Location Data Hub for Mobile Indoor Services

Abstract

Provides a location data hub for mobile indoor services. [Solution] This embodiment provides a location data hub for mobile indoor services that uses artificial intelligence algorithms to provide reliable location information based on big data from various wireless signals received from mobile devices and data that can be analyzed using AI camera functions in the form of an SDK (Software Development Kit) that can be used on various mobile devices.

Description

[Technical field]

[0001] One embodiment of the present invention relates to a location data hub for mobile indoor services. [Background technology]

[0002] The following discussion provides background information related to the present embodiment only and does not constitute prior art.

[0003] Conventionally, to recognize location information using UWB wireless signals, TDoA (Time Difference of Arrival) and TWR (Two-Way Ranging) are used for signal transmission and reception. Multiple access is supported using a time division method so that multiple devices can communicate with each other without wireless interference.

[0004] To support multiple connections, the time division method allocates time at regular intervals. This value allows multiple connections by providing a margin in the time required for signal transmission. The TWR method is preferred for calculating accurate location information, but since the aforementioned TWR is a structure for sending and receiving signals, a different interval must be guaranteed when allocating time division compared to the TDoA method.

[0005] Previously, there were no rules for multiple access control by UWB wireless signals. Rather than multiple access control, a method was adopted for UWB to avoid interference between devices by using random access.

[0006] In order to support multiple connections, it is being considered to adopt a method of performing time-division allocation by supporting random connections within a specific time range between an anchor and a smartphone.

[0007] However, communication methods using random connections can cause interference with two-way communication information provision and often do not provide protection when the purpose is to transmit information rather than for positioning purposes.

[0008] Until recently, indoor positioning technology using smartphones (mobile terminals) was based on LTE, Wi-Fi, and BLE signal strength (RSSI). Due to technical limitations, the accuracy of the positioning was not satisfactory to users, and services were restricted. With the incorporation of UWB communication technology in iPhones and Androids, it has become possible to calculate the time of flight (ToF) using wireless technology instead of the existing signal strength, making it possible to calculate indoor positions with higher accuracy. The existing BLE and Wi-Fi technologies are also being upgraded with the incorporation of new standardized distance calculation wireless technology. Summary of the Invention [Problem to be solved by the invention]

[0009] The present embodiment aims to provide a location data hub for mobile indoor services that can provide reliable location information based on big data using artificial intelligence algorithms from various wireless signals received from mobile devices and data that can be analyzed using AI camera functions in the form of an SDK (Software Development Kit) that can be used on various mobile devices. [Means for solving the problem]

[0010] According to one aspect of the present embodiment, a location data hub is provided, comprising: a DB for storing mapping information in which a plurality of sensing values ​​previously collected are mapped for each divided area obtained by dividing a predetermined area by predetermined identification information; a data acquisition unit for acquiring a plurality of sensing values ​​from a mobile device; a first reference position positioning unit for locating a first reference position for the mobile device based on a Received Signal Strength Indicator (RSSI) of a specific sensing value among the plurality of sensing values ​​and a reference position of the same category as the specific sensing value included in the mapping information; and a second reference position positioning unit for locating a second reference position for the mobile device based on remaining sensing values ​​among the plurality of sensing values ​​excluding the specific sensing value and information having the same category as the remaining sensing values ​​included in the mapping information. Effect of the Invention

[0011] As described above, according to this embodiment, it is possible to provide various wireless signals received from a mobile device and data that can be analyzed by an AI camera function in the form of an SDK (Software Development Kit) that can utilize reliable location information based on big data using an artificial intelligence algorithm in various mobile devices. [Brief description of the drawings]

[0012] [Figure 1A] FIG. 2 illustrates a location data hub according to an embodiment of the present invention. [Figure 1B] FIG. 2 illustrates a location data hub according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram illustrating a method for providing a user location based on a Visual Localization And Mapping (VLAM) technique according to the present embodiment. [Diagram 3] FIG. 4 is a diagram showing position data according to the embodiment; [Figure 4] A diagram showing a process in which data is transmitted from a VPS anchor to a location data hub in this embodiment. [Diagram 5] FIG. 1 is a diagram showing location data using a VPS anchor, BLE, UWB, and Wi-Fi signals in this embodiment. [Figure 6] 1A and 1B are diagrams showing a TPH reference anchor and a TPH reference position according to this embodiment. [Figure 7] 5A to 5C are diagrams illustrating an operation process of the location data hub according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] The present embodiment will be described in detail below with reference to the accompanying drawings.

