Positioning method and device, electronic equipment and computer readable medium

Abstract

The invention discloses a positioning method and device, electronic equipment and a computer readable medium, and belongs to the technical field of intelligent card switching, and the method comprises the steps: determining a target fence region where mobile equipment is located currently and a fence type corresponding to the target fence region based on currently obtained radio frequency data; determining a target number of alternative card swiping points in the target fence area; if the fence type is a preset type and the target number is greater than a specified number, acquiring motion track data of the mobile device in the target fence area; and based on the motion track data, determining a target card swiping point from the plurality of alternative card swiping points. The target card swiping point can be accurately positioned, the target card swiping point can be accurately positioned in a conventional card swiping scene, and the problem that a plurality of card swiping points are easily confused in a small range is solved.

Description

Technical Field

[0001] The present application relates to the field of automatic positioning technology, and more specifically, to a positioning method, device, electronic device and computer-readable medium. Background Art

[0002] In the field of intelligent card cutting, the card swiping point can be predicted based on the honeycomb fence. However, when there are multiple card swiping points within the honeycomb fence, the accuracy of predicting the card swiping point is low. Summary of the invention

[0003] The present application proposes a positioning method, device, electronic device and computer-readable medium to improve the above-mentioned defects.

[0004] In a first aspect, the present application provides a positioning method for a mobile device, the method comprising: determining a target fence area in which the mobile device is currently located and a fence type corresponding to the target fence area based on currently acquired radio frequency data; determining the target number of candidate card swiping points within the target fence area; if the fence type is a preset type and the target number is greater than a specified number, obtaining motion trajectory data of the mobile device in the target fence area; and determining a target card swiping point from a plurality of the candidate card swiping points based on the motion trajectory data.

[0005] In a second aspect, the present application also provides a positioning device, which is applied to a mobile device, and the device includes: a determination unit, which is used to determine the target fence area where the mobile device is currently located and the fence type corresponding to the target fence area based on the currently acquired radio frequency data; a detection unit, which is used to determine the target number of alternative card swiping points in the target fence area; a judgment unit, which is used to obtain the motion trajectory data of the mobile device in the target fence area if the fence type is a preset type and the target number is greater than a specified number; a prediction unit, which is used to determine the target card swiping point from a plurality of the alternative card swiping points based on the motion trajectory data.

[0006] In a third aspect, the present application also provides an electronic device, comprising: one or more processors; a memory; one or more applications, wherein the one or more applications are stored in the memory, the one or more applications are configured to be executed by the one or more processors, and the one or more applications are configured to execute the above method.

[0007] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a program code executable by a processor, and when the program code is executed by the processor, the processor executes the above method.

[0008] In a fifth aspect, the present application also provides a computer program product, including a computer program / instruction, which implements the above method when executed by a processor.

[0009] The solution provided by the present application first determines the target fence area where the mobile device is currently located and the fence type corresponding to the target fence area based on the currently acquired radio frequency data; secondly, determines the target number of candidate card swiping points in the target fence area; then, if the fence type is a preset type and the target number is greater than a specified number, obtains the motion trajectory data of the mobile device in the target fence area; finally, based on the motion trajectory data, determines the target card swiping point from the multiple candidate card swiping points.

[0010] Based on the target fence area and the motion trajectory data of the mobile device in the target fence area, this application can accurately locate the target card swiping point. It can not only accurately locate the target card swiping point in conventional card swiping scenarios, but also solve the pain point problem of multiple card swiping points in a small range being easily confused.

[0011] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or be understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0013] Figure 1 A method flow chart of a positioning method provided by an embodiment of the present application is shown;

[0014] Figure 2 A schematic diagram showing a card swiping scenario;

[0015] Figure 3 A schematic diagram showing another card swiping scenario;

[0016] Figure 4 A method flow chart of a positioning method provided by another embodiment of the present application is shown;

[0017] Figure 5 A method flow chart of a positioning method provided by another embodiment of the present application is shown;

[0018] Figure 6A schematic diagram showing a card swiping scenario applied to the present application is shown;

[0019] Figure 7 A schematic diagram showing another card swiping scenario applied to the present application;

[0020] Figure 8 A method flow chart of a positioning method provided by another embodiment of the present application is shown;

[0021] Fig. 9 A method flow chart of a positioning method provided by another embodiment of the present application is shown;

[0022] Fig.10 A method flow chart of a positioning method provided by another embodiment of the present application is shown;

[0023] Fig.11 A method flow chart of a positioning method provided by another embodiment of the present application is shown;

[0024] Fig.12 The structure block diagram of the positioning method and device provided by the embodiment of the present application is shown;

[0025] Fig.13 A structural block diagram of an electronic device provided in an embodiment of the present application is shown;

