KR102579579B1 - A method and system for calibrating indoor positioning using mobile devices located in a proximity zone - Google Patents

Abstract

According to an embodiment of the present disclosure, an electronic device for estimating the location of at least one user device located in an indoor space, comprising a memory and at least one processor electronically connected to the memory, the at least one The processor identifies a first user device and a second user device that have the same destination location, and determines the location of the first user device identified as the first location to be a first correction location that corresponds to the first anchor location at the first time point. And, the location of the second user device identified as the second location is determined as the second correction position corresponding to the first anchor position at the second time point corresponding to the first time point, and the location of the first user device is determined to be the second correction position. When the third correction position corresponding to the second anchor position is determined at a third time point, the location of the second user device is set to be determined as the third correction position at a fourth time point corresponding to the third time point, An electronic device may be provided, wherein a first distance between the first position and the first correction position is smaller than a second distance between the second position and the second correction position.

Description

Indoor position correction method and system using mobile devices located in the proximity area {A METHOD AND SYSTEM FOR CALIBRATING INDOOR POSITIONING USING MOBILE DEVICES LOCATED IN A PROXIMITY ZONE}

This disclosure relates to an electronic device that provides an indoor positioning function. More specifically, it relates to an electronic device that provides an indoor positioning function and an indoor map service using indoor map data and positioning data.

Fingerprinting-based indoor positioning technology is used to accurately determine the location of mobile devices and IoT devices indoors. Specifically, to measure indoor location, a map database is created by collecting signals emitted by devices such as Wi-Fi access points (APs) or Bluetooth beacons installed indoors, and then devices such as mobile devices or IoT devices that want to determine the location are used. The location of the device can be determined by comparing the signal received from the database.

Since the indoor positioning technology described above shows high accuracy in determining location, it is used in fields such as smart home, robots, augmented reality, and industrial automation that require accurate location information indoors.

However, because fingerprint-based indoor positioning technology is sensitive to environmental changes, there is a problem in that positioning accuracy is very low when changes occur in the indoor environment (e.g., change in location of indoor structure, change in store location, etc.).

In addition, fingerprint-based indoor positioning technology has the problem of the high cost and effort required to build a map database. In order to create a map database by collecting the location and signal strength of Wi-Fi APs or Bluetooth beacons, it is necessary to travel indoors and collect data directly, so it is inevitable that cost and effort will be incurred in building the database.

One object of the present disclosure is to provide a method for automatically updating indoor maps and positioning data by reflecting changes in the indoor environment.

Another task of the present disclosure is to provide a method of controlling a map application in consideration of the user's usage environment.

Another task of the present disclosure is to improve indoor location accuracy of user devices located in indoor spaces.

Meanwhile, the problem to be solved in this disclosure is not limited to the above-mentioned problems, and problems not mentioned are clear to those skilled in the art from this specification and the attached drawings. It will be understandable.

According to an embodiment of the present disclosure, an electronic device for providing a map service to a plurality of user devices includes a memory and at least one processor electronically connected to the memory, wherein the at least one processor includes at least Receiving a first data set from at least one user device located in a first place including one point of interest, the first data set, first indoor map data corresponding to the first place - At this time, the first indoor map data includes a footprint indicating an area corresponding to the point of interest - and first positioning data corresponding to the first indoor map data - At this time, the first positioning data is Identifying the location of the at least one user device based on at least one of the first location point set including a plurality of location points corresponding to the first indoor map data, and identifying the at least one user identified A second data set reflecting the location of the device is stored in the memory, and the second data set and first movable path data are stored in advance - at this time, the first movable path data is included in the first positioning data. Set based on at least some of a plurality of positioning points or set in consideration of the footprint of the at least one point of interest and the location of at least one fixture included in the first location - Adjustment based on An electronic device configured to identify the target area may be provided.

Additionally, according to an embodiment of the present disclosure, an electronic device for providing a map service to a plurality of user devices includes a memory and at least one processor electronically connected to the memory, wherein the at least one processor , receiving a first data set from at least one user device located in a first place including at least one point of interest, and first indoor map data corresponding to the first place based on the first data set ( At least one attribute of first positioning data corresponding to (indoor map data) - where the first positioning data includes a first positioning point set including a plurality of positioning points corresponding to the first indoor map data. Adjust to obtain second positioning data including a second positioning point set, identify a first target area included in the first indoor map data based on the second positioning data, and identify the first target area included in the first indoor map data. Based on , an electronic device configured to obtain second indoor map data by adjusting at least one parameter related to the first target area may be provided.

Additionally, according to an embodiment of the present disclosure, an electronic device for providing a map service to a plurality of user devices includes a memory and at least one processor electronically connected to the memory, wherein the at least one processor , providing a first indoor map corresponding to the first place to at least one user device located in a first place including at least one point of interest, and providing a first data set from the at least one user device - the first 1 data set includes first sensor data collected by a first sensor included in the user device and second sensor data collected by a second sensor, and based on the first sensor data, the An inter-floor device that identifies inter-floor movement of at least one user device and, in response to the identification operation of the inter-floor movement, indicates an inter-floor movement means associated with inter-floor movement among a plurality of inter-floor movement means pre-stored based on the second sensor data. An electronic device may be provided that is configured to obtain information on means of transportation and provide a second indoor map reflecting the information on means of transportation between floors to a plurality of user devices located in the first location.

Additionally, according to an embodiment of the present disclosure, an electronic device for controlling a map application includes at least one sensor, a memory, and at least one processor electronically connected to the memory, wherein the at least one processor includes, Running an application according to a first operation mode to identify whether indoor entry has occurred, and in response to the indoor entry identification operation, if the movement pattern of the electronic device is the first movement pattern, controlling the application according to a second operation mode, In response to an indoor entry identification operation, when the movement pattern of the electronic device is a first movement pattern, the application is controlled according to a third operation mode, and the operation according to the second operation mode is performed by the at least one processor. , an operation of acquiring first location data corresponding to the location of the electronic device based on access point (AP) data and first acceleration data obtained using the at least one sensor, and the third operation mode. The operation according to this includes acquiring, by the at least one processor, second location data corresponding to the location of the electronic device based on second acceleration data acquired using the at least one sensor, and the second location data corresponding to the location of the electronic device. Based on the location data, a first time period in which the movement pattern of the electronic device changes from the second movement pattern to the first movement pattern is identified, and third location data corresponding to the first time period is stored in the memory. An electronic device including a storage operation may be provided.

Additionally, according to an embodiment of the present disclosure, an electronic device for estimating the location of at least one user device located in an indoor space includes a memory and at least one processor electronically connected to the memory, and the at least one One processor identifies a first user device and a second user device that have the same destination location, and wherein the location of the first user device identified as the first location is configured to generate a first correction location that corresponds to the first anchor location at the first time point. and determine the location of the second user device identified as the second location to be a second correction position corresponding to the first anchor position at a second time point corresponding to the first time point, and If the location is determined to be a third correction position corresponding to the second anchor position at a third time point, the location of the second user device is set to be determined as the third correction position at a fourth time point corresponding to the third time point. An electronic device may be provided, wherein a first distance between the first position and the first correction position is smaller than a second distance between the second position and the second correction position.

The means for solving the problem according to various embodiments are not limited to the above-mentioned solution means, and the solution methods not mentioned may be understood by those skilled in the art from this specification and the attached drawings. You will be able to understand it clearly.

According to various embodiments, a database for indoor positioning can be efficiently built by automatically updating indoor maps and positioning data using the electronic device of the present disclosure.

Additionally, according to various embodiments, using the electronic device of the present disclosure, a map application can be controlled in consideration of the user's usage environment, and functions optimized for each usage environment can be provided to the user.

Additionally, according to various embodiments, the indoor location accuracy of user devices located in an indoor space can be improved using the electronic device of the present disclosure.

The effects according to the embodiments included in the present disclosure are not limited to the above-mentioned effects, and effects not mentioned are clearly apparent to those skilled in the art from the present specification and the attached drawings. It will be understandable.

1 is a diagram illustrating an example system 1 for providing indoor map information, estimating an indoor location, and providing an indoor route, according to various embodiments.
FIG. 2 is a diagram illustrating the configuration of an electronic device included in the example system 1 of FIG. 1 according to various embodiments.
FIG. 3 is a diagram illustrating a detailed configuration of an electronic device that provides a map service based on indoor map data, according to various embodiments.
FIG. 4 is a diagram for explaining indoor map data included in an electronic device, according to various embodiments.
FIG. 5 is a diagram illustrating an indoor positioning data set corresponding to a first location included in an electronic device, according to various embodiments.
FIG. 6 is a diagram illustrating a method by which an electronic device builds a positioning data set, according to various embodiments.
FIG. 7 is a flowchart illustrating a method for an electronic device to measure the location of a user device using an indoor positioning data set, according to various embodiments.
FIG. 8 is a diagram for explaining various types of positioning algorithms performed by an electronic device according to various embodiments.
FIG. 9 is a diagram illustrating an example of an electronic device updating indoor map data, according to various embodiments.
FIG. 10 is a flowchart illustrating an example of an electronic device updating indoor map data, according to various embodiments.
FIG. 11 is a diagram illustrating a specific method for an electronic device to identify a zone to be adjusted, according to various embodiments.
FIG. 12 is a diagram illustrating operations that an electronic device can perform in response to an operation to identify an area to be adjusted, according to various embodiments.
FIG. 13 is a flowchart illustrating another example of an electronic device updating an indoor positioning data set, according to various embodiments.
FIG. 14 is a diagram illustrating an example of an electronic device updating positioning data, according to various embodiments.
FIG. 15 is a diagram illustrating another example of an electronic device updating positioning data, according to various embodiments.
FIG. 16 is a diagram illustrating another example of an electronic device updating positioning data, according to various embodiments.
FIG. 17 is a diagram illustrating an example of an electronic device updating indoor map data, according to various embodiments.
FIG. 18 is a diagram illustrating another example of an electronic device updating an indoor positioning data set, according to various embodiments.
FIG. 19 is a diagram illustrating another example of an electronic device updating an indoor map, according to various embodiments.
FIG. 20 is a flowchart illustrating another example of an electronic device updating an indoor map, according to various embodiments.
FIG. 21 is a diagram illustrating a method by which an electronic device obtains inter-floor movement means information, according to various embodiments.
FIG. 22 is a diagram illustrating a method in which an electronic device provides a second indoor map by reflecting information on means of transportation between floors, according to various embodiments.
FIG. 23 is a flowchart illustrating another example in which an electronic device updates an indoor map by reflecting a means of moving between floors, according to various embodiments.
FIG. 24 is a diagram illustrating air pressure data obtained in situations where various means of moving between floors are used, according to various embodiments.
FIG. 25 is a diagram illustrating a method of controlling an application depending on whether an electronic device enters a room, according to various embodiments.
FIG. 26 is a diagram for explaining various situations in which an electronic device enters an indoor environment from outdoors, according to various embodiments.
FIG. 27 is a diagram illustrating a method by which an electronic device controls the execution of an application based on a movement pattern, according to various embodiments.
FIG. 28 is a diagram for explaining an operation of an electronic device switching an operation mode, according to various embodiments.
FIG. 29 is a diagram illustrating a method for an electronic device to identify floor information, according to various embodiments.
FIG. 30 is a diagram illustrating a specific method for an electronic device and a server to obtain floor information, according to various embodiments.
FIG. 31 is a diagram illustrating an example of a method by which an electronic device corrects its location using positioning results of a plurality of user devices, according to various embodiments.
FIG. 32 is a diagram illustrating an example of a method for an electronic device to correct location information of a user device, according to various embodiments.
FIG. 33 is a diagram illustrating an example of a method by which an electronic device corrects a location based on a path of a user device, according to various embodiments.
FIG. 34 is a flowchart illustrating an example of a method by which an electronic device corrects a location based on a path of a user device, according to various embodiments.
FIG. 35 is a diagram illustrating a method for correcting positions according to differences in scan cycles of a plurality of user devices that are determined to be traveling together, according to various embodiments.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the attached drawings. In describing the embodiments, description of technical content that is well known in the technical field to which this disclosure belongs and that is not directly related to this disclosure will be omitted. This is to convey the gist of the present disclosure more clearly without obscuring it by omitting unnecessary explanation.

The embodiments described in this specification are intended to clearly explain the idea of the present invention to those skilled in the art to which the present invention pertains, and the present invention is not limited to the embodiments described in this specification, and the present invention is not limited to the embodiments described in this specification. The scope should be construed to include modifications or variations that do not depart from the spirit of the present invention.

The terms used in this specification are general terms that are currently widely used as much as possible in consideration of their function in the present invention, but this may vary depending on the intention of those skilled in the art, precedents, or the emergence of new technology in the technical field to which the present invention belongs. You can. However, if a specific term is defined and used with an arbitrary meaning, the meaning of the term will be described separately. Therefore, the terms used in this specification should be interpreted based on the actual meaning of the term and the overall content of this specification, not just the name of the term.

The drawings attached to this specification are intended to easily explain the present invention, and the shapes shown in the drawings may be exaggerated as necessary to aid understanding of the present invention, so the present invention is not limited by the drawings.

As used herein, “A or B”, “at least one of A and B”, “at least one of A or B”, “A, B or C”, “at least one of A, B and C”, and “A Each of phrases such as “at least one of , B, or C” may include any one of the items listed together in the corresponding phrase, or any possible combination thereof.

In this specification, if it is determined that a detailed description of a known configuration or function related to the present invention may obscure the gist of the present invention, the detailed description thereof will be omitted as necessary. In addition, numbers (eg, first, second, etc.) used in the description of this specification are merely identifiers to distinguish one component from another component.

In addition, the suffixes "part" and "part" for components used in the following description are given or used interchangeably only considering the ease of writing the specification, and do not have distinct meanings or roles in themselves.

In other words, the embodiments of the present disclosure are provided to ensure that the present disclosure is complete and to inform those skilled in the art of the present disclosure of the scope of the present disclosure, and that the invention of the present disclosure is within the scope of the claims. It is only defined by Like reference numerals refer to like elements throughout the specification.

Terms such as “first” and/or “second” may be used to describe various components, but the components should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another component, for example, without departing from the scope of rights according to the concept of the present disclosure, a first component may be named a second component, and similarly The second component may also be referred to as the first component.

When a component is said to be "connected" or "connected" to another component, it is understood that it may be directly connected to or connected to the other component, but that other components may exist in between. It should be. On the other hand, when it is mentioned that a component is “directly connected” or “directly connected” to another component, it should be understood that there are no other components in between. Other expressions that describe the relationship between components, such as "between" and "immediately between" or "neighboring" and "directly adjacent to" should be interpreted similarly.