[0014] 1A and 1B are diagrams illustrating a location data hub according to an embodiment of the present invention.

[0015] The location data hub 110 in this embodiment measures the user location using a VPS anchor, UWB (Ultra-Wide Band), BLE beacon (Bluetooth Low Energy Beacon), Wi-Fi RSSI (Received Signal Strength Indicator), LTE / 5G, Wi-Fi ranging, and BLE ranging.

[0016] The location data hub 110 can provide various wireless signals received from mobile devices and data that can be analyzed using AI camera functions in the form of an SDK (Software Development Kit) that can utilize reliable location information based on big data using artificial intelligence algorithms on various mobile devices.

[0017] The location data hub 110 measures a location using Wi-Fi RSSI-based fingerprinting-based analysis data. The location data hub 110 measures a location using BLE RSSI-based fingerprinting-based analysis data. The location data hub 110 measures a location using LTE / 5G base station-based RSSI-based analysis data provided by a mobile communication company. The location data hub 110 measures a location using UWB ranging-based analysis data. The location data hub 110 measures a location using BLE channel sounding-based analysis data. The location data hub 110 measures a location using Wi-Fi FTM (Fine Time Measurement)-based analysis data. The location data hub 110 measures a location using data converted from location photos on portals (Google / Naver / Kakao) and the like into VPS-based data. The location data hub 110 measures a location by performing beacon positioning.

[0018] The position data hub 110 determines a precise position by using a combination of BLE RSSI and Wi-Fi RSSI.The position data hub 110 determines a precise position by using a combination of BLE RSSI and BLE precise distance.The position data hub 110 determines a precise position by using a combination of BLE RSSI and Wi-Fi precise distance.

[0019] The location data hub 110 is a beacon bank that stores beacon data in a database. For example, the location data hub 110 is a mobile device that can transmit relevant information (e.g., coupons) to the office by scanning a beacon installed in the office using a positioning application installed in the mobile device.

[0020] The position data hub 110 stores UWB distance values, Wi-Fi distance values, and camera-based location recognition values ​​in a database. The position data hub 110 stores BLE RSSI, beacon data, UWB distance information, and Wi-Fi ranging information in a database for use. For example, the position data hub 110 can provide guidance specialized for a specific location when a user enters a specific location using the databased sensing values. The position data hub 110 performs precise positioning using at least two of BLE, UWB, and Wi-Fi in combination.

[0021] When the location data hub 110 stores sensing data in a database, the more categories in the database, the more accurate the positioning becomes. The location data hub 110 can store and store the BLE range for each location in addition to the RSSI of the beacon.

[0022] A mobile device can use the installed SDK to receive a precise positioning service using a DB established in the position data hub 110. After connecting to the position data hub 110 using the installed SDK, the mobile device can confirm its own location or the location of others using the DB established in the position data hub 110.

[0023] The location data hub 110 stores distance measurement information collected through various communication methods including Wi-Fi, BLE, UWB, LTE, and 5G in a database, and performs precise positioning based on the databased sensing values ​​and distance measurement information.

[0024] The location data hub 110 performs highly accurate and precise positioning by combining Wi-Fi, BLE, UWB, LTE, and 5G RSSI and distance measurement information. The location data hub 110 can perform precise positioning by using information captured using a camera on a mobile device, recognizing the image based on AI, and storing it in a database. The location data hub 110 can perform precise positioning by objectifying signs, sales booths, etc. in an image.

[0025] When a beacon or anchor is not identified, the location data hub 110 performs reference positioning based on multiple distance data, selects the closest candidates, and then measures the location again with some error based on the reference position.

[0026] The location data hub 110 performs a primary location determination of a rough location, and then performs a secondary location determination of a precise location using UWB, anchors, and BLE beacons installed in the vicinity. The location data hub 110 performs secondary location determination of connected devices based on the location of the anchor. The location data hub 110 performs indexing based on a reference location.

[0027] The location data hub 110 can determine one of a plurality of location methods when performing a second precise positioning if there is a location where a data value sensed by the corresponding mobile device is present and there is an empty location after locating the current closest reference location. When UWB data is not collected, the location data hub 110 can perform precise positioning using BLE2 and Wi-Fi2 other than UWB. When performing a second precise positioning, the location data hub 110 identifies and uses a plurality of anchors and a plurality of beacons in a table in a DB.

