger area, it generates a danger notification HN.

[0091] Next, the output module 340 outputs the generated danger notification HN to the user terminal (100 in FIG. 1) of the worker.

[0092] 3A to 3C, 4, 5A and 5B, when the solution type information STI included in the request data RD is construction site danger notification STI1 and the priority information PI is acquisition cost SIPA2, the selection module 320 can select any one of the drone data SID2.

[0093] That is, the drone data SID2 may include first drone data SID2_1 captured in a first shooting cycle and second drone data SID2_2 captured in a second shooting cycle having a shooting cycle longer than the first shooting cycle.

[0094] In this case, when the priority information PI is the acquisition cost SIPA2, the selection module 320 can select the drone data SID2 as the required data ND, and select the second drone data SID2, which has a longer shooting period, from the first drone data SID2_1 and the second drone data SID2_2.

[0095] In other words, if a user places priority on the acquisition cost SIPA2, they will want to be provided with the spatial information fusion solution SICS at a low cost. In this case, by using the second drone data SID2_2 captured at a longer interval, the cost of generating the spatial information fusion solution SICS can be reduced, thereby better meeting the user's needs.

[0096] 6A and 6B are diagrams illustrating a process of providing a spatial information fusion solution when the solution type information is urban heat warning management. Specifically, Fig. 6A is a diagram illustrating a case where the solution type information is urban heat warning management and priority information is not set, and Fig. 6B is a diagram illustrating a case where the solution type information is urban heat warning management and priority information is set.

[0097] Referring to Figures 3A to 3C, 4 and 6A, if the solution type information STI included in the request data RD is urban heat wave warning management STI2, the fusion module 330 generates a heat wave notification (hereinafter referred to as "HWN") as the spatial information fusion solution SICS, and the output module 340 outputs the generated heat wave notification HWN.

[0098] Specifically, when the solution type information STI is urban heatwave warning management STI2, the data collection module 310 can further receive weather data (hereinafter referred to as "WD") in addition to the spatial information data SID and request data RD. In this case, the weather data WD may include temperature information and humidity information. As an example, the data collection module 310 can receive the weather data WD from a database (not shown) of the Japan Meteorological Agency, but the embodiment of the present invention is not limited thereto.

[0099] Next, when the solution type information STI is urban extreme heat warning management STI2, the selection module 320 selects the GPS data SID3 and the satellite image data SID4 as the required data ND from the plurality of spatial information data SID1 to SID5. That is, when the type of solution the user wishes to receive is urban extreme heat warning management STI2, the selection module 320 can select the GPS data SID3 and the satellite image data SID4 from the plurality of spatial information data SID1 to SID5 and determine them as the required data ND.

[0100] Next, the fusion module 330 generates a heat wave notification HWN based on the weather data WD and the GPS data SID3 and the satellite photography data SID4 selected as the required data ND.

[0101] More specifically, the fusion module 330 first determines the perceived temperature for each location in a predetermined area based on the weather data WD, GPS data SID3, and satellite image data SID4. In this case, the predetermined area may be the area where a pedestrian is located, as determined through the GPS data SID3. For example, the fusion module 330 extracts the ground surface temperature for the predetermined area from the satellite image data SID4 and inputs the extracted ground surface temperature and the temperature and humidity information included in the weather data WD into a predefined perceived temperature determination algorithm to determine the perceived temperature for each location. In this case, the perceived temperature determination algorithm may be pre-trained to output the perceived temperature using the ground surface temperature, temperature information, and humidity information as input values. In this case, the perceived temperature determination algorithm may output the perceived temperature by calculating and combining a heat index, wet bulb globe temperature (WBGT), universal thermal climate index (UTCI), etc., based on the ground surface temperature, temperature information, and humidity information. Next, the fusion module 330 generates an extreme heat notification HWN for pedestrians traveling along the road. In this case, the extreme heat notification HWN may include a notification regarding an area where extreme heat is predicted and a notification regarding an area where evacuation is possible. For example, the fusion module 330 may determine an area where the determined location-specific perceived temperature is the highest as an area where extreme heat is predicted and determine an area where the determined location-specific perceived temperature is the lowest as an area where evacuation is possible (e.g., trees, shade, lake, etc.), and generate a notification regarding the determined area where extreme heat is predicted and an area where evacuation is possible as the extreme heat notification HWN.

[0102] Next, the output module 340 outputs the generated extreme heat notification HWN to the user terminal (100 in FIG. 1) of the corresponding passerby.

[0103] 3A to 3C, 4, 6A and 6B, when the solution type information STI included in the request data RD is urban heatwave warning management STI2 and the priority information PI is resolution SIPA1, the selection module 320 can select one of the satellite image data SID4.

