Intelligent Indoor Sign Management System for Buildings Based on Geographic Information

Abstract

The present invention discloses an intelligent indoor building identification management system based on geographic information, belonging to the technical field of indoor intelligent identification management, including: comprehensively collecting multi-dimensional information data of the indoor building by integrating laser scanning, Wi-Fi and Bluetooth signal strength measurement, and built-in sensors of user equipment; calculating the real-time position coordinates of the user by using a multi-source data fusion positioning model and uploading them to the user terminal; traversing the multi-dimensional information data to obtain the real-time position, traveling direction and speed of the user, and calculating the predicted position coordinates; obtaining the first identification by calculating the distance between the position information of each identification and the predicted position coordinates and comparing it with a preset radius, and dynamically adjusting the display priority thereof; optimizing and adjusting its size and brightness according to the priority of the first identification and the indoor ambient light intensity; receiving and displaying the first identification through the user terminal to realize dynamic update of the real-time position of the user.

Description

Technical Field

[0001] The present invention relates to the technical field of indoor intelligent sign management, and particularly to an indoor intelligent sign management system for buildings based on geographic information. Background Art

[0002] In modern society, the scale and complexity of buildings are constantly increasing. For buildings such as large shopping malls, hospitals, office buildings, airports, etc., their indoor structures are intricate, and people often face many difficulties when looking for specific destinations indoors; traditional indoor intelligent sign systems usually use fixed signboards, and these signboards have many limitations:

[0003] They cannot be dynamically adjusted and personalized according to the user's real-time position and traveling direction, resulting in users may get lost in the complex indoor environment, and need to spend a lot of time and energy to find the target location, reducing people's passing efficiency and experience.

[0004] The information displayed by the fixed signboards is relatively fixed and limited, which is difficult to meet the diverse needs of users; and it cannot be adjusted according to the changes of the indoor environment, resulting in users being unable to accurately obtain the sign information. Summary of the Invention

[0005] The purpose of the present invention is to overcome the deficiencies of the prior art and provide an indoor intelligent sign management system for buildings based on geographic information to solve the problems raised in the above background art.

[0006] The purpose of the present invention can be achieved by the following technical solutions: An indoor intelligent sign management system for buildings based on geographic information, including:

[0007] A data collection module, which comprehensively collects multi-dimensional information data of the indoor of the building through laser scanning, signal strength measurement of Wi-Fi and Bluetooth beacons, and built-in sensors of user equipment;

[0008] A positioning module, which uses a multi-source data fusion positioning model to calculate the user's real-time position coordinates and uploads the user's real-time position coordinates to the user terminal module;

[0009] A dynamic sign management module, which traverses the multi-dimensional information data to obtain the user's real-time position, traveling direction and speed, and calculates the predicted position coordinates; by calculating the distance between the position information of each sign and the predicted position coordinates and comparing it with a preset radius for judgment, the first sign is obtained and its display priority is dynamically adjusted;

[0010] A first sign adjustment module, which obtains the priority of the first sign and the indoor ambient light intensity, and respectively optimizes and adjusts the size and brightness of the first sign and displays it on the user terminal module;

[0011] The user terminal module is used to receive and display the first identifier and dynamically update the real-time position coordinates of the user.

[0012] Preferably, the specific implementation process of comprehensively collecting multi-dimensional information data includes:

[0013] Obtain the three-dimensional structure data of the building through laser scanning and record the position information of all identifiers in the building; wherein, the identifier is the name of the indoor layout of the building;

[0014] Deploy Wi-Fi access points and Bluetooth beacons at different positions indoors in the building, record the position information of the signal sources, and collect the signal strength between the user device and the signal sources; wherein, the signal sources include Wi-Fi access points and Bluetooth beacons;

[0015] Based on the sensors built in the user device, receive sensor data in real time, including geomagnetic data and user movement data at the current position of the user device; wherein, the geomagnetic data includes magnetic field strength and direction; the user movement data includes the travel direction vector and travel speed.