[0028] In one step, the location data hub 110 compares databased reference locations with data received from the mobile device based on data sensing values ​​associated with various positioning methods measured using the mobile device to find the closest data reference location.

[0029] In the second step, the location data hub 110 selects a method for precise positioning based on whether or not data to be used for precise positioning is received from among the sensed values, and selects anchors or beacons installed in nearby locations to perform precise positioning. The location data hub 110 performs precise positioning using UWB, BLE, and Wi-Fi.

[0030] The location data hub 110 stores measured values ​​(measured values ​​of RSSI values ​​at a specific reference location) of RSSI signals of various communication methods in a database. The location data hub 110 determines the location by comparing information received from a mobile device with the databased information. The location data hub 110 stores two or more RSSI signals of UWB, BLE, and Wi-Fi in a DB table for each reference location and then compares them.

[0031] The location data hub 110 performs positioning using a combination of BLE and UWB, BLE and BLE2, and BLE and Wi-Fi. The location data hub 110 basically uses BLE RSSI. The location data hub 110 combines one or more of Wi-Fi RSSI, BLE distance, and Wi-Fi distance with BLE RSSI, and compares it with a reference table to measure a reference location.

[0032] The position data hub 110 basically performs positioning by a distance positioning method using BLE RSSI. The position data hub 110 measures a reference position by using at least one of various distance positioning methods in combination.

[0033] The location data hub 110 according to this embodiment includes a DB 102, a data acquisition unit 104, a first reference position measurement unit 106, a second reference position measurement unit 108, and a mixed position measurement unit 109. The components included in the location data hub 110 are not necessarily limited to these.

[0034] Each component included in the location data hub 110 may be connected to a communication path that connects software modules or hardware modules within the device and operate organically between each other. Such components communicate with each other using one or more communication buses or signal lines.

[0035] Each component of the location data hub 110 shown in FIG. 1B represents a unit that processes at least one function or operation, and may be realized as a software module, a hardware module, or a combination of software and hardware.

[0036] DB102 refers to a general data structure implemented in the storage space (hard disk or memory) of a computer system using a database management program (DBMS). DB102 refers to a data storage format that allows data search (extraction), deletion, editing, addition, etc. DB102 has fields or elements to achieve its own functions.

[0037] The DB 102 stores mapping information in which a plurality of sensing values ​​previously collected are mapped to each divided area obtained by dividing a preset area according to preset identification information.

[0038] The data acquisition unit 104 acquires a plurality of sensing values ​​from the mobile device.

[0039] The multiple sensing values ​​include at least two of Wi-Fi RSSI, BLE RSSI, UWB RSSI, LTE / 5G RSSI, UWB Ranging, BLE Channel Sounding, Wi-Fi FTM (Fine Time Measurement), and Vision.

[0040] The first reference position positioning unit 106 locates a first reference position for the mobile device based on a received signal strength indicator (RSSI) of a specific sensing value among the multiple sensing values ​​and a reference position of the same category as the specific sensing value included in the mapping information.

[0041] The first reference position measurement unit 106 extracts a plurality of BLE RSSIs included in a plurality of sensing values ​​and selects a BLE RSSI having the maximum strength from the plurality of BLE RSSIs. The first reference position measurement unit 106 extracts identification information having the same category as the BLE having the maximum strength from the mapping information. The first reference position measurement unit 106 measures a first reference position for the mobile device based on the reference position mapped to the identification information having the same category as the BLE having the maximum strength.

[0042] The second reference position positioning unit 108 locates a second reference position for the mobile device based on the remaining sensing values ​​excluding a specific sensing value among the plurality of sensing values ​​and information having the same category as the remaining sensing values ​​included in the mapping information.

[0043] The second reference position measurement unit 108 extracts remaining sensing values ​​excluding BLE from the plurality of sensing values, and measures a second reference position for the mobile device based on a reference position having the same category as the remaining sensing values ​​included in the mapping information.

[0044] The second reference position measurement unit 108 extracts a plurality of Wi-Fi RSSIs included in the plurality of sensing values ​​and selects a Wi-Fi RSSI having the maximum strength from the plurality of Wi-Fi RSSIs. The second reference position measurement unit 108 extracts identification information having the same category as the Wi-Fi having the maximum strength from the mapping information. The second reference position measurement unit 108 measures a second reference position for the mobile device based on the reference position mapped to the identification information having the same category as the Wi-Fi having the maximum strength.