In the drawings, each block of the processing flow diagrams and combinations of the flow diagram diagrams may be performed by computer program instructions. These computer program instructions can be mounted on a processor of a general-purpose computer, special-purpose computer, or other programmable data processing equipment, so that the instructions performed through the processor of the computer or other programmable data processing equipment are described in the flow chart block(s). It creates the means to perform functions. These computer program instructions may also be stored in computer-usable or computer-readable memory that can be directed to a computer or other programmable data processing equipment to implement a function in a particular manner, so that the computer-usable or computer-readable memory The instructions stored in may also be capable of producing manufactured items containing instruction means to perform the functions described in the flow diagram block(s). Computer program instructions can also be mounted on a computer or other programmable data processing equipment, so that a series of operational steps are performed on the computer or other programmable data processing equipment to create a process that is executed by the computer, thereby generating a process that is executed by the computer or other programmable data processing equipment. Instructions that perform processing equipment may also provide steps for executing the functions described in the flow diagram block(s).

Additionally, device-readable storage media may be provided in the form of non-transitory storage media. Here, 'non-transitory' only means that the storage medium is a tangible device and does not contain signals (e.g. electromagnetic waves), and this term refers to cases where data is semi-permanently stored in the storage medium. There is no distinction between temporary storage cases.

Additionally, each block may represent a module, segment, or portion of code that includes one or more executable instructions for executing specified logical function(s). Additionally, it should be noted that in some alternative execution examples it is possible for the functions mentioned in the blocks to occur out of order. For example, it is possible for two blocks shown in succession to be performed substantially at the same time, or it is possible for the blocks to be performed in reverse order depending on the corresponding function. For example, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or One or more other operations may be added.

The term 'unit' used in this disclosure refers to software or hardware components such as FPGA (Field Programmable Gate Array) or ASIC (Application Specific Integrated Circuit). '~part' performs specific roles, but is not limited to software or hardware. The '~ part' may be configured to reside in an addressable storage medium and may be configured to reproduce on one or more processors. Therefore, according to some embodiments, '~ part' refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, and processes. Includes scissors, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided within the components and 'parts' may be combined into a smaller number of components and 'parts' or may be further separated into additional components and 'parts'. Additionally, components and 'parts' may be implemented to regenerate one or more CPUs within a device or a secure multimedia card. Additionally, according to various embodiments of the present disclosure, '˜unit' may include one or more processors.

Hereinafter, the operating principle of the present disclosure will be described in detail with reference to the attached drawings. In the following description of the present disclosure, if a detailed description of a related known function or configuration is determined to unnecessarily obscure the gist of the present disclosure, the detailed description will be omitted. In addition, the terms described below are terms defined in consideration of the functions in the present disclosure, and may vary depending on the intention or custom of the user or operator. Therefore, the definition should be made based on the contents throughout this specification.

According to various embodiments, an electronic device for estimating the location of at least one user device located in an indoor space, comprising: a memory; and at least one processor electronically connected to the memory, wherein the at least one processor identifies a first user device and a second user device that have the same destination location, and identifies the first user device identified by the first location. The location of the device is determined to be a first correction position corresponding to the first anchor position at a first point in time, and the location of the second user device identified as the second location is determined to be the first correction position at a second point in time corresponding to the first point in time. If the second correction position is determined to be the anchor position, and the location of the first user device is determined to be the third correction position corresponding to the second anchor location at the third time point, the location of the second user device is determined as the second correction position. is set to determine the third correction position at a fourth time point corresponding to the third time point, and the first distance between the first position and the first correction position is the second distance between the second position and the second correction position. An electronic device may be provided featuring a distance of less than 2.

The at least one processor is further configured to provide a first route to the first user device and a second route to the second user device, wherein the destination location of the first route and the destination location of the second route are: may be the same.

The distance between the first correction position and the second correction position may be less than or equal to a predetermined threshold.

The first anchor location and the second anchor location are included in anchor location information pre-stored in the memory, and the at least one processor selects at least some of the plurality of points included in the indoor space based on location accuracy. It can be set to obtain the anchor location information based on the points.

The at least one processor is further configured to identify the location of the at least one user device based on a plurality of location points corresponding to a plurality of points in the indoor space, and the first location is the location of the first location point. and the second location may be determined based on the location of the second positioning point.

The at least one processor is further configured to calculate a first location accuracy corresponding to the first location based on the first distance and calculate a second location accuracy corresponding to the second location based on the second distance. is set, and the first location accuracy may be greater than the second location accuracy.

The at least one processor may estimate the location of the first user device according to a first operation mode, but may estimate the location of the second user device according to a second operation mode in which the amount of operation is set to be smaller than that of the first operation mode. there is.

According to the first calculation mode, the location of the first user device is set to be estimated based on AP data and acceleration data received from the first user device, and according to the second calculation mode, the second user device It may be further configured to estimate the location of the second user device based on one of AP data or acceleration data received from.

The at least one processor is set to estimate the location of the second user device based on the acceleration data received from the second user device according to the second operation mode, wherein the at least one processor is configured to estimate the location of the second user device based on the acceleration data received from the first user device. It may be further configured to correct the location of the second user device based on the location estimated based on AP data.

The at least one processor may be further configured to switch the second operation mode to the first operation mode when a preset condition is achieved.

The time interval between the first time point and the third time point may be N (N = natural number) times the AP signal scan period of the first user device.

According to various embodiments, a method of operating an electronic device for estimating the location of at least one user device located in an indoor space, wherein the first user whose destination location is the same is operated by at least one processor included in the electronic device. identifying a device and a second user device; determining the location of the first user device identified as the first location as a first correction location corresponding to the first anchor location at the first time; determining the location of the second user device identified as the second location as a second correction position corresponding to the first anchor location at a second time point corresponding to the first time point; and when the location of the first user device is determined to be a third correction position corresponding to the second anchor position at a third time point, the location of the second user device is determined as the third correction position at a fourth time point corresponding to the third time point. 3 determining a correction position; wherein the first distance between the first position and the first correction position is smaller than the second distance between the second position and the second correction position. A method of operating the device may be provided.

According to various embodiments, a user device located in an indoor space; and an electronic device for estimating the location of the user device in an indoor space.

[SYSTEM]

1 is a diagram illustrating an example system 1 for providing indoor map information, estimating an indoor location, and providing an indoor route, according to various embodiments.

Referring to FIG. 1, the system 1 includes an electronic device (100, e.g., a server device, hereinafter referred to as “electronic device”) to provide an indoor location and route based on an indoor map, and an electronic device provided by the electronic device. It may include a plurality of user devices 101 that use a navigation service. For example, the electronic device 100 may represent a computing device or a plurality of computing devices associated with a map (eg, navigation) service provider. The electronic device 100 may correspond to a server hardware architecture and may include at least one processor for providing map and/or navigation services. The detailed configuration of the electronic device 100 is described in the disclosure regarding FIG. 3 .

According to an embodiment of the present disclosure, the electronic device 100 can provide an indoor map environment. At this time, the indoor map environment may be provided by a map software server that provides backend processing for the map service provider. For example, the software server obtains map data (e.g., map images, indoor map data, points of interest, navigation and/or route information) from a map database, and allows user devices 101 to configure user devices 101 ) Map data can be transmitted to a plurality of user devices to provide maps and/or navigation information to users. For example, the map software server may transmit map data to the user device while the user device is connected to the electronic device 100 through a network (e.g., the Internet, etc.). The user device may provide map data to the user using a map or navigation application on the user device.

The plurality of user devices 101 may represent user terminals for using the map service 110 provided by the electronic device 100. For example, the plurality of user devices 101 may be computing devices such as laptop computers, smartphones, tablets, etc. Additionally, for example, the plurality of user devices 101 may be wearable devices such as smart watches, smart glasses, smart glasses, etc. Also, for example, the plurality of user devices 101 may be media devices such as streaming media devices, media players, car entertainment systems, etc. That is, the plurality of user devices 101 may be devices that connect to the network to obtain map data according to various embodiments of the present disclosure.

Each of the plurality of user devices 101 may be composed of user devices corresponding to a user ID using an application. For example, the plurality of user devices 101 include a first user device 101a corresponding to the first user ID, a second user device 101b corresponding to the second user ID, and a third user device corresponding to the third user ID. It may include a third user device 101c, etc.

[Configuration of electronic devices]

FIG. 2 is a diagram illustrating the configuration of an electronic device included in the example system 1 of FIG. 1 according to various embodiments.

Referring to FIG. 2, an electronic device (e.g., a user device or electronic device, hereinafter referred to as “electronic device”) 200 according to an embodiment includes a processor 210, a memory 220, a communication circuit 230, and a sensor. It may include 240 and a display 250. Here, the electronic device 200 may be a concept that includes both an electronic device implemented as a user device of FIG. 1 and an electronic device implemented as a server device. The configuration of the electronic device 200 is not limited to the configuration shown in FIG. 2 or the configuration described above, and of course may further include hardware or software configurations included in a general computing device or mobile device.

The processor 210 may include at least one processor, at least some of which are implemented to provide different functions. For example, software (e.g., a program) may be executed to control at least one other component (e.g., a hardware or software component) of the electronic device 200 connected to the processor 210, perform various data processing or Calculations can be performed. According to one embodiment, as at least part of data processing or computation, processor 210 stores instructions or data received from other components in memory 220 (e.g., volatile memory), and stores instructions or data stored in the volatile memory. Data can be processed and the resulting data can be stored in non-volatile memory. According to one embodiment, the processor 210 is a main processor (e.g., a central processing unit or an application processor) or an auxiliary processor that can operate independently or together (e.g., a graphics processing unit, a neural processing unit (NPU)). , an image signal processor, a sensor hub processor, or a communication processor). For example, when the electronic device 200 includes a main processor and a auxiliary processor, the auxiliary processor may be set to use less power than the main processor or to specialize in a designated function. The auxiliary processor may be implemented separately from the main processor or as part of it. A coprocessor may, for example, act on behalf of the main processor while the main processor is in an inactive (e.g. sleep) state, or together with the main processor while the main processor is in an active (e.g. application execution) state, in an electronic device. At least some of the functions or states related to at least one of the components of 200 (eg, the display 250 or the communication circuit 230) may be controlled. According to one embodiment, an auxiliary processor (e.g., an image signal processor or a communication processor) may be implemented as part of another functionally related component (e.g., communication circuitry 230). According to one embodiment, an auxiliary processor (eg, neural network processing unit) may include a hardware structure specialized for processing artificial intelligence models. Artificial intelligence models can be created through machine learning. For example, such learning may be performed in the electronic device 200 itself on which the artificial intelligence model is performed, or may be performed through a separate server. Learning algorithms may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but It is not limited. An artificial intelligence model may include multiple artificial neural network layers. Artificial neural networks include deep neural network (DNN), convolutional neural network (CNN), recurrent neural network (RNN), restricted boltzmann machine (RBM), belief deep network (DBN), bidirectional recurrent deep neural network (BRDNN), It may be one of deep Q-networks or a combination of two or more of the above, but is not limited to the examples described above. In addition to hardware structures, artificial intelligence models may additionally or alternatively include software structures. Meanwhile, the operation of the electronic device 200 described below may be understood as the operation of the processor 210.

According to various embodiments, the memory 220 may include at least one memory, at least some of which are implemented to provide different functions. The memory 220 may store various data used by at least one component (eg, the processor 210) of the electronic device 200. Data may include, for example, input data or output data for software (e.g., a program) and instructions related thereto. Memory 220 may include volatile memory or non-volatile memory. Memory 220 may be implemented to store an operating system, middleware or applications, and/or the artificial intelligence model described above.

For example, the memory 220 may include a map application to access the map service 110. A map application may provide a function that allows a user to search for and/or specify a destination. In one embodiment, a map application may be implemented to allow a user to search for a specific place and/or item within a specific location and/or in proximity to the user device. A maps application allows a user to view a map that corresponds to the user's current location, a map that corresponds to a location associated with search results or other points of interest, and/or a representation of a map that corresponds to a destination location or geographic area selected by the user. function can be provided. The maps application may receive user input requesting directions to a destination, and the maps application may provide directions from a starting location (e.g., the current location of the user's device, a user-specified location, etc.) to a specified destination. .

Additionally, a map application can provide a representation of the physical structure of a location (e.g., a shopping mall complex, an airport, a construction site, or an underground parking lot, etc.). Additionally, as discussed below, a map application may provide information about the location of a venue, including the physical layout and geometry of the venue structure, as well as the location, structure, and layout of points of interest within the venue (e.g., stores, restaurants, security checkpoints, restrooms). A view can be provided. The view can become more detailed as the user zooms in on the venue to mark points of interest. In some embodiments, views inside a venue may include an outdoor walking area or courtyard included in some types of venues.

Additionally, for example, the memory 220 may include a plurality of instructions that direct operations of the processor 210 to implement functions provided by the map service 110.

At this time, the processor 210 may include a map software server that executes functions provided by the map service 110 based on a plurality of instructions stored in the memory 220.

The map software server may provide indoor map data building functions. The map software server can be configured to construct indoor map data that defines the physical structures of a place using poly-lines and various corresponding information.

Additionally, the map software server can provide a function to build positioning data corresponding to indoor map data. Specifically, the map software server may be set to construct positioning data corresponding to indoor map data based on sensor data acquired using the sensor 240.

Additionally, the map software server may provide an update function for a positioning data set consisting of indoor map data and positioning data.

Additionally, the map software server can provide an indoor location correction function.

Details of the functions provided by the map software server are described in detail below.

According to various embodiments, the communication circuit 230 establishes a direct (e.g., wired) or wireless communication channel between the electronic device 200 and an external electronic device (e.g., an endoscope device), and maintains the established communication channel. It can support communication through Communication circuitry 230 operates independently of processor 210 (e.g., a program processor) and may include one or more communication processors (e.g., communication chips) that support direct (e.g., wired) communication or wireless communication. . According to one embodiment, the communication circuit 230 is a wireless communication module (e.g., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module (e.g., a local area network (LAN) ) may include a communication module, or a power line communication module). Among these communication modules, the corresponding communication module is a first network (e.g., a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network (e.g., a legacy cellular network, 5G network, It can communicate with external electronic devices through a next-generation communication network, the Internet, or a telecommunication network such as a computer network (e.g., LAN or WAN). These various types of communication modules may be integrated into one component (e.g., a single chip) or may be implemented as a plurality of separate components (e.g., multiple chips). The wireless communication module may identify or authenticate the electronic device 100 within a communication network, such as a first network or a second network, using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module. . The wireless communication module may support 5G networks after the 4G network and next-generation communication technologies, for example, NR access technology (new radio access technology). NR access technology provides high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and access to multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low latency). -latency communications)) can be supported. The wireless communication module may support high frequency bands (e.g., mmWave bands), for example, to achieve high data rates. Wireless communication modules use various technologies to secure performance in high frequency bands, such as beamforming, massive MIMO (multiple-input and multiple-output), and full-dimensional multiple input/output (FD). -It can support technologies such as full dimensional MIMO (MIMO), array antenna, analog beam-forming, or large scale antenna. The wireless communication module can support various requirements specified in the electronic device 200, endoscopic device, or network system. According to one embodiment, the wireless communication module has Peak data rate (e.g., 20Gbps or more) for realizing eMBB, loss coverage (e.g., 164dB or less) for realizing mMTC, or U-plane latency (e.g., downtime) for realizing URLLC. Link (DL) and uplink (UL) each of 0.5 ms or less, or round trip 1 ms or less) can be supported.

