Patent Publication Number: US-2023135277-A1

Title: Hybrid indoor positioning system

Description:
BACKGROUND OF THE INVENTION 
     Field of Invention 
     The invention relates to an indoor positioning system, and more particularly to a hybrid indoor positioning system capable of computing a positioning result by combining a user&#39;s inertial momentum with an ambient wireless signal and an ambient magnetic force in an indoor field, thereby achieving precise positioning and reducing set up costs. 
     Related Art 
     At present, the common indoor positioning technologies can mainly be divided into wireless signal positioning, image visual positioning, optical sensor positioning and inertial positioning. Wherein the signal types of wireless signal positioning include wireless signal technologies such as Bluetooth, UWB, RFID, Wi-Fi, wireless signal positioning is achieved by setting up multiple wireless signal sources in the field, and using a signal receiving device with algorithms such as AOA, TOA, triangular positioning, fingerprint positioning to compute the absolute position of the receiving device in the field. But the wireless signal of signal positioning technology will be affected by ambient factors, such as indoor structure or indoor structure materials, which will cause the wireless signal to oscillate, and the condition of unstable wireless signal will cause the signal positioning result to drift constantly, relatively causing difficulties in actual positioning. 
     Wherein the image visual positioning mainly uses computer vision to collect images from the entire field, it is mainly combined with AI model training such as YOLO algorithm for model training. In application, a camera lens is used to capture the surrounding ambient pictures and input the AI model to obtain the positioning position, but the image visual positioning is very dependent on the ambient complexity, if the ambient appearance is too monotonous, the positioning accuracy will be greatly reduced. 
     Wherein the optical sensor positioning is achieved by scanning and modeling the field environment by using optical sensors of invisible light such as laser and infrared ray, it mainly needs to have a transmitting end and a receiving end to accurately compute the distance between the equipment and the scanning point, and the ambient model is established by 360-degree surround method, which is then used as the basis for positioning. But the optical sensor is an expensive device, it also requires stable operating conditions and is not suitable for being placed on the user as a wearable device, so the application is relatively limited by situations. 
     Wherein the inertial positioning mainly uses the motion data collected by the terminal inertial sensor to measure the speed, direction, acceleration of the object, and then obtains the position information of the object through various computations based on dead reckoning, but with the increase of walking time, the error of its inertial navigation positioning is also continuously accumulated, so the problem of errors increasing with time occurs. 
     Therefore, the inventor of the invention and relevant manufacturers engaged in this industry are eager to research and make improvement to solve the above-mentioned problems and drawbacks in the prior art. 
     SUMMARY OF THE INVENTION 
     Therefore, in order to effectively solve the above problems, a main object of the invention is to provide a hybrid indoor positioning system capable of computing a positioning result by combining a user&#39;s inertial momentum with an ambient wireless signal and an ambient magnetic force in an indoor field, thereby achieving precise positioning and reducing set up costs. 
     In order to achieve the above object, the invention provides a hybrid indoor positioning system comprising an electronic label, the electronic label is configured by a user, the electronic label is provided with an acceleration sensing module, a first direction sensing module, a second direction sensing module and an operational module, wherein the acceleration sensing module senses movement of the user and generates an acceleration signal, the operational module receives the acceleration signal and generates a movement data, the first direction sensing module and the second direction sensing module sense the movement of the user and generate a first direction signal and a second direction signal respectively, the operational module receives the first direction signal and the second direction signal and generates a direction data, the electronic label is provided with a signal receiving module to receive an ambient wireless information within a range that can be received by the user and to generate an ambient wireless signal, the movement data and the direction data of the operational module are transmitted to a signal sending module; and a remote server, the remote server has a central processing unit and a signal receiving unit, the signal receiving unit receives the movement data, the direction data and the ambient wireless signal which are transmitted to the central processing unit, at least one field map data and an ambient signal database are set up in the remote server, the ambient signal database has a plurality of wireless signal combination data and a plurality of corresponding coordinate data, the central processing unit captures the ambient wireless signal and compares with the wireless signal combination data and generates an initial coordinate information, the central processing unit also captures the movement data and the direction data and compares with the field map data and generates a movement information, so that the remote server is capable of acquiring a user&#39;s starting position through the coordinate information and acquiring a user&#39;s moving direction through the movement information and generating a real-time coordinate information. 