[0045] The second reference position measurement unit 108 extracts a plurality of BLE rangings included in the plurality of sensing values, and selects a BLE ranging having a closest distance based on the plurality of BLE rangings. The second reference position measurement unit 108 extracts identification information having the same category as the BLE having the closest distance from the mapping information. The second reference position measurement unit 108 measures a second reference position for the mobile device based on the reference position mapped to the identification information having the same category as the BLE having the closest distance.

[0046] The second reference position positioning unit 108 extracts a plurality of Wi-Fi rangings included in the plurality of sensing values, and selects a Wi-Fi ranging having a closest distance based on the plurality of Wi-Fi rangings. The second reference position positioning unit 108 extracts identification information having the same category as the Wi-Fi having the closest distance from the mapping information. The second reference position positioning unit 108 positions a second reference position for the mobile device based on the reference position mapped to the identification information having the same category as the Wi-Fi having the closest distance.

[0047] The mixed position measurement unit 109 measures a precise position of the mobile device based on the first reference position and the second reference position. The mixed position measurement unit 109 measures one of an average value, a weighted average value, an interpolated value, and an intermediate value of the first reference position and the second reference position as the precise position of the mobile device.

[0048] FIG. 2 is a diagram illustrating a method for providing a user location based on a visual localization and mapping (VLAM) technique according to the present embodiment.

[0049] 3D scanning of the target area is performed (S210). In step S210, a person wears the 3D mapping equipment and performs 3D scanning of the target area. The real view is modeled in 3D and sensor data is collected for generating a Visual-Geo DB for camera-based precise positioning.

[0050] A DB is constructed by 3D modeling (S220). In step S220, a 3D mesh is generated and a Visual-Geo DB is generated.

[0051] A user takes a picture of his / her location using a mobile device (S230). In step S230, the user takes a picture of the surroundings using a camera and transmits the picture to a cloud server.

[0052] The cloud server calculates the location (S240). In step S240, the cloud server applies deep learning-based SLAM (Simultaneous Localization and Mapping) technology to measure its own location and simultaneously create a map of the surrounding environment. The cloud server estimates the exact camera position / direction by matching the image taken by the customer with the mobile device with the Visual-Geo DB.

[0053] The user's current location information is provided (S250).

[0054] 2, steps S210 to S250 are executed in sequence, but this is not necessarily limited to this. In other words, the steps shown in FIG. 2 may be executed in a modified manner, or one or more steps may be executed in parallel, and FIG. 2 is not limited to a chronological order.

[0055] As described above, the method for providing a user location based on the VLAM technology according to the present embodiment shown in FIG. 2 may be implemented by a program and recorded in a computer-readable recording medium. The computer-readable recording medium on which the program for implementing the method for providing a user location based on the VLAM technology according to the present embodiment is recorded includes any kind of recording device on which data readable by a computer system is stored.

[0056] FIG. 3 is a diagram showing the position data according to the present embodiment.

[0057] The location data hub 110 measures the reference position of the BLE beacon and the signal strength based calculated position (BLE RSSI based calculated position) from the reference position, and then manages it.

[0058] The location data hub 110 measures and then manages the reference position of the Wi-Fi AP and the Wi-Fi RSSI Based calculated position from the reference position.

[0059] The location data hub 110 measures and then manages the reference position of the LTE / 5G base station and the signal strength based calculated position (LTE / 5G RSSI based calculated position) from the reference position.

[0060] The position data hub 110 measures the reference position of the UWB anchor and the UWB ranging based calculated position from the reference position, and then manages the measured position.

[0061] The location data hub 110 measures and manages the reference position of a BLE beacon (Channel Sounding) and the BLE Channel Sounding based calculated position from the reference position. The location data hub 110 measures and manages the reference position of a Wi-Fi AP (FTM) and the UWB ranging calculated position from the reference position.

[0062] The location data hub 110 can anchor images acquired from indoor images of stores acquired using Google / Apple Map Portal API based on ML (Machine Learning). The location data hub 110 measures the reference position and manages the ML (Machine Learning) based image anchoring. The location data hub 110 recognizes image anchors using mobile camera Vision AI technology, measures its own position, and manages it. The location data hub 110 recognizes its own position indoors / outdoors using BLE / Wi-Fi / UWB / Vision information in the form of a mobile SDK and provides the information.

