Electronic device, information conversion method, and method for training neural network model using training data generated by information conversion method

Abstract

An information conversion method performed by an electronic device is disclosed. The method comprises the following steps: acquiring a moving track and radio environment information based on a set coordinate system; acquiring absolute coordinate system data of the interest point corresponding to the moving track; and converting the radio environment information based on the set coordinate system into radio environment information based on an absolute coordinate system by using the absolute coordinate system data of the point of interest.

Description

Technical Field

[0001] The present invention relates to an electronic device and an information conversion method performed by the electronic device. Background Art

[0002] In a positioning method based on a radio environment, a fingerprint positioning method is a pattern recognition technique that measures the wireless received signal strength at a plurality of pre-known reference positions to generate a radio environment map, and then determines a reference position in the radio environment map that has the most similar signal strength characteristics relative to the signal strength received at the positioning position as the positioning position. As the interval between reference positions becomes smaller, the fingerprint positioning method achieves higher accuracy, and as the number of wireless signal transmission sources increases, higher accuracy is also achieved.

[0003] However, in a wireless signal shadow area, it may not be possible to generate a radio environment map or the reliability of the generated radio environment map may not be high, which leads to positioning difficulties.

[0004] Recently, the positioning performance has also been improved through deep learning techniques, which use training data composed of Global Positioning System (GPS) information and radio environment information as an absolute coordinate system to train an artificial neural network model, and use the pre-trained artificial neural network model to derive a positioning result.

[0005] However, in a GPS shadow area such as an underground shopping mall, wireless signals may be received from indoor wireless APs, but GPS information, that is, absolute coordinate system information, may not be received, which makes it difficult to collect training data for training the artificial neural network model. Summary of the Invention

[0006] Technical Problem

[0007] According to an embodiment, the present invention provides an electronic device and an information conversion method for converting radio environment information based on a set coordinate system that can be obtained without being restricted by a position such as a GPS shadow area into radio environment information based on an absolute coordinate system.

[0008] However, the problems to be solved by the present disclosure are not limited to the above problems, and other problems to be solved that are not mentioned can be clearly understood by those of ordinary skill in the art to which the present disclosure pertains from the following description.

[0009] Technical Solution

[0010] According to a first aspect of a method for converting information performed by an electronic device, the method includes the following steps: obtaining a movement trajectory based on a set coordinate system and radio environment information based on the set coordinate system; obtaining absolute coordinate system data of a point of interest corresponding to the movement trajectory based on the set coordinate system; and converting the radio environment information based on the set coordinate system into radio environment information based on the absolute coordinate system by using the absolute coordinate system data of the point of interest.

[0011] According to a second aspect of the electronic device, it includes: a memory that stores one or more instructions; and a processor that executes the one or more instructions stored in the memory, wherein the one or more instructions, when executed by the processor, cause the processor to perform the following operations: obtaining a movement trajectory based on a set coordinate system and radio environment information based on the set coordinate system; obtaining absolute coordinate system data of a point of interest corresponding to the movement trajectory based on the set coordinate system; and converting the radio environment information based on the set coordinate system into radio environment information based on the absolute coordinate system by using the absolute coordinate system data of the point of interest.

[0012] According to a third aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, includes: instructions for causing the processor to obtain a movement trajectory based on a set coordinate system and radio environment information based on the set coordinate system; obtain absolute coordinate system data of a point of interest corresponding to the movement trajectory based on the set coordinate system; and convert the radio environment information based on the set coordinate system into radio environment information based on the absolute coordinate system by using the absolute coordinate system data of the point of interest.

[0013] According to a fourth aspect of a method for training a neural network model by an electronic device, the method includes the following: preparing training data, where the training data includes training input data and training label data, the training input data includes radio environment information at a predetermined position, and the training label data includes absolute coordinate system data of a point of interest corresponding to the predetermined position; and using the training data to train the neural network model to output absolute coordinate system data of a point of interest corresponding to the radio environment information.

[0014] Advantageous Effects

[0015] According to the embodiment, the radio environment information based on the set coordinate system, which can be obtained without being limited by positions such as GPS shadow areas, is converted into radio environment information based on the absolute coordinate system. Thus, it is possible to collect training data that can be used for positioning training of the artificial neural network model without being limited by positions such as GPS shadow areas.