[0026] Fig.14 A structural block diagram of a computer-readable storage medium provided in an embodiment of the present application is shown;

[0027] Fig.15 A structural block diagram of a computer program product provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0028] In order to make those skilled in the art better understand the present application scheme, the technical scheme in the present application embodiment will be clearly and completely described below in conjunction with the drawings in the present application embodiment. Obviously, the described embodiment is only a part of the present application embodiment, rather than all the embodiments. The components of the present application embodiment usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application for protection, but merely represents the selected embodiment of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0029] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0030] It should be noted that with the continuous development of radio frequency technology, radio frequency technology is widely used in various industries, especially in public transportation, access control systems, mobile payment and other card swiping scenarios. To realize intelligent card cutting based on mobile devices, it is crucial to identify the card swiping points. When there are multiple card swiping points in a micro area, such as elevator cards, gate cards, and access control cards, these card swiping points cannot be distinguished, resulting in the mobile device being unable to automatically select the card to be swiped after the user enters these micro areas.

[0031] Therefore, in the embodiments of the present application, a positioning method, device, electronic device and computer-readable medium are provided to solve or partially solve the above-mentioned problems.

[0032] See also Figure 1 , which shows a method flow chart of a positioning method provided in an embodiment of the present application, which is applied to a mobile device, and the mobile device may be a mobile phone, a tablet, a smart watch, and other wearable devices, etc. The method specifically includes steps S110 to S140.

[0033] Step S110: Based on the currently acquired radio frequency data, determine the target fence area where the mobile device is currently located and the fence type corresponding to the target fence area.

[0034] It should be noted that the radio frequency data may include but is not limited to at least one of GPS data, cellular data, WI FI data or Bluetooth data. The target fence area is a fence area where the mobile device is located. If the mobile device is in multiple fence areas at the same time, one of the fence areas is selected as the target fence area of ​​the mobile device. The fence types include GPS fence, cellular fence, WI FI fence and Bluetooth fence, etc. Different fence types correspond to different fence ranges.

[0035] Fence refers to the management or restriction measures of RF signals to ensure that RF signals propagate within a specific range. Fence area refers to the propagation range of RF signals, and RF signals are only effective within the fence area.

[0036] Radio frequency data can be obtained through passive monitoring or active monitoring, and the specific acquisition method can be determined according to actual needs.

[0037] It should be noted that for a fixed location, the surrounding cellular base stations and WI FI routers are relatively fixed. Therefore, before locating the card swiping point, a clustering algorithm can be used to unsupervisedly aggregate the radio frequency data related to a fixed location. When locating the card swiping point, when the mobile device approaches this area and connects to the cellular base station or WI FI router in the cluster, it can be determined as entering this micro area.

[0038] Specifically, in the process of locating the card swiping point, the acquired radio frequency data can be matched with the cluster features in the clustering cluster. When the matching degree is greater than a threshold, it is determined that the mobile device has entered the micro area, and the micro area is used as the target fence area, and the type corresponding to the micro area is used as the fence type of the target fence area.

[0039] An exemplary method is to use data from multiple satellites to define a virtual boundary or area as a GPS fence in advance. During actual use, multiple satellite signals can be received by a GPS receiver on a mobile device to calculate the current location coordinates of the mobile device, and the target fence area and fence type can be determined based on the current location coordinates.

[0040] Step S120: Determine the target number of candidate card swiping points within the target fence area.

[0041] After the target fence area is determined, the number of candidate card swiping points in the target fence area can be determined based on a pre-established data management system, which is the target number. The data management system includes a device identification code and a location identification code for each card swiping point in the target fence area.

[0042] Step S130: If the fence type is a preset type and the number of targets is greater than a specified number, then obtaining the motion trajectory data of the mobile device in the target fence area.

[0043] Specifically, the motion state of the mobile device can be measured by a designated sensor built into the mobile device, and the displacement and direction of the mobile device can be calculated, thereby estimating the dead reckoning (DR) trajectory of the mobile device. The designated sensor may include but is not limited to sensors such as accelerometers, magnetometers, and gyroscopes.

[0044] The motion trajectory data may include data such as the path length, the head heading angle, the tail heading angle, and the positioning coordinates of the DR trajectory.

[0045] It should be noted that the preset type is pre-set, and the designated number is an integer not less than 1. The designated number may be a preset number, or may be learned and updated based on the user's card swiping habits over a period of time.

[0046] In an exemplary embodiment, the preset type is WI FI fence, the specified number is 2, and if the fence type corresponding to the target fence area is WI FI fence, and the target number of target card swiping points in the target fence area is greater than 2, it means that there are at least 3 candidate card swiping points in the WI FI fence area where the mobile device is located, and for this purpose, it is necessary to obtain the motion trajectory data of the mobile device in the target fence area, so as to locate the target card swiping point in combination with the motion trajectory data of the mobile device in the target fence area.

