KR101950328B1 - Method and server for updating database for indoor localization - Google Patents

Abstract

According to another aspect of the present invention, there is provided a database updating method for indoor location measurement, comprising the steps of: (a) sequentially receiving fingerprint information indicative of Wi-Fi signal strength at each reference point in an indoor area according to movement of the user terminal from a user terminal; (b) detecting a movement path of the user terminal using the fingerprint information previously stored in the database, based on the order of the received fingerprint information, Storing fingerprint information for each reference point classified according to clusters; And (c) updating the database based on the reference point of the fingerprint information included in the movement path of the user terminal and the Wi-Fi signal strength.

Description

[0001] METHOD AND SERVER FOR UPDATING DATABASE FOR INDOOR LOCALIZATION [0002]

The present invention relates to a database updating technique, and more particularly, to a database updating method for updating a database for storing and managing fingerprint information necessary for performing indoor position measurement according to fingerprint information received from a user, An update method and a server.

Recently, indoor location tracking technology has been applied not only to private sector such as indoor navigation, location based advertisement service and social network service, but also to emergency rescue service and rescuer (eg, firefighter) , Police officers, etc.) in the public sector.

There is a method of using the fingerprint database in the indoor location measurement method, which is more stable than other methods in terms of location accuracy, and does not require additional infrastructure cost. A method of using a fingerprint information database is firstly conducted to conduct a survey of an indoor place to generate a database of Wi-Fi fingerprint information, and a test to find similar fingerprint information for position measurement is performed. The investigation of the indoor place is performed in order to collect fingerprint information for each reference point, where the fingerprint information includes the location of the reference point and the received signal strength ). ≪ / RTI > In the test step, the kth closest position (kNN) is measured according to RSSI (Received Signal Strength Indicator) received from the user terminal, or the position is measured by probabilistic approaches.

In methods using such a fingerprint information database, the accuracy of the measured indoor location is highly dependent on the reliability of the fingerprint information database. However, the WiFi signal intensity is changed even at the same position, and when the structures blocking the WiFi signal are newly arranged in the middle, the condition of the RSS stored in the fingerprint information database differs from the condition of the RSS stored beforehand. Therefore, it is necessary to update and maintain the fingerprint information database in the latest state.

Several methods for updating the fingerprint information database according to the necessity of updating the fingerprint information database have been proposed, and there is a method of receiving feedback from a user, a method using RF bluetooth or a reference device such as a sensor.

The user feedback based methods are a method of receiving the changed characteristics of the RSS from the user and acquiring the fingerprint information database so that additional sensor devices are not required but should prompt user feedback and incorrect RSS features and positions There is a problem that can be reported.

The methods using additional referencing devices may be used to locate additional sensor devices such as ZigBee, Blutooth, RFID, and UWB as landmark points to update the fingerprint information database, detect transient changes in WiFi terminals, Or Wi-Fi detectors to re-create fingerprint information databases based on machine learning-based algorithms. Such methods do not require additional room inspection, but have a problem of cost loss because additional devices are required, and are not suitable for handling a relatively large indoor area such as a large shopping mall.

Korean Patent No. 10-1621839 U.S. Patent No. 9,335,175

It is an object of the present invention to provide a database updating method for updating a fingerprint information database by a crowd sourcing method so that an indoor location measuring system automatically recognizes a current state of RSS conditions.

It is an object of the present invention to provide a method and system for updating a fingerprint information database that updates a fingerprint information database based on fingerprint information contained in a path of a user by using the entire sequence of RSS vectors of fingerprint information received from a user terminal, Method.

According to a first aspect of the present invention, there is provided a wireless communication method comprising the steps of: (a) sequentially receiving fingerprint information indicative of a Wi-Fi signal strength at each reference point in an indoor area in accordance with movement of the user terminal from a user terminal and (b) detecting a movement path of the user terminal using the fingerprint information previously stored in the database, based on the order of the received fingerprint information, Stores fingerprint information for each reference point classified according to clusters according to the reference points; And (c) updating the database based on the reference point of the fingerprint information included in the movement path of the user terminal and the Wi-Fi signal strength.