     According to one embodiment of the hybrid indoor positioning system of the invention, wherein the electronic label further has a label identification code, the label identification code is transmitted by the signal sending module to the signal receiving unit, so that the central processing unit is capable of simultaneously capturing the movement data, the direction data, the ambient wireless signal and the label identification code. 
     According to one embodiment of the hybrid indoor positioning system of the invention, wherein the wireless signal combination data comprise at least one network domain combination information and at least one network domain signal strength information. 
     According to one embodiment of the hybrid indoor positioning system of the invention, wherein the ambient signal database further comprises a sampling extension data. 
     According to one embodiment of the hybrid indoor positioning system of the invention, wherein the field map data comprise a movable area and an immovable area. 
     According to one embodiment of the hybrid indoor positioning system of the invention, wherein the remote server further comprises a step database, the step database is electrically connected to the central processing unit, the central processing unit captures the movement data that is compared with the step database, and then compares the compared movement data and the direction data with the field map data and generates the movement information. 
     According to one embodiment of the hybrid indoor positioning system of the invention, wherein the first direction sensing module senses a user&#39;s ambient magnetic force and generates a magnetic force information, and the signal sending module receives the magnetic force information. 
     According to one embodiment of the hybrid indoor positioning system of the invention, wherein the remote server further comprises a judgment model, the signal receiving unit receives the magnetic force information and transmits the magnetic force information to the judgment model, the judgment model captures the magnetic force information and generates a corresponding coordinate information and transmits the corresponding coordinate information to the central processing unit, and the central processing unit generates a positioning position by computing the real-time coordinate information and the corresponding coordinate information, so that the remote server is capable of acquiring a user&#39;s real-time position through the positioning position. 
     According to one embodiment of the hybrid indoor positioning system of the invention, wherein the remote server further comprises a data cleaning module, the data cleaning module is signally connected to the signal receiving unit and the judgment model, the data cleaning module receives the magnetic force information and generates a cleaning data that is transmitted to the judgment model, and the judgment model captures the cleaning data and generates the corresponding coordinate information. 
     According to one embodiment of the hybrid indoor positioning system of the invention, wherein the signal receiving unit receives an acceleration data and a direction data and transmits the acceleration data and the direction data to the judgment model, the judgment model captures the magnetic force information, the acceleration data and the direction data and generates a corresponding coordinate information and transmits the corresponding coordinate information to the central processing unit, and the central processing unit generates a positioning position by computing the real-time coordinate information and the corresponding coordinate information, so that the remote server is capable of acquiring a user&#39;s real-time position through the positioning position. 
     According to one embodiment of the hybrid indoor positioning system of the invention, wherein the remote server further comprises a data cleaning module, the data cleaning module is signally connected to the signal receiving unit and the judgment model, the data cleaning module receives the magnetic force information, the acceleration data and the direction data, and generates a cleaning data that is transmitted to the judgment model, and the judgment model captures the cleaning data and generates the corresponding coordinate information. 
     According to one embodiment of the hybrid indoor positioning system of the invention, wherein the central processing unit captures the ambient wireless signal and compares with the wireless signal combination data and generates an ambient coordinate information, and the central processing unit generates the positioning position by computing the real-time coordinate information, the corresponding coordinate information and the ambient coordinate information, so that the remote server is capable of acquiring a user&#39;s real-time position through the positioning position. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a block diagram of a hybrid indoor positioning system of the invention. 
         FIG.  2    is a schematic diagram of wireless signal combination data of the hybrid indoor positioning system of the invention. 
         FIG.  3    is a first block diagram of the hybrid indoor positioning system of the invention. 
         FIG.  4    is a schematic diagram of travel path in a movable area and an immovable area of the hybrid indoor positioning system of the invention. 
         FIG.  5    is a second block diagram of the hybrid indoor positioning system of the invention. 
         FIG.  6    is a third block diagram of the hybrid indoor positioning system of the invention. 