According to various embodiments, the sensor 240 may include at least one sensor, at least some of which are implemented to provide different functions. For example, the sensor 240 may include a wireless communication sensor (e.g., a WiFi sensor, a Bluetooth (BLE) sensor, etc.), a magnetic field sensor, an inertial sensor, an acceleration sensor, a gyroscope, a geomagnetic sensor, a barometer, or a pressure sensor. there is.

At this time, the processor 210 may generate sensor data based on the electrical signal obtained from the sensor 240.

As an example, the processor 210 uses a wireless communication sensor (e.g., WiFi sensor, Bluetooth (BLE) sensor, etc.) to scan a wireless communication signal output from at least one of a plurality of access points (APs) to detect at least one A signal strength value (RSS) can be obtained. Additionally, the processor 210 may generate wireless communication strength data based on at least one signal strength value. At this time, the wireless communication sensor may be a concept that includes a wireless communication chip included in the communication circuit 230.

As another example, the processor 210 may obtain magnetic field intensity values for each location by identifying the intensity of magnetic fields occurring inside the location using a magnetic field sensor. Additionally, the processor 210 may generate magnetic field data based on magnetic field intensity values for each location.

As another example, the processor 210 may generate acceleration data by identifying the acceleration value of the electronic device using an acceleration sensor.

As another example, the processor 210 may generate barometric pressure data based on barometric pressure values measured using a barometer.

According to various embodiments, the display 250 may be configured to provide information (eg, visual information, auditory information using sound data, tactile information using vibration, etc.). For example, the display 250 may include a display device (eg, a monitor, a hologram device, or a projector and a control circuit for controlling the device). According to one embodiment, the display may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of force generated by the touch.

The processor 210 may be implemented to provide an input/output interface using the display 250. For example, the processor 210 may be implemented to provide a pre-stored graphical user interface (GUI) using the display 250.

The electronic device 200 may be implemented to include at least some of the above-described components (processor, communication circuit, memory, sensor, display). For example, a user device may be implemented to include a processor, communication circuitry, memory, sensors, and a display. Additionally, for example, a server device may be implemented to include a processor, communication circuitry, and memory.

FIG. 3 is a diagram illustrating a detailed configuration of an electronic device that provides a map service based on indoor map data, according to various embodiments.

Referring to FIG. 3 , the electronic device 300 may include a processor 310 and a memory 320. The processor 310 of the electronic device 100 may store various types of data accompanying the map service 110 in the memory 320. Specifically, the processor 310 may operate based on operations indicated by a plurality of instructions stored in the memory 320. Accordingly, the processor 310 may store at least some of the data accompanying the operation in the memory 320.

The electronic device 300 may store the indoor map data 330 in the memory 320 . The indoor map data 330 in the present disclosure is a concept that includes all indoor map image files or indoor map data defined based on computer code, and is data representing information about an indoor space (or venue). It can be. Additionally, the indoor map data 330 may be composed of a plurality of indoor map data each corresponding to a plurality of indoor spaces. For example, the indoor map data 330 may include first indoor map data 331 corresponding to a first location and second indoor map data 332 corresponding to a second location, but is not limited thereto. .

The electronic device 300 may store the positioning data 340 in the memory 320 . Positioning data 340 in the present disclosure refers to a database built to track the indoor location of a user device, and can be used as a location database, sensing data, sensing map, location fingerprint, Access Point fingerprint, or Wi-Fi fingerprint, etc. It can also be expressed. Additionally, the positioning data 340 may be composed of a plurality of positioning data respectively corresponding to a plurality of indoor spaces. For example, the positioning data 340 may include first positioning data 341 corresponding to a first place and second positioning data 342 corresponding to a second place, but is not limited thereto.

The electronic device 300 may associate indoor map data 330 and positioning data 340 corresponding to the same location and store them in the memory 320 . In the present disclosure, indoor map data and positioning data that are related to each other may be expressed as an “indoor positioning data set,” but the term itself is not intended to limit the configuration. Additionally, the processor 310 may measure (or position) the indoor location of the user device based on the indoor map data 330 and positioning data 340 that are associated with each other.

Details of how the processor 310 builds the indoor map data 330 and the positioning data 340 and predicts the indoor location will be described below (FIGS. 4 to 8).

The electronic device 300 may store user data 350 in the memory 320 . User data 350 in this disclosure refers to data acquired by user devices, such as data received from user devices and data based on data received from user devices. For example, the user data 350 may include first user data 351 received from user devices. As a specific example, the first user data 351 may consist of sensor data collected by a plurality of user devices. In the present disclosure, this type of data may be expressed in terms such as first user data, user sensing data, user collection data, or harvest data. Additionally, for example, the user data 350 may include second user data 352 generated based on data received from user devices. As a specific example, the second user data 352 may be composed of location data (or route data) generated based on sensor data collected by a plurality of user devices. In the present disclosure, this type of data may be expressed as second user data, (user) location data, (user) route data, or trace data, etc.

The electronic device 300 may store the outdoor map data 360 in the memory 320 . At this time, the outdoor map data 360 may be map data representing information about the outdoor space. At this time, the electronic device 300 may acquire outdoor map data 360 from an external source (e.g., API, source code, application, etc.).

The electronic device 300 may store user information 370 in memory 320 . The user information 370 in the present disclosure refers to information about user devices and refers to information that can distinguish user devices, such as user ID information for each user device.

[Method of constructing indoor positioning data set]

FIG. 4 is a diagram for explaining indoor map data included in an electronic device, according to various embodiments.

Referring to FIG. 4, an electronic device may provide indoor map data including a plurality of indoor maps corresponding to a plurality of place maps. At this time, the indoor map data may be an indoor map corresponding to a plurality of places included in at least part of the outdoor map. For example, the electronic device may include first indoor map data 400 for a first place located in a specific area.

The first indoor map data 400 may include various information related to the first place.

The first indoor map data 400 may include floor map information (floor map information) 410 indicating physical structures included in each floor (level or floor) of the first location. For example, the floor map information 410 includes a first floor map 410a indicating physical structures located on the first floor of the first location, and a second floor map indicating physical structures located on the second floor of the first location ( 410b), etc., but is not limited thereto.

The first indoor map data 400 may include point of interest information 420 indicating information about a plurality of points of interest (POI) included in the first location. The point of interest information 420 includes floor information indicating the floor on which each of the plurality of points of interest is located, location information of each of the plurality of points of interest, detailed information of each of the plurality of points of interest, or a plurality of points of interest. It may include information on the area (or footprint) each occupies, but is not limited to this. For example, the detailed information of a point of interest may include the name of the point of interest, the type of point of interest (category), the status of the point of interest (e.g., whether access is possible, etc.), or the event of the point of interest (e.g., information uploaded by the seller), etc. It may be information representing .

The first indoor map data 400 may include fixture information 430 indicating information about a plurality of fixtures included in the first location. The fixture information 430 may include location information of each of a plurality of fixtures included in the first location, or area (or footprint) information occupied by each of the plurality of fixtures, but is not limited thereto.

The first indoor map data 400 may include means of transportation information 440 indicating information about means of transportation included in the first location. At this time, the transportation means information 440 may include information about inter-floor transportation means (eg, escalator, elevator, stairs, etc.) for moving between floors in the first location. For example, the transportation means information 440 may include first inter-floor transportation information 440a, second inter-floor transportation information 440b, and third inter-floor transportation information 440c, each of which has different types of transportation means. However, it is not limited to this. Additionally, the transportation means information 440 may include location information for each of a plurality of transportation devices included in the first location, or information on the area (or footprint) occupied by each of the plurality of transportation devices. It is not limited to this.

Although not shown in FIG. 4 , the first indoor map data 400 may further include additional information about the first place in addition to the above-described information. For example, the first indoor map data 400 includes entrance information indicating the location of a plurality of entrances located in the first location, and a relationship defining a physical or conceptual connection between at least two map elements included in the first location. It may further include relationship information, anchor information indicating a location with high location prediction accuracy within the first location, etc.

The information included in the first indoor map data 400 will be described in detail below.

The electronic device may provide first indoor map data 400 to the user device. Specifically, the user device may output the first indoor map data 400 to the display using an application. Additionally, the first indoor map data 400 may appear in the form of a 3D drawing, but is not limited to this and may also appear in the form of a 2D drawing. In this case, the 3D drawing and the 2D drawing may be switched and displayed depending on the user input input by the user device.

FIG. 5 is a diagram illustrating an indoor positioning data set corresponding to a first location included in an electronic device, according to various embodiments.

Figure 5(a) shows an example of indoor map data 500 constituting an indoor positioning data set. For convenience of explanation, (a) in FIG. 5 represents indoor map data using a 2D drawing, but it is not limited to what is shown in the drawing, and indoor map data 500 includes an indoor map image or computer code. It may be multidimensional data consisting of a plurality of polylines defined as a basis.

Figure 5(b) shows an example of positioning data 550 constituting an indoor positioning data set. For convenience of explanation, (b) in FIG. 5 expresses the positioning data as if it appears on a 2D drawing, but it is not limited to what is shown in the drawing, and the positioning data 550 is a data value defined in a specific domain ( It may be a database containing values. For example, the positioning data 550 may be composed of location coordinates corresponding to indoor map data and at least one feature value corresponding to the location coordinates.

Referring to Figures 5(a) and 5(b), the electronic device may generate positioning data 550 corresponding to indoor map data 500. The electronic device may generate positioning data 550 by acquiring sensor data (sensor data or sensed data) corresponding to the positions of a plurality of points included in the first location. . At this time, the positioning data 550 may include a plurality of positioning points (positioning points or reference points or nodes) corresponding to the positions of each point of the indoor map data 500. Additionally, the positioning data 550 may include a plurality of grids and a plurality of nodes corresponding to intersections of the plurality of grids. At this time, each of the plurality of positioning points may include location coordinates on the corresponding indoor map data and at least one feature value (e.g., signal strength corresponding to at least one access point, etc.) corresponding to the location coordinates. It is not limited.

The electronic device can acquire sensor data corresponding to the positions of a plurality of points using a plurality of sensors, and can obtain positioning data 550 including a plurality of positioning points based on the acquired sensor data.

As an example, the electronic device uses a wireless communication sensor (e.g., a WiFi sensor or a BLE sensor, etc.) at the first point 501 to use a plurality of access points (APs), where the AP is a wireless communication signal (e.g., a wireless local area network (WLAN)). For example, an AP is an Ethernet router that outputs a WiFi signal, a beacon that outputs a Bluetooth signal, a UWB (ultra-wideband) based short-range wireless communication protocol, etc. At least one signal strength value (RSS, Received Signal Strength) can be obtained by scanning a wireless communication signal output from at least one of the. At this time, the electronic device may generate a first location point 551 based on at least one signal strength value identified by scanning a wireless communication signal output by at least one AP. As a specific example, the first positioning point 551 is identified by scanning the wireless communication signal output from the first AP (AP1) and the first signal strength value identified by scanning the wireless communication signal output from the second AP (AP2). It may be generated based on the second signal strength value and the third signal strength value identified by scanning the wireless communication signal output from the third AP (AP3).

As another example, the electronic device may obtain the magnetic field intensity value at the first point 501 by identifying the strength of magnetic fields occurring inside the first location using a magnetic field sensor. At this time, the electronic device may generate the first positioning point 551 based on the magnetic field intensity value at the first point 501.

According to an embodiment of the present disclosure, the electronic device may construct positioning data 550 by acquiring sensor data while moving points within the first location. At this time, the electronic device may set the interval between positioning points included in the positioning data 550 using an acceleration sensor (or inertial sensor, gyroscope, etc.). Specifically, the electronic device may set the interval between location points based on properties related to the movement of the electronic device (e.g., movement distance, movement direction, movement speed, etc.) obtained using acceleration data. For example, the electronic device can estimate the number of steps based on acceleration data and set the interval between location points based on the number of steps. Of course, it is not limited to this, and the interval between a plurality of positioning points can be arbitrarily set. That is, the spacing between the first positioning point and the second positioning point may be different from the spacing between the third positioning point and the fourth positioning point.

A plurality of positioning points included in the positioning data 550 may define a reference position where the user device can be located. Specifically, the electronic device may generate positioning data 550 by reflecting information about a point where the user can be located on the indoor map data 500. The electronic device may generate positioning data 550 by reflecting information about a possible path for the user to move on the indoor map data 500. The electronic device may generate positioning data 550 by considering at least some of the plurality of physical structures included in the indoor map data 500.

The electronic device may acquire positioning data 550 by reflecting point of interest (POI) information included in the indoor map data 500. The positioning data 550 may include a plurality of positioning points reflecting at least one of location information of a plurality of points of interest, area information occupied by the plurality of points of interest, or detailed information of the plurality of points of interest. The positions of the plurality of positioning points may be determined by considering at least one of location information of the plurality of points of interest, area information occupied by the plurality of points of interest, or detailed information of the plurality of points of interest.

For example, the electronic device may generate a location point based on the footprint 511 of the first point of interest 511, which indicates the area occupied by the first point of interest 510. At this time, the footprint 511 of the first point of interest may represent a polygon area related to the location of the first point of interest, but is not limited thereto. Specifically, the electronic device may generate the positioning data 550 so that the positioning point is not located in a predetermined area including the boundary of the footprint of the first point of interest 510.

Additionally, for example, the electronic device may identify whether the second point of interest 520 is accessible based on detailed information about the second point of interest 520 . In this case, the electronic device may generate a location point based on whether the second point of interest 520 is accessible. Specifically, the electronic device may generate positioning data 550 so that the positioning point is not located in the inner area 521 of the second point of interest 520 that is inaccessible to the general public. At this time, the inner area 521 of the second point of interest may be an area defined based on the boundary of the footprint of the second point of interest.

The electronic device may acquire positioning data 550 by reflecting information about fixtures (eg, walls, pillars, etc.) included in the indoor map data 500. The positioning data 550 may include a plurality of positioning points reflecting the location information of a plurality of fixtures (or information on the area occupied by the plurality of fixtures). The positions of the plurality of positioning points may be determined by considering the position information of the plurality of fixtures (or information on the area occupied by the plurality of fixtures).

For example, the electronic device may generate a positioning point based on the location of the first fixture 530 or the area 531 occupied by the first fixture 530. Specifically, the electronic device may generate positioning data 550 so that the positioning point is not located in the area corresponding to the position of the first fixture 530.

The electronic device may acquire positioning data 550 by reflecting section information included in the indoor map data 500. Here, zone information may mean information about a specific zone in the indoor map data 500. Positioning data 550 may include a plurality of positioning points reflecting area information occupied by a plurality of zones. The positions of the plurality of positioning points may be determined by considering area information occupied by the plurality of areas.

For example, the electronic device may generate a positioning point based on the area 536 occupied by the first area 535. At this time, the first zone 535 may represent an area including a plurality of fixtures (eg, pillars), and information about the first zone may be stored in the indoor map data 500. Specifically, the electronic device may generate positioning data 550 so that the positioning point is not located inside the area 536 occupied by the first zone.