[0016] In addition, by performing coordinate system conversion using the points of interest (obtained from the movement trajectory of the camera and the captured images), it is possible to achieve the versatility of devices that are easily accessible in the surroundings, such as smartphones equipped with cameras.

[0017] Furthermore, by extracting the coordinate information in the absolute coordinate system of the objects in the images captured by the camera from the electronic map, this coordinate information can be regarded as verification data for navigation and the like, and the previously verified coordinate information can be easily obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a configuration diagram of a radio environment-based positioning system to which the information conversion method according to an embodiment of the present invention can be applied.

[0019] Figure 2 is in Figure 1 a radio environment-based positioning system and is a block diagram of an electronic device that can be used as a client device or a server device and can execute the information conversion method according to an embodiment of the present invention.

[0020] Figures 3 to 5 is a flowchart for describing the information conversion method according to an embodiment of the present invention.

[0021] Figure 6 is in Figure 1 a radio environment-based positioning system and is an example diagram of a movement trajectory based on a set coordinate system that can be obtained.

[0022] Figure 7 shows in Figure 1 a radio environment-based positioning system an embodiment of converting a movement trajectory based on a set coordinate system into a movement trajectory based on an absolute coordinate system.

[0023] Figure 8 shows when managing Figure 1 a radio environment-based positioning system an embodiment of determining a positioning position when training data for each set space. DETAILED DESCRIPTION

[0024] Through the following description in conjunction with the accompanying drawings, the advantages and features of the embodiments and the methods for implementing the embodiments will be clearly understood. However, the embodiments are not limited to the described embodiments, as the embodiments can be implemented in various forms. It should be noted that the present embodiments are provided for a complete disclosure and also to allow those skilled in the art to know the full scope of the embodiments. Therefore, the embodiments are only defined by the scope of the appended claims.

[0025] The terms used herein will be briefly described, and the present disclosure will be described in detail.

[0026] Among the terms used in this disclosure, in consideration of the functions in this disclosure, general terms that are as widely used as possible currently are adopted. However, the terms may change according to the intention of those skilled in the art, precedents, the emergence of new technologies, etc. In addition, in some cases, there are terms arbitrarily selected by the applicant, and in such cases, the meanings of the terms will be described in detail in the description of the corresponding invention. Therefore, the terms used in this disclosure should be defined based on the meanings of the terms and the overall content of this disclosure, rather than just the names of the terms.

[0027] When a part in the whole specification is described as "comprising" a component, this means that other components may be further included rather than excluding other components, unless specifically stated to the contrary.

[0028] In addition, terms such as "unit" or "part" used in this specification refer to software components or hardware components such as FPGA or ASIC, and the "unit" or "part" plays a certain role. However, the "unit" or "part" is not limited to software or hardware. The "part" or "unit" may be configured in an addressable storage medium, or may be configured to reproduce one or more processors. Therefore, by way of example, the "unit" or "part" includes components (such as software components, object-oriented software components, class components, and task components), processes, functions, attributes, procedures, subroutines, program code segments, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided in the components and "units" may be combined into a smaller number of components and "units", or may be further divided into additional components and "units".

[0029] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings so that those of ordinary skill in the art can easily implement the present disclosure. In the drawings, parts irrelevant to the description are omitted for clarity.

[0030] Figure 1 It is a configuration diagram of a radio environment-based positioning system to which an information conversion method according to an embodiment of the present invention can be applied.

[0031] The radio environment-based positioning system 100 can be connected to at least one client device 111, 112, and 113 and a server device 120 through a communication network 101.

[0032] Client devices 111, 112, and 113 can acquire the movement trajectory and radio environment information based on a set coordinate system, and provide the acquired movement trajectory and radio environment information based on the set coordinate system to the server device 120 through the communication network 101. Here, the set coordinate system can be arbitrarily set according to a reference initially set in advance. For example, the set coordinate system can be a coordinate system in which the forward direction of the camera is set as the Z-axis, the downward direction of the camera is set as the Y-axis, the rightward direction of the camera is set as the X-axis, and the initial position is set as the origin. In addition, the movement trajectory based on the set coordinate system can be the movement trajectory of the cameras installed on the client devices 111, 112, and 113, and the client devices 111, 112, and 113 can provide the images captured by the cameras within the movement trajectory based on the set coordinate system to the server device 120 through the communication network 101. In addition, the client devices 111, 112, and 113 can provide GPS information to the server device 120 together.