Preferably, the database may manage fingerprint information of at least one reference point included in a specific path of the indoor area as one cluster corresponding to the specific path.

Preferably, the database may arrange at least one fingerprint information included in the cluster in the cluster according to x-y coordinates of the position of the reference point.

Preferably, the step (b) includes searching the database for a cluster including fingerprint information similar to the fingerprint information at each reference point received by the user terminal according to movement of the user terminal, , The clusters may be sequentially retrieved according to the order of the received fingerprint information.

The step (b) may further include detecting a moving direction of the user terminal based on the searched cluster.

Preferably, the step (b) may include filtering and removing redundant clusters and erroneous clusters in the retrieved clusters.

The step (b) may include searching fingerprint information included in the same cluster as the filtered cluster in the database and rearranging the reference points included in the cluster according to the moving direction have.

The step (b) may include extracting an expected movement path from the reordered fingerprint information according to a pattern length of a Wi-Fi signal intensity received from the user terminal; And calculating a distance difference between the extracted anticipated movement route and the Wi-Fi signal intensity received from the user terminal, and determining an anticipated movement route corresponding to the minimum distance difference as the movement route of the user terminal can do.

The step (c) may include calculating a reference point and a WiFi signal intensity of the fingerprint information included in the movement path of the user terminal and an average value of WiFi signal strengths of the corresponding reference point previously stored in the database; And updating the corresponding fingerprint information of the database with the average value.

According to a second aspect of the present invention, there is provided a fingerprint information receiving apparatus for sequentially receiving fingerprint information indicative of a WiFi signal strength at each reference point in an indoor area in accordance with movement of the user terminal from a user terminal, ; And a movement path detector for detecting a movement path of the user terminal using the fingerprint information previously stored in the database based on the order of the received fingerprint information, Storing fingerprint information for each reference point grouped by cluster; And an update unit updating the database based on the reference point and the WiFi signal strength included in the movement path of the user terminal.

Preferably, the database may manage fingerprint information of at least one reference point included in a specific path of the indoor area as one cluster corresponding to the specific path.

Preferably, the database may include at least one fingerprint information included in the cluster arranged in each cluster according to an x-y coordinate of a position of the reference point.

Preferably, the movement path detecting unit searches the database for a cluster including fingerprint information similar to the fingerprint information at the reference point received by the user terminal according to movement of the user terminal, The clusters may be sequentially retrieved according to the order of the information.

Preferably, the movement path detecting unit may detect a moving direction of the user terminal based on the searched cluster.

Preferably, the movement path detecting unit removes redundant clusters and erroneous clusters in the retrieved clusters.

Preferably, the movement path detecting unit searches the database for fingerprint information included in the same cluster as the filtered cluster, and rearranges the reference points included in the cluster according to the moving direction.

Preferably, the movement path detecting unit extracts an estimated movement path from the reordered fingerprint information according to the pattern length of the WiFi signal intensity received from the user terminal, extracts an expected movement path from the re- The mobile terminal can determine the estimated movement path corresponding to the minimum distance difference as the movement path of the user terminal by calculating the distance difference between the WiFi signal strengths.

Preferably, the updating unit calculates a reference point of the fingerprint information included in the movement path of the user terminal, a Wi-Fi signal strength, and an average value of Wi-Fi signal strength for a corresponding reference point previously stored in the database, It is possible to update the corresponding fingerprint information of the fingerprint information.

As described above, according to the present invention, even if the environment of the indoor space is changed, the database for storing the fingerprint information can be updated without further investigation of the indoor space.

Further, even if the environment of the indoor space is changed and the user moves through the area where the RSS conditions are changed, there is an effect that the travel path of the user can be accurately detected.

In addition, since the database for storing and managing the fingerprint information is updated, the accuracy of the indoor position measurement is improved.