The electronic device may acquire the positioning data 550 without reflecting information about movable objects (e.g., desks, chairs, amenities, etc.) included in the indoor map data 500. The positioning data 550 may include a plurality of positioning points ignoring the location information of the plurality of movable objects (or information on the area occupied by the plurality of movable objects). The positions of the plurality of positioning points may be determined without considering the position information of the plurality of movable objects (or information on the area occupied by the plurality of movable objects).

For example, the electronic device may generate a positioning point without considering the location of the first object 540 or the area occupied by the first object 540. Specifically, the electronic device may generate positioning data 550 so that the positioning point is located in an area corresponding to the position of the first object 540.

However, it is not limited to this, and the electronic device may generate a positioning point by considering information about a movable object. In this case, the electronic device may generate positioning data so that the positioning point is not located in an area corresponding to the position of the movable object.

The positioning data 550 generated by the electronic device may not include positioning points corresponding to at least some areas on the indoor map data 500. This may be because sensor data was not acquired in that area. In this case, when sensor data in the corresponding area is received by the user device, the electronic device may update the positioning data by creating a positioning point based on the received sensor data. Details on how to update positioning data of an electronic device will be described below.

FIG. 6 is a diagram illustrating a method by which an electronic device builds a positioning data set, according to various embodiments.

Referring to (a) of FIG. 6, the electronic device may acquire indoor map data (S601) and construct positioning data based on the acquired indoor map data (S602). In this case, the electronic device can obtain indoor map data by receiving an indoor map image from outside. Additionally, the electronic device may construct positioning data based on sensor data acquired from a plurality of points included in indoor map data.

Referring to (b) of FIG. 6, the electronic device may construct indoor map data (S603) and positioning data based on the constructed indoor map data (S604). In this case, the electronic device can obtain indoor map data by generating an indoor map of the place using a plurality of polylines. Additionally, the electronic device may construct positioning data based on sensor data acquired from a plurality of points included in indoor map data.

Referring to (c) of FIG. 6, the electronic device can construct indoor map data (S605). Additionally, the electronic device can construct positioning data (S606). In this case, the electronic device can construct positioning data based on the constructed indoor map data. Alternatively, the electronic device may construct indoor map data based on the established positioning data. More specifically, the electronic device can construct indoor map data by generating an indoor map of a place using a plurality of polylines, and based on sensor data acquired from a plurality of points included in the constructed indoor map data. Positioning data can be constructed. Alternatively, the electronic device may construct positioning data based on sensor data acquired by the user device, and may construct indoor map data by generating polylines based on the established positioning data.

Based on the above-described technical ideas of the present disclosure, the electronic device provides indoor location service by automatically constructing indoor map data and positioning data using data acquired from the user device even if the service provider does not directly establish positioning data. can do.

[Indoor positioning algorithm]

FIG. 7 is a flowchart illustrating a method for an electronic device to measure the location of a user device using an indoor positioning data set, according to various embodiments.

Referring to FIG. 7, the electronic device can acquire a positioning data set including indoor map data and positioning data (S701). The electronic device may load a positioning data set from memory in response to an application execution operation of the user device.

Additionally, the electronic device may receive a first data set obtained using at least one sensor from the user device (S703). For example, the electronic device uses access point (AP) data (and BLE data) acquired using a wireless communication sensor, acceleration data acquired using an acceleration sensor, barometric pressure data acquired using a barometer, or a magnetic field sensor. Thus, a first data set including at least one of the acquired magnetic field data can be received.

Additionally, the electronic device may calculate at least one location prediction value based on at least one of the positioning data set and the first data set (S705).

Additionally, the electronic device may identify the location of the user device based on at least one location prediction value (S707)

The detailed positioning algorithms involved in steps S703 to S707 are described in detail in the description of FIG. 8.

FIG. 8 is a diagram for explaining various types of positioning algorithms performed by an electronic device according to various embodiments.

Referring to FIG. 8, the electronic device may measure the location of the user device using at least some of a plurality of positioning algorithms. Specifically, the electronic device measures the location of the user device based on the predicted value calculated by a positioning algorithm, or calculates the final predicted value based on the predicted values calculated by a plurality of positioning algorithms to determine the location of the user device. It can be measured.

The electronic device may calculate the first prediction value by processing the AP data based on the first algorithm 810. At this time, AP data can be obtained by receiving it from the user device. At this time, the AP data may include at least one of communication signal strength (RSSI) data, AP location data (e.g., location (gps) coordinates of the AP), MAC address information of the AP, or identification information of the AP. Specifically, the electronic device may calculate the first prediction value based on AP data and pre-stored first positioning data (here, the first positioning data includes a plurality of positioning points). For example, the electronic device may calculate the first prediction value by comparing the communication signal strength value identified by the AP data with the first positioning data. At this time, the electronic device may calculate the first prediction value based on the location of one positioning point among the plurality of positioning points included in the positioning data.

Additionally, the electronic device may calculate the second prediction value by processing the magnetic field data based on the second algorithm 820. Specifically, the electronic device may calculate the second prediction value based on magnetic field data received from the user device and pre-stored second positioning data.

Additionally, the electronic device is not limited to this, and may process the first prediction value and magnetic field data based on the second algorithm 820 to calculate the second prediction value. Specifically, the electronic device may calculate a corrected second prediction value by correcting the first prediction value calculated using AP data based on magnetic field data.

Additionally, the electronic device may calculate a third prediction value by processing acceleration data based on the third algorithm 830. At this time, the third algorithm 830 may include a PDR algorithm. Since the technical features of general PDR algorithms known to those skilled in the art can be applied to the PDR algorithm implemented to process acceleration data in the present disclosure, detailed information will be omitted. Additionally, the electronic device may calculate a third prediction value by further using atmospheric pressure data. In this case, the electronic device can obtain location prediction information including floor information.

Additionally, the electronic device may calculate the fourth prediction value by processing the trajectory data based on the fourth algorithm 840. At this time, the trajectory data may represent the user's trajectory indicated by the user's location data over time. For example, trajectory data may include a set of location data acquired over a predetermined time period. The electronic device may calculate the fourth prediction value by comparing trajectory data with pre-stored movable path data. At this time, the movable path data may indicate a path that the user can move on the indoor map data. Specifically, the movable path data may include at least some of a plurality of positioning points included in positioning data corresponding to indoor map data. Additionally, the electronic device may generate movable path data by considering a plurality of physical structures included in the indoor map data.

As a specific example, the electronic device may acquire movable path data consisting of a plurality of nodes and links. Additionally, the electronic device may acquire trajectory data using an acceleration sensor (or inertial sensor or gyroscope). In this case, the electronic device may obtain location information of the user device based on the matching synchronization rate between the trajectory data and the possible movement path.

The electronic device may set conditions for performing a position estimation operation according to the fourth positioning algorithm. Specifically, when the location data of a specific user device is acquired more than a predetermined volume, the electronic device may calculate a location prediction value according to the fourth positioning algorithm. This is because, in order to obtain trajectory data, the location data of a specific user device needs to be accumulated over a certain volume.

Additionally, the electronic device may calculate a fifth prediction value by processing a plurality of prediction values obtained using a plurality of positioning algorithms based on the weighting model 850. At this time, the weighting model 850 may be implemented to assign predetermined weights to a plurality of prediction values. Specifically, the electronic device may calculate the fifth prediction value by calculating a weighted sum based on a plurality of prediction values using the weighting model 850.

At this time, the weights assigned to the plurality of prediction values may be set based on the accuracy of the location prediction. For example, the electronic device may assign the highest weight to the first prediction value obtained based on AP data. This is because the prediction accuracy of the location measured based on wireless communication strength is the highest. However, although not explicitly shown in FIG. 8, when an electronic device performs location prediction based on a BLE signal, the lowest weight may be assigned to the BLE-based prediction value. This is because the prediction accuracy of the location measured based on BLE signal strength is the lowest.

Additionally, the electronic device may adjust weights assigned to a plurality of prediction values. Specifically, the electronic device may adjust the weight so that a higher weight is assigned to a prediction value with higher accuracy among a plurality of prediction values.

Additionally, as described above, an electronic device can not only perform location measurement using a positioning algorithm, but also perform location measurement by receiving a location prediction value identified by the user device's own processor.

Additionally, the prediction value calculation period of at least some of the plurality of positioning algorithms may be different from each other or may be set differently by the processor.

For example, when the electronic device calculates a prediction value in a first period based on Wifi data acquired by scanning a WiFi signal, the electronic device calculates a prediction value in a first period smaller than the first period based on BLE data acquired by scanning a BLE signal. The predicted value can be calculated in 2 cycles. Additionally, in this case, the electronic device may be implemented to calculate the predicted value in a third period that is smaller than the second period based on acceleration data. Additionally, in this case, the electronic device may calculate the predicted value with a fourth period that is smaller than the second period based on the magnetic field data. Additionally, in this case, the electronic device may be implemented to calculate the predicted value in a fifth period that is smaller than the second period based on acceleration data and/or barometric pressure data. Additionally, in this case, the electronic device may be implemented to calculate the prediction value in a sixth period smaller than the second period based on trajectory data and possible movement path data.

[How to update indoor positioning data set]

An electronic device according to an embodiment of the present disclosure can update an indoor positioning data set. Specifically, the electronic device can update the indoor positioning data set by identifying changes in the indoor environment. For example, an electronic device can update an indoor localization data set by identifying changes in the positions of physical structures within a venue. Additionally, for example, the electronic device may update the indoor localization data set by identifying changes in information associated with at least one point of interest within the location. Additionally, for example, the electronic device may update the indoor positioning data set by identifying at least one physical structure that is not included in the indoor map data.

The electronic device may update indoor map data. In this case, the electronic device can identify an adjustment target area that needs to be updated on indoor map data.

Additionally, the electronic device can update the positioning data set based on data acquired inside the location.

FIG. 9 is a diagram illustrating an example of an electronic device updating indoor map data, according to various embodiments.

Referring to Figures 9(a) and 9(b), the electronic device may obtain second indoor map data 900b by updating the first indoor map data 900a.

Specifically, the electronic device may update indoor map data based on pre-stored movable route data and the actual route of at least one user device. At this time, the movable path data may indicate a movable path within indoor map data. For example, the first possible path data 910 may include a plurality of paths along which the user device can move within the first indoor map data 900a.

The movable path data may be set based on physical structures included in the indoor map data. Specifically, the electronic device may generate movable route data based on at least one point of interest included in indoor map data. The electronic device may generate movable path data by considering the footprint of at least one area of interest indicating the area occupied by at least one point of interest. More specifically, the electronic device may generate a movable path such that the movable path is not associated with an area defined by the footprint of at least one point of interest. Additionally, the electronic device may generate movable path data 910 to be spaced a predetermined distance from the boundary of the footprint of at least one point of interest. For example, the electronic device may generate the first possible movement path data 910 by considering the footprint of the first point of interest 940, but the present invention is not limited to this.

Additionally, movable path data may be set based on positioning data corresponding to indoor map data. Specifically, the electronic device may generate movable path data based on at least some of the plurality of positioning points included in the positioning data. More specifically, the electronic device may generate a plurality of links connecting a plurality of location points and generate movable path data based on the plurality of links. For example, the electronic device may generate the first movable path data 910 based on at least some of the plurality of positioning points (not shown) included in the positioning data corresponding to the first indoor map data 900a. You can.

The actual path of at least one user device may be identified based on a first data set received from the at least one user device. At this time, the first data set may include sensor data acquired using at least one sensor included in the user device and location data generated from the user device. For example, the first data set may include, but is not limited to, access point (AP) data collected from the user device, acceleration data, magnetic field data, barometric pressure data, and location data generated from the user device.

Additionally, the electronic device may identify the actual path of at least one user device by measuring the location of at least one user device based on the first data set. Specifically, the electronic device may identify the location of at least one user device based on at least one of the first data set, first indoor map data, and first positioning data corresponding to the first indoor map data.

Additionally, the electronic device may obtain a second data set reflecting the location of at least one identified user device. At this time, the second data set may be a trace data set consisting of location data of at least one user device. Alternatively, the second data set may be a trajectory data set based on location data of at least one user device. In this case, the electronic device may obtain the actual path of at least one user device based on the second data set. For example, the electronic device may obtain the first actual path 920 based on a second data set reflecting the location of at least one user device on the first indoor map data 900a.

Additionally, the electronic device can identify an adjustment target area that needs to be updated on the indoor map data by comparing the pre-stored movable route data with the actual route. For example, the electronic device identifies the adjustment target area 930 by comparing the pre-stored movable route data 910 and the first actual route 920 of at least one user device on the first indoor map data 900a. can do.

As an example, the electronic device may identify the adjustment target area 930 based on the difference between the movable path data 910 and the second data set constituting the first actual path 920. Specifically, when the difference between the position coordinates corresponding to the movable path data 910 and the position coordinates corresponding to the first actual path 920 is greater than a predetermined threshold in a specific area, the electronic device selects the specific area as an adjustment target area. It can be determined as (930).

At this time, the electronic device can set temporal conditions for identifying the adjustment target area 930. Specifically, when the difference between the movable path data 910 and the second data set persists for more than a predetermined time, the electronic device may designate the area where the difference occurs as the adjustment target area. Conversely, if the difference between the movable path data 910 and the second data set is not identified after a predetermined time, the electronic device may determine it to be a temporary change and not designate an adjustment target area.

Additional methods for identifying the adjustment target area will be explained through the description of FIG. 11.

Additionally, the electronic device may update the first indoor map data 900a by adjusting at least one parameter related to the adjustment target area 930, and thereby obtain the second indoor map data 900b. . At this time, at least one parameter may include a feature related to the physical structure of the indoor map data. For example, the at least one parameter may include a first parameter for adjusting a poly-line of the indoor map data, a second parameter for adjusting the footprint of the indoor map data, and a fixture of the indoor map data. It may include a third parameter for adjusting the fixture, a fourth parameter for adjusting point of interest information of indoor map data, etc., but is not limited thereto.

As an example, the electronic device may update indoor map data by adjusting at least some of the plurality of poly-lines included in the adjustment target area 930. As another example, the electronic device may update indoor map data by modifying information about at least one point of interest associated with the adjustment target area 930.

Additional operations performed by the electronic device after identifying the adjustment target area will be described with reference to FIG. 12 .

FIG. 10 is a flowchart illustrating an example of an electronic device updating indoor map data, according to various embodiments.

Referring to FIG. 10, the electronic device may receive a first data set from at least one user device located in a first location including at least one point of interest (S1001). At this time, the first data set may include access point (AP) data collected from at least one user device. At this time, the AP data may represent at least one intensity value corresponding to a wireless communication signal output from at least one AP, but is not limited to this. Additionally, the first data set may include location data generated from at least one user device. Additionally, the first data set may include acceleration data obtained using an acceleration sensor included in at least one user device.