[0033] The server device 120 can receive and acquire the movement trajectory and radio environment information based on the set coordinate system from at least one of the client devices 111, 112, and 113 through the communication network 101. The server device 120 can acquire the absolute coordinate system data of the points of interest related to the movement trajectory based on the set coordinate system, and use the absolute coordinate system data of the points of interest to convert the radio environment information based on the set coordinate system into radio environment information based on the absolute coordinate system. Here, the points of interest can be the positions of the objects included in the images captured by the cameras within the movement trajectory based on the set coordinate system, and can be at least three positions. For example, the object whose position is the point of interest can be an object including the name of the point of interest (e.g., a signboard, etc.).

[0034] In addition, when the server device 120 acquires the absolute coordinate system data of the points of interest, the server device 120 can identify the names of the objects in the images captured by the cameras, and extract the coordinate information on the absolute coordinate system corresponding to the identified names from the electronic map. Here, in the case of repeatedly identifying the names of the objects included in the images captured within the movement trajectory based on the set coordinate system, if the same name is identified, only the object with the largest size among the objects can be determined to be valid.

[0035] In addition, the server device 120 can generate absolute coordinate position information of interest points related to a movement trajectory based on a set coordinate system and radio environment information at the corresponding positions as training data. In addition, the server device 120 can train an artificial neural network model by using the training data generated through the above operations to generate a positioning map based on the radio environment information. Here, the training data can exist for each of a plurality of set spaces, and when the server device 120 generates the training data, the server device can generate the training data based on the outdoor positioning information (e.g., GPS data) of the client devices 111, 112, and 113 corresponding to one of the plurality of set spaces. For example, the client devices 111, 112, and 113 further include an outdoor positioning confirmation module capable of confirming outdoor positioning information (e.g., GPS data) and can periodically confirm the outdoor positioning information (e.g., GPS data). When the client devices 111, 112, and 113 enter a shadow area or enter the interior of a building, the outdoor positioning information (e.g., GPS data) may not be detected by the outdoor positioning confirmation module. Therefore, the client devices 111, 112, and 113 can confirm the identifier of the shadow area existing within a predetermined range, the identifier of the building existing within the corresponding range, etc. based on the finally confirmed outdoor positioning information (e.g., GPS data), and determine one of the plurality of set spaces by selecting one of the confirmed identifiers of the shadow area or the building.

[0036] Referring to Figure 1 the positioning system 100 based on radio environment, an embodiment has been described in which the client devices 111, 112, and 113 provide a movement trajectory based on a set coordinate system and radio environment information to the server device 120, and the server device 120 performs information conversion processing. In contrast, another embodiment in which information conversion processing is directly performed based on the movement trajectory and radio environment information of the set coordinate system already acquired by the client devices 111, 112, and 113 themselves can also be performed. These two embodiments only differ in the subject of the information conversion processing, but the information conversion processing and principles are the same or similar, which will be described again below.

[0037] Composed of Figure 1 The client devices 111, 112, and 113 and / or the server device 120 of the positioning system 100 based on radio environment can be implemented by an electronic device capable of performing computing operations. For example, the electronic device can include a mobile communication terminal, also known as a smart phone, which includes a camera, a GPS receiver, a communication module, etc. In addition, the electronic device can include a desktop PC, a laptop PC, a tablet PC, etc.

[0038] As Figure 2As shown, the electronic device 200 may include an information acquisition unit 210 and a processor unit 220. In addition, the electronic device 200 may further include a display unit (not shown) for providing the processing results of the processor unit 220. In addition, the electronic device may further include a communication unit (not shown) capable of sending the processing result data of the processor unit 220 to an external device. In addition, the electronic device 200 may further include a memory (not shown), where information related to various functions or instructions may be stored. For example, in addition to ROM and RAM, the memory may include a hard disk, an SSD, a flash memory, etc. The processor unit 220 may include one or more processors. For example, the one or more processors may be general-purpose processors such as a central processing unit (CPU) and a digital signal processor (DSP), or only an artificial intelligence processor such as a neural processing unit (NPU).

[0039] In the above description, with reference to Figure 1 , embodiments in which the client devices 111, 112, 113 provide the server device 120 with a movement trajectory and radio environment information based on a set coordinate system and the server device 120 performs information conversion processing have been described, and other embodiments in which the client devices 111, 112, 113 directly perform information conversion processing based on the movement trajectory and radio environment information based on the set coordinate system acquired by themselves have also been described.