[0047] An exemplary example is that the specified number is 2. In some scenarios, there are only two alternative card swiping points. In this case, the two alternative card swiping points are used as the target card swiping points, that is, both alternative card swiping points are pushed to the user, and the user can choose by himself. Compared with the situation where there are three or four or even more alternative card swiping points in a small range, this application can improve the positioning accuracy of the target card swiping point to a certain extent.

[0048] Step S140: Based on the motion trajectory data, determine a target card swiping point from the plurality of candidate card swiping points.

[0049] Based on the motion trajectory data, a target card swiping point is determined from multiple candidate card swiping points, and then the target card swiping point where the user wants to swipe the card is predicted.

[0050] Specifically, the motion trajectory data may be input into a target model corresponding to the target fence area, and a target check-in point may be predicted from a plurality of candidate check-in points based on the target model. For details, please refer to subsequent embodiments.

[0051] In an optional embodiment, the preset type is WI FI fence, the specified number is 2, based on the currently acquired WI FI data, it is determined that the current target fence area is a WI FI fence area, the fence type is a WI FI fence, and it is determined that there are 3 candidate card swiping points in the WI FI fence area, then the motion trajectory data of the mobile device in the WI FI fence area is acquired, and the target card swiping point is determined from the 3 candidate card swiping points based on the motion trajectory data. That is, the purpose of accurately locating the target card swiping point is achieved.

[0052] It is important to note that when locating the target card point through different fences, if there are still multiple candidate card points within the fence area of ​​the minimum fence range, the target card point cannot be accurately located. Figure 2-Figure 3 ,Within a fence 11, there are two alternative card swiping points, namely card swiping point A and card swiping point B. If the target card swiping point cannot be accurately predicted, it may cause the automatic card cutting to fail, and in serious cases, it may cause erroneous transactions, which will bring a poor experience to users, and this is also a pain point for users.

[0053] The present application proposes a positioning method, which first determines the target fence area where the mobile device is currently located and the fence type corresponding to the fence area based on the acquired radio frequency data, and then determines the target number of candidate card swiping points in the target fence area; secondly, if the fence type is a preset type and the target number is greater than a specified number, the motion trajectory data of the mobile device in the target fence area is obtained; finally, based on the motion trajectory data, the target card swiping point is determined from the multiple candidate card swiping points.

[0054] Based on the target fence area and the motion trajectory data of the mobile device in the target fence area, this application can accurately locate the target card swiping point. It can not only accurately locate the target card swiping point in conventional card swiping scenarios, but also solve the pain point problem of multiple card swiping points in a small range being easily confused.

[0055] In an implementation scenario of intelligent card switching, first, the mobile device determines the current target fence area and the fence type corresponding to the target fence area based on the acquired radio frequency data, and further determines the target number of candidate card swiping points in the target fence area. If the fence type is a preset type and the target number is greater than the specified number, the motion trajectory data of the mobile device in the target fence area is obtained, and then, based on the motion trajectory data, the target card swiping point is determined from multiple candidate card swiping points. Finally, the card to be swiped is selected based on the target card swiping point, and the card to be swiped can be calculated in advance before the user walks to the target card swiping point, which improves the user's experience of automatic card switching without feeling.

[0056] See also Figure 4 , which shows a method flow chart of a positioning method provided in an embodiment of the present application, applied to a mobile device, and the method specifically includes steps S210 to S250.

[0057] Step S210: Based on the currently acquired radio frequency data, determine the target fence area where the mobile device is currently located and the fence type corresponding to the target fence area.

[0058] Step S220: Determine the target number of candidate card swiping points within the target fence area.

[0059] Among them, step S210 and step S220 have been introduced in detail in the above embodiments and will not be repeated here.

[0060] Step S230: If the target quantity is greater than the specified quantity, determine whether the fence type is a preset type.

[0061] When locating the target card swiping point, it is necessary to first determine whether the number of targets is greater than the specified number. If the number of targets is greater than the specified number, then determine whether the fence type is the preset type.

[0062] Further, the specified number is 1, and step S230 includes the following steps.

[0063] Step S2301: If the target number is equal to 1, the candidate card swiping point is used as the target card swiping point.

[0064] If there is only one alternative card swiping point in the target fence area, then the alternative card swiping point will be used as the target card swiping point.

[0065] Step S2302: If the target quantity is greater than 1, determine whether the fence type is a preset type.

[0066] When there are multiple candidate card swiping points in the target fence area, it is necessary to determine the target card swiping point in combination with the motion trajectory.