In addition, the electronic device may detect at least one user based on at least one of a first data set, first indoor map data corresponding to a first location, and first positioning data corresponding to the first indoor map data. The location of the device can be identified (S1002). At this time, the first indoor map data may include a footprint indicating an area corresponding to the point of interest. Additionally, the first positioning data may include a first positioning point set including a plurality of positioning points corresponding to the first indoor map data.

For example, the electronic device may identify the location of at least one user device on the first indoor map data based on location data included in the first data set. Additionally, for example, the electronic device may identify the location of at least one user device on the first indoor map data by comparing the first data set and the first positioning data. Additionally, for example, the electronic device may identify the location of the at least one user device on the first indoor map data by comparing the first data set and the first positioning data.

Additionally, the electronic device may store a second data set reflecting the location of the at least one identified user device in the memory (S1003). Here, the second data set may be expressed as a trace data set or a trajectory data set.

At this time, the second data set may be obtained based on the trajectory of at least one user device within the first location. More specifically, the electronic device may identify the trajectory of at least one user device based on location prediction data acquired in a predetermined time period and obtain a second data set based on the identified trajectory. For example, the electronic device may obtain a second data set based on location prediction data from the time at least one user device enters the room to the current time. Alternatively, the electronic device may acquire a second data set based on location prediction data of at least one user device from a time point before the first predetermined time interval from the current time point to the current time point.

Additionally, the electronic device may identify the area to be adjusted based on the second data set and the first movable path data stored in advance (S1004). At this time, the first possible movement path data is set based on at least some of the plurality of positioning points included in the first positioning data, or is set based on the footprint of at least one point of interest and at least one fixture included in the first location. ) can be set considering the location of. Specifically, the electronic device may generate movable path data by creating a plurality of links connecting some of the plurality of positioning points. In this case, the electronic device generates traversable path data such that the links connecting the positioning points are not associated with the footprint of at least one point of interest (e.g., the link is set not to pass through an area inside the footprint). can do. Additionally, the electronic device may be moved so that the link connecting the positioning points is not associated with at least one fixture included in the first location (for example, the link is set not to pass through an area containing the location of the fixture). Path data can be generated. That is, the movable path data may include a plurality of paths that can be provided to at least one user device within the first location.

FIG. 11 is a diagram illustrating a specific method for an electronic device to identify a zone to be adjusted, according to various embodiments.

Referring to FIG. 11, the electronic device may identify an area to be adjusted based on the difference between the second data set and the movable path data. Specifically, when the difference between the second data set and the first possible movement path data satisfies a predetermined standard, the electronic device selects at least a portion of the area on the first indoor map data that satisfies the predetermined standard as an adjustment target area. Can be identified (S1101).

Additionally, for example, if the location of at least one user device included in the second data set corresponds to a first footprint area corresponding to the first point of interest, the electronic device may select an area including the first point of interest. can be identified as the adjustment target area (S1102).

Additionally, for example, the electronic device may identify an area including a second point of interest that corresponds to the second data set but does not correspond to the first possible movement path data as the adjustment target area (S1103).

Additionally, for example, the electronic device may identify at least some areas included in the second data set but not included in the first movable path data as the adjustment target area (S1104).

FIG. 12 is a diagram illustrating operations that an electronic device can perform in response to an operation to identify an area to be adjusted, according to various embodiments.

Referring to FIG. 12, in response to the identification operation (S1004) of the area to be adjusted, the electronic device generates second positioning data in which at least some of the plurality of positioning points included in the first positioning data have been changed based on the second data set. can be obtained (S1201).

Additionally, the electronic device may obtain second indoor map data by deleting at least one polyline included in the adjustment target area in response to the identification operation of the adjustment target area (S1004) (S1202).

Additionally, the electronic device may acquire third indoor map data by adding at least one poly line to the adjustment target area in response to the identification operation of the adjustment target zone (S1004) (S1203).

Additionally, the electronic device may acquire second movable path data in which at least a portion of the first movable data is adjusted based on the second data set in response to the identification operation (S1004) of the adjustment target area (S1004). S1204).

Additionally, the electronic device may provide information about the adjustment target zone to at least one user device in response to the identification operation of the adjustment target zone (S1004) (S1205).

The electronic device according to an embodiment of the present disclosure may continuously update the positioning data even after distributing the positioning data for indoor location estimation to a plurality of user devices (eg, users using API).

More specifically, the electronic device can collect sensor data obtained from a plurality of user devices using an indoor space, and can detect changes in the collected sensor data to statistically detect updates to the positioning data.

Accordingly, the electronic device can automatically distribute the updated and latest indoor positioning data to a plurality of user devices.

FIG. 13 is a flowchart illustrating another example of an electronic device updating an indoor positioning data set, according to various embodiments.

Referring to FIG. 13, the electronic device may receive a first data set from at least one user device located in a first location including at least one point of interest (S1301). At this time, the first data set may include, but is not limited to, AP data collected from at least one user device, location data generated from at least one user device, and acceleration data obtained from at least one user device. .

The first data set may be comprised of a harvest dataset including a plurality of sub-data sets received from each of a plurality of user devices. For example, the electronic device may include a first sub-data set received from a first user device, a second sub-data set received from a second user device, and a third sub-data set received from a third user device. , but is not limited to this.

In addition, the electronic device may obtain second positioning data by adjusting at least one attribute of the first positioning data corresponding to the first indoor map data corresponding to the first place based on the first data set. (S1302). At this time, the first indoor map data may include a plurality of polylines. Specifically, the first indoor map data may include a footprint of at least one point of interest defined based on a plurality of polylines. Additionally, the first positioning data may include a first positioning point set including a plurality of positioning points corresponding to the first indoor map data.

At least one attribute of the positioning data may include the number of positioning points included in the positioning data, a location attribute of the positioning data (or a position attribute of the positioning point), or an intensity attribute of the positioning data (or an intensity attribute of the positioning point). , but is not limited to this. Specifically, the location attribute of the positioning data may mean the location where each of a plurality of positioning points included in the positioning data corresponds to the indoor map data. Additionally, the strength attribute of the positioning data may mean the wireless communication signal strength (RSS) corresponding to each of a plurality of positioning points included in the positioning data.

In this case, the electronic device may filter the first data set according to predetermined conditions. Specifically, the electronic device may obtain a filtered first data set by removing noise data from the first data set received from at least one user device. Additionally, the electronic device may be set to update the first positioning data using the filtered first data set.

Additionally, the electronic device can check whether the first indoor map data needs to be updated. This is because there may be a situation where indoor map data does not need to be updated even if the positioning data is updated. Specifically, the electronic device can determine whether an indoor map update is necessary based on whether the update of the positioning data has caused a change in the physical structure inside the place. For example, if the electronic device determines that updating the indoor map data is unnecessary after performing the operation of step S1302, the electronic device may perform the operation of step S1301 again.

Additionally, the electronic device may identify the first target area that requires correction in the first indoor map data based on the second positioning data (S1303).

Additionally, the electronic device may acquire second indoor map data by adjusting at least one parameter related to the first target area based on the first indoor map data (S1304).

FIG. 14 is a diagram illustrating an example of an electronic device updating positioning data, according to various embodiments. Referring to Figures 14(a) and 14(b), the electronic device may obtain second positioning data 1400b by updating the first positioning data 1400a.

The electronic device may update positioning data based on the location of at least one user device. Since the method for an electronic device to predict the location of at least one user device has been described above, it will be omitted. In this case, the electronic device may acquire second positioning data 1400b by adjusting at least one attribute of the first positioning data 1400a based on the location of at least one identified user device.

Referring to FIGS. 14(a) and 14(b), the electronic device acquires a location data set 1410 indicating the location of at least one user device based on a data set received from at least one user device. can do. For example, the location data set 1410 may include, but is not limited to, first location data indicating the location of a first user device and second location data indicating the location of a second user device.

At this time, the location data set 1410 may correspond to the first area 1420 where no positioning point exists.

In this case, the electronic device may obtain the second positioning data 1400b by adjusting the attributes associated with the number of positioning points of the first positioning data 1400a based on the position data set 1410. The electronic device may acquire second positioning data 1400b by adding a positioning point to the first area 1410 where no positioning point exists based on the position data set 1410. Specifically, the electronic device may receive AP data from at least one user device located inside the first area 1410, and at least one user device located inside the first area 1410 based on the received AP data. Second positioning data 1400b can be obtained by creating a positioning point 1430. At this time, the number of positioning points included in the second positioning data 1400b may be greater than the number of positioning points included in the first positioning data 1400a.

At this time, the first area 1420 may be related to the first point of interest 1420. For example, the first area 1420 may be included in an area inside the first point of interest 1420.

In this case, the electronic device may receive AP data from at least one user device located inside an area corresponding to the first point of interest 1420, and determine the first point of interest 1420 based on the received AP data. Second positioning data 1400b can be obtained by creating at least one positioning point 1430 inside the area corresponding to .

Through this, the electronic device can build more accurate positioning data by supplementing data in areas where positioning points have not been established based on data obtained from the user. Alternatively, the electronic device may determine that a point of interest whose access was restricted has become accessible based on data obtained from the user device and automatically update information about the point of interest.

The electronic device may update indoor map data based on the second positioning data 1400b. Specifically, the electronic device may update indoor map data when information related to the indoor space changes as the positioning data is updated with the second positioning data 1400b.

For example, when at least one positioning point 1430 is created in an area inside the first point of interest 1420, the electronic device may identify the area corresponding to the first point of interest 1420 as the target area. . Additionally, the electronic device may update indoor map data by updating information about the first point of interest 1420 identified as the target area. As a specific example, the electronic device may update the first point of interest 1420, which is designated as access-controlled, to a state where access is possible. Alternatively, the electronic device may update the first point of interest 1420, which is designated as under construction, to a state where construction is completed.

FIG. 15 is a diagram illustrating another example of an electronic device updating positioning data, according to various embodiments. Referring to Figures 15(a) and 15(b), the electronic device may obtain second positioning data 1500b by updating the first positioning data 1500a.

When the identified location is corrected according to the method described above and corrected location data is obtained, the electronic device may update the positioning data based on the corrected location data.

As an example, the electronic device may acquire corrected location data using at least one positioning algorithm. Since the specific details of the positioning algorithm have been described above, they will be omitted. For example, when the electronic device acquires first position data 1510 using a first positioning algorithm and then acquires second position data using a second positioning algorithm with higher accuracy than the first positioning algorithm, Corrected location data 1520 may be obtained by correcting the first location data based on the second location data.

As another example, the electronic device may obtain corrected position data using a predetermined position correction algorithm. Specific details about the correction algorithm will be described below (FIGS. 31 to 35). For example, the electronic device may obtain corrected location data 1520 based on location data of another user device with high location accuracy.

As another example, the electronic device may obtain corrected location data by receiving a location correction input from at least one user device.

At this time, the electronic device adjusts at least one attribute of at least one positioning point included in the area 1530 corresponding to the corrected positioning data 1520 among the plurality of positioning points included in the first positioning data 1500a. Thus, second positioning data 1500b can be obtained. Specifically, the electronic device may acquire second positioning data 1500b by adjusting the intensity properties of at least one positioning point included in the area 1530 corresponding to the corrected positioning data 1520.

The electronic device may receive AP data from at least one user device located in the area 1530 corresponding to the corrected location data 1520, and at least one user device within the area 1530 based on the received AP data. The strength properties of the positioning point can be adjusted. Here, the electronic device can adjust the strength properties of the positioning point by modifying communication signal strength information corresponding to at least one AP included in the positioning point.

This means that the electronic device recognizes that the location accuracy in the corresponding area 1530 is reduced due to location correction and adjusts the intensity properties of the location point to increase location accuracy. Through this, the accuracy of location prediction using positioning data can be continuously secured.

Additionally, the electronic device may set the area 1530 corresponding to the corrected location data as the first target area where indoor map data needs to be updated. In this case, the electronic device may update the indoor map data by adjusting at least one parameter of an area corresponding to the first target area on the indoor map data. At this time, at least one parameter may include a feature related to the physical structure of the indoor map data. For example, the at least one parameter may include a first parameter for adjusting a poly-line of the indoor map data, a second parameter for adjusting the footprint of the indoor map data, and a fixture of the indoor map data. It may include a third parameter for adjusting the fixture, a fourth parameter for adjusting point of interest information of indoor map data, etc., but is not limited thereto.

FIG. 16 is a diagram illustrating another example of an electronic device updating positioning data, according to various embodiments. Referring to Figures 16(a) and 16(b), the electronic device may obtain second positioning data 1600b by updating the first positioning data 1600a.

The electronic device may acquire the second positioning data 1600b as the location properties of at least some of the plurality of positioning points included in the first positioning data 1600a are adjusted. Specifically, the electronic device can acquire a harvest dataset from a plurality of user devices existing in an indoor space, and update the positioning data set based on the harvest dataset. At this time, the corresponding positions of at least some of the positioning points included in the positioning data set on the indoor map data may be different.

For example, the first positioning data 1600a may include at least one positioning point corresponding to the inside of the specific area 1610. At this time, as the location properties of at least one positioning point corresponding to the inside of the specific area 1610 are adjusted, the second positioning data 1600b may not include the positioning point corresponding to the inside of the specific area 1610. .

Alternatively, the electronic device may acquire second positioning data as at least some of the plurality of positioning points included in the first positioning data are deleted. For example, the electronic device may acquire second positioning data as at least one positioning point corresponding to the inside of the specific area 1610 is deleted. In this case, the number of positioning points included in the first positioning data may be greater than the number of positioning points included in the second positioning data.

This may be because physical structures (eg, fixtures, etc.) are placed in the indoor space corresponding to the specific area 1610, making it impossible for the user to be located at the location corresponding to the specific area 1610. That is, as data is not received from the user device at a location corresponding to the specific area 1610, the electronic device can determine the presence of a physical structure at a location corresponding to the specific area 1610.

FIG. 17 is a diagram illustrating an example of an electronic device updating indoor map data, according to various embodiments. Referring to FIGS. 17(a) and 17(b), the electronic device determines the location of FIG. 16 based on the first indoor map data 1700a corresponding to the first positioning data 1600a of FIG. 16(a). Second indoor map data 1700b corresponding to the second positioning data 1600b in (b) can be obtained.

The electronic device may identify a first target area 1710 in which indoor map data needs to be modified based on a specific area including at least some location points whose properties have been adjusted.

The electronic device may obtain the second indoor map data 1700b by adjusting at least one parameter corresponding to the target area 1710 of the first indoor map data 1700a. For example, the electronic device may adjust at least one parameter to add at least one polyline to the target area 1710. Specifically, the electronic device may generate the footprint 1720 by adding at least one polyline to the target area 1710. Additionally, in this case, the electronic device may obtain the second indoor map data 1700b by generating information about the point of interest corresponding to the footprint 1720. At this time, information about the point of interest may be received from at least one user device.