[0040] In one embodiment and another embodiment, the information acquisition unit 210 may acquire a movement trajectory and radio environment information based on a set coordinate system. Here, the movement trajectory based on the set coordinate system may be the movement trajectory based on the set coordinate system of a camera included in the information acquisition unit 210, and the information acquisition unit 210 may acquire an image captured by the camera within the movement trajectory based on the set coordinate system of the electronic device 200. For example, the radio environment information may be the received signal strength of signals sent from a nearby mobile communication repeater and / or wireless access point (AP). In addition, the information acquisition unit 210 may acquire GPS information. In addition, the information acquisition unit 210 may directly measure and / or receive a movement trajectory, radio environment information, GPS information, etc. based on a set coordinate system, or may receive the measured and / or set movement trajectory, radio environment information, GPS information, etc. based on a coordinate system from a nearby communication device.

[0041] In one embodiment, the electronic device 200 serving as the client devices 111, 112, and 113 may further include a communication unit, and the communication unit may provide various types of information acquired by the information acquisition unit 210 to the server device 120 through the communication network 101 under the control of the processor unit 220.

[0042] In an embodiment, the electronic device 200 serving as the client devices 111, 112, and 113 may further include a communication unit that can receive and obtain various types of information acquired by the client devices 111, 112, and 113 through the communication network 101 under the control of the processor unit 220.

[0043] In an embodiment of the present disclosure, the information acquisition unit 210 is disclosed as a separate component different from the processor unit 220. However, the present disclosure is not limited thereto and can be changed and applied in various ways. For example, the operations performed by the information acquisition unit 210, that is, the operations of acquiring the movement trajectory and radio environment information based on the set coordinate system, can be performed by the processor unit 220.

[0044] In one embodiment and another embodiment, the processor unit 220 may acquire the absolute coordinate system data of the point of interest related to the movement trajectory based on the set coordinate system, and use the absolute coordinate system data of the point of interest to convert the radio environment information based on the set coordinate system into radio environment information based on the absolute coordinate system. Here, the point of interest may be the position of an object included in the image captured by the camera within the movement trajectory based on the set coordinate system, and may be at least three positions. For example, the object whose position is the point of interest may be an object including the name of the point of interest (e.g., a signboard, etc.).

[0045] In addition, when the processor unit 220 acquires the absolute coordinate system data of the point of interest, the processor unit 220 may identify the name of the object within the image captured by the camera, and extract the coordinate information on the absolute coordinate system corresponding to the identified name from the electronic map. Here, in the case of repeatedly identifying the names of the objects included in the images captured within the movement trajectory based on the set coordinate system, if the same name is identified, only the object with the largest size among the objects may be determined to be valid.

[0046] In addition, the processor unit 220 may generate the absolute coordinate system position information of the point of interest related to the movement trajectory based on the set coordinate system and the radio environment information at the corresponding position as training data. In addition, the processor unit 220 may train an artificial neural network model by using the training data generated through the above operations to generate a positioning map based on the radio environment information. Here, the training data may exist for each of the multiple set spaces, and the processor unit 220 may generate the training data based on the GPS data of the client devices 111, 112, and 113 corresponding to one of the multiple set spaces when generating the training data. Here, one of the multiple set spaces may be a space determined by the identifier of the shaded area or the identifier of the building described above.

[0047] Figures 3 to 5is a flowchart for describing an information conversion method according to an embodiment of the present invention, Figure 6 is an example diagram of a movement trajectory based on a set coordinate system that can be obtained in a radio environment-based positioning system of Figure 1 and shows an embodiment of converting a movement trajectory based on a set coordinate system into a movement trajectory based on an absolute coordinate system in a radio environment-based positioning system of Figure 7 and shows an embodiment of determining a positioning position when managing training data for each set space in a radio environment-based positioning system of Figure 1 and shows an embodiment of converting a movement trajectory based on a set coordinate system into a movement trajectory based on an absolute coordinate system in a radio environment-based positioning system of Figure 8 and shows an embodiment of determining a positioning position when managing training data for each set space in a radio environment-based positioning system of Figure 1 Hereinafter, an information conversion method performed by an electronic device 200 that can be used as client devices 111, 112, and 113 or a server device 120 will be described with reference to