[0104] That is, the satellite image data SID4 may include first satellite image data SID4_1 having high resolution and photographed by a low-orbit satellite located in a relatively low orbit above the ground G, and second satellite image data SID4_2 having low resolution and photographed by a geostationary orbit satellite located in a relatively high orbit above the ground G. In this case, when the priority information PI is the resolution SIPA1, the selection module 320 can select the first satellite image data SID4_1 having higher resolution from the first satellite image data SID4_1 and the second satellite image data SID4_2 when selecting the satellite image data SID4 as the necessary data ND.

[0105] In other words, if a user places priority on the resolution SIPA1, they would like to be provided with a spatial information fusion solution SICS that can ensure high resolution. In this case, by using the first satellite image data SID4_1, which is taken at a higher resolution, the resolution of the spatial information fusion solution SICS can be improved, thereby further meeting the user's needs.

[0106] 7A and 7B are diagrams illustrating a process of providing a spatial information fusion solution when the solution type information is forest fire risk monitoring. Specifically, FIG. 7A is a diagram illustrating a case where the solution type information is forest fire risk monitoring and priority information is not set, and FIG. 7B is a diagram illustrating a case where the solution type information is forest fire risk monitoring and priority information is set.

[0107] Referring to Figures 3A to 3C, 4 and 7A, if the solution type information STI included in the request data RD is wildfire risk monitoring STI3, the fusion module 330 generates a wildfire parameter (hereinafter referred to as "WP") as the spatial information fusion solution SICS, and the output module 340 outputs the generated wildfire parameter WP.

[0108] Specifically, first, when the solution type information STI is wildfire risk monitoring STI3, the selection module 320 can select drone data SID2 and satellite photography data SID4 as required data ND from the plurality of spatial information data SID1 to SID5. That is, when the type of solution the user wants to receive is wildfire risk monitoring STI3, the selection module 320 can select drone data SID2 and satellite photography data SID4 from the plurality of spatial information data SID1 to SID5 and determine them as required data ND.

[0109] Next, the fusion module 330 generates a forest fire parameter WP based on the drone data SID2 and the satellite image data SID4 selected as the required data ND.

[0110] More specifically, the fusion module 330 can generate the wildfire parameter WP by inputting the drone data SID2 and the satellite image data SID4 into a pre-trained wildfire management algorithm. In this case, the wildfire parameter WP may include the wildfire damage area and the wildfire spread rate, and the wildfire management algorithm can be pre-trained to combine the drone data SID2 and the satellite image data SID4 when the drone data SID2 and the satellite image data SID4 are input and output the wildfire parameter WP. As an example, the wildfire management algorithm may include an algorithm based on FireNet, Deepfire, ForestNet, Wildfire Detection and Prediction System using CNNs (WDPS-CNN), etc., but the embodiment of the present invention is not limited thereto.

[0111] Next, the output module 340 outputs the generated forest fire parameters WP to the user terminal of the forest fire manager (100 in FIG. 1).

[0112] 3A to 3C, 4, 7A, and 7B, when the solution type information STI included in the request data RD is wildfire risk monitoring STI3 and the priority information PI is real-time SIPA4, the data collection module 310 can further receive early detection data (EDD) in addition to the spatial information data SID and the request data RD. In this case, the early detection data EDD can include smoke data and sound data. The smoke data can include data related to the quantity of smoke generated by a wildfire and can be acquired by a smoke sensor installed in the area where a wildfire is predicted to occur. The sound data can include data detecting noise generated by a wildfire and can be acquired by a sound sensor installed in the area where a wildfire is predicted to occur. In this case, the data collection module 310 can receive smoke data and sound data from the smoke sensor and sound sensor, respectively.

[0113] The data collection module 310 then communicates the received initial sensed data EDD to the fusion module 330 .

[0114] Next, the fusion module 330 transmits a control signal (hereinafter referred to as "CS") to the data collection module 310 regarding whether to determine the forest fire parameter WP based on the received initial sensing data EDD.