The electronic device may generate the footprint 1720 based on the location properties of at least one location point corresponding to the target area 1710. Specifically, the electronic device may generate the footprint 1720 so that the internal area of the footprint 1720 does not include a location point. For example, referring again to (b) of FIG. 16 , the electronic device may generate a footprint 1720 in a shape corresponding to a specific area 1620 surrounded by at least one location point.

That is, the electronic device can identify the characteristics of physical structures included in the indoor map data based on the location distribution of the positioning data. Through this, when the positioning data is updated, the electronic device can automatically update the indoor map data based on it.

FIG. 18 is a diagram illustrating another example of an electronic device updating an indoor positioning data set, according to various embodiments. Referring to FIGS. 18(a) and 18(b) , the electronic device may update indoor map data 1850 based on the positioning data 1800.

The electronic device may obtain updated positioning data 1800 as the intensity properties of at least some of the plurality of positioning points included in the positioning data are adjusted. Specifically, the electronic device may obtain updated positioning data 1800 as the communication signal strength corresponding to at least one AP associated with at least some of the positioning points is adjusted.

At this time, the electronic device may identify a target area 1860 to be updated on the indoor map data by identifying a specific area 1810 including at least one location point whose intensity properties have been adjusted.

For example, when the specific area 1810 is related to the first point of interest, the electronic device may determine the area corresponding to the first point of interest as the target area 1860. Specifically, when the specific area 1810 is included in the area corresponding to the first point of interest, the electronic device may determine the area corresponding to the first point of interest as the target area 1860. Additionally, when the specific area 1810 overlaps the area corresponding to the first point of interest by more than a predetermined threshold, the electronic device may determine the area corresponding to the first point of interest as the target area 1860.

In addition, for example, when the intensity properties of at least some of the location points included in the specific area 1810 are adjusted to more than a predetermined threshold, the electronic device selects the area including the specific area 1810 as the target area 1860. You can decide. At this time, a predetermined threshold may be set to determine whether the adjustment of the intensity properties of the location point was accompanied by a change in the physical structure. The electronic device may determine whether the physical structure at a location corresponding to the specific area 1810 has changed based on the intensity properties of at least some location points included in the specific area 1810.

The electronic device may obtain updated indoor map data 1850 by adjusting at least one parameter at a location included in the target area 1860 identified based on the specific area 1810. For example, the electronic device may obtain updated indoor map data 1850 by changing AP 1865 information placed in the indoor map data. As a specific example, the electronic device may change the address information of the AP (1865) placed within the target area (1860).

Additionally, the electronic device may obtain updated indoor map data 1850 by modifying information about the point of interest corresponding to the target area 1860. For example, the electronic device may modify information about a point of interest where the AP 1865 information has changed, but is not limited to this.

Through this, the electronic device can automatically update the indoor map data to reflect this when a specific store located in the location is changed to another store.

FIG. 19 is a diagram illustrating another example of an electronic device updating an indoor map, according to various embodiments. Referring to Figures 19(a) and 19(b), the electronic device may obtain the second indoor map 1900b by updating the first indoor map 1900a.

The electronic device may update the indoor map based on sensor data acquired from at least one user device located within the first location including at least one point of interest. Specifically, the electronic device may update indoor map data based on a data set acquired using at least one sensor included in at least one user device.

Additionally, the electronic device may obtain information related to floor movement of at least one user device based on sensor data acquired from the at least one user device.

Specifically, the electronic device can identify whether the floor is moving based on the first sensor data. At this time, the first sensor data may include atmospheric pressure data, but is not limited thereto. For example, the electronic device may identify floor movement based on the amount of change in the first sensor data. When the air pressure increases during a specific time period, the electronic device may determine that at least one user device is moving downstairs. Additionally, when the air pressure decreases during a specific time period, the electronic device may determine that at least one user device is moving upstairs.

Additionally, the electronic device may acquire location information related to floor movement in response to the identification operation of floor movement. Specifically, the electronic device may obtain location information related to floor movement based on location data corresponding to a specific time period involving floor movement. For example, the electronic device may determine the first area 1910 on the first indoor map 1900a as a location related to floor movement.

Additionally, the electronic device may identify an inter-floor movement means involved in floor movement based on sensor data acquired from at least one user device. Specifically, the electronic device may identify a means of moving between floors based on the second sensor data. At this time, the second sensor data may include acceleration data, but is not limited thereto. For example, the electronic device may identify the inter-floor movement means involved in floor movement based on the change rate of the second sensor data. The electronic device may identify a means of moving between floors based on a data window of second sensor data corresponding to a specific time period involving floor movement. The electronic device may identify the means for moving between floors based on the pattern of the data window of the second sensor data.

For example, when the acceleration value changes rapidly in the time section corresponding to the start point and the end point of a specific time section, the electronic device may determine the means of moving between floors to be an elevator.

Additionally, for example, the electronic device may select one of the escalator and stairs as a means of moving between floors by estimating the number of steps based on the data window of the second sensor data. Specifically, when the number of steps determined based on the data window is less than or equal to a predetermined threshold, the electronic device may determine the means of moving between floors to be an escalator, and if the number of steps is greater than or equal to a predetermined threshold, the electronic device may determine the means of moving between floors to be stairs.

This is because the number of steps required for moving between floors using an escalator is smaller than the number of steps required for moving between floors using stairs.

Additionally, the electronic device may update the second indoor map 1900b by reflecting inter-floor transportation means information in the first indoor map 1900a.

At this time, the electronic device may identify a location involving movement between floors on the first indoor map 1900a based on a data set acquired from at least one user device.

The electronic device may reflect inter-floor transportation means information by creating at least one feature associated with the inter-floor transportation means at the identified location. Specifically, the electronic device can obtain the second indoor map 1900b by adding an indicator 1920 (or marker or icon) indicating the type of means of moving between floors.

At this time, the inter-floor transportation means information may include relationship information indicating the driving direction or driving time of the moving means. Specifically, the electronic device may generate relationship information by generating a parameter that defines the direction in which the inter-floor movement means is driven (eg, unidirectional or bidirectional). Alternatively, the electronic device may generate relationship information by creating a parameter that defines the time at which the inter-floor movement means is driven (eg, 7 a.m. to 7 p.m.).

The electronic device may generate an indoor route based on relationship information included in the indoor map. Specifically, the electronic device may generate an indoor route by reflecting relationship information of at least one physical structure included in the indoor map.

As an example, the electronic device may generate an indoor route based on relationship information of at least one entrance included in the indoor map. Specifically, when the indoor map includes an entrance that only allows movement in one direction, the electronic device may generate an indoor route by considering the direction of movement using the entrance.

As another example, the electronic device may generate an indoor route based on relationship information of inter-floor movement means included in the indoor map. Specifically, when the indoor map includes a means of moving between floors (e.g., an elevator) that operates only at specific times (e.g., 7:00 a.m. to 7:00 p.m.), the electronic device determines an indoor route by considering the operating time of the means of moving between floors. can be created. For example, if a route is created at a time other than the specific time, the electronic device may create an indoor route so that it is not associated with the means of moving between floors.

FIG. 20 is a flowchart illustrating another example of an electronic device updating an indoor map, according to various embodiments.

Referring to FIG. 20, the electronic device may provide a first indoor map corresponding to the first place to at least one user device located in a first place including at least one point of interest (S2001). Additionally, the electronic device may receive a first data set including first sensor data and second sensor data from the at least one user device (S2002). Additionally, the electronic device may identify inter-floor movement of the at least one user device based on the first sensor data (S2003). Additionally, in response to the identification operation of the inter-floor movement, the electronic device may acquire inter-floor movement means information indicating an inter-floor movement means related to inter-floor movement among a plurality of pre-stored inter-floor movement means based on the second sensor data. There is (S2004). At this time, the plurality of means of moving between floors may include, but is not limited to, escalators, stairs, and elevators. Additionally, the electronic device may provide a second indoor map reflecting information on means of transportation between floors to a plurality of user devices (S2005).

FIG. 21 is a diagram illustrating a method by which an electronic device obtains inter-floor movement means information, according to various embodiments. Referring to FIG. 21, the operation of step S2004 of the electronic device may include a plurality of operations.

The electronic device may identify at least one time section related to inter-floor movement based on the first sensor data (S2101). At this time, at least one time section may include at least two or more time points where the amount of change in the first sensor data is greater than or equal to a threshold. The electronic device may identify inter-floor movement of at least one user device by identifying at least one time interval in which the size of the first sensor data changes by more than a predetermined amount.

Additionally, the electronic device may identify at least one data window corresponding to the at least one time section among the second sensor data (S2102).

Additionally, the electronic device may obtain inter-floor movement means information based on at least one data window (S2103).

FIG. 22 is a diagram illustrating a method in which an electronic device provides a second indoor map by reflecting information on means of transportation between floors, according to various embodiments.

Referring to FIG. 22, the electronic device may identify at least one time section related to inter-floor movement based on the first sensor data (S2201). Additionally, the electronic device may identify at least one data window corresponding to the at least one time section among the second sensor data (S2202).

Additionally, the electronic device may identify the location of at least one user device on the first indoor map based on at least one data window (S2203). For example, the location of at least one user device may be predicted based on acceleration data of at least one user device, but the method is not limited to this.

Additionally, the electronic device may generate features associated with the means of moving between floors at a location on the identified first indoor map (S2204). At this time, the feature related to the inter-floor movement means may include at least one indicator indicating the type of the inter-floor movement means.

Additionally, the electronic device may provide a second indoor map reflecting information on means of transportation between floors to a plurality of user devices (S2205).

FIG. 23 is a flowchart illustrating another example in which an electronic device updates an indoor map by reflecting a means of moving between floors, according to various embodiments.

Referring to FIG. 23, the electronic device may provide a first indoor map corresponding to the first place to at least one user device located in a first place including at least one point of interest (S2301). Additionally, the electronic device may receive a first data set including first sensor data from at least one user device (S2302). At this time, the first sensor data may include atmospheric pressure data, but is not limited thereto.

Additionally, the electronic device may identify at least one time section in which the at least one user device moves between floors based on the first sensor data (S2303).

Additionally, the electronic device may determine an inter-floor movement means accompanying inter-floor movement based on the length of at least one time section (S2304). The method by which the electronic device determines the inter-floor movement means involved in inter-floor movement based on the length of at least one time interval is described in detail in the disclosure with respect to FIG. 24.

Additionally, the electronic device may provide a second indoor map reflecting information about means of transportation between floors to a plurality of user devices (S2305).

FIG. 24 is a diagram illustrating air pressure data obtained in situations where various means of moving between floors are used, according to various embodiments.

Referring to FIGS. 24(a), 24(b), and 24(c), the electronic device may identify floor movement using stairs based on the first air pressure data 2400a, and the second air pressure data 2400a. Floor movement using an escalator can be identified based on the air pressure data 2400b, and floor movement using an elevator can be identified based on the third air pressure data 2400c.

If the length of at least one time section associated with floor movement included in the air pressure data is greater than or equal to a predetermined length, the electronic device may determine the means of inter-floor movement accompanying the inter-floor movement as an escalator or stairs, and the floor is associated with the building. If the length of the time section is less than or equal to a predetermined length, the inter-floor movement means used for inter-floor movement may be determined to be an elevator.

As an example, the electronic device may identify floor movement using stairs based on the first data window 2401 corresponding to the first time interval (interval1) of the first atmospheric pressure data 2400a.

The electronic device may identify the first time interval (interval1) associated with floor movement based on the first atmospheric pressure data 2400a. Additionally, the electronic device may identify the means for moving between floors based on the length of the first time interval (interval1). Specifically, when the first time interval (interval1) is longer than or equal to the first predetermined length, the electronic device may determine that the means of moving between floors corresponding to the first data window 2401 is stairs.

As another example, the electronic device may identify floor movement using an escalator based on the second data window 2402 corresponding to the second time interval (interval2) of the second air pressure data 2400b.

The electronic device may identify a second time interval (interval2) related to floor movement based on the second air pressure data 2400b. Additionally, the electronic device may identify the inter-floor movement means based on the length of the second time interval (interval 2). Specifically, when the second time interval (interval2) is less than or equal to the first predetermined length and greater than or equal to the second predetermined length, the electronic device may determine the inter-floor movement means corresponding to the second data window 2402 to be an escalator. .

Here, the first predetermined length may be set in consideration of the minimum time required to move to a floor using stairs and the maximum time required to move to a floor using an escalator. Additionally, the second predetermined length may be set in consideration of the minimum time required to move between floors using an escalator and the maximum time required to move between floors using an elevator.

Additionally, the second time interval (interval2) may be smaller than the first time interval (interval1). This is because the time required to move between floors using an escalator is usually shorter than the time required to move between floors using stairs.

As another example, the electronic device includes a third data window 2403 corresponding to the third time interval (interval3) and a fourth data window 2404 corresponding to the fourth time interval (interval4) of the third atmospheric pressure data 2400c. Based on this, floor movement using the elevator can be identified.

The electronic device may identify a third time interval (interval3) and a fourth time interval (interval4) related to floor movement based on the third atmospheric pressure data 2400c. Additionally, the electronic device may identify the means for moving between floors based on the lengths of the third time interval (interval3) and the fourth time interval (interval4). Specifically, when the length of the third time interval (interval3) and the fourth time interval (interval4) is less than or equal to the second predetermined length, the electronic device corresponds to the third data window 2403 and the fourth data window 2404. The method of transportation between floors can be determined to be an elevator.

Additionally, the electronic device can identify a means of moving between floors based on the number of time sections. Specifically, when the number of time sections is more than a predetermined number (e.g., 2), the electronic device may determine the inter-floor movement means corresponding to the third data window 2403 and the fourth data window 2404 to be an elevator. .

The reason that the time section related to floor movement using an elevator is identified as a plurality of time sections is because when a user moves between multiple floors using an elevator, there may be floors that stop in between.

Also, here, the fourth time interval (interval4) may be smaller than the third time interval (interval3). This is because when the user device moves between floors using an elevator, the number of floors it moves to without stopping at a time may be different.

[Application control method]

When a user device (or mobile device or electronic device, hereinafter referred to as “electronic device”) using a map service enters a space (e.g., indoor space) where GPS coordinates cannot be obtained, according to an embodiment of the present disclosure The server may estimate the indoor location of the electronic device based on various data acquired by the electronic device. At this time, the server can achieve high location estimation accuracy by tracking the indoor location from the time the electronic device enters the room.

To this end, at least one processor included in the electronic device may be set to measure the indoor location by controlling the application from the time of entering the room.

FIG. 25 is a diagram illustrating a method of controlling an application depending on whether an electronic device enters a room, according to various embodiments.

Referring to FIG. 25, at least one processor included in the electronic device may operate in a first operation mode to detect whether or not one has entered the room (S2501). Specifically, at least one processor may control the application to be executed in the background environment of the mobile device so that only minimal functions are implemented. For example, at least one processor may execute the application in a first operation mode so that only the function for detecting whether or not the user has entered the room is implemented, but the application is not limited to this.

Additionally, at least one processor may check whether a predetermined first condition has been achieved (S2502). At this time, the predetermined first condition may be a condition set to check whether or not to enter the room.