         FIG.  7    is a fourth block diagram of the hybrid indoor positioning system of the invention. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     The above object of the invention, as well as its structural and functional features, will be described in accordance with the preferred embodiments of the accompanying drawings. 
     In the following, for the formation and technical content related to a hybrid indoor positioning system of the invention, various applicable examples are exemplified and explained in detail with reference to the accompanying drawings; however, the invention is of course not limited to the enumerated embodiments, drawings, or detailed descriptions. 
     Furthermore, those who are familiar with this technology should also understand that the enumerated embodiments and accompanying drawings are only for reference and explanation, and are not used to limit the invention; other modifications or alterations that can be easily implemented based on the detailed descriptions of the invention are also deemed to be within the scope without departing from the spirit or intention thereof as defined by the appended claims and their legal equivalents. 
     And, the directional terms mentioned in the following embodiments, for example: “above”, “below”, “left”, “right”, “front”, “rear”, etc., are only directions referring in the accompanying drawings. Therefore, the directional terms are used to illustrate rather than limit the invention. In addition, in the following embodiments, the same or similar elements will be labeled with the same or similar numerals. 
     Firstly, please refer to  FIG.  1    for a block diagram of a hybrid indoor positioning system  1  of the invention. It can be clearly seen from the figure that the hybrid indoor positioning system  1  comprises an electronic label  2  and a remote server  3 . 
     Wherein the electronic label  2  is provided with an acceleration sensing module  21 , a first direction sensing module  22 , a second direction sensing module  23  and an operational module  24 , wherein the acceleration sensing module  21  is an accelerometer, the first direction sensing module  22  is a magnetometer, the second direction sensing module  23  is a gyroscope, and wherein the electronic label  2  further has a signal receiving module  25 , a signal sending module  26  and a label identification code  27 . 
     The remote server  3  has a central processing unit  31  and a signal receiving unit  32 , the central processing unit  31  is electrically connected to the signal receiving unit  32 , and the signal receiving unit  32  is signally connected to the signal sending module  26 . At least one field map data  33 , an ambient signal database  34  and a step database  35  are set up in the remote server  3 , the field map data  33  and the ambient signal database  34  are set up before the hybrid indoor positioning system  1  is put into use. Wherein the field map data  33  is a floor plan of building information and can be 2D or 3D, so the field map data  33  comprises a movable area  331  and an immovable area  332  (as shown in  FIG.  4   ). Wherein the movable area  331  is an area that the user can move or can be moved therein such as elevator, aisle or room, the immovable area  332  is an object that the user cannot move or traverse therein, such as wall or column, the ambient signal database  34  comprises a plurality of wireless signal combination data  341  and a plurality of coordinate data  342 , the wireless signal combination data  341  comprises at least one network domain combination information  3411  and a network domain signal strength information  3412  (as shown in  FIG.  2   ), wherein when the ambient signal database  34  is set up, a builder tests and samples wireless signal conditions in an indoor environment first, as shown in  FIG.  2   . Assuming wireless signal conditions displayed at a coordinate position ( 125 ,  50 ) comprise domain A, domain B and domain C, the domain A, the domain B and the domain C are the network domain combination information  3411 , or hardware device ID (BSSID) that generates network domain signals of the domain A, the domain B and the domain C is the network domain combination information  3411 , and the domain A, the domain B and the domain C have their respective displayed network domain signal strength information  3412 , the network domain combination information  3411  and the network domain signal strength information  3412  are used to create the wireless signal combination data  341 , and the wireless signal combination data  341  correspond to the coordinate data  342  of the coordinate position ( 125 ,  50 ), and so on. The builder tests the network domain combination information  3411  and the coordinate data  342  of coordinate positions in an indoor environment, and after the builder has tested multiple sets of the network domain combination information  3411  and the coordinate data  342  in the indoor environment, the remote server  3  calculates each set of the network domain combination information  3411  and the coordinate data  342  into an ambient signal model through machine learning algorithm, random forest algorithm, and stores the ambient signal model in the ambient signal database  34 , wherein when data in the ambient signal database  34  are used, the cleaned wireless signal combination data  341  and the coordinate data  342  can be generated through data cleaning first. The central processing unit  31  is signally connected to the field map data  33  and the ambient signal database  34 , and the step database  35  is set up with different step distances for different users. 