[0048] In the following, an information conversion method performed by an electronic device 200 that can be used as client devices 111, 112, and 113 or a server device 120 will be described with reference to Figures 1 to 8 Based on the radio environment, the positioning measurement is performed on the wireless reception signal strength at several pre-known reference positions to generate a radio environment map, and then the reference position having the most similar signal strength characteristic in the radio environment map with respect to the signal strength received at the positioning position is determined as the positioning position. In addition, in order to improve the positioning performance by using a deep learning technique for deriving a positioning result using an artificial neural network model, training data composed of GPS information as an absolute coordinate system and radio environment information should be collected, and the collected training data should be pre-trained for the artificial neural network model. However, in a GPS shadow area such as an "underground shopping mall" as shown in

[0049] it may be impossible to receive GPS information, that is, absolute coordinate system information, so it is difficult to collect training data for training the artificial neural network model. This difficulty can be overcome by converting the radio environment information based on a set coordinate system pre-configured in the electronic device 200 used as client devices 111, 112, and 113 into radio environment information based on an absolute coordinate system, and using the converted radio environment information based on an absolute coordinate system to generate training data. Figure 6 Referring to

[0050] Referring to Figure 3 the information acquisition unit 210 of the electronic device 200 used as client devices 111, 112, and 113 acquires a movement trajectory based on a set coordinate system and radio environment information in a GPS shadow area such as an "underground shopping mall" as shown in Figure 6 Here, the movement trajectory based on a set coordinate system may be a movement trajectory based on a set coordinate system of a camera installed on the client devices 111, 112, and 113, and the client devices 111, 112, and 113 may be images captured by the camera within the movement trajectory based on a set coordinate system (S310).

[0051] In an implementation where the client devices 111, 112, and 113 perform information conversion processing themselves, the client devices 111, 112, and 113 may process the information obtained in step S310, and in an implementation where the server device 120 performs information conversion processing, the server device 120 may provide the information obtained in step S310 to the server device 120 via the communication network 101.

[0052] Then, the information conversion processing is performed by the client devices 111, 112, 113 or the server device 120, and the information conversion processing is performed by the processor unit 220 of the electronic device 200 that functions as the client devices 111, 112, 113 or the server device 120, which is the main body of the information conversion processing.

[0053] For the information conversion processing, the processor unit 220 of the electronic device 200 first obtains the absolute coordinate system data of the points of interest related to the movement trajectory based on the set coordinate system (S320).

[0054] Here, the points of interest may be the positions of the objects included in the image captured by the camera within the movement trajectory based on the set coordinate system, and there may be at least three positions. For example, the object whose position is the point of interest may be an object including the name of the point of interest (such as a signboard, etc.).

[0055] Refer to Figure 4 and various stores may be located Figure 6In the "underground shopping mall" shown, and these stores may have signs with names such as their store names installed on the outside. The processor unit 220 can identify the names of the objects 631, 632, and 633 within the surrounding images captured by the camera while moving along the movement trajectory 620 based on the set coordinate system. In this way, since it is a well-known technical concept for the processor unit 220 to identify the names of the objects 631, 632, and 633 within the image, its detailed description will be omitted here. Here, when the processor unit 220 identifies the names of the objects 631, 632, and 633 included in the images captured within the movement trajectory based on the set coordinate system multiple times, if the same name is identified, only the object with the largest size among the objects 631, 632, and 633 can be determined as valid. For example, in the case where the same signboard is identified multiple times, since the object and name identified within the image captured at the closest distance are more reliable than other recognition results, only the case where the size of the identified object is the largest is determined as valid, thereby preventing the points of interest from being duplicated (S410). In this way, when the names of the objects 631, 632, and 633 are identified, the processor unit 220 can obtain the coordinate information on the absolute coordinate system corresponding to the identified name from the electronic map 610 as the absolute coordinate system data of the points of interest related to the movement trajectory based on the set coordinate system. Here, the electronic map 610 can be stored in a separate electronic map device or can be pre-stored in the memory (not shown) constituting the electronic device 200 (S420).

[0056] Return reference Figure 3 , the processor unit 220 converts the radio environment information based on the set coordinate system into radio environment information based on the absolute coordinate system by using the absolute coordinate system data of the points of interest related to the movement trajectory based on the set coordinate system obtained through step S320.