[0016] Preferably, the specific implementation content of the positioning module includes:

[0017] Obtain the signal strength between the user device and the signal sources, and use the Wi-Fi positioning model and the Bluetooth positioning model to calculate and obtain the estimated coordinate positions of the user device indoors in the building, including the first estimated coordinate position and the second estimated coordinate position;

[0018] Obtain the real-time geomagnetic data collected at the current position of the user device, and use the geomagnetic positioning model to match the user position according to the geomagnetic characteristics of each collection point in the pre-constructed geomagnetic feature database to obtain the third estimated coordinate position;

[0019] Based on the first, second, and third estimated coordinate positions, use the weighted fusion algorithm to calculate the real-time position coordinates of the user.

[0020] Preferably, the method for obtaining the estimated coordinate position of the user device indoors in the building is as follows:

[0021] Use the wireless signal propagation model to establish a signal source positioning model and obtain the estimated distance values of the user device from each signal source; wherein, the signal source positioning model is a Wi-Fi positioning model or a Bluetooth positioning model;

[0022] The calculation formula of the wireless signal propagation model is: ; where RSSI is the signal strength between the user device and any signal source; is the transmitted signal power, which is a known fixed value determined by the signal source; n is the path loss exponent; d is the estimated distance value between the signal source and the user device; It is a Gaussian random variable with a mean of 0, representing shadow fading; the trilateration method is used to obtain the estimated coordinate positions of the user equipment in the building indoor, namely the first estimated coordinate position and the second estimated coordinate position.

[0023] Preferably, the method for obtaining the third estimated coordinate position is as follows:

[0024] Based on the geomagnetic positioning model, by pre-measuring the geomagnetic intensity and direction at each position in the building, a three-dimensional geomagnetic feature database is formed;

[0025] Perform feature matching between the real-time geomagnetic data and the data in the geomagnetic feature database, and calculate the Euclidean distance between the real-time geomagnetic data and the geomagnetic features at each acquisition point in the geomagnetic feature database;

[0026] The calculation formula is as follows: ; In the formula, is the Euclidean distance between the real-time geomagnetic data and the geomagnetic features at any acquisition point in the geomagnetic feature database; is the real-time geomagnetic data, representing the horizontal component H in the magnetic north direction, the vertical component Z in the vertically downward direction, and the combined magnetic field intensity F respectively; is the geomagnetic feature of this acquisition point; among them, the subscript SS represents real-time data; the subscript K represents any acquisition point; obtain the Euclidean distance between the current position of the user equipment and the geomagnetic features at all acquisition points, and select the position of the acquisition point with the smallest distance as the third estimated coordinate position.

[0027] Preferably, the calculation formula of the weighted fusion algorithm is as follows: ; ;

[0028] ; In the formula, is the first estimated coordinate position; is the second estimated coordinate position, and the subscript b represents the Bluetooth positioning model; is the third estimated coordinate position, and the subscript m represents the geomagnetic positioning model; is the real-time position coordinate of the user, and the subscript u represents the user; 、 、 represent the Wi-Fi positioning weight, Bluetooth positioning weight, and geomagnetic positioning weight respectively.

[0029] Preferably, the specific implementation content of the dynamic identification management module includes:

[0030] Obtain the current travel direction vector and travel speed v of the user, and combine the current position coordinate of the user to calculate the predicted position coordinate; the calculation formula of the predicted position coordinate is as follows: ; ; ; wherein, is the time interval, representing the difference between the current time and the time to reach the predicted position coordinates; a, b, and c are the components of the user's current traveling direction vector on the x-axis, y-axis, and z-axis respectively; represents the predicted position coordinates, and the subscript p represents prediction; based on the predicted position coordinates and all the identified position information, the distance between each identifier and the predicted position coordinates is calculated through the Euclidean distance formula and compared with the preset radius R for judgment; if the calculated distance is less than or equal to the radius R, the corresponding identifier is marked as the first identifier and preferentially and intelligently displayed; among them, the identifiers within the circular area with the predicted position coordinates as the center and the radius of R are regarded as the first identifiers.