     Then, please refer to  FIG.  3    for a first block diagram of the hybrid indoor positioning system of the invention, wherein when a user is equipped with the electronic label  2  and enters an indoor environment, the signal receiving module  25  of the electronic label  2  first receives wireless signal conditions in the environment, so the signal receiving module  25  receives the network domain combination information  3411  and the network domain signal strength information  3412 , and the signal receiving module  25  transmits the network domain combination information  3411  and the network domain signal strength information  3412  to the signal receiving unit  32  by an ambient wireless signal S1 through the signal sending module  26 . The central processing unit  31  captures the label identification code  27  and the ambient wireless signal S1, the central processing unit  31  calculates into an ambient signal model through algorithms such as machine learning algorithm, random forest algorithm, the central processing unit  31  compares the coordinate data  342  corresponding to the ambient signal model calculated by algorithm from the network domain combination information  3411  and the coordinate data  342 , and then generates an initial coordinate information. The initial coordinate information is a starting position of the user, after the builder captures the starting position of the user, the electronic label  2  of the user is positioned from the starting position, and the initial coordinate information can be displayed on a display screen  36  with the field map data  33 , or the remote server  3  can be a cloud system, and the cloud system enables a smart device at an application end to access the starting coordinate position through API and the starting coordinate position is displayed on a screen of the smart device. 
     When the user is equipped with the electronic label  2  to move in the field map data  33 , the acceleration sensing module  21  senses the user&#39;s movement and generates an acceleration signal S2, the operational module  24  receives the acceleration signal S2 and generates a movement data D1 through a peak detection algorithm, wherein the acceleration signal S2 is mainly a waveform signal with periodic changes generated by its moving speed, and the operational module  24  captures a number of crests of the waveform signal and then calculates a number of moving steps from the number of crests. For example: when a person is walking, each time he takes a step, the continuously generated acceleration signal S2 will form a waveform of crests and troughs. Therefore, a number of crests can be used to determine a number of moving steps, and the movement data D1 is transmitted to the signal receiving unit  32  via the signal sending module  26 . The central processing unit  31  captures the movement data D1 and compares the movement data D1 with the step database  35 , and the step database  35  stored in the remote server  3  is set up with different step distances for different users. For example, a step for an adult is 60 cm, and a step for a child is 40 cm, a moving distance of the user can be converted by using a number of moving steps obtained through the above and the step database  35 , and conversion of the moving distance only needs to be performed once for the same target. For example, when a crest is generated and the user is an adult, it can be judged that the user has moved 60 cm. 
     When the user is equipped with the electronic label  2  to move in the field map data  33 , the first direction sensing module  22 , which is a magnetometer, senses a moving direction of the user and generates a first direction signal S3, and the second direction sensing module  23 , which is a gyroscope, generates a second direction signal S4, the first direction signal S3 and the second direction signal S4 are transmitted to the operational module  24 , and the operational module  24  receives the first direction signal S3 and the second direction signal S4 and generates a direction data D2 through a four-element compensation correction algorithm, and then transmits the direction data D2 to the central processing unit  31 , so that through the direction data D2, the central processing unit  31  is capable of determining an absolute direction of the electronic label  2 , such as orientation of facing east or west or south or north. However, the first direction sensing module  22 , which is a magnetometer, is easily interfered by ambient magnetic field. In order to prevent the first direction sensing module  22  from being interfered by magnetic field of a surrounding environment, resulting in inaccurate determination of orientation, signals generated by the second direction sensing module  23 , which is a gyroscope, are used for comparison and correction to obtain a relatively accurate orientation, so the second direction sensing module  23 , which is a gyroscope, generates the second direction signal S4, so that through the direction data D2, the central processing unit  31  is capable of determining a relative direction of the electronic label  2  in order to obtain a relatively accurate orientation. Specifically: because signals of the gyroscope are not easily interfered by environment, they are used to compare and correct signals of the magnetometer, and