[0067] Specifically, it is determined whether the fence type is a preset type. If it is a preset type, the motion trajectory data of the mobile device in the fence area is obtained, and the target card swiping point is determined from multiple candidate card swiping points based on the motion trajectory data, which can solve the problem of not being able to accurately locate the target card swiping point.

[0068] Step S240: If it is a preset type, obtaining the motion trajectory data of the mobile device in the fence area.

[0069] If the fence type is a preset type, the motion trajectory data of the mobile device in the fence area is obtained. In other words, the motion trajectory data is obtained only when the fence type and the number of targets meet the conditions, and the target card swiping point is located in combination with the motion trajectory data.

[0070] Step S250: Based on the motion trajectory data, determine a target card swiping point from the plurality of candidate card swiping points.

[0071] Among them, step S250 has been introduced in detail in the above embodiment and will not be repeated here.

[0072] In an exemplary embodiment, the preset type is WI FI fence, the specified number is 1, and based on the currently acquired WI FI data, the current target fence area is determined to be the WI FI fence area, and the fence type is the WI FI fence. If it is determined that there is one candidate card swiping point in the WI FI fence area, the candidate card swiping point is used as the target card swiping point. If it is determined that there are two candidate card swiping points in the WI FI fence area, the motion trajectory data of the mobile device in the WI FI fence area is obtained, and the target card swiping point is determined from the two candidate card swiping points based on the motion trajectory data. That is, the purpose of accurately locating the target card swiping point is achieved.

[0073] See also Figure 5, which shows a method flow chart of a positioning method provided in an embodiment of the present application, applied to a mobile device, the method specifically includes steps S310 to S370.

[0074] Step S310: Determine the communication type of the communication data corresponding to the maximum fence range as the target type.

[0075] It should be noted that the radio frequency data includes different types of communication data, and each type of communication data corresponds to a different fence range.

[0076] Exemplarily, different types of communication data may include but are not limited to GPS data, cellular data, WI FI data, and Bluetooth data, etc. The GPS fence range is larger than the cellular fence range, the cellular fence range is larger than the WI FI fence range, and the WI FI fence range is larger than the Bluetooth fence range.

[0077] Based on different types of communication data, the communication type of the communication data corresponding to the maximum fence range can be determined as the target type.

[0078] Exemplarily, the cellular type fence range is used as the maximum fence range, and the communication type of cellular data is used as the target type.

[0079] Step S320: determining the target fence area where the mobile device is currently located based on the communication data of the target type in the currently acquired radio frequency data.

[0080] It should be noted that before the user brings the mobile device to the card swiping point, the radio frequency data collected by the mobile device is constantly changing. In one case, the currently acquired radio frequency data includes communication data of the target type. Based on the communication data of the target type in the currently acquired radio frequency data, the target fence area where the mobile device is currently located is determined.

[0081] In another case, if the currently acquired radio frequency data does not include communication data of the target type, the radio frequency data is continuously acquired until communication data of the target type is acquired, and then the operation of determining the target fence area where the mobile device is currently located is entered.

[0082] Specifically, the target fence area where the mobile device is currently located may be determined based on the communication data of the target type in the acquired radio frequency data. For details, please refer to the aforementioned embodiment.

[0083] Step S330: Determine the fence type corresponding to the target fence area based on the target type.

[0084] A target fence area may be determined based on the communication data of the target type, and a corresponding fence type may be determined based on the target fence area.

[0085] It should be noted that if communication data of the same target type corresponds to fence areas of different ranges, the fence areas of different ranges correspond to different fence types.

[0086] Step S340: Determine the target number of candidate card swiping points within the target fence area.

[0087] Among them, step S340 has been introduced in detail in the above embodiment and will not be repeated here.

[0088] Step S350: When the number of targets is greater than the specified number, if the fence type is a preset type, obtaining the motion trajectory data of the mobile device in the target fence area.

[0089] When the number of targets is greater than the specified number, if the fence type is a preset type, the motion trajectory data of the mobile device in the target fence area is obtained.

[0090] Step S360: If it is not the preset type, based on the trend of the fence range gradually becoming smaller, the next communication type of the current target type is used as the new target type, and the operation of determining the target fence area where the mobile device is currently located and subsequent operations are returned based on the communication data of the target type in the currently acquired radio frequency data, until it is determined that the current fence type is the preset type and the number of targets is greater than the specified number.

[0091] It should be noted that the smaller the range of the preset type of fence is, the higher the accuracy of locating the target card swiping point will be.

[0092] Preferably, the WI FI type or the Bluetooth type can be selected as the preset type.

[0093] Step S370: Based on the motion trajectory data, determine a target card swiping point from the plurality of candidate card swiping points.

[0094] Among them, step S370 has been introduced in detail in the above embodiment and will not be repeated here.