[0031] Preferably, the specific implementation content of the first identifier adjustment module includes:

[0032] Obtain the resolution of the screen and the original size of the first identifier, and calculate the scaling ratio of the first identifier through the formula ; wherein, s is the scaling ratio of the first identifier; BL is the proportion occupied by the first identifier on the screen. If BL = 0.1, it means that the first identifier occupies 10% of the screen area; W and H respectively represent the height and width of the screen; and are the original height and width of the first identifier respectively;

[0033] Calculate and obtain the size of the scaled first identifier through the formulas and ; wherein, YG and YK are the height and width of the scaled first identifier respectively.

[0034] Preferably, adjust the brightness of the first identifier through the formula ; wherein, B is the display brightness of the first identifier; is the original brightness of the first identifier; k is the adjustment coefficient, used to control the sensitivity of the brightness change with the ambient light; L is the current indoor ambient light intensity; is the average light intensity of normal indoor lighting; is the light intensity threshold.

[0035] To solve the above problems, the present invention also provides a method for intelligent management of indoor building identifiers based on geographic information, including the following steps:

[0036] Step 1: Comprehensively collect multi-dimensional information data of the indoor building through laser scanning, signal strength measurement of Wi-Fi and Bluetooth beacons, and built-in sensors of user equipment;

[0037] Step 2: Use the multi-source data fusion positioning model to calculate the user's real-time position coordinates and upload the user's real-time position coordinates to the user terminal;

[0038] Step 3: Traverse the multi-dimensional information data to obtain the user's real-time position, traveling direction and speed, and calculate the predicted position coordinates; by calculating the distance between the position information of each identifier and the predicted position coordinates and comparing it with the preset radius, obtain the first identifier and dynamically adjust its displayed priority;

[0039] Step 4: Obtain the priority of the first identifier and the indoor ambient light intensity, and respectively optimize and adjust the size and brightness of the first identifier and display it;

[0040] Step 5: Receive and display the first identifier, and dynamically update the user's real-time position coordinates.

[0041] Compared with the existing solutions, the beneficial effects achieved by the present invention are as follows:

[0042] Through laser scanning technology, the present invention can accurately obtain the spatial structure and object distribution information inside the building, providing basic data for constructing an accurate indoor map;

[0043] Using Wi-Fi and Bluetooth signal strength measurement technologies, the distance between the user and the signal source can be estimated by detecting the signal strength, thereby assisting in locating the user's approximate position indoors; while the sensors built into the user device, such as accelerometers, gyroscopes, etc., can real-time sense the user's motion state, including information such as traveling direction and speed;

[0044] Integrating and applying these technologies to the indoor identifier management system of the building can achieve precise positioning of the user's position and dynamic management of the identifier information, thereby effectively overcoming the shortcomings of the traditional indoor identifier system, improving the accuracy and convenience of indoor navigation, and meeting the needs of people to quickly and accurately find the destination in a complex indoor environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The following further describes the present invention with reference to the drawings.

[0046] Figure 1 It is a module structure diagram of the indoor intelligent identifier management system of the building based on geographic information proposed by the present invention.

[0047] Figure 2 It is a flow block diagram of the indoor intelligent identifier management method of the building based on geographic information proposed by the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0048] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0049] Embodiment 1, as Figure 1 shown, the present invention is an intelligent indoor building identification management system based on geographic information, including: a data collection module, a positioning module, a dynamic identification management module, a first identification adjustment module, and a user terminal module;

[0050] The data collection module comprehensively collects multi-dimensional information data of the building interior through laser scanning, signal strength measurement of Wi-Fi and Bluetooth beacons, and built-in sensors of user devices, specifically including:

[0051] Obtain the three-dimensional structure data of the building through laser scanning, and record the position information of all identifications in the building; among them, the identification is the name of the indoor layout of the building;

[0052] Deploy Wi-Fi access points and Bluetooth beacons at different positions in the building interior, record the position information of the signal sources, and collect the signal strength between the user device and the signal sources; among them, the signal sources include Wi-Fi access points and Bluetooth beacons;

[0053] Based on the built-in sensors of the user device, sensor data is received in real time, including geomagnetic data and user movement data at the current position of the user device; among them, the geomagnetic data includes magnetic field strength and direction; the user movement data includes the travel direction vector and travel speed;

[0054] In the embodiments of the present invention, through the integration of multiple sensors and technical means, a comprehensive perception and data collection of the building interior environment are realized, providing a data basis for subsequent indoor positioning.