signals of the gyroscope are related to a starting orientation, so it is called a relative direction. For example, when a starting orientation is based on the east, a display angle of the gyroscope is 0 degree. When the direction turns to the south, the angle changes to positive 90 degrees. On the contrary, if a starting orientation is facing the south, at this time, it is based on the south, and a display angle is minus 90 degrees when the direction is turned to the east. Therefore, when a starting orientation is known, changes of its angle can be used to judge a current direction. Therefore, the hybrid indoor positioning system  1  is capable of confirming an orientation of the user through the first direction signal S3 and the second direction signal S4 obtained by the first direction sensing module  22  and the second direction sensing module  23 , if the first direction signal S3 is interfered by ambient magnetic field during movement, the second direction signal S4 can be used to correct orientation easily. For example, when the first direction signal S3 and the second direction signal S4 are judged by the operational module  24  to face inconsistency, at this time, the first direction signal S3 may be interfered ambiently, the operational module  24  can compute a relatively accurate orientation by using the first direction signal S3 and the second direction signal S4. For example, a direction determined by the first direction signal S3 faces south, while the second direction signal S4 determines that the direction is southeast, an orientation computed by the operational module  24  is south-south-east, and the orientation is between the orientations determined by the two signals. Therefore, a relatively accurate orientation can be obtained through correction. In addition, the central processing unit  31  captures the movement data D1 and the direction data D2 and compares with the field map data  33  and generates a movement information, and therefore movement information of the user in the field map data  33  can be determined stably. Through the initial coordinate information the remote server  3  is capable of acquiring a starting position of the user, and through the movement information the remote server  3  is capable of acquiring a moving direction of the user, and a real-time coordinate information is generated. Thereby, after the central processing unit  31  determines an absolute direction, a relative direction and a moving distance of the user through the movement data D1 and the direction data D2, a facing position, a movement information and a real-time coordinate information of the user can be acquired. The facing position, the movement information and the real-time coordinate information can also be displayed on the display screen  36  with the field map data  33 . Further, when the operational module  24  receives the first direction signal S3 and the second direction signal S4, the operational module  24  can simultaneously receive the acceleration signal S2. The operational module  24  uses a four-element compensation correction algorithm to compute the acceleration signal S2, the first direction signal S3 and the second direction signal S4 in order to calculate the direction data D2 with three-axis changes, and accuracy of the direction data D2 can be improved through more correction information. 
     As shown in  FIG.  4   , the central processing unit  31  is capable of further optimizing the movement data D1 and the direction data D2. The central processing unit  31  is capable of calculating displacement of the user by using moving distance and travel direction with collision processing algorithm or discrepancy correction algorithm or multi-path algorithm or particle filter algorithm, and superimposing position coordinates of a previous position to calculate its movement track and optimize its movement track in order to reduce the occurrence of judgment errors caused by accumulated errors. The optimization method is that the central processing unit  31  can be used for correction with the field map data  33 . If travel direction is within the movable area  331 , travel direction can be continuously positioned. Otherwise, if travel direction is within the immovable area  332 , travel direction will be restored to a coordinate position of a previous reasonable position. After judging the absolute direction and relative direction and moving distance of the user through the movement data D1 and the direction data D2 again, travel direction can be corrected, or travel direction can be displayed by the display screen  36  or displayed by a smart device at an application end after computed by a cloud system. Thereby the hybrid indoor positioning system  1  of the invention is capable of calculating positioning result by combining the user&#39;s inertial momentum with the ambient wireless signal in an indoor field to achieve an efficacy of precise positioning and reducing set up costs. 
     Furthermore, if the movement data D1 received by the central processing unit  31  do not change within a set time, the central processing unit  31  uses the movement data D1 to determine a position of the user to see if the user has not moved or the acceleration sensing module  21  is faulty, so as to achieve an object of fault detection and positioning a position of the user. 