[0095] In an exemplary embodiment, the specified number is 1, the preset type is the WI FI type, and the fence types include the cellular type, the WI FI type, and the Bluetooth type based on the gradually decreasing fence range. Figure 6, determine that the communication type of the communication data corresponding to the maximum fence range is cellular data, and the target type is cellular type. Based on the obtained cellular data, determine the cellular fence area 12 where the mobile device is currently located, and the fence type is a cellular fence, and determine that there are 5 candidate card swiping points in the cellular fence area. It can be seen that the condition that the target number is greater than the specified number is met, but the fence type is not a preset type. For this reason, the WI FI type is used as the new target type, and return to execute based on the obtained WI FI data, determine the WI FI fence area 13 where the mobile device is currently located, and the fence type is a WI FI fence, and determine that there are 2 candidate card swiping points in the WI FI fence area. At this time, the conditions that the target number is greater than the specified number and the fence type is a preset type are met, then obtain the motion trajectory data of the mobile device in the WI FI fence area 13; based on the motion trajectory data, determine the target card swiping point from the 2 candidate card swiping points.

[0096] This application proposes a positioning method, which can gradually find the target card swiping point based on the trend of the fence range gradually becoming smaller, and further improve the accuracy of the target card swiping point positioning in combination with the motion trajectory data.

[0097] Furthermore, the different types of communication data include passively monitored GPS type communication data with a gradually decreasing fence range, passively monitored cellular type communication data, passively monitored first WI FI type communication data, and actively monitored second WI FI type communication data.

[0098] Exemplarily, if the target type in step S310 is a GPS type, satellite data is acquired based on passive monitoring. If the target type in step S310 is a cellular type, radio frequency data is acquired based on passive monitoring. If the target type in step S310 is a first WI FI type, radio frequency data is acquired based on passive monitoring. If the target type in step S310 is a second WI FI type, radio frequency data is acquired based on active monitoring.

[0099] It should be noted that different methods can be used to obtain radio frequency data. Passive monitoring can be used to obtain radio frequency data in a large fence area, which can effectively reduce power consumption. Active monitoring can be used to obtain radio frequency data in a small fence area, which can quickly detect the communication data of the second WIFI, and then the motion trajectory data can be obtained in time, and the target card swiping point can be predicted in time. The target card swiping point can be accurately predicted before the user reaches the target card swiping point, which can provide sufficient time for measuring the target card swiping point to ensure that the card can be intelligently cut in advance.

[0100] In an exemplary embodiment, the designated number is 1, the preset type is a WI FI type, and the fence types gradually decrease based on the fence range, including a GPS type, a cellular type, a WI FI type, and a Bluetooth type. Determine that the communication type of the communication data corresponding to the maximum fence range is satellite data, and the target type is GPS type. Based on the acquired satellite data, determine the GPS fence area where the mobile device is currently located, and the fence type is GPS fence. Determine that there are 50 candidate card swiping points in the GPS fence area. It can be seen that the number of targets is greater than the specified number, but the fence type is not a preset type. For this reason, the cellular type is used as a new target type. Based on the acquired cellular data, determine the cellular fence area where the mobile device is currently located, and the fence type is cellular fence. Determine that there are 6 candidate card swiping points in the cellular fence area. At this time, the number of targets is greater than the specified number, but the fence type is not a preset type. Then use WI FI type as a new target type. Based on the acquired WI FI data, determine the WI FI fence area where the mobile device is currently located, and the fence type is WI FI fence. Determine that there are 2 candidate card swiping points in the WI FI fence area. At this time, the number of targets is greater than the specified number and the fence type is a preset type, then obtain the motion trajectory data of the mobile device in the WI FI fence area; based on the motion trajectory data, determine the target card swiping point from the 2 candidate card swiping points.

[0101] Further, the fence area corresponding to the communication data of the second WI FI type is obtained by performing similarity calculation on a temporary fence area, and the temporary fence area is the fence area corresponding to the communication data of the first WI FI type.

[0102] It should be noted that the fence area corresponding to the communication data of the second WI FI type is included in the fence area corresponding to the communication data of the first WI FI type.

[0103] Specifically, a WI FI signal scan is performed at each location within the first WI FI fence area, the WI FI access point and signal strength of each location are recorded, the WI FI access point and signal strength recorded at each location are constructed into a feature vector, the similarity between the locations is calculated based on a distance measurement method, a similarity matrix is ​​generated, the similarity matrix is ​​clustered based on a clustering algorithm, and then a plurality of second WI FI fences are divided.

[0104] This application can perform similarity calculation on the first WI FI fence to obtain the second WI FI fence. Based on the WI FI fence, a smaller fence area is obtained, which can achieve a higher precision positioning card swiping point.