[0055] The positioning module obtains the signal strength between the user device and the signal sources, and uses the Wi-Fi positioning model and the Bluetooth positioning model to calculate and obtain the estimated coordinate positions of the user device in the building interior, including the first estimated coordinate position and the second estimated coordinate position;

[0056] Furthermore, a signal source positioning model is established using the wireless signal propagation model to obtain the estimated distance values of the user device from each signal source; among them, the signal source positioning model is a Wi-Fi positioning model or a Bluetooth positioning model;

[0057] The calculation formula of the wireless signal propagation model is:

[0058] ; where RSSI is the signal strength between the user device and any signal source; is the transmit signal power, which is a known fixed value determined by the signal source; n is the path loss exponent; d is the estimated distance between the signal source and the user equipment; is a Gaussian random variable with a mean of 0, representing shadow fading;

[0059] It should be noted that the path loss exponent is related to the indoor environment of the building. For example, the value may be different in an empty indoor corridor and an indoor room with many partitions, and it needs to be determined through multiple on-site tests and calibrations;

[0060] Exemplarily, obtain its transmit power from the device specification of the Wi-Fi access point ; By selecting multiple location points with known distances within the Wi-Fi coverage area, measuring the Wi-Fi signal strength values corresponding to the location points, substituting them into the calculation formula of the wireless signal propagation model, and using the least squares method to fit the value of n, obtain the Wi-Fi positioning model; Similarly, obtain the Bluetooth positioning model;

[0061] Furthermore, use the trilateration method to obtain the estimated coordinate positions of the user equipment in the building indoor, which are the first estimated coordinate position and the second estimated coordinate position respectively;

[0062] Exemplarily, obtain the coordinate positions of four Wi-Fi access points and the estimated distances corresponding to the user equipment, and use the trilateration method to calculate the first estimated coordinate position of the user equipment in the building indoor;

[0063] The calculation formula is as follows:

[0064] ; In the formula, , , , are the coordinate positions of the four Wi-Fi access points respectively; , , , are the estimated distances corresponding to the user equipment respectively; represents the first estimated coordinate position, and the subscript w represents the Wi-Fi positioning model;

[0065] Similarly, obtain the coordinate positions of four Bluetooth beacons and the estimated distances corresponding to the user equipment, and use the trilateration method to calculate the second estimated coordinate position of the user equipment in the building indoor;

[0066] Obtain the real-time geomagnetic data collected at the current position of the user equipment, and use the geomagnetic positioning model to match the user position according to the geomagnetic characteristics of each collection point in the pre-constructed geomagnetic feature database to obtain the third estimated coordinate position;

[0067] Further, based on the geomagnetic positioning model, by pre-measuring the geomagnetic intensity and direction at each location within a building, a three-dimensional geomagnetic feature database is formed;

[0068] Among them, each record in the geomagnetic feature database includes a collection point number, three-dimensional coordinate position, horizontal component of the magnetic north direction, vertical component in the vertically downward direction, and synthetic magnetic field intensity;

[0069] Match the real-time geomagnetic data with the data in the geomagnetic feature database, and calculate the Euclidean distance between the real-time geomagnetic data and the geomagnetic features of each collection point in the geomagnetic feature database;

[0070] The calculation formula is as follows: ; In the formula, is the Euclidean distance between the real-time geomagnetic data and the geomagnetic features of any collection point in the geomagnetic feature database; is the real-time geomagnetic data, representing the horizontal component H of the magnetic north direction, the vertical component Z in the vertically downward direction, and the synthetic magnetic field intensity F respectively; is the geomagnetic feature of this collection point; among them, the subscript SS represents real-time data; the subscript K represents any collection point;

[0071] Obtain the Euclidean distance of the geomagnetic features between the current position of the user device and all collection points, and select the position of the collection point with the smallest distance as the third estimated coordinate position;