     Then, please refer to  FIG.  5    for a second block diagram of the hybrid indoor positioning system of the invention, wherein the ambient signal database  34  further comprises a sampling extension data  343 , wherein the sampling extension data  343  are data operationally amplified in the ambient signal database  34  by the builder based on a data normal distribution algorithm after the ambient signal database  34  is set up. The sampling extension data  343  are used to increase signal volume of comparable wireless signals, and its sampling data generate the sampling extension data  343  through calculation, so that the central processing unit  31  is capable of adding information of the sampling extension data  343  for comparison, and also making the coordinate data  342  generated by the central processing unit  31  more accurate. 
     Then, please refer to  FIG.  6    for a third block diagram of the hybrid indoor positioning system of the invention, wherein the remote server  3  further comprises a judgment model  37 , and the judgment model  37  can be an AI learning model or a DTW dynamic time warping calculation model, wherein when the judgment model  37  is an AI learning model, the AI learning model can be a neural network model, a deep learning model, a machine learning model, etc., multiple locations in a positioning environment and corresponding coordinate information and corresponding magnetic force information of each location are acquired and used for training to obtain the judgment model  37  serving as an AI learning model; when the judgment model  37  is a DTW dynamic time warping calculation model, the judgment model  37  further comprises a magnetic force database. The magnetic force database comprises at least one corresponding time magnetic force parameter data and at least one corresponding magnetic force coordinate data. The time magnetic force parameter data are magnetic force information measured within a period of time, and the magnetic force coordinate data are location coordinates for obtaining the time magnetic force parameter data. 
     Wherein the first direction sensing module  22  senses the user&#39;s ambient magnetic force and generates a magnetic force information I 1 , the magnetic force information I 1  is a magnetic signal of a current position measured by the user using a magnetometer. The signal sending module  26  receives the magnetic force information I 1 , the signal sending module  26  transmits the magnetic force information I 1  to the signal receiving unit  32 , and the signal receiving unit  32  transmits the magnetic force information I 1  to the judgment model  37 . Wherein when the judgment model  37  is an AI learning model, the judgment model  37  captures the magnetic force information I 1  and generates a corresponding coordinate information I 2  and transmits the corresponding coordinate information I 2  to the central processing unit  31 , the central processing unit  31  generates a positioning position through the real-time coordinate information and the corresponding coordinate information I 2  using a particle filter algorithm, so that the remote server  3  is capable of acquiring a real-time position of the user through the positioning position. Because the same set of judgment system will inevitably have errors, the positioning position comprehensively determined using the corresponding coordinate information I 2  obtained by the added judgment model  37  and the aforementioned real-time coordinate information is more stable, reliable and universal than that obtained using a single system. 
     In addition, in addition to comparing the network domain combination information  3411  with the coordinate data  342  corresponding to the ambient signal model computed by algorithm, the central processing unit  31  generates the initial coordinate information. The signal receiving module  25  of the electronic label  2  equipped by the user also receives wireless signal conditions in an environment, so the signal receiving module  25  will receive the network domain combination information  3411  and the network domain signal strength information  3412 , and the signal receiving module  25  transmits the network domain combination information  3411  and the network domain signal strength information  3412  to the signal receiving unit  32  by the ambient wireless signal S1 through the signal sending module  26 . The central processing unit  31  captures the label identification code  27  and the ambient wireless signal S1, and the central processing unit  31  compares the coordinate data  342  corresponding to the ambient signal model calculated by algorithm from the network domain combination information  3411  and the coordinate data  342 , and then generates an ambient coordinate information. Then the central processing unit  31  generates the positioning position through the real-time coordinate information, the corresponding coordinate information I 2  and the ambient coordinate information using a particle filter algorithm, so that the remote server  3  is capable of acquiring a real-time position of the user through the positioning position. The positioning position comprehensively determined using the corresponding coordinate information I 2  and the aforementioned real-time coordinate information obtained by more modules is more stable, reliable and universal than that obtained using a single system. 
     In addition, when the judgment model  37  is a DTW dynamic time warping calculation model, the judgment model  37  captures the magnetic force information within a period of time and compares with the matched time magnetic force parameter data to generate the corresponding coordinate information I 2  from the magnetic force coordinate data corresponding to the time magnetic force parameter data. The central processing unit  31  generates a positioning position through the real-time coordinate information and the corresponding coordinate information I 2  using a particle filter algorithm, so that the remote server  3  is capable of acquiring a real-time position of the user through the positioning position. 