[0057] In Figure 6 the "underground shopping mall" shown, when the coordinate information on the absolute coordinate system of three or more points of interest (i.e., objects 631, 632, and 633) near the movement trajectory 620 based on the set coordinate system is known, the movement trajectory 701 on the set coordinate system can be converted into the movement trajectory 703 on the absolute coordinate system by using the rotation / translation transformation matrix of Equation 1 as shown Figure 7 shown. Figure 7 The reference numeral 702 in is an example of an electronic map 702 that can be used for navigation, etc., and this electronic map 702 includes the coordinate information on the absolute coordinate system of each point of interest.

[0058] [Equation 1]

[0059]

[0060] Here, R and t represent the rotation / translation matrix for converting to the absolute coordinate system, and p i represents the position of the i-th key frame where the name is recognized, and q i represents the position information of the point of interest where the name is recognized in the i-th key frame. Since Equation 1 is non-linear, non-linear optimization such as Gauss-Newton or Levenberg-Marquardt optimization can be used to perform the non-linear optimization.

[0061] In Figure 6 the exemplified "underground shopping mall", among objects 631, 632, and 633, objects 631 and 632 are offset to the left of the camera position, i.e., based on the movement trajectory 620 of the set coordinate system, and object 633 is offset to the right of the camera position, i.e., based on the movement trajectory 620 of the set coordinate system. In this case, when the movement trajectory 701 of the set coordinate system is converted to the absolute coordinate system as shown in Figure 7 by using the rotation / translation transformation matrix obtained through Equation 2, the movement trajectory 703 based on the set coordinate system can be slightly offset to the left. These errors decrease as the number of corresponding points of interest in the movement trajectory of the set coordinate system increases. This is because when there is a uniform match rather than a point of interest at a specific position during the movement trajectory of the camera based on the set coordinate system, the probability of not being offset in a specific direction increases, and when the rotation / translation transformation matrix is obtained through Equation 1, these errors cancel each other out.

[0062] By converting the movement trajectory 701 based on the set coordinate system on the set coordinate system to the movement trajectory 703 based on the set coordinate system on the absolute coordinate system in this way, the processor unit 220 can also convert the radio environment information corresponding to the movement trajectory 701 based on the set coordinate system on the set coordinate system to the radio environment information corresponding to the movement trajectory 703 based on the set coordinate system on the absolute coordinate system (S330).

[0063] In addition, referring to Figure 5 , the processor unit 220 can generate the absolute coordinate position information of the point of interest related to the movement trajectory based on the set coordinate system and the radio environment information at the corresponding position as training data (S510) in a state where the radio environment information based on the absolute coordinate system is ensured, and can use the training data to train an artificial neural network model to generate a positioning map based on the radio environment information (S520).

[0064] As Figure 8As shown, multiple underground malls can be located in a city. In other words, GPS shadow areas can exist in multiple locations. Therefore, training data for training an artificial neural network model can exist for each of multiple set spaces. In this case, when the processor unit 220 generates training data, the processor unit 220 can generate training data based on the GPS data of the client devices 111, 112, and 113 corresponding to one of the multiple set spaces. For example, when the client devices 111, 112, and 113 enter the shadow area or the interior (or basement) of a building, the outdoor positioning confirmation module may not be able to detect outdoor positioning information (e.g., GPS data). Therefore, the processor unit 220 can select the identifier of the underground mall 1 802 and the identifier of the underground mall 2 803 as candidates based on the valid GPS information 801 before the electronic device 200 enters the GPS shadow area. In addition to the position information, the GPS information also includes horizontal dilution of precision (HDOP) information indicating reliability, which is a value representing "the degree of interference in the position accuracy of the horizontal coordinates", and the smaller this value, the higher the accuracy of the position coordinates. For example, when the HDOP is about 2.5 or less, it can be determined that the GPS information is valid.

[0065] The processor unit 220 can display the candidate locations on a display unit (not shown), and then generate training data corresponding to the identifier of the underground mall 1 802 or the identifier of the underground mall 2 803 according to the input selection information. Alternatively, the processor unit 220 can be based on the recognition reference Figure 4 As a result of describing the names of the objects in the image, training data can be generated by automatically selecting the locations of the objects (i.e., points of interest) with the corresponding names in the underground mall 1 802 and the underground mall 2 803. For example, when finally selecting the locations in the underground mall 1 802 and the underground mall 2 803 with more matching points of interest to generate training data, even if some points of interest with the same name exist repeatedly, errors can be minimized.