[0063] The location data hub 110 can generally provide various location-based services indoors by calculating a more accurate indoor location compared to fingerprinting methods based on wireless signal strength. The location data hub 110 will improve accuracy in various indoor spaces in the future as standardized UWB / BLE / Wi-Fi technologies become more widespread. The location data hub 110 enables centimeter (CM) level accurate positioning indoors in the case of a mobile device equipped with UWB capabilities. The location data hub 110 can be used in emergency rescue and disaster situations.

[0064] The location data hub 110 manages BLE RSSI, Wi-Fi RSSI, LTE&5G RSSI reference information. The location data hub 110 manages UWB ranging, BLE channel sounding, and Wi-Fi FTM information. The location data hub 110 manages anchors that can be image recognized in Google Maps Place image. The location data hub 110 calculates the user's location using image anchor recognition from a mobile camera. The location data hub 110 provides location information to the user using TPH information in the mobile SDK.

[0065] FIG. 4 is a diagram illustrating a process in which data is transmitted from a VPS anchor to a location data hub according to an embodiment of the present invention.

[0066] A VPS (Virtual Private Server) anchor performs image crawling based on a path on a mobile device to generate image crawling data. The VPS anchor extracts only place images from the image crawling data using AI analysis. The VPS anchor transmits location measurement information to the location data hub 110 based on the place images.

[0067] FIG. 5 is a diagram illustrating location data using a VPS anchor, BLE, UWB, and Wi-Fi signals according to this embodiment.

[0068] The location data hub 110 determines a precise location using a combination of BLE RSSI and Wi-Fi RSSI, and then maps the precise location on a map using VLAM. The location data hub 110 determines a precise location using a combination of VPS anchors, BLE, UWB, and Wi-Fi radio round trip time (RTT), and then maps the precise location on a map using VLAM.

[0069] FIG. 6 is a diagram showing the TPH reference anchor and the TPH reference position according to this embodiment.

[0070] The location data hub 110 classifies categories for TPH reference anchors into BLE, Wi-Fi, UWB, BLE2, Wi-Fi2, LTE, 5G, and Vision, maps them in a table, and stores them. The location data hub 110 classifies types for categories for TPH reference anchors into Beacon, AP, Anchor, Carrier, and Image, maps them in a table, and stores them. The location data hub 110 maps installation location coordinates (X, Y, Z) for categories for TPH reference anchors in a table, and stores them. The location data hub 110 maps installation addresses for categories for TPH reference anchors in a table, and stores them.

[0071] The location data hub 110 classifies the type of the TPH reference location into point and area and stores the type in a table. The location data hub 110 maps and stores the installation position coordinates (X, Y, Z) of the TPH reference location in a table. The location data hub 110 maps and stores the signal strength (RSSI) of BLE, Wi-Fi, LTE, 5G, UWB, BLE2, Wi-Fi2, and Vision for the TPH reference location in a table.

[0072] The TPH reference location is stored in a table with values ​​corresponding to each communication method based on the current location of the terminal. The location data hub 110 extracts from the database the signal most similar to the signal received from the mobile device and determines the reference location. The location data hub 110 searches for the closest location among the multiple reference locations.

[0073] FIG. 7 is a diagram illustrating an operation process of the location data hub according to the present embodiment.

[0074] The position data hub 110 downloads the reference anchor information using the SDK and then starts indoor positioning (S710). The position data hub 110 performs BLE / Wi-Fi RSSI-based indoor positioning (S720).

[0075] The location data hub 110 selects a reference device (Ref Device) closest to the mobile device based on the indoor location result (S730). The location data hub 110 checks whether a ranging device (Ranging Device) has been selected (S740).

[0076] If the device is selected as a ranging device as a result of the check in step S740, the location data hub 110 calculates a ranging distance value to calculate a final location (S750).The location data hub 110 provides location information to the user using the SDK (S760).

[0077] The location data hub 110 restarts the BLE / Wi-Fi RSSI location calculation (S770). If the device is not selected as a ranging device as a result of the check in step S740, the location data hub 110 selects another ranging device via the server (S780).

[0078] In Fig. 7, steps S710 to S780 are executed in sequence, but this is not necessarily limited to this. In other words, the steps shown in Fig. 7 may be executed in a modified manner, or one or more steps may be executed in parallel, and Fig. 7 is not limited to a chronological order.

[0079] As described above, the operation process of the location data hub according to this embodiment shown in Fig. 7 may be implemented by a program and recorded in a computer readable recording medium. The computer readable recording medium on which the program for implementing the operation process of the location data hub according to this embodiment is recorded includes any kind of recording device in which data readable by a computer system is stored.