[0115] For example, the fusion module 330 may determine a wildfire likelihood index based on the initial detection data EDD, and if the determined wildfire likelihood index exceeds a predetermined critical value, transmit a first control signal CS1 to the data collection module 310 to instruct the data collection module 310 to generate a wildfire parameter WP. Conversely, if the determined wildfire likelihood index is equal to or less than the predetermined critical value, transmit a second control signal CS2 to the data collection module 310 to instruct the data collection module 310 not to generate the wildfire parameter WP. In this case, the fusion module 330 may extract features from the smoke data and sound data and then combine the extracted features to determine the wildfire likelihood index. For example, the fusion module 330 may extract smoke density and smoke color from the smoke data and extract amplitude in a predetermined frequency range (e.g., 500 Hz to 2,000 Hz) associated with the occurrence of a wildfire from the sound data. In this case, the fusion module 330 can output a wildfire likelihood index by inputting the extracted smoke density, smoke color, and amplitude in a specific frequency range into a pre-trained early detection algorithm. The early detection algorithm can be pre-trained to output a wildfire likelihood index when each feature (smoke density, smoke color, and amplitude in a specific frequency range) is input. As an example, the early detection algorithm may include an algorithm based on an algorithm such as FireDetectNet or WildFirePredector, but the embodiment of the present invention is not limited thereto.

[0116] Next, when the data collection module 310 receives a first control signal CS1, it can transmit spatial information data SID and request data RD to the selection module 320 so that the wildfire parameter WP is generated as the spatial information fusion solution SICS, and conversely, when it receives a second control signal CS2, it can prevent the spatial information fusion solution SICS from being generated by not transmitting the spatial information data SID and request data RD to the selection module 320.

[0117] In other words, if a user prioritizes real-time SIPA4, they will judge the possibility of a wildfire at very short intervals, but using drone data SID2 and satellite image data SID4 every time will incur excessive costs and may result in misjudgments. Therefore, in this case, performing early detection using early detection data EDD has the new effect of preventing server overload and reducing costs.

[0118] 8A and 8B are diagrams illustrating a process of providing a spatial information fusion solution when the solution type information is farmland status monitoring. Specifically, Fig. 8A is a diagram illustrating a case where the solution type information is farmland status monitoring and priority information is not set, and Fig. 8B is a diagram illustrating a case where the solution type information is farmland status monitoring and priority information is set.

[0119] Referring to Figures 3A to 3C, 4 and 8A, if the solution type information STI included in the request data RD is farmland condition monitoring STI4, the fusion module 330 generates a Normalized Difference Vegetation Index (hereinafter referred to as "NDVI") as the spatial information fusion solution SICS, and the output module 340 outputs the generated Normalized Difference Vegetation Index NDVI.

[0120] Specifically, first, when the solution type information STI is farmland condition monitoring STI4, the selection module 320 can select the first satellite image data SID4_1 and the second satellite image data SID4_2 as the required data ND from the plurality of spatial information data SID1 to SID5. That is, when the type of solution the user wants to receive is farmland condition monitoring STI4, the selection module 320 can select the first satellite image data SID4_1 and the second satellite image data SID4_2 from the plurality of spatial information data SID1 to SID5 and determine them as the required data ND.

[0121] Next, the fusion module 330 generates a normalized difference vegetation index (NDVI) based on the first satellite image data SID4_1 and the second satellite image data SID4_2 selected as the necessary data ND. As an example, the fusion module 330 may generate a normalized difference vegetation index (NDVI) by combining the first satellite image data SID4_1 and the second satellite image data SID4_2.

[0122] More specifically, the fusion module 330 may perform image alignment to adjust temporal and spatial differences between the first satellite image data SID4_1 and the second satellite image data SID4_2, and then generate the Normalized Difference Vegetation Index (NDVI) based on a predefined relational expression. An example of the predefined relational expression is shown in Equation 1 below.

[0123]

number

[0124] In the above-mentioned formula 1, NDVI means the normalized difference vegetation index, NIR means the near-infrared band value, and Red means the red band value included in the visible band value.

[0125] Next, the output module 340 outputs the generated Normalized Difference Vegetation Index NDVI to the user terminal (100 in FIG. 1) corresponding to the manager of the farmland.

[0126] 3A to 3C, 4, 8A and 8B, when the solution type information STI included in the request data RD is farmland condition monitoring STI4 and the priority information PI is resolution SIPA1, the selection module 320 can further select drone data SID2 in addition to the above-mentioned first satellite photography data SID4_1 and second satellite photography data SID4_2.

[0127] Next, the fusion module 330 determines an area where the Normalized Difference Vegetation Index (NDVI) is below a predetermined threshold value as a degraded area. In this case, the fusion module 330 may determine a pest infestation index (PII) for the degraded area using drone data SID2 captured by the drone. In this case, the fusion module 330 may determine the pest infestation index (PII) for the degraded area by inputting the drone data SID2 into a pre-trained discoloration determination algorithm. In this case, the discoloration determination algorithm may be pre-trained to, when the drone data SID2 is input, identify a pattern indicating damage caused by pests or the like from the drone data SID2, and then determine the pest infestation index (PII) based on the quantification of the identified pattern. For example, the discoloration determination algorithm may be based on an algorithm such as PlantCV, LeafNet, or PestID, but the present invention is not limited thereto.