[0066] As described above, according to an embodiment of the present invention, radio environment information based on a set coordinate system that can be obtained without being restricted by positions such as GPS shadow areas is converted into radio environment information based on an absolute coordinate system. Thus, training data that can be used for the positioning training of an artificial neural network model can be collected without being restricted by positions such as GPS shadow areas.

[0067] In addition, by using the points of interest (obtained by using the movement trajectory and captured images of the camera), coordinate system conversion can be achieved, enabling the versatility of devices such as smartphones equipped with cameras that are easily obtainable in the surroundings.

[0068] In addition, by extracting coordinate information on the absolute coordinate system of an object in an image captured by a camera from an electronic map, the coordinate information can be regarded as verification data for navigation and the like, and the previously verified coordinate information can be easily obtained.

[0069] Meanwhile, a computer program can be implemented to include instructions for causing a processor to execute each step included in the information conversion method performed by the electronic device according to the above-described embodiment.

[0070] In addition, a computer program including instructions for causing a processor to execute each step included in the information conversion method performed by the electronic device according to the above-described embodiment can be recorded on a computer-readable recording medium.

[0071] The combination of steps incorporated into each flowchart of the present disclosure can be executed by computer program instructions. Since the computer program instructions can be installed on the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, the instructions executed by the processor of the computer or other programmable data processing device create means for performing the functions described in each step of the flowchart. The computer program instructions can also be stored on a computer-usable or computer-readable storage medium, which can be directed to the computer or other programmable data processing device to implement the functions in a specific manner. Therefore, the instructions stored on the computer-usable or computer-readable recording medium can also produce an article of manufacture that includes means for performing the functions described in each step of the flowchart. The computer program instructions can also be installed on the computer or other programmable data processing device. Therefore, a series of operation steps are performed on the computer or other programmable data processing device to create a computer-executable process, and the instructions can cause the computer or other programmable data processing device to provide steps for performing the functions described in each step of the flowchart.

[0072] In addition, each step can represent a module, section, or portion of code that includes one or more executable instructions for performing a specified logical function. It should also be noted that in some alternative embodiments, the functions recited in the steps may occur out of order. For example, two steps shown in succession may actually be performed substantially simultaneously, or the steps may sometimes be performed in the reverse order depending on the corresponding functions.

[0073] The above description is only an exemplary description of the technical scope of the present disclosure. Those skilled in the art will understand that various changes and modifications can be made without departing from the original features of the present disclosure. Therefore, the embodiments disclosed in the present disclosure are intended to illustrate rather than limit the technical scope of the present disclosure, and the technical scope of the present disclosure is not limited by the embodiments. It should be understood that the protection scope of the present disclosure should be interpreted based on the following claims, and it should be understood that all technical scopes within the scope equivalent thereto are included in the protection scope of the present disclosure.

Claims

1. A method for converting information performed by an electronic device, the method comprising the following steps: Obtaining a movement trajectory based on a set coordinate system and radio environment information based on the set coordinate system; Obtaining absolute coordinate system data of a point of interest corresponding to the movement trajectory based on the set coordinate system; And Converting the radio environment information based on the set coordinate system into radio environment information based on an absolute coordinate system by using the absolute coordinate system data of the point of interest.

2. The method according to claim 1, wherein, The movement trajectory based on the set coordinate system is the movement trajectory of a camera, and The point of interest is the position of an object included in an image captured by the camera within the movement trajectory based on the set coordinate system.

3. The method according to claim 2, wherein, The captured image within the movement trajectory based on the set coordinate system includes information indicating the name of the point of interest, and The step of obtaining the absolute coordinate system data includes: Identifying the name of the point of interest from the image captured within the movement trajectory based on the set coordinate system; and Extracting coordinate information corresponding to the identified name on the absolute coordinate system from an electronic map.

4. The method according to claim 2, wherein, The captured image within the movement trajectory based on the set coordinate system includes information indicating the name of the point of interest, and The step of obtaining the absolute coordinate system data includes: Identifying the name of the point of interest from each of a plurality of images captured within the movement trajectory based on the set coordinate system; and When there are identical names among the names of the points of interest identified from the plurality of images, determining the absolute coordinate system data based on the size of the object included in the plurality of images.