[0080] The above description is merely an illustrative example of the technical idea of ​​the present embodiment, and various modifications and variations are possible within the scope of the essential characteristics of the present embodiment if one has ordinary knowledge in the technical field to which the present embodiment belongs. Therefore, the present embodiment is intended to explain, not to limit, the technical idea of ​​the present embodiment, and the scope of the technical idea of ​​the present embodiment is not limited by such an embodiment. The scope of protection of the present embodiment should be interpreted according to the appended claims, and all technical ideas within the scope equivalent thereto should be interpreted as being included in the scope of the present embodiment. [Explanation of symbols]

[0081] 110 Location Data Hub 102 DB 104 Data Acquisition Section 106 First reference positioning unit 108 Second reference positioning unit 109 Mixed Positioning Unit

Claims

1. a DB for storing mapping information in which a plurality of sensing values ​​previously collected are mapped to each divided area obtained by dividing a predetermined area by predetermined identification information; a data acquisition unit that acquires a plurality of sensing values ​​from a mobile device and location measurement information from a VPS (Virtual Private Server) anchor; a first reference position determining unit for determining a first reference position for the mobile device based on a received signal strength indicator (RSSI) of a specific sensing value among the plurality of sensing values ​​and a reference position of the same category as the specific sensing value included in the mapping information; a second reference position determining unit for determining a second reference position for the mobile device based on information having a same category as the remaining sensing values ​​excluding the specific sensing value among the plurality of sensing values; a hybrid position measurement unit that measures a precise position of the mobile device based on the first reference position and the second reference position, The VPS anchor generates image crawling data based on a route for the mobile device, extracts a place image from the image crawling data using AI analysis, and transmits the location measurement information based on the place image to the data acquisition unit; The location data hub is characterized in that the hybrid location measurement unit measures a precise location by combining a VPS anchor, BLE, UWB, and Wi-Fi radio wave round trip time (RTT).

2. The plurality of sensing values ​​are 2. The location data hub of claim 1, comprising at least two of Wi-Fi RSSI, BLE RSSI, UWB RSSI, LTE / 5G RSSI, UWB Ranging, BLE Channel Sounding, Wi-Fi FTM (Fine Time Measurement), and Vision.

3. The first reference position measurement unit includes: Extracting a plurality of the BLE RSSIs included in the plurality of sensing values, and selecting a BLE RSSI having a maximum strength from the plurality of the BLE RSSIs; Extracting identification information having the same category as the BLE having the maximum strength from the mapping information; 3. The location data hub of claim 2, further comprising: determining a first reference location for the mobile device based on a reference location mapped to an identity having the same category as the BLE having the greatest strength.

4. The second reference position measuring unit includes: Extracting remaining sensing values ​​excluding the BLE from the plurality of sensing values; The location data hub of claim 1 , further comprising: determining a second reference location for the mobile device based on a reference location having the same category as the remaining sensing values ​​included in the mapping information.

5. The second reference position measuring unit includes: Extracting a plurality of the Wi-Fi RSSIs included in the plurality of sensing values, and selecting a Wi-Fi RSSI having a maximum strength from the plurality of the Wi-Fi RSSIs; Extracting identification information having the same category as the Wi-Fi having the maximum strength from the mapping information; 10. The location data hub of claim 1, further comprising: determining a second reference location for the mobile device based on a reference location mapped to an identity having the same category as the Wi-Fi with the strongest strength.

6. The second reference position measuring unit includes: Extracting a plurality of BLE rangings included in the plurality of sensing values, and selecting a BLE ranging having a closest distance based on the plurality of BLE rangings; Extracting identification information having the same category as the BLE having the closest distance from the mapping information; 2. The location data hub of claim 1, further comprising: determining a second reference location for the mobile device based on a reference location mapped to an identity having the same category as the BLE having the closest distance.

7. The second reference position measuring unit includes: Extracting a plurality of Wi-Fi rangings included in the plurality of sensing values, and selecting a Wi-Fi ranging having a closest distance based on the plurality of Wi-Fi rangings; Extracting identification information having the same category as the Wi-Fi with the closest distance from the mapping information; 10. The location data hub of claim 1, further comprising: determining a second reference location for the mobile device based on a reference location mapped to an identity having the same category as the Wi-Fi having the closest distance.

8. The mixed position measurement unit is The location data hub of claim 1 , wherein the precise location for the mobile device is determined to be one of an average value, a weighted average value, an interpolated value, and an intermediate value of the first reference location and the second reference location.

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