At least one processor may detect whether or not the device has entered the room based on GPS data. Specifically, at least one processor may determine the time at which the GPS sensor included in the electronic device fails to acquire GPS data as the indoor entry point. Additionally, when at least one processor scans a wireless communication signal at a time when GPS data cannot be obtained, it may determine that the device has entered the room.

Additionally, at least one processor may detect whether or not the device has entered the room based on an operation of receiving a communication signal indicating entry into the room. Specifically, at least one processor may receive a communication signal from the parking control system as the vehicle passes through the parking lot entrance, and may identify indoor entry based on the reception operation.

Additionally, at least one processor may detect whether or not the device has entered the room based on whether or not the destination has arrived. Specifically, when at least one processor provides a route guidance function to a specific place, the time when it is determined that the specific place has been arrived may be determined as the indoor entry point.

Additionally, the present invention is not limited to this, and at least one processor may detect whether or not the user has entered the room based on temperature information, illumination information, or AP information.

Additionally, at least one processor may maintain the application in the first operation mode when the first condition is not achieved (eg, when located in an outdoor space).

Additionally, the at least one processor may operate in a second operation mode for estimating the indoor location of the electronic device when the first condition is achieved (e.g., when it is determined that the electronic device has entered the room) (S2503). .

FIG. 26 is a diagram for explaining various situations in which an electronic device enters an indoor environment from outdoors, according to various embodiments.

For example, referring to (a) of FIG. 26, an electronic device may enter an indoor space through the user's walking movement. Additionally, for example, referring to (b) of FIG. 26, the electronic device may enter the indoor space through the user's vehicle movement.

Electronic devices can control applications differently depending on the method of entering an indoor space.

For example, when the user enters an indoor space through walking movement, the electronic device may control the application to execute an indoor location estimation function, but when the user enters the indoor space through vehicle movement, the electronic device may control the application to execute the indoor location estimation function. Because it is necessary to identify the location, it is necessary to control the application to execute the parking location tracking function together with the indoor location estimation function.

FIG. 27 is a diagram illustrating a method by which an electronic device controls the execution of an application based on a movement pattern, according to various embodiments.

FIG. 28 is a diagram for explaining an operation of an electronic device switching an operation mode, according to various embodiments.

Referring to FIG. 27, at least one processor included in the electronic device can drive an application according to the first operation mode to identify whether the electronic device has entered the room (S2710). Since the specific method for identifying whether at least one processor enters the room has been described above, it will be omitted.

At least one processor may set an operation mode based on the movement pattern of the electronic device in response to the indoor entry identification operation. For example, the movement pattern of the electronic device may include, but is not limited to, a first movement pattern indicating walking movement and a second movement pattern indicating vehicle movement.

Specifically, in response to an indoor entry identification operation, at least one processor may control an application according to a second operation mode when the movement pattern of the electronic device is the first movement pattern (S2720). At this time, the second operation mode may include an application control operation that activates the indoor location estimation function.

Additionally, in response to the indoor entry identification operation, the electronic device may control the application according to the third operation mode when the movement pattern of the electronic device is the second movement pattern (S2730). At this time, the third operation mode may include an application control operation that activates the indoor location estimation function and the parking location tracking function. Additionally, the indoor location estimation function may be implemented differently in the third operation mode and the second operation mode.

The operation according to the second operation mode of at least one processor includes acquiring first location data corresponding to the location of the electronic device based on AP data and first acceleration data collected by the electronic device (S2721) ) may include. In this case, at least one processor may use AP data and acceleration data for indoor location estimation according to the second operation mode. Since the indoor location estimation method using AP data and acceleration data has been described above, it will be omitted. Of course, the present invention is not limited to this, and at least one processor may further use magnetic field data to estimate the indoor location.

In addition, the operation according to the second operation mode of the at least one processor further includes acquiring floor information indicating the floor on which the electronic device is located based on air pressure data obtained using the at least one sensor. can do. Specifically, at least one processor may obtain floor information based on barometric pressure data and a barometric pressure data set indicating the distribution of barometric pressure data for each floor. Details of the operation method for acquiring floor information are described below (FIGS. 29 and 30).

Additionally, the operation according to the third operation mode of the at least one processor includes an operation (S2731) of acquiring second location data corresponding to the location of the electronic device based on second acceleration data collected by the electronic device. It can be included. In this case, at least one processor may use acceleration data to estimate indoor position according to the third operation mode. That is, AP data may not be used for the indoor location estimation function according to the third operation mode, but the method is not limited to this.

Additionally, the operation according to the third operation mode may further include correcting the second location data based on magnetic field data obtained using at least one sensor.

Additionally, the operation according to the third operation mode may further include estimating the indoor location based on trajectory data and a possible movement path of the electronic device. At this time, the trajectory data may include location data of the electronic device during a specific time period. Since the detailed description of the method for estimating indoor location based on trajectory data and possible movement paths has been described above, it will be omitted.

In addition, the operation according to the third operation mode is performed by identifying a first time period in which the movement pattern of the electronic device changes from the second movement pattern to the first movement pattern based on the second location data and An operation (S2732) of storing third location data corresponding to the section in the memory may be further included. Specifically, at least one processor may identify the parking location of the vehicle based on a change in movement pattern. For example, the at least one processor may identify the first time interval in which the movement pattern changes from vehicular movement to pedestrian (walking) movement, and determine the parking location based on third location data corresponding to the first time interval. can be decided.

The method of identifying the parking position of the at least one processor is not limited to the above-described description, and the at least one processor may identify the parking position based on another embodiment.

For example, at least one processor may identify the parking location based on location data at the time the communication connection between the electronic device and the vehicle is disconnected.

Additionally, for example, at least one processor may identify the parking location based on location data at the time when execution of the outdoor navigation application of the electronic device ends.

At least one processor may generate parking information based on the first time period and the third location data and store it in the memory. At this time, the parking information may include parking location information generated based on the third location data and parking time information generated based on the first time section.

Accordingly, the electronic device can provide information on elapsed parking time to the user and further provide information on parking fees accordingly.

Additionally, referring to FIG. 28, after performing an operation of storing third position data in memory, at least one processor may switch the third operation mode to the second operation mode (S2740). Specifically, after storing the third location data, at least one processor may control the application to disable the parking location tracking function and activate only the indoor location estimation function.

Additionally, when an input requesting parking location guidance is received from the user, at least one processor may provide parking location information to the user based on third location data stored in the memory. Additionally, when an input requesting route guidance to the parking location is received from the user, at least one processor may generate a route to the parking location and provide the route to the user.

FIG. 29 is a diagram illustrating a method for an electronic device to identify floor information, according to various embodiments.

Referring to FIG. 29, at least one processor included in the electronic device may execute an application (S2910). At least one processor may obtain floor information indicating the floor on which the electronic device is located (S2920). Additionally, at least one processor may obtain indoor location information indicating the indoor location of the electronic device (S2930).

At this time, at least one processor may obtain floor information and/or indoor location information based on the current floor and user input indicating the current location.

For example, at least one processor may obtain floor information and indoor location information based on information about surrounding points of interest input from the user. Specifically, when receiving an input for the name of a nearby store from a user, at least one processor may obtain basic floor information and indoor location information regarding the location of the store.

Additionally, for example, at least one processor may obtain floor information and indoor location information by receiving an input about the current floor and an input about the current location from the user.

Additionally, at least one processor may obtain floor information and indoor location information based on visual information acquired by a visual sensor (e.g., camera device, lidar device, etc.) included in the electronic device. For example, at least one processor may obtain floor information and indoor location information based on visual information about surrounding points of interest.

FIG. 30 is a diagram illustrating a specific method for an electronic device and a server to obtain floor information, according to various embodiments.

Referring to FIG. 30, the server may receive atmospheric pressure data from a plurality of user terminals (S3001). At this time, barometric pressure data may be obtained by a barometer included in a plurality of user terminals.

Additionally, the server can obtain an air pressure data set representing the distribution of air pressure data for each floor by grouping the air pressure data into a plurality of layers (S3002). Specifically, the server may construct an atmospheric pressure data set by matching atmospheric pressure data obtained from user devices located on a plurality of floors to the corresponding floor. For example, the server may include a first sub-atmospheric pressure data set corresponding to the first layer, a second sub-atmospheric pressure data set corresponding to the second layer, and a third sub-atmospheric pressure data set corresponding to the third layer. can be built, but is not limited to this.

At this time, the server may be set to construct the barometric pressure data set based on barometric pressure data acquired during a predetermined time period. Specifically, the server may collect barometric pressure data for a predetermined time period to build a barometric pressure data set for estimating floor information of the device. For example, the server may construct an atmospheric pressure data set based on atmospheric pressure data acquired during a certain period of time before the complex shopping mall is opened to general customers. Alternatively, the server may construct an atmospheric pressure data set based on atmospheric pressure data acquired during a certain period of time after the complex shopping mall is closed to general customers.

The electronic device may obtain floor information indicating the floor on which the electronic device is located based on the barometric pressure data set constructed by the server. Specifically,

Specifically, the electronic device may transmit barometric pressure data obtained using a barometer to the server (S3003).

At this time, the server may obtain floor information corresponding to the electronic device based on the barometric pressure data and the previously constructed barometric pressure data set (S3004). Specifically, the server may estimate the floor on which the electronic device is located by comparing the received barometric pressure data and the barometric pressure data set. For example, the server can identify a value corresponding to the received barometric pressure value among the barometric pressure data set, and obtain floor information by identifying the floor corresponding to the value.

Additionally, the server may provide the obtained floor information to the electronic device (S3005).

[Indoor position correction method using nearby devices]

A server device (or computing device or electronic device, hereinafter referred to as “electronic device”) that provides a map service can receive data from a plurality of user devices that use the map service and measure the positions of the plurality of user devices. there is.

Due to technical differences (e.g., differences in user device specifications, differences in user device models, etc.) between the plurality of user devices, the indoor location estimation accuracy of the plurality of user devices may be different.

Accordingly, the electronic device can correct the location measurement value of another user device using a measurement value with high accuracy among the location measurement values of a plurality of user devices.

FIG. 31 is a diagram illustrating an example of a method by which an electronic device corrects its location using positioning results of a plurality of user devices, according to various embodiments.

Referring to FIG. 31, the electronic device may obtain location prediction values corresponding to each of a plurality of user devices (S3101). Specifically, the electronic device measures the positions of a plurality of user devices based on data received from the plurality of user devices (e.g., location data, AP data, acceleration data, magnetic field data, barometric pressure data, etc.) to obtain the location prediction value. can be obtained. Since the description of how the electronic device measures its position has been described above, it will be omitted.

Additionally, when at least some of the plurality of user devices satisfy a predetermined correction condition, the electronic device may correct the location prediction values of at least some of the user devices (S3102).

The electronic device may store predetermined correction conditions in memory.

At this time, the predetermined correction condition may be set based on at least one of location prediction accuracy, distance between devices, or communication status between devices.

The electronic device may predict the location of a specific user device and then calculate the location accuracy of the specific user device. Here, location accuracy may refer to the reliability of the location prediction value output according to at least one positioning algorithm. At this time, location accuracy can be calculated as an output value of the location measurement algorithm. More specifically, the electronic device may output the location prediction value and location prediction accuracy of a specific user device based on data received from the specific user device, but is not limited to this.

For example, the electronic device may measure the location of the first user device based on data received from the first user device and output a first location prediction value, and may output a first location prediction value based on data received from the second user device. 2 The location of the user device may be measured and a second location prediction value may be output.

The electronic device may correct the location prediction values of at least two user devices based on a highly accurate location prediction value.

For example, if the accuracy of the second location prediction value is higher than the accuracy of the first location prediction value, the electronic device may use the first location prediction value of the first user device based on the second location prediction value of the second user device. It can be corrected. Specifically, the electronic device may correct the location prediction value of the first user device to the second location prediction value. Alternatively, the electronic device may correct the location prediction value of the first user device to a value obtained by interpolating the first location prediction value and the second location prediction value based on accuracy.

Additionally, for example, if the distance between the first user device and the second user device is within a threshold, the electronic device may provide at least one of the location prediction value of the first user device and the location prediction value of the second user device. can be corrected.

In addition, for example, when the first user device and the second user device are in a state in which a wireless communication connection is possible (e.g., a state in which a Bluetooth signal is being scanned), the electronic device may store the location prediction value of the first user device and the second user device. 2 At least one of the location prediction values of the user device can be corrected.

In addition, for example, when the first user device is a first type with relatively high positioning accuracy and the second user device is a second type with relatively low positioning accuracy, the electronic device predicts the location of the first user device. The location prediction value of the second user device may be corrected based on the value. For example, the first model may be a model with higher specifications than the second model (e.g., a model including a uwb sensor), but is not limited to this.

FIG. 32 is a diagram illustrating an example of a method for an electronic device to correct location information of a user device, according to various embodiments.

Referring to FIG. 32, the electronic device may obtain first expected location information corresponding to the first user device and second expected location information corresponding to the second user device (S3201). At this time, the expected location information may include a location prediction (or estimate) value and accuracy information about the location prediction. At this time, the accuracy information may appear based on the position prediction error value and may include an accuracy level (or accuracy radius) defined according to the position prediction error value. Illustratively, the location accuracy of the first user device may be higher than that of the second user device.

Additionally, the electronic device may obtain expected distance information between the first user device and the second user device (S3202). Specifically, the electronic device may obtain expected distance information based on the wireless communication state between the first user device and the second user device.

For example, the electronic device may obtain expected distance information based on the strength of a wireless communication signal of the second user device scanned from the first user device. Specifically, the closer the distance between the first user device and the second user device, the stronger the wireless communication signal of the second user device scanned by the first user device.

Additionally, for example, the electronic device may obtain expected distance information based on the time when a wireless communication connection between the first user device and the second user device is first enabled. Specifically, the electronic device may store in advance the maximum distance at which a wireless communication connection between user devices is possible, and based on the pre-stored distance corresponding to the time when a communication connection between the first user device and the second user device is first possible, Expected distance information can be obtained.

Additionally, the electronic device may receive information about the wireless communication status from at least one of the first user device or the second user device and obtain expected distance information based on this.

Additionally, the electronic device may determine a correction parameter based on the first accuracy information and expected distance information included in the first expected location information (S3203). Specifically, the electronic device may determine a correction parameter based on the location prediction error of the first user device and the expected distance to the second user device. Additionally, the electronic device may correct the location estimate value included in the second expected location information based on the correction parameter (S3203).

FIG. 33 is a diagram illustrating an example of a method by which an electronic device corrects a location based on a path of a user device, according to various embodiments.

Referring to FIG. 33, at least two user devices moving along a corresponding path can be identified. For example, the electronic device may identify a first user device moving along a first path 3301 and a second user device moving along a second path 3302 corresponding to the first path 3301. there is. At this time, the first path 3301 may be defined based on the location of the first user device over time, and the second path 3302 may be defined based on the location over time of the second user device.