1 is a block diagram of a database updating system for indoor position measurement according to a preferred embodiment of the present invention.
2 is a block diagram of a database update server for indoor location measurement according to an embodiment of the present invention.
3 is a flowchart illustrating a database updating method for indoor location measurement according to an embodiment of the present invention.
4 is a diagram illustrating an environment in which a database updating method for indoor location measurement is performed according to an embodiment of the present invention.
5 is a graph illustrating changes in RSSI characteristics according to relocation of a Wi-Fi terminal.
6 is a diagram showing a region where the RSS characteristic is changed and a movement route of the user.
7 is a diagram showing reference points.
8A and 8B are diagrams showing experimental results on the error rate of the indoor position measurement.
9 is a diagram showing an experimental result on the error rate of the indoor position measurement.

BRIEF DESCRIPTION OF THE DRAWINGS The advantages and features of the present invention and the manner of achieving them will be more apparent from the following detailed description taken in conjunction with the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Is provided to fully convey the scope of the invention to those skilled in the art, and the invention is only defined by the scope of the claims. Like reference numerals refer to like elements throughout the specification. "And / or" include each and every combination of one or more of the mentioned items.

Although the first, second, etc. are used to describe various elements, components and / or sections, it is needless to say that these elements, components and / or sections are not limited by these terms. These terms are only used to distinguish one element, element or section from another element, element or section. Therefore, it goes without saying that the first element, the first element or the first section mentioned below may be the second element, the second element or the second section within the technical spirit of the present invention.

Also, in each step, the identification code (e.g., a, b, c, etc.) is used for convenience of explanation, and the identification code does not describe the order of each step, Unless the order is described, it may happen differently from the stated order. That is, each step may occur in the same order as described, may be performed substantially concurrently, or may be performed in reverse order.

The terminology used herein is for the purpose of illustrating embodiments and is not intended to be limiting of the present invention. In the present specification, the singular form includes plural forms unless otherwise specified in the specification. It is noted that the terms "comprises" and / or "comprising" used in the specification are intended to be inclusive in a manner similar to the components, steps, operations, and / Or additions.

Unless defined otherwise, all terms (including technical and scientific terms) used herein may be used in a sense commonly understood by one of ordinary skill in the art to which this invention belongs. Also, commonly used predefined terms are not ideally or excessively interpreted unless explicitly defined otherwise.

In the following description of the present invention, detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear. The following terms are defined in consideration of the functions in the embodiments of the present invention, which may vary depending on the intention of the user, the intention or the custom of the operator. Therefore, the definition should be based on the contents throughout this specification.

1 is a block diagram of a database updating system for indoor position measurement according to a preferred embodiment of the present invention.

Referring to FIG. 1, a database update system 100 for indoor location measurement includes a Wi-Fi terminal 110, a user terminal 120, a database update server 130, and a database 140.

The Wi-Fi terminal 110 is a device for generating a Wi-Fi signal and may be disposed in an indoor space, and preferably, a plurality of Wi-Fi terminals 110 may be provided in an indoor space.

The user terminal 120 is a terminal carried by a user moving in the indoor space and is a device for receiving a Wi-Fi signal from the Wi-Fi terminal 110. Preferably, the user terminal 120 can receive a Wi-Fi signal having a different signal strength generated from each Wi-Fi terminal 110 disposed in the indoor space, and can receive the Wi- And may provide the database update server 130 with fingerprint information that includes the strength of the signal. For example, the user terminal 120 may be a smart phone based on an open operating system that allows a user to freely use and delete various application programs desired by the user. In addition, the user terminal 120 has not only all the mobile phones having the mobile office function or the voice communication function but also all the tablet PCs that can access the internet, It is preferable that the communication device is a communication device.

The database update server 130 is connected to the user terminal 120 through a network to perform indoor position measurement and updates the fingerprint information stored in the database 140 according to the fingerprint information provided from the user terminal 120 Device. The database update server 130 may measure the indoor position of the user terminal 120 in accordance with the fingerprint information provided from the user terminal 120. In addition to measuring the indoor position of the user terminal 120, And can update the database using the fingerprint information included in the movement path of the user. In addition, the database update server 130 may receive the fingerprint information from the plurality of user terminals 120 and update the database.