[0072] Based on the first, second, and third estimated coordinate positions, use a weighted fusion algorithm to calculate the real-time position coordinates of the user;

[0073] The calculation formula is as follows: ; ; ; In the formula, is the first estimated coordinate position; is the second estimated coordinate position, and the subscript b represents the Bluetooth positioning model; is the third estimated coordinate position, and the subscript m represents the geomagnetic positioning model; is the real-time position coordinates of the user, and the subscript u represents the user; 、 、 respectively represent the Wi-Fi positioning weight, Bluetooth positioning weight, and geomagnetic positioning weight, and their weight values are determined according to the accuracy test results of each positioning method in different environments.

[0074] The dynamic identification management module traverses the multi-dimensional information data to obtain the real-time position, traveling direction, and speed of the user, and calculates the predicted position coordinates; by calculating the distance between the position information of each identification and the predicted position coordinates, and comparing it with the preset radius for judgment, the first identification is obtained and its display priority is dynamically adjusted;

[0075] Further, obtain the current traveling direction vector of the user and the traveling speed v, and combine with the current position coordinates of the user to calculate the predicted position coordinates; wherein, the predicted position coordinates represent the position coordinates that the user can reach at the next time;

[0076] The calculation formula of the predicted position coordinates is as follows: ; ; ; In the formula, is the time interval, representing the difference between the current time and the time to reach the predicted position coordinates; a, b, and c are the components of the current traveling direction vector of the user on the x-axis, y-axis, and z-axis respectively; represents the predicted position coordinates, and the subscript p represents prediction;

[0077] Based on the predicted position coordinates and the position information of all identifiers, calculate the distance between each identifier and the predicted position coordinates through the Euclidean distance formula, and compare it with the preset radius R for judgment;

[0078] If the calculated distance is less than or equal to the radius R, mark the corresponding identifier as the first identifier and display it preferentially and intelligently; among them, the identifiers within the circular area with the predicted position coordinates as the center and the radius of R are regarded as the first identifiers;

[0079] It should be noted that the above-mentioned preferential intelligent display is to perform intelligent display on the user terminal module according to the principle that the closer the distance, the higher the priority;

[0080] The first identifier adjustment module obtains the priority of the first identifier and the indoor ambient light intensity, and optimizes and adjusts the size and brightness of the first identifier respectively and displays them on the user terminal module; further, obtain the screen resolution and the original size of the first identifier, and use the formula to calculate the scaling ratio of the first identifier; where s is the scaling ratio of the first identifier; BL is the proportion occupied by the first identifier on the screen. If BL = 0.1, it means that the first identifier occupies 10% of the screen area; W and H respectively represent the height and width of the screen; and are the original height and width of the first identifier respectively; use the formulas and to calculate and obtain the size of the first identifier after scaling; where YG and YK are the height and width of the first identifier after scaling respectively; further, use the formula to adjust the brightness of the first identifier; where B is the display brightness of the first identifier; is the original brightness of the first identifier; k is the adjustment coefficient, used to control the sensitivity of the brightness change with the ambient light; L is the current indoor ambient light intensity; is the average light intensity of normal indoor lighting; is the light intensity threshold;

[0081] It should be noted that when the ambient light is strong, increase the display brightness B of the first identifier to make the first identifier more clearly visible; when the ambient light is weak, decrease the display brightness B of the first identifier to avoid being too bright and dazzling.

[0082] The user terminal module is used to receive and display the first identifier and dynamically update the real-time position coordinates of the user.