[0105] For an exemplary example, see Figure 7, the solid line with an arrow in the figure represents the possible movement trajectory of the user, the specified number is 1, if 2 candidate card swiping points are detected in the cellular fence area 12, they can be distinguished based on the first WI FI fence, if 2 candidate card swiping points are detected in the first WI FI fence area 13, they can be distinguished based on the second WI FI fence, if 2 candidate card swiping points are detected in the second WI FI fence area 14, the movement trajectory data of the mobile device in the second WI FI fence area 14 is obtained, and based on the movement trajectory data, the target card swiping point is determined from the 2 candidate card swiping points.

[0106] For the case of multi-layer RF fences, this application can match a variety of different identification situations, effectively covering everything from routine user identification scenarios to pain point identification scenarios.

[0107] See also Figure 8 , which shows a method flow chart of a positioning method provided in an embodiment of the present application, applied to a mobile device, and the method specifically includes steps S410 to S470.

[0108] Step S410: Determine the communication type of the communication data corresponding to the maximum fence range as the target type.

[0109] Step S420: determining the target fence area where the mobile device is currently located based on the communication data of the target type in the currently acquired radio frequency data.

[0110] Step S430: Determine the fence type corresponding to the target fence area based on the target type.

[0111] Step S440: Determine the target number of candidate card swiping points within the target fence area.

[0112] Among them, step S410 and step S440 have been introduced in detail in the above embodiments and will not be repeated here.

[0113] Step S450: When the number of targets is greater than the specified number, if the fence type is a preset type, obtaining the motion trajectory data of the mobile device in the target fence area.

[0114] Furthermore, when the number of targets is greater than a specified number, if the fence type is a preset type, the acquisition of radio frequency data is stopped, and the motion trajectory data of the mobile device in the target fence area is acquired.

[0115] In an exemplary embodiment, the fence type is determined to be the second WI FI type based on the acquired radio frequency data, and the preset type is the second WI FI type. When the number of targets is greater than the specified number, the fence type is the preset type, and the radio frequency data is stopped to save power consumption. The motion trajectory data of the mobile device is collected, and the target card swiping point is predicted based on the motion trajectory data.

[0116] Step S460: If it is not a preset type, and the target type is the first WI FI type for passive monitoring, when it is detected that the mobile device meets the specified conditions, the next communication type of the current target type is used as the new target type, and the operation of determining the target fence area where the mobile device is currently located and subsequent operations based on the communication data of the target type in the currently acquired radio frequency data is returned until it is determined that the current fence type is a preset type and the number of targets is greater than the specified number.

[0117] If the fence type is not a preset type, and the target type is the first WI FI type of passive monitoring, it means that the RF data is currently obtained by passive monitoring. When it is detected that the mobile device meets the specified conditions, the second WI FI type of active monitoring is used as the target type, and the communication data of the target type in the currently obtained RF data is returned to determine the operation of the target fence area where the mobile device is currently located and subsequent operations. Since the current target type is the second WI FI type of active monitoring, the RF data is obtained by active monitoring.

[0118] By passively monitoring the cellular data and the first WI FI data, power consumption can be reduced, while actively monitoring the second WI FI data can detect the second WI FI data in time.

[0119] Step S470: Based on the motion trajectory data, determine a target card swiping point from the plurality of candidate card swiping points.

[0120] Among them, step S470 has been introduced in detail in the above embodiment and will not be repeated here.

[0121] See also Fig. 9 , which shows a method flow chart of a positioning method provided in an embodiment of the present application, applied to a mobile device, and the method specifically includes steps S510 to S570.

[0122] Step S510: Determine the communication type of the communication data corresponding to the maximum fence range as the target type.

[0123] Step S520: determining the target fence area where the mobile device is currently located based on the communication data of the target type in the currently acquired radio frequency data.

[0124] Step S530: Determine the fence type corresponding to the target fence area based on the target type.

[0125] Step S540: Determine the target number of candidate card swiping points within the target fence area.

[0126] Step S550: When the number of targets is greater than the specified number, if the fence type is a preset type, obtaining the motion trajectory data of the mobile device in the target fence area.

[0127] Among them, step S510 and step S550 have been introduced in detail in the above embodiments and will not be repeated here.

[0128] Step S560: If it is not a preset type, and the target type is the first WI FI type for passive monitoring, when it is detected that the mobile device meets the specified conditions, the next communication type of the current target type is used as the new target type, and the operation of determining the target fence area where the mobile device is currently located and subsequent operations based on the communication data of the target type in the currently acquired radio frequency data is returned until it is determined that the current fence type is a preset type and the number of targets is greater than a specified number, and the specified conditions include at least one of the duration of the motion state of the mobile device meeting the preset duration condition and the current time being in a preset time period.