The database 140 is a device connected to the database update server 130 to provide data so that the database update server 130 can perform indoor position measurement. Preferably, the database 140 may store and manage WiFi signal strength, i.e. fingerprint information, at each reference point for a particular indoor space, and may store and manage fingerprint information stored and managed by the database update server 130 Can be updated.

2 is a block diagram of a database update server for indoor location measurement according to an embodiment of the present invention.

2, the database update server 130 includes a fingerprint information receiving unit 210, a movement path detecting unit 220, an updating unit 230, and a control unit 240, Controls the operation of the fingerprint information receiving unit 210, the movement path detecting unit 220, and the updating unit 230 and the flow of data.

Hereinafter, a database update method for indoor position measurement according to an embodiment of the present invention, which is performed through each configuration of the database update server 130, will be described with reference to FIG.

First, a database updating method according to the present invention is a method for updating a database, wherein a user has a user terminal 120, moves an indoor area while maintaining a moving direction and a moving speed, And receiving the Wi-Fi signal generated from the mobile terminal 110 and providing the order of RSS vectors to the database update server 130. Hereinafter, the method of updating the database will be described with reference to the indoor space shown in FIG. do. In addition, it is assumed that a database including fingerprint information for the indoor space shown in FIG. 4 is generated in advance, and indoor position measurement is performed using such a database.

During the performance of indoor positioning in the environment shown in FIG. 4, some WiFi terminals 110 may be relocated as shown in FIG. However, if the database 140 does not recognize a change to the relocation of the WiFi terminal 110, the RSS features will be significantly changed as shown in FIG. Referring to FIG. 5, it can be seen that the blue asterisk is an RSS characteristic before relocation of the Wi-Fi terminal 110, and the red square indicates a change in RSS measurement value as an RSS characteristic after relocation of the Wi-Fi terminal 110 . Significant changes in these RSS features cause the accuracy of the indoor location measurement to deteriorate drastically, and in particular, the position error occurs in the area where the Wi-Fi terminal 110 is removed (FIG. 4A).

Accordingly, the present invention allows the indoor location measurement system 100 to recognize changed RSS features through the database update method, and only a part of the user's movement path is in the area where the RSS feature is changed, And to determine the movement route of the user using the fact that the user is in the unchanged area. For example, referring to FIG. 6, if the RSS characteristic of the fingerprint information of the database 140 initially generated in the blue circle is considerably changed, and the user moves from A to B, Can be included in the changed portion of the RSS feature.

First, the fingerprint information receiving unit 210 sequentially receives fingerprint information indicating the Wi-Fi signal strength at each reference point in the indoor area according to the movement of the user terminal 120 from the user terminal 120 (step S310 ). Herein, RSS vectors of sequentially received fingerprint information may describe a WiFi signal space for a spatially contiguous area, and sequentially receiving may correspond to receiving information on the order of received fingerprint information do. Referring to FIG. 7, the reference points indicate points in the indoor space where the fingerprint information receiving unit 210 receives the WiFi signal strength from the user terminal 120, and are represented by red squares in FIG.

The movement path detection unit 220 detects the movement path of the user terminal 120 using the fingerprint information stored in the database 140 based on the order of the fingerprint information received through the fingerprint information receiving unit 210 (Step S320). Preferably, the movement path detecting unit 220 detects clusters including fingerprint information similar to the fingerprint information at the reference point received by the user terminal 120 according to the movement of the user terminal 120 in the database 140 And sequentially search clusters according to the order of the received fingerprint information.

Here, the database 140 may manage the fingerprint information of at least one reference point included in a specific path of the indoor area as one cluster corresponding to a specific path, and may include at least one fingerprint The information may be arranged in the cluster according to the xy coordinates of the location of the reference point.