5. The method according to claim 4, wherein The step of determining the absolute coordinate system data based on the size of the object included in the plurality of images includes: Selecting the image among the plurality of images that includes the object with the largest size; and Verifying the absolute coordinate system data corresponding to the selected image.

6. The method according to claim 1, wherein the method further comprises the following steps: Generating training data, the training data including training label data and training input data, the training label data including absolute coordinate system position information of the point of interest corresponding to the movement trajectory based on the set coordinate system, and the training input data including radio environment information of the position corresponding to the absolute coordinate system position information of the point of interest.

7. The method according to claim 1, the method further comprising the following steps: Verifying outdoor positioning information from an outdoor positioning confirmation module equipped in the electronic device; And Determining an area for obtaining the movement trajectory based on the set coordinate system and the radio environment information based on the outdoor positioning information.

8. The method according to claim 7, wherein The step of determining an area for obtaining the movement trajectory based on the set coordinate system and the radio environment information includes: Based on the outdoor positioning information, verifying an identifier of a shadow area or an identifier of a building existing within a predetermined range; and Selecting one of the identifier of the shadow area or the identifier of the building existing within the confirmed predetermined range.

9. The method according to claim 8, wherein, The step of selecting one of the identifier of the shadow area or the identifier of the building existing within the confirmed predetermined range includes: Providing the user with an identifier of the confirmed shadow area or an identifier of the confirmed building; and Determining one of an identifier of the shadow area or an identifier of the building based on information input by the user.

10. The method according to claim 8, wherein, The step of selecting one of an identifier of the shadow area or an identifier of the building existing within a confirmed predetermined range includes: determining an identifier of the nearest shadow area or an identifier of the nearest building based on the outdoor positioning information.

11. The method according to claim 7, the method further comprising the following steps: Generating training data, the training data including training label data and training input data, the training label data including information identifying the determined area and absolute coordinate system position information of the point of interest corresponding to the movement trajectory based on the set coordinate system, the training input data including radio environment information of a position corresponding to the absolute coordinate system position information of the point of interest.

12. An electronic device, the electronic device comprising: A memory storing one or more instructions; And A processor that executes the one or more instructions stored in the memory, Wherein, when executed by the processor, the one or more instructions cause the processor to perform the following operations: Obtaining a movement trajectory based on a set coordinate system and radio environment information based on the set coordinate system; Obtaining absolute coordinate system data of a point of interest corresponding to the movement trajectory based on the set coordinate system; And Converting the radio environment information based on the set coordinate system into radio environment information based on an absolute coordinate system by using the absolute coordinate system data of the point of interest.

13. The electronic device according to claim 12, wherein, The movement trajectory based on the set coordinate system is a movement trajectory of a camera, and The point of interest is a position of an object included in an image captured by the camera within the movement trajectory based on the set coordinate system.

14. The electronic device according to claim 13, wherein, The captured image within the movement trajectory based on the set coordinate system includes information indicating the name of the point of interest, and Wherein, when executed by the processor, the one or more instructions further cause the processor to perform the following operations: Identifying the name of the point of interest from the image captured within the movement trajectory based on the set coordinate system; and Extracting coordinate information corresponding to the identified name on an absolute coordinate system from an electronic map.

15. The electronic device according to claim 12, wherein, When executed by the processor, the one or more instructions further cause the processor to perform the following operations: Generating training data, the training data including training label data and training input data, the training label data including absolute coordinate system position information of the point of interest corresponding to the movement trajectory based on the set coordinate system, the training input data including radio environment information of a position corresponding to the absolute coordinate system position information of the point of interest.

16. A method for training a neural network model by an electronic device, the method comprising the following steps: Prepare training data, where the training data includes training input data and training label data. The training input data includes radio environment information at a predetermined location, and the training label data includes absolute coordinate system data of a point of interest corresponding to the predetermined location; and Train the neural network model by using the training data to output the absolute coordinate system data of the point of interest corresponding to the radio environment information.

17. The method according to claim 16, wherein, The training label data further includes an identifier selected from among identifiers of buildings or identifiers of shadow areas existing within a predetermined range, and the training of the neural network model is trained to further output an identifier selected from among identifiers of the buildings or identifiers of the shadow areas existing within the predetermined range.

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