[0129] It should be noted that the specified condition includes at least one of the duration of the motion state of the mobile device meeting the preset duration condition and the current time being in a preset time period. Among them, the duration of the motion state of the mobile device meeting the preset duration indicates that the user is moving and has a high probability of entering the second WI FI fence. The second WI FI type is used as a new target type, and the second WI FI data will be actively monitored, so that the second WI FI data can be detected in time.

[0130] The preset time period may be a high-frequency card swiping time period. If the current time is in the preset time period, it means that the user has a greater probability of needing to swipe the card during the current time period. Therefore, there is a greater probability of entering the second WI FI fence. The second WI FI type is taken as the new target type, and active monitoring of the second WI FI data will be performed, so that the second WI FI data can be detected in time.

[0131] Actively monitoring the second WI FI data can detect the second WI FI data in time. When the second WI FI data is detected, that is, the mobile device enters the second WI FI fence area, the RF data is stopped to save power consumption. The motion trajectory data of the mobile device is collected, and the target card swiping point is predicted based on the motion trajectory data.

[0132] It should be noted that actively monitoring the second WI FI data may be performing high-frequency scanning for multiple times, each high-frequency scanning lasts for k minutes, and a WI FI scan is triggered every n seconds within k minutes; wherein, the values ​​of k and n may be determined according to actual conditions.

[0133] Optionally, each high-frequency scan lasts for 1 minute, triggering a WI FI scan every 3 seconds within 1 minute.

[0134] In an exemplary embodiment, after monitoring the first WI FI data, it indicates that the user has entered the first WI FI fence area with the mobile device, and the duration of the mobile device's motion state meets the preset duration condition and the current time is in the preset time period, then multiple high-frequency scans are triggered, each high-frequency scan lasts for 1 minute, and a WI FI scan is triggered every 3 seconds within 1 minute. After detecting the second WI FI data, it indicates that the user has entered the second WI FI fence area with the mobile device, and then active monitoring of radio frequency data is stopped.

[0135] It should be noted that the high-frequency card swiping period and the low-frequency card swiping period can be determined based on the previous card swiping data. This application adopts an all-weather dynamic RF scanning strategy, which only increases the scanning frequency during the user's high-frequency card swiping period, ensuring a balance between high accuracy, fast identification and low power consumption.

[0136] Step S570: Based on the motion trajectory data, determine a target card swiping point from the plurality of candidate card swiping points.

[0137] Among them, step S570 has been introduced in detail in the above embodiment and will not be repeated here.

[0138] See also Fig.10 , which shows a method flow chart of a positioning method provided in an embodiment of the present application, applied to a mobile device, and the method specifically includes steps S610 to S640.

[0139] Step S610: Based on the currently acquired radio frequency data, determine the target fence area where the mobile device is currently located and the fence type corresponding to the target fence area.

[0140] Step S620: Determine the target number of candidate card swiping points within the target fence area.

[0141] Step S630: If the fence type is a preset type and the number of targets is greater than a specified number, then obtaining the motion trajectory data of the mobile device in the target fence area.

[0142] Among them, step S610 and step S630 have been introduced in detail in the above embodiments and will not be repeated here.

[0143] Step S640: inputting the motion trajectory data into a target model corresponding to the target fence area, and predicting a target check-in point from the plurality of candidate check-in points based on the target model.

[0144] It should be noted that the target model is pre-set, and different target fence areas correspond to different target models. The motion trajectory data can be input into the target model corresponding to the target fence area to predict the target check-in point from multiple candidate check-in points.

[0145] Among them, step S440 and step S450 have been introduced in detail in the above embodiments and will not be repeated here.

[0146] See also Fig.11 , which shows a method flow chart of a positioning method provided in an embodiment of the present application, applied to a mobile device, the method specifically includes steps S710 to S760.

[0147] Step S710: Based on the currently acquired radio frequency data, determine the target fence area where the mobile device is currently located and the fence type corresponding to the target fence area.

[0148] Step S720: Determine the target number of candidate card swiping points within the target fence area.

[0149] Step S730: If the fence type is a preset type and the number of targets is greater than a specified number, then obtaining the motion trajectory data of the mobile device in the target fence area.

[0150] Among them, step S710 and step S730 have been introduced in detail in the above embodiments and will not be repeated here.

[0151] Step S740: Collect training samples, where the training samples include motion data corresponding to motion trajectories generated when a mobile device moves to different card swiping points within a reference fence area, and the fence type of the reference fence area is the preset type.

[0152] Before actually locating the target card swiping point, it is necessary to train the model based on the training data to obtain the target model. To this end, it is necessary to collect training samples, that is, collect motion data corresponding to the motion trajectory generated by the mobile device moving to different card swiping points in the reference fence area. The fence type of the reference fence area is the preset type, and the motion data includes the path length of the DR trajectory, the head heading angle, the tail heading angle, and the positioning coordinates.