For example, each of the reference points shown in FIG. 7 is clustered as shown in [Table 1] below, and each of the reference points included in each cluster can be arranged according to their coordinates. Here, RP _i is a reference point corresponding to i in Fig. Referring to Table 1, the reference points in C ₁ are arranged in ascending order of their x coordinates, and the reference points in C ₄ are arranged in descending order of their y coordinates.

Clusters Elements C _One RP ₁ , RP ₂ , RP ₃ , RP ₄ , RP ₅ , RP ₆ , RP ₇ C ₂ RP ₈ , RP ₉ , RP ₁₀ , RP ₁₁ , RP ₁₂ C ₃ RP ₁₃ , RP ₁₉ , RP ₁₈ , RP ₁₇ , RP ₁₆ , RP ₁₅ , RP ₁₄ C ₄ RP ₂₀ , RP ₂₁ , RP ₂₂ , RP ₂₃ , RP ₂₄

That is, the database 140 manages each reference point as a cluster as shown in [Table 1], and the movement path detecting unit 220 detects finger points of the reference points received at the reference points received by the user terminal 120, will the cluster containing the printed information to retrieve from the database 140 in order, for _{example, {C 1, C 1,} C 3, C 1, C 2, C 2, C 1, C 2, C 2} . ≪ / RTI >

Preferably, the movement path detecting unit 220 can detect the moving direction of the user terminal 120 through filtering and removing redundant clusters and erroneous clusters in the retrieved clusters. For example, on the basis of the fingerprint information received from a user terminal 120, the cluster is retrieved from the database _{(140) {C 1, C} 1, C 3, C 1, C 2, C 2, C 1, C 2 , C ₂ }, the clusters are filtered to {C ₁ , C ₂ } when the duplicated clusters and the wrong clusters are removed, whereby the movement path detecting unit 220 detects the moving direction of the user terminal 120 C ₁ - > C ₂ .

More specifically, removing the wrong clusters from the retrieved clusters may be performed using the feature that one cluster represents a relatively large space, i.e., one cluster includes a plurality of reference points. For example, the discovered clusters _{{C 1, C 1, C} 3, C 1, C 2, C 2, C 1, C 2, C 2} as determined by the case, based on the fingerprint information, C _1, C ₂ Is determined in consideration of the error range of the system according to the present invention and can be determined relatively accurately in consideration of an error range that can be caused by using the Wi-Fi. In this case, since the position of the user terminal 120 held by the user can not be largely changed in reality, if the user is assumed to be in the C ₁ cluster, the user can move to the C ₂ cluster which is the adjacent region, a C ₃ because it is not possible to abruptly move to the cluster, the movement route detecting section 220 may filter the wrong cluster, taking into account the flow of the retrieved cluster. That is, when the retrieved cluster is {C ₁ , C ₁ , C ₃ , C ₁ , C ₂ , C ₂ , C ₁ , C ₂ , C ₂ }, C ₃ can be filtered as a bad cluster.

Preferably, the movement path detector 220 searches the database 140 for reference points included in the same cluster as the filtered cluster, and reorders the reference points according to the detected movement direction. For example, the filtered clusters are {C ₁ , C ₂ } and the reference points included in the cluster are C ₁ = {RP ₁ , RP ₂ , ... , RP ₇ } and C ₂ = {RP ₈ , RP ₉ , ... , RP ₁₂ }, and since the detected movement direction is C ₁ - > C ₂ , the movement path detection unit 220 detects C ₁ And the reference points included in C ₂ are {RP ₁ , RP ₂ , ... , RP ₁₂ }. If the detected movement direction is C ₂ -> C _1, then the reference points are {RP ₁₂ , RP ₁₁ , ... , RP ₁ }.

Preferably, the movement path detector 220 detects the reference point (s) according to the length of the RS _user (RSS sequence reported by the user) of the user terminal 120, that is, the pattern length of the signal strength received by the user terminal 120 It is possible to determine the estimated travel route corresponding to the minimum distance difference as the travel route of the user terminal 120 by calculating the estimated travel route among the estimated travel route and the estimated distance traveled by the RS _user . Here, the length of the RS _user differs depending on the position at which the user terminal 120 receives the Wi-Fi signal. For example, when the user terminal 120 receives a signal at each step as the user moves five steps The length of the RS _user is 5, and if the user terminal 120 receives a signal at each step as the user moves 10 steps, the length of the RS _user may be 10.