[0128] Next, the fusion module 330 generates the normalized difference vegetation index NDVI and the pest infestation index PII for the poor areas as the spatial information fusion solution SICS, and the output module 340 outputs the normalized difference vegetation index NDVI and the pest infestation index PII to the user terminal (100 in Figure 1) corresponding to the manager of the relevant agricultural land.

[0129] The above description is an illustrative example of the technical concept of the present embodiment, and various modifications and variations are possible within the scope of the essential characteristics of the present embodiment, as long as they do not deviate from the essential characteristics of the present embodiment. Therefore, the present embodiment is intended to illustrate, not limit, the technical concept of the present embodiment, and the scope of the technical concept of the present embodiment is not limited by the above embodiment. The scope of protection of the present embodiment should be interpreted by the following claims, and all technical concepts within the scope equivalent thereto should be interpreted as being included in the scope of rights of the present embodiment.

Claims

1. a data collection module that receives a plurality of spatial information data and user request data; a selection module that selects necessary data required for generating the request data from the plurality of spatial information data; a fusion module that fuses the necessary data to generate a spatial information fusion solution; and an output module for providing the spatial information fusion solution to a user terminal corresponding to the user; The spatial information fusion solution providing device, wherein the plurality of spatial information data includes at least one of CCTV data, drone data, GPS data, satellite photography data, and aeronautical data.

2. The satellite photography data The spatial information fusion solution providing device according to claim 1 , comprising first satellite photography data taken from a low-earth orbit satellite and second satellite photography data taken from a geostationary orbit satellite.

3. The request data is The spatial information fusion solution providing device according to claim 2 , further comprising solution type information relating to the type of solution to be provided and priority information relating to the priority of spatial information parameters.

4. The spatial information fusion solution providing device of claim 3 , wherein the solution type information includes any one of construction site danger notification, urban heat wave warning management, forest fire risk monitoring, and farmland condition monitoring.

5. the spatial information parameters include at least one of resolution, acquisition cost, imaging area, and real-time performance; The spatial information fusion solution providing apparatus according to claim 4 , wherein the priority information includes the user's selection of at least one of the plurality of spatial information parameters.

6. When the solution type information is the construction site danger notification, the selection module selects the CCTV data, the drone data, and the GPS data as the required data; The fusion module determines a danger area in a predetermined area based on the drone data, and generates a danger notification as the spatial information fusion solution when a worker enters the danger area based on the CCTV data and the GPS data; The spatial information fusion solution providing device according to claim 5 , wherein the output module provides the danger notification to the user terminal corresponding to the worker.

7. If the priority information is acquisition cost, 7. The spatial information fusion solution providing device of claim 6, wherein the selection module selects the second drone data as the necessary data from among first drone data captured at a first shooting period and second drone data captured at a second shooting period having a shooting period longer than the first shooting period.

8. When the solution type information is urban heat wave warning management, the data collection module further receives weather data including temperature information and humidity information; the selection module selects the satellite image data and the GPS data as the required data; The fusion module determines a location-specific perceived temperature in a predetermined area based on the meteorological data and the satellite photography data, and generates an extreme heat notification as the spatial information fusion solution for passersby based on the location-specific perceived temperature and the GPS data; The output module provides the extreme heat notification to the user terminal corresponding to the passerby; The spatial information fusion solution providing device according to claim 5 , wherein the notification of extreme heat includes at least one of a notification regarding an area where extreme heat is predicted and a notification regarding an area where evacuation is possible.

9. When the solution type information is the wildfire risk monitoring, the selection module selects the drone data and the satellite photography data as the necessary data; The fusion module generates wildfire parameters by inputting the drone data and the satellite image data into a pre-trained wildfire management algorithm, and determines the generated wildfire parameters as the spatial information fusion solution; the output module provides the wildfire parameters to the user terminal; The spatial information fusion solution providing device according to claim 5 , wherein the forest fire parameters include at least one of a forest fire damage area and a forest fire spreading speed.

10. When the solution type information is farmland condition monitoring, the selection module selects the first satellite photography data and the second satellite photography data as the necessary data; the fusion module combines the first satellite image data and the second satellite image data to determine a Normalized Difference Vegetation Index (NDVI), and determines the determined NDVI as the spatial information fusion solution; The spatial information fusion solution providing device according to claim 5 , wherein the output module provides the normalized difference vegetation index to the user terminal.

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