[0153] An exemplary method is to collect 2-3 days of card swiping data in a reference fence area. For card swiping points with more card swiping data, the radio frequency data and the corresponding trajectory when the card is swiped can be directly obtained. For card swiping points with less card swiping data, parameters such as angle thresholds or path length thresholds can be manually defined to distinguish the card swiping points.

[0154] Step S750: input the training samples into the model for training to obtain a target model, wherein the trained target model is used to determine the possibility of the mobile device reaching each card swiping point based on the motion data of the motion trajectory.

[0155] The training samples are input into the model for supervised or unsupervised training to obtain a target model, which is used to determine the possibility of the mobile device reaching each card swiping point based on the motion data of the motion trajectory. The target model can be a classification model.

[0156] Specifically, a target model is obtained by learning the motion data of the motion trajectory from the reference fence area to each card swiping point. The target model can match the motion trajectory data with the trajectories corresponding to different learned card swiping points, and take the card swiping point corresponding to the trajectory with the highest matching degree as the target card swiping point.

[0157] It should be noted that the sequence of step S740 and step S750 and steps S710 to S730 is not specifically limited here.

[0158] Step S760: Based on the motion trajectory data, determine a target card swiping point from the plurality of candidate card swiping points.

[0159] It should be noted that, in the process of locating the target card swiping point, if the mobile device does not store the target model, the target card swiping point can be determined based on a predetermined angle and a track length threshold in the motion track data.

[0160] See also Fig.12 , which shows a structural block diagram of a positioning device 600 provided in an embodiment of the present application. The testing device 600 includes: a determination unit 610, a detection unit 620, a judgment unit 630 and a prediction unit 640.

[0161] The determination unit 610 is configured to determine the target fence area where the mobile device is currently located and the fence type corresponding to the target fence area based on the currently acquired radio frequency data.

[0162] Furthermore, the determination unit 610 can also be used to determine the communication type of the communication data corresponding to the maximum fence range as the target type; determine the target fence area where the mobile device is currently located based on the communication data of the target type in the currently acquired radio frequency data; and determine the fence type corresponding to the target fence area based on the target type.

[0163] The detection unit 620 is used to determine the target number of candidate card swiping points within the target fence area.

[0164] The judgment unit 630 is configured to obtain the motion trajectory data of the mobile device in the target fence area if the fence type is a preset type and the number of targets is greater than a specified number.

[0165] Furthermore, the judgment unit 630 may also be configured to determine whether the fence type is a preset type if the number of targets is greater than a specified number; if it is a preset type, obtain the motion trajectory data of the mobile device in the fence area.

[0166] Furthermore, the judgment unit 630 can also be used to obtain the motion trajectory data of the mobile device in the target fence area when the number of targets is greater than the specified number, if the fence type is a preset type; if it is not the preset type, based on the trend of the fence range gradually decreasing, the next communication type of the current target type is used as the new target type, and the communication data of the target type in the currently acquired radio frequency data is returned to determine the operation of the target fence area where the mobile device is currently located and subsequent operations, until it is determined that the current fence type is the preset type and the number of targets is greater than the specified number.

[0167] Furthermore, the specified number is 1.

[0168] Furthermore, the different types of communication data include cellular type communication data of passive monitoring with a gradually decreasing fence range, first WI FI type communication data of passive monitoring, and second WI FI type communication data of active monitoring.

[0169] Further, the fence area corresponding to the communication data of the second WI FI type is obtained by performing similarity calculation on a temporary fence area, and the temporary fence area is the fence area corresponding to the communication data of the first WI FI type.

[0170] Furthermore, the judgment unit 630 may also be configured to, if it is not a preset type and the target type is the first WI FI type for passive monitoring, take the next communication type of the current target type as a new target type when it is detected that the mobile device meets a specified condition.

[0171] Furthermore, the specified condition includes at least one of a duration of the motion state of the mobile device satisfying a preset duration condition and a current time being within a preset time period.

[0172] The prediction unit 640 is used to determine a target check-in point from the plurality of candidate check-in points based on the motion trajectory data.

[0173] Furthermore, the prediction unit 640 may also be configured to input the motion trajectory data into a target model corresponding to the target fence area, and predict a target check-in point from the plurality of candidate check-in points based on the target model.

[0174] Furthermore, the prediction unit 640 can also be used to collect training samples, wherein the training samples include motion data corresponding to a motion trajectory generated by a mobile device moving to different card swiping points within a reference fence area, and the fence type of the reference fence area is the preset type; the training samples are input into the model for training to obtain a target model, wherein the trained target model is used to determine the possibility of the mobile device reaching each card swiping point based on the motion data of the motion trajectory.

[0175] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0176] In several embodiments provided in the present application, the coupling between modules may be electrical, mechanical or other