More specifically, the reordered reference points {RP ₁ , RP ₂ , ... , RP ₁₂ }, the movement path detecting unit 220 can extract seven expected movement paths according to the length of the RS _user (for example, the length of the RS _user = 6) as shown in Table 2 below , And the distance from the RS _user can be calculated using the following Equation (1) for each of the predicted movement paths extracted. Here, when RSS is sequentially received from the user terminal 120, {rss ₁ , rss ₂ , ... rss _6} of the RS and each _{user i} rss is an RSS (Received Signal Strength) value vector consisting of RSSI from a plurality of Wi-Fi terminals. That is, rss _i and rss _j are vector values of the RSS values received at the i-th and j-th positions, respectively, and represent vector values of the Wi-Fi signal strengths received at the i-th and j-th positions.

RP ₁ , RP ₂ , RP ₃ , RP ₄ , RP ₅ , RP ₆ RP ₅ , RP ₆ , RP ₇ , RP ₈ , RP ₉ , RP ₁₀ RP ₂ , RP ₃ , RP ₄ , RP ₅ , RP ₆ , RP ₇ RP ₆ , RP ₇ , RP ₈ , RP ₉ , RP ₁₀ , RP ₁₁ RP ₃ , RP ₄ , RP ₅ , RP ₆ , RP ₇ , RP ₈ RP ₇ , RP ₈ , RP ₉ , RP ₁₀ , RP ₁₁ , RP ₁₂ RP ₄ , RP ₅ , RP ₆ , RP ₇ , RP ₈ , RP ₉

[Formula 1]

Here, d _seq is the difference between the distance, that is, the user terminal WiFi signal strength received by the (120) (rss) and stored in the database, wi-fi signal strength (rss) in from the RS _user, RS _user (i) And path (i) denote RS _user and path i, respectively, and d (rss _i , rss _j ) is the Euclidean distance between rss _i and rss _j . For example, the Wi-Fi signal strength difference pre-stored in the Wi-Fi signal strengths with a database (140) received by the user terminal 120 has any similarity d _seq If the Wi-Fi signal strength received by the user terminal 120 is not similar to the Wi-Fi signal strength stored in the database 140, the difference d _seq may be large.

If d _seq for each expected movement route is calculated through Equation (1), the movement route detection unit 220 determines the estimated movement route having the minimum d _seq value as the movement route of the user. Since the present invention detects the movement path of the user using the sequence of the fingerprint information received from the user terminal 120, it is possible to perform more accurate position measurement than the RSS vector-based position measurement method, Likewise, even if the RSS characteristic is changed due to the movement of the Wi-Fi terminal 110 or the like, the position can be accurately measured.

When the movement path of the user terminal 120 is determined through the movement path detection unit 220, the update unit 230 updates the reference point of the fingerprint information included in the movement path of the user terminal 120 and the WiFi signal strength (Step S330). The update unit 230 may calculate the average value of the WiFi signal intensity of the fingerprint information included in the movement path of the user terminal 120 and the WiFi signal intensity and the WiFi signal intensity of the corresponding reference point previously stored in the database 140 And updates the corresponding fingerprint information of the database 140, that is, the WiFi signal strength for the reference point, as an average value.

In one embodiment, if all the RSS vectors in the RS _{user result} in an erroneous RSSI (e.g., all RSS vectors are reported in the changed area, or the user has signal blocking materials) Lt; / RTI > More specifically, in order to determine whether or not the data is erroneous, it is possible to measure d _seq for RSS sequences labeled at similar positions, and to use the Wi-Fi signal intensity of the reference points included in the movement path having the minimum d _seq value, (140) is updated. That is, the RSS sequences labeled with the same path are similar to each other even if the RSS conditions are changed, but the wrong RSS sequences are not. If the situation changes such as change of indoor structure, change of people condition, addition of Wi-Fi terminals, etc., the RSS may be changed, but as a whole, it may be similar to the RSS stored in the database.