[0083] Embodiment 2, as Figure 2 shown, the intelligent indoor identification management method of a building based on geographic information includes the following steps:

[0084] Step 1: Comprehensively collect multi-dimensional information data of the indoor of the building through laser scanning, signal strength measurement of Wi-Fi and Bluetooth beacons, and built-in sensors of user devices;

[0085] Step 2: Use the multi-source data fusion positioning model to calculate the real-time position coordinates of the user and upload the real-time position coordinates of the user to the user terminal;

[0086] Step 3: Traverse the multi-dimensional information data to obtain the real-time position, traveling direction and speed of the user, and calculate the predicted position coordinates; by calculating the distance between the position information of each identifier and the predicted position coordinates and comparing it with the preset radius for judgment, obtain the first identifier and dynamically adjust its display priority;

[0087] Step 4: Obtain the priority of the first identifier and the indoor ambient light intensity, and respectively optimize and adjust the size and brightness of the first identifier and display it;

[0088] Step 5: Receive and display the first identifier and dynamically update the real-time position coordinates of the user.

[0089] In several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described invention embodiments are merely illustrative. For example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0090] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0091] In addition, in each embodiment of the present invention, each functional module can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware, or in the form of a combination of hardware and software functional modules.

[0092] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. The building indoor intelligent identification management system based on geographic information is characterized by: include: The data collection module collects comprehensive multi-dimensional indoor information data of buildings through laser scanning, signal strength measurement of Wi-Fi and Bluetooth beacons, and built-in sensors of user devices; The specific implementation process of comprehensively collecting multi-dimensional information data includes but is not limited to: obtaining three-dimensional structural data of the building through laser scanning, and recording the location information of all signs in the building; wherein the signs are the names of the indoor layouts of the buildings; A positioning module, using a multi-source data fusion positioning model to calculate the first, second, and third estimated coordinate positions of the user equipment in the building; Acquire the signal strength between the user equipment and the signal source, and use the Wi-Fi positioning model and the Bluetooth positioning model to respectively calculate and obtain the estimated coordinate position of the user equipment in the building, including a first estimated coordinate position and a second estimated coordinate position; Acquire real-time geomagnetic data collected at the current position of the user device, use the geomagnetic positioning model to match the user position according to the geomagnetic features of each collection point in the pre-built geomagnetic feature database, and obtain a third estimated coordinate position; Based on the first, second and third estimated coordinate positions, a weighted fusion algorithm is used to obtain the user's real-time position coordinates and upload them to the user terminal module; The dynamic identification management module traverses the multi-dimensional information data to obtain the user's real-time location, travel direction and speed, and calculates the predicted location coordinates; by calculating the distance between the location information of each identification and the predicted location coordinates, and comparing and judging with the preset radius, the first identification is obtained and its display priority is dynamically adjusted; A first identification adjustment module, which obtains the priority of the first identification and the indoor ambient light intensity, optimizes and adjusts the size and brightness of the first identification respectively and displays it on the user terminal module; The user terminal module is used to receive and display the first identification and dynamically update the user's real-time location coordinates.

2. The building indoor intelligent identification management system based on geographic information according to claim 1 is characterized in that: The specific implementation process of comprehensive collection of multi-dimensional information data also includes: Deploy Wi-Fi access points and Bluetooth beacons at different locations indoors in buildings, record the location information of signal sources, and collect signal strengths between user devices and signal sources; signal sources include Wi-Fi access points and Bluetooth beacons; Based on the built-in sensors of the user device, sensor data is received in real time, including geomagnetic data of the current location of the user device and user motion data; wherein the geomagnetic data includes magnetic field strength and direction; the user motion data includes the moving direction vector and moving speed.

3. The building indoor intelligent identification management system based on geographic information according to claim 1 is characterized in that: The method for obtaining the estimated coordinate position of the user equipment in the building is as follows: A signal source positioning model is established using a wireless signal propagation model to obtain an estimated value of the distance between the user device and each signal source; wherein the signal source positioning model is a Wi-Fi positioning model or a Bluetooth positioning model; The calculation formula of the wireless signal propagation model is: RSSI=P T -10nlog 10 (d)+X σ ; Where RSSI is the signal strength between the user equipment and any signal source; P T is the transmitted signal power, which is a known fixed value determined by the signal source; n is the path loss index; d is the estimated distance between the signal source and the user equipment; X σ is a Gaussian random variable with mean 0, representing shadow fading; The three-sided positioning method is used to obtain the estimated coordinate position of the user equipment in the building, which are the first estimated coordinate position and the second estimated coordinate position.