     Then, please refer to  FIG.  7    for a fourth block diagram of the hybrid indoor positioning system of the invention, wherein the remote server  3  further comprises a data cleaning module  38 , the data cleaning module  38  is signally connected to the signal receiving unit  32  and the judging model  37 , and the data cleaning module  38  receives the magnetic force information I 1  and performs data processing such as field misplacement, null value processing, field elimination, normalization, and generates a cleaning data D 3  which is transmitted to the judgment model  37 , wherein with the data cleaning module  38  provided, the judgment model  37  is an AI learning model which is trained based on acquiring multiple positions and corresponding coordinate information of each position in a positioning environment and the corresponding cleaning data D 3 . Therefore, the magnetic force information I 1  first passes through the data cleaning module  38  and generates the cleaning data D 3 , the judgment model  37  captures the cleaning data D 3  and generates the corresponding coordinate information I 2  which is transmitted to the central processing unit  31 , and the central processing unit  31  generates a positioning position through the real-time coordinate information and the corresponding coordinate information I 2  using a particle filter algorithm, so that the remote server  3  is capable of acquiring a real-time position of the user through the positioning position. The AI learning model trained through the cleaning data D 3  is capable of making the AI learning model more accurate when judging a position of the corresponding coordinate information I 2 . 
     In addition, when the judgment model  37  is a DTW dynamic time warping calculation model, with the data cleaning module  38  provided, the magnetic force database stores the time magnetic force parameter data and the magnetic force coordinate data after being treated by the cleaning data D 3 . The data cleaning module  38  receives the magnetic force information within a period of time and performs data processing such as field misplacement, null value processing, field elimination, normalization, and generates the cleaning data D 3 . In addition, the magnetic force information I 1  first passes through the data cleaning module  38  and generates the cleaning data D 3 . The judging model  37  captures the cleaning data D 3  and compares with the matched time magnetic force parameter data processed with data cleaning to generate the corresponding coordinate information I 2  based on the magnetic force coordinate data corresponding to the time magnetic force parameter data processed with data cleaning. The central processing unit  31  generates a positioning position through the real-time coordinate information and the corresponding coordinate information I 2  using a particle filter algorithm, so that the remote server  3  is capable of acquiring a real-time position of the user through the positioning position. The magnetic force database created through the cleaning data D 3  is capable of making the DTW dynamic time warping calculation model more accurate when judging a position of the corresponding coordinate information I 2 . 
     In addition, the signal receiving unit  32  is capable of further receiving an acceleration data and a direction data and transmit the acceleration data and the direction data to the judgment model  37 , and the judgment model  37  captures the magnetic force information, the acceleration data and the direction data. When the judging model  37  is an AI learning model, each position in a positioning environment and corresponding coordinate information of each position, and the magnetic force information I 1 , the acceleration data and the direction data are acquired first for training before the judging model  37  can be served as an AI learning model. Alternatively, the data cleaning module  38  receives the magnetic force information I 1 , the acceleration data and the direction data, and generates the cleaning data D 3  and transmits the cleaning data D 3  to the judgment model  37 . The judgment model  37  captures the cleaning data D 3  and performs learning and training again, and the judgment model  37  after learning and training captures the magnetic force information I 1  or a label of the cleaning data D 3  and generates the corresponding coordinate information I 2  and transmits the corresponding coordinate information I 2  to the central processing unit  31 . The central processing unit  31  generates a positioning position through the real-time coordinate information and the corresponding coordinate information I 2  using a particle filter algorithm, so that the remote server  3  is capable of acquiring a real-time position of the user through the positioning position. The AI learning model trained with more parameters is capable of making the AI learning model more accurate when judging a position of the corresponding coordinate information I 2 . 
     It is to be understood that the above description is only preferred embodiments of the invention and is not used to limit the invention, and changes in accordance with the concepts of the invention may be made without departing from the spirit of the invention, for example, the equivalent effects produced by various transformations, variations, modifications and applications made to the configurations or arrangements shall still fall within the scope covered by the appended claims of the invention.