Accordingly, the present invention is based on a comparison between the Wi-Fi signal strength received from the user terminal 120 and the Wi-Fi signal intensity previously stored in the database 140, However, since the WiFi signal strength is collected at a plurality of locations and the pattern is viewed as a whole, there will be a similarity between the WiFi signal strengths. Therefore, a plurality of WiFi signal strengths collected at a plurality of locations through calculation of d _seq , To compare the set of WiFi signal strengths previously stored in the database 140, and thus to determine the data for updating the database 140.

8A and 8B are diagrams showing experimental results on the error rate of the indoor position measurement.

8A and 8B, experimental results of the indoor location measurement using the database updating method according to the present invention and the indoor location measurement using the clustering based kNN will be described.

The results of the measured indoor positions are compared after relocating the three WiFi terminals in a state where an initial database for storing and managing the fingerprint information for the indoor area as shown in FIG. 8A is created.

Referring to FIG. 8A, as a result of the indoor position measurement, the indoor positions measured according to the present invention are indicated by red asterisks, and the indoor positions measured by the kNN system are indicated by black squares.

Referring to FIG. 8B, it can be seen that the error rate of the present invention and the kNN scheme for the movements shown in FIG. 8A are lower than that of the kNN scheme. Specifically, the method according to the present invention shows that the maximum error corresponds to 3 (m) while the method according to kNN corresponds to a maximum error of 6 (m). That is, it can be seen that the method according to the present invention has better performance than the kNN method and can provide more accurate position measurement.

9 is a diagram showing an experimental result on the error rate of the indoor position measurement.

The results of the experiment shown in FIG. 9 are obtained by rearranging a plurality of Wi-Fi terminals as shown in FIG. 4 in a state where a database is created, and then applying indoor location measurement results using a database updating method according to the present invention and kNN Indicates the result of indoor location measurement.

Referring to FIG. 9, the errors of the indoor positions measured by applying the kNN-based method are much larger than the errors of the indoor positions measured by updating the database according to the present invention. In particular, the kNN-based scheme exhibits much larger position errors in areas where Wi-Fi terminals are moved to other areas, but the scheme according to the present invention still exhibits high accuracy even when Wi-Fi terminals are rearranged.

Therefore, when the indoor location is measured by applying the database updating method according to the present invention, the database is updated using the fingerprint information provided from a plurality of user terminals even if the RSS characteristics of the indoor environment change, , The database for storing and managing fingerprint information is always kept up-to-date, so that the accuracy of position measurement can be kept high compared to other conventional methods.

Meanwhile, the database updating method for indoor position measurement according to an embodiment of the present invention can also be implemented as a computer-readable code on a computer-readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored.

For example, the computer-readable recording medium includes a ROM, a RAM, a CD-ROM, a magnetic tape, a hard disk, a floppy disk, a removable storage device, a nonvolatile memory, , And optical data storage devices.

In addition, the computer readable recording medium may be distributed and executed in a computer system connected to a computer communication network, and may be stored and executed as a code readable in a distributed manner.

Although the present invention has been described in connection with the preferred embodiments thereof with reference to the accompanying drawings, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, It is possible to carry out the modification and belong to the present invention.