The first path 3301 and the second path 3302 may be paths created by an electronic device and provided to the user device. For example, the electronic device may provide a first path 3301 to a first user device and a second path 3302 to a second user device. At this time, the first path 3301 and the second path 3302 may be the same.

Additionally, the electronic device is not limited to this and can identify at least two user devices moving to the corresponding destination location. At this time, the destination location may be a destination location included in the route provided to the user device by the electronic device. For example, the electronic device may identify a first user device to which the first destination location is set and a second user device to which the first destination location is set.

The electronic device can predict the location of the user device, regardless of the path provided to the user device. For example, the electronic device may determine the location of the first user device as the first location 3310 and determine the location of the second user device as the second location 3320. At this time, the electronic device may be set to identify the location of at least one user device based on a plurality of positioning points (or positioning data including a plurality of positioning points) corresponding to a plurality of points in the indoor space.

Additionally, the electronic device may correct the identified location based on the location of at least one anchor. At this time, the anchor location may mean a location with high location accuracy. Specifically, the electronic device may set a location where the accuracy of location prediction is greater than or equal to a predetermined threshold as the anchor location.

For example, the electronic device may determine the location of the user device based on the location of at least one location point among a plurality of location points included in the location data. If the determined location accuracy of the user device is greater than or equal to a predetermined threshold, the location corresponding to the at least one location point may be set as the anchor location.

Additionally, the electronic device may obtain anchor location information based on at least some points with high location accuracy among a plurality of points included in the indoor space. For example, the anchor location information may include a first anchor location 3330 and a second anchor location 3340, but is not limited thereto.

The electronic device may identify at least two user devices identified by the anchor location corresponding to the corresponding viewpoint. Additionally, in this case, the electronic device may correct the locations of at least two identified user devices based on location prediction accuracy. Additionally, the electronic device may correct the location of at least one user device based on the location prediction accuracy of at least two user devices that have the same destination location.

At this time, the location prediction accuracy can be determined based on the distance at which the location has been corrected.

Specifically, the electronic device may determine the location prediction accuracy based on the distance corrected from the previously identified location to the anchor location. Specifically, the electronic device may determine that the smaller the corrected distance of the identified location of at least one user device, the higher the accuracy of the identified location.

As an example, the electronic device may determine the location of the first user device identified as the first location 3310 as the first correction location 3315 corresponding to the first anchor location 3330. At this time, the distance between the first correction position 3315 and the first position 3310 may be a first distance d1.

Additionally, the electronic device may determine the location of the second user device identified as the second location 3320 as the second correction location 3325 corresponding to the first anchor location 3330. At this time, the distance between the second correction position 3325 and the second position 3320 may be a second distance d2. Additionally, the distance between the second correction position 3325 and the first correction position 3315 may be less than or equal to a predetermined threshold.

Since the first distance d1 is smaller than the second distance d2, the electronic device may determine that the location prediction accuracy of the first user device is higher than the location prediction accuracy of the second user device.

If at least two user devices with the same destination location are identified as corresponding locations at corresponding times, the electronic device may determine that the two user devices are traveling together.

In this case, the electronic device may determine the location of the user device with the highest location prediction accuracy among the locations of the at least two user devices.

Exemplarily, the electronic device may determine the location of the second user device to be the same as the location of the first user device from the time after the first time point and the second time point. Specifically, as the first user device and the second user device have the same destination location and are identified as locations (first correction location and second correction location) corresponding to corresponding time points (first time point and second time point), The electronic device may be set to determine that the first user device and the second user device are traveling together and calculate the location of only one of the first user device and the second user device.

For example, if the location of the first user device is determined to be the third correction position 3350 corresponding to the second anchor position 3340 at a third time, the electronic device may change the location of the second user device to the third correction position. The fourth correction position 3360 corresponding to the third correction position 3350 may be determined at a fourth viewpoint corresponding to (or the same as) the viewpoint. Preferably, the fourth correction position 3360 may be set to be the same as the third correction position 3350.

Additionally, the electronic device may set the operation modes of the two user devices to be different. Specifically, among the two user devices, the user device with high location prediction accuracy calculates an accurate location based on a high computation amount, and the user device with low location prediction accuracy calculates an approximate location based on a low computation amount. can do.

Through this, the electronic device can reduce the amount of unnecessary calculations by predicting the locations of a plurality of user devices based only on the location of a user device with high location prediction accuracy among the plurality of accompanying user devices.

As an example, the electronic device may estimate the location of the first user device according to a first operation mode, and may estimate the location of the second user device according to a second operation mode with a smaller calculation amount than the first operation mode. there is. Depending on the embodiment, the electronic device may not estimate the location of the second user device.

The electronic device may set at least one calculation mode based on the volume of data used for location estimation.

For example, the electronic device may be set to estimate the location of the first user device using AP data and acceleration data collected from the first user device according to the first operation mode.

Additionally, in this case, the electronic device determines the location of the second user device using one of AP data or acceleration data collected from the second user device according to a second calculation mode set to have a smaller calculation amount than the first calculation mode. Can be set to estimate. For example, the electronic device updates the location of the second user device based on acceleration data received from the second user device, but corrects the location of the second user device based on AP data received from the first user device. It can be set to do so.

The electronic device can switch operation modes when a preset condition is achieved. Specifically, when it is determined that the second user device is not accompanying the first user device, the electronic device may predict the location of the second user device by switching the second calculation mode to the first calculation mode.

Specifically, when the location of the second user device predicted according to the second operation mode and the location of the second user device corrected according to the location of the first user device differ by more than a predetermined threshold, the electronic device operates in the second operation mode. Can be set to switch to the first operation mode.

FIG. 34 is a flowchart illustrating an example of a method by which an electronic device corrects a location based on a path of a user device, according to various embodiments.

Referring to FIG. 34, the electronic device can identify a first user device and a second user device that have the same destination location (S3401).

Additionally, the electronic device may determine that the location of the first user device identified as the first location is the first correction location corresponding to the first anchor location at the first time point (S3402).

Additionally, the electronic device may determine the location of the second user device identified as the second location as the second correction position corresponding to the first anchor position at the second time point corresponding to the first time point (S3401).

Additionally, when the location of the first user device is determined to be the third correction position corresponding to the second anchor position at the third time point, the electronic device adjusts the location of the third user device to the fourth time point corresponding to the third time point. 3 It can be determined by the correction position (S3401).

FIG. 35 is a diagram illustrating a method for correcting positions according to differences in scan cycles of a plurality of user devices that are determined to be traveling together, according to various embodiments.

Figure 35(a) is a diagram showing the location of the first user device according to the AP data scan cycle of the first user device. Figure 35(b) is a diagram showing the location of the second user device according to the AP data scan cycle of the second user device.

The electronic device can predict the location of the user device based on AP data collected from the user device.

For example, referring to (a) of FIG. 35, the first user device may collect AP data according to the first scan cycle 3501. Additionally, the electronic device may predict the location of the first user device based on AP data received from the first user device. For example, the electronic device may determine the location of the first user device as P11 according to the first scan (scan1) of the first user device. Additionally, referring to (b) of FIG. 35, the electronic device may determine the location of the second user device as P21 according to the first scan (scan1) of the second user device.

Additionally, the electronic device may update the location of the first user device (3510). Specifically, the electronic device may update the location of the first user device based on at least one of location data, magnetic field data, acceleration data, or trajectory data received from the first user device (3510).

Additionally, when the electronic device determines that at least two user devices are traveling together, the electronic device may be set to correct its location according to the information disclosed in FIGS. 33 and 34.

For example, when it is determined that the first user device and the second user device are traveling together at a specific time t0, the corrected position of the second user device may be determined based on the corrected position of the first user device. Additionally, in this case, the electronic device may switch the calculation mode for estimating the location of the second user device before and after the specific time t0. For example, before the specific time t0, the electronic device may predict the location of the second user device based on AP data and acceleration data collected from the second user device according to the first calculation mode. At this time, the electronic device switches to the second calculation mode after a specific point in time (t0), predicts the location of the second user device based on acceleration data obtained from the second user device, and predicts the location of the first user device based on the location of the first user device. The position of the second user device can be corrected.

Additionally, when the user device scans AP data at a location corresponding to the anchor location, the electronic device may determine that an anchoring event (AE) has occurred and correct the location of the user device based on the anchor location. there is.

For example, when the first anchoring event (AE1) occurs according to the second scan (scan2) of the first user device at a location corresponding to the first anchor location, the location of the first user device is changed to the first anchor location. It can be determined by the corresponding first correction position.

Accordingly, the electronic device can correct the position of the second user device based on the position correction of the first user device. Specifically, the electronic device may determine the location of the second user device as the first correction position at a first time point (t1) corresponding to the time point at which the first anchoring event (AE1) occurs.

The electronic device can predict the location of the user device depending on the above-described calculation mode.

For example, as the electronic device predicts the location of the second user device in the second calculation mode, when the second user device scans AP data (scan2), the electronic device determines the location corresponding to the scanned AP data. It may not be calculated. On the contrary, as the electronic device predicts the location of the first user device in the first calculation mode, the location of the first user device is P13 based on the AP data obtained according to the third scan (scan3) of the first user device. can be decided.

In addition, when the second anchoring event (AE2) occurs according to the fourth scan (scan4) of the first user device at a position corresponding to the second anchor position, the position of the first user device is changed to the second anchor position. It can be determined as the second correction position.

Additionally, in this case, the electronic device may determine the location of the second user device as the second correction position at a second time point (t2) corresponding to the time when the second anchoring event (AE2) occurs.

At this time, the position correction interval 3502 of the first user device according to the occurrence of the anchoring event may be related to the scan cycle 3501 of the first user device. This is because an anchoring event occurs when the first user device scans AP data around the anchor location, and the location of the first user device is corrected accordingly.

For example, the position correction interval 3502 of the first user device may be N (where N is a natural number) times the scan period 3501 of the first user device.

Additionally, the position correction interval 3552 of the second user device may not be associated with the scan period 3551 of the second user device. This is because the position correction of the second user device is performed depending on the position correction of the first user device.

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

Therefore, other implementations, other embodiments, and equivalents of the claims also fall within the scope of the claims described below.

Claims (20)

An electronic device for estimating the location of at least one user device located in an indoor space, comprising:
Memory; and
At least one processor electronically connected to the memory,
The at least one processor,
Identifying a first user device and a second user device having the same destination location,
Determine the location of the first user device identified as the first location as a first correction location corresponding to the first anchor location at the first time point,
determining the location of the second user device identified as the second location as a second correction position corresponding to the first anchor location at a second time point corresponding to the first time point;
When the location of the first user device is determined to be a third correction position corresponding to the second anchor position at a third time point, the location of the second user device is determined to be the third correction position at a fourth time point corresponding to the third time point. is set to determine the correction position,
The electronic device, wherein a first distance between the first position and the first correction position is smaller than a second distance between the second position and the second correction position.
According to paragraph 1,
the at least one processor is further configured to provide a first path to the first user device and a second path to the second user device,
An electronic device, wherein the destination location of the first route and the destination location of the second route are the same.
According to paragraph 1,
An electronic device, wherein the distance between the first correction position and the second correction position is less than or equal to a predetermined threshold.
According to paragraph 1,
The first anchor position and the second anchor position are included in anchor position information pre-stored in the memory,
The at least one processor is configured to obtain the anchor location information based on at least some points identified based on location accuracy among a plurality of points included in the indoor space.
According to paragraph 1,
The at least one processor is further configured to identify the location of the at least one user device based on a plurality of positioning points corresponding to a plurality of points in the indoor space,
The first location is determined based on the location of the first location point, and the second location is determined based on the location of the second location point.
According to paragraph 1,
The at least one processor is further configured to calculate a first location accuracy corresponding to the first location based on the first distance and calculate a second location accuracy corresponding to the second location based on the second distance. is set,
The first location accuracy is greater than the second location accuracy.
According to paragraph 1,
The at least one processor estimates the location of the first user device according to a first operation mode, and estimates the location of the second user device according to a second operation mode in which the amount of calculation is set to be smaller than the first operation mode. Electronic device being set up.
In clause 7,
The at least one processor,
According to the first calculation mode, the location of the first user device is estimated based on AP data and acceleration data received from the first user device,
According to the second calculation mode, the electronic device is further configured to estimate the location of the second user device based on one of AP data or acceleration data received from the second user device.
According to clause 8,
The at least one processor,
According to the second calculation mode, the location of the second user device is set to be estimated based on the acceleration data received from the second user device,
The electronic device is further configured to correct the location of the second user device based on the location estimated based on AP data received from the first user device.
In clause 7,
The electronic device is further configured to switch the second operation mode to the first operation mode when a preset condition is achieved.
According to paragraph 1,
The time interval between the first time point and the third time point is N (N = natural number) times the AP signal scan period of the first user device.
A method of operating an electronic device for estimating the location of at least one user device located in an indoor space, using at least one processor included in the electronic device, the method comprising:
identifying a first user device and a second user device having the same destination location;
determining the location of the first user device identified as the first location as a first correction location corresponding to the first anchor location at the first time;
determining the location of the second user device identified as the second location as a second correction position corresponding to the first anchor location at a second time point corresponding to the first time point; and
When the location of the first user device is determined to be a third correction position corresponding to the second anchor position at a third time point, the location of the second user device is determined to be the third correction position at a fourth time point corresponding to the third time point. Including determining a correction position,
A method of operating an electronic device, wherein a first distance between the first position and the first correction position is smaller than a second distance between the second position and the second correction position.
According to clause 12,
A method of operating an electronic device, characterized in that the distance between the first correction position and the second correction position is less than or equal to a predetermined threshold.
According to clause 12,
The first anchor position and the second anchor position are included in anchor position information previously stored in a memory,
The method of operating the electronic device is,
A method of operating an electronic device further comprising: acquiring the anchor location information based on at least some points identified based on location accuracy among a plurality of points included in the indoor space.
According to clause 12,
Further comprising: identifying the location of the at least one user device based on a plurality of positioning points corresponding to a plurality of points in the indoor space,
The first position is determined based on the position of the first positioning point, and the second position is determined based on the position of the second positioning point.
According to clause 12,
Calculating a first location accuracy corresponding to the first location based on the first distance, and calculating a second location accuracy corresponding to the second location based on the second distance,
A method of operating an electronic device, characterized in that the first location accuracy is greater than the second location accuracy.
According to clause 12,
estimating, by the at least one processor, a location of the first user device according to a first operation mode; and
A method of operating an electronic device further comprising estimating the location of the second user device according to a second calculation mode in which a calculation amount is set to be smaller than that of the first calculation mode.
According to clause 17,
The estimating step according to the first calculation mode includes estimating the location of the first user device based on AP data and acceleration data received from the first user device,
The estimating step according to the second calculation mode includes estimating the location of the second user device based on one of AP data or acceleration data received from the second user device.
According to clause 12,
A method of operating an electronic device, characterized in that the time interval between the first time point and the third time point is N (N = natural number) times the AP signal scan period of the first user device.
A user device located in an indoor space; and
A system comprising: an electronic device according to claim 1 for estimating a location of the user device in an indoor space.

Images