4. The building indoor intelligent identification management system based on geographic information according to claim 3 is characterized in that: The method for obtaining the third estimated coordinate position is as follows: Based on the geomagnetic positioning model, a three-dimensional geomagnetic feature database is formed by pre-measuring the geomagnetic intensity and direction of each location in the building; Perform feature matching on the real-time geomagnetic data and the data in the geomagnetic feature database, and calculate the Euclidean distance between the real-time geomagnetic data and the geomagnetic feature of each acquisition point in the geomagnetic feature database; The calculation formula is as follows: In the formula, OS d is the Euclidean distance between the real-time geomagnetic data and the geomagnetic feature of any acquisition point in the geomagnetic feature database; (H SS ,Z SS ,F SS ) are real-time geomagnetic data, representing the horizontal component H in the magnetic north direction, the vertical component Z in the vertical downward direction, and the synthetic magnetic field intensity F; (H K ,Z K ,F K ) is the geomagnetic characteristic of the collection point; wherein, the subscript SS represents real-time data; the subscript K represents any collection point; The Euclidean distances of the geomagnetic features between the current position of the user device and all the collection points are obtained, and the collection point position with the smallest distance is selected as the third estimated coordinate position.

5. The building indoor intelligent identification management system based on geographic information according to claim 4 is characterized in that: The calculation formula of the weighted fusion algorithm is as follows: In the formula, (x w ,y w ,z w ) is the first estimated coordinate position; (x b ,y b ,z b ) is the second estimated coordinate position, and the subscript b represents the Bluetooth positioning model; (x m ,y m ,z m ) is the third estimated coordinate position, and the subscript m represents the geomagnetic positioning model; (x u ,y u ,z u ) is the user's real-time location coordinates, and the subscript u represents the user; ω w ,ω b ,ω m They represent Wi-Fi positioning weight, Bluetooth positioning weight, and geomagnetic positioning weight respectively.

6. The building indoor intelligent identification management system based on geographic information according to claim 5 is characterized in that: The specific implementation contents of the dynamic identification management module include: Get the user's current direction vector and the travel speed v, combined with the user's current location coordinates, to calculate the predicted location coordinates; The calculation formula for the predicted position coordinates is as follows: x p =x u +v×a×△t; and p =and u +v×b×△t; With p =from u +v×c×△t; Where △t is the time interval, which represents the difference between the current time and the time to reach the predicted location coordinates; a, b, and c are the components of the user's current travel direction vector on the x-axis, y-axis, and z-axis respectively; (x p ,y p ,z p ) represents the predicted position coordinates, and the subscript p represents prediction; Based on the predicted location coordinates and the location information of all markers, the distance between each marker and the predicted location coordinates is calculated using the Euclidean distance formula, and compared with the preset radius R for judgment; If the calculated distance is less than or equal to the radius R, the corresponding marker is recorded as the first marker and displayed intelligently with priority; among them, the marker within the circular area with a radius of R centered on the predicted position coordinates is regarded as the first marker.

7. The building indoor intelligent identification management system based on geographic information according to claim 6 is characterized in that: The specific implementation content of the first identification adjustment module includes: Get the screen resolution and the original size of the first logo, through the formula Calculate the scaling ratio of the first logo; where s is the scaling ratio of the first logo; BL is the ratio of the first logo on the screen, if BL=0.1, it means that the first logo occupies 10% of the screen area; W and H represent the height and width of the screen respectively; YG0 and YK0 are the original height and width of the first logo respectively; The size of the scaled first logo is calculated by formulas YG=s×YG0 and YK=s×YK0; wherein YG and YK are the height and width of the scaled first logo, respectively.

8. The building indoor intelligent identification management system based on geographic information according to claim 7 is characterized in that: By formula Adjust the brightness of the first mark; wherein B is the display brightness of the first mark; B0 is the original brightness of the first mark; k is the adjustment coefficient, which is used to control the sensitivity of the brightness to changes in ambient light; L is the current indoor ambient light intensity; L0 is the average light intensity of normal indoor lighting; L1 is the light intensity threshold.

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