100: Database Update System
110: Wi-Fi terminal
120: User terminal
130: database update server
140: Database
210: fingerprint information receiver
220:
230:
240:

Claims (18)

(a) sequentially receiving fingerprint information indicating a Wi-Fi signal strength at each reference point in an indoor area, in accordance with movement of the user terminal from a user terminal;
(b) detecting a movement path of the user terminal using the fingerprint information previously stored in the database, based on the order of the received fingerprint information, Storing fingerprint information for each reference point classified according to clusters; And
(c) updating the database based on a reference point of the fingerprint information included in the movement path of the user terminal and a Wi-Fi signal intensity, the method comprising the steps of:
The step (b)
Searching the database for a cluster including fingerprint information similar to fingerprint information at each reference point received by the user terminal according to movement of the user terminal, wherein the sequence of received fingerprint information Wherein the clusters are sequentially searched according to the location of the clusters.
2. The method of claim 1, wherein the database
Wherein fingerprint information of at least one reference point included in a specific path of the indoor area is managed as one cluster corresponding to the specific path.
3. The method of claim 2, wherein the database
Wherein at least one fingerprint information included in the cluster is arranged in the cluster according to xy coordinates of a position of the reference point.
delete 2. The method of claim 1, wherein step (b)
Further comprising the step of detecting a direction of movement of the user terminal based on the searched cluster.
6. The method of claim 5, wherein step (b)
And filtering and removing redundant clusters and erroneous clusters in the retrieved clusters.
7. The method of claim 6, wherein step (b)
Searching the fingerprint information included in the same cluster as the filtered cluster and rearranging the reference points included in the cluster according to the moving direction in the database, How to update.
8. The method of claim 7, wherein step (b)
Extracting an expected movement path from the reordered fingerprint information according to a pattern length of a Wi-Fi signal intensity received from the user terminal; And
And calculating a distance difference between each of the extracted anticipated movement paths and Wi-Fi signal strength received from the user terminal, and determining an anticipated movement path corresponding to the minimum distance difference as the movement path of the user terminal Wherein the method comprises the steps of:
2. The method of claim 1, wherein step (c)
Calculating a reference point of the fingerprint information included in the movement path of the user terminal and a Wi-Fi signal intensity and an average value of a Wi-Fi signal intensity for a corresponding reference point previously stored in the database; And
And updating the corresponding fingerprint information of the database with the average value.
A fingerprint information receiving unit sequentially receiving fingerprint information indicating a Wi-Fi signal strength at each reference point in an indoor area in accordance with movement of the user terminal from a user terminal;
And a movement path detector for detecting a movement path of the user terminal using the fingerprint information previously stored in the database based on the order of the received fingerprint information, Storing fingerprint information for each reference point grouped by cluster; And
A database update server for indoor location measurement including a reference point included in a movement path of the user terminal and an update unit for updating the database based on a Wi-Fi signal intensity,
The movement path detecting unit
Searching the database for a cluster including fingerprint information similar to the fingerprint information at the reference point received by the user terminal according to the movement of the user terminal, Wherein the server is sequentially retrieved.
11. The system of claim 10, wherein the database
Wherein fingerprint information of at least one reference point included in a specific path of the indoor area is managed as one cluster corresponding to the specific path.
12. The system of claim 11, wherein the database
Wherein at least one fingerprint information included in the cluster is arranged in each cluster according to xy coordinates of a position of the reference point.
delete The apparatus according to claim 10, wherein the movement path detecting unit
Wherein the moving direction of the user terminal is detected based on the searched cluster.
15. The apparatus of claim 14, wherein the movement path detecting unit
And removing duplicated clusters and invalid clusters in the retrieved clusters and filtering the clusters.
16. The apparatus of claim 15, wherein the movement path detecting unit
Wherein in the database, fingerprint information included in the same cluster as the filtered cluster is searched, and the reference points included in the cluster are rearranged according to the moving direction.
17. The apparatus according to claim 16, wherein the movement path detecting unit
Extracting a predicted movement path from the reordered fingerprint information according to a pattern length of the WiFi signal intensity received from the user terminal and comparing a distance difference between the extracted expected movement path and a WiFi signal strength received from the user terminal And determining an estimated movement path corresponding to the minimum distance difference as a movement path of the user terminal.
11. The apparatus of claim 10, wherein the update unit
Calculating a reference point of the fingerprint information included in the movement path of the user terminal and a Wi-Fi signal intensity and an average value of Wi-Fi signal strength for a corresponding reference point previously stored in the database, And updating the indoor position of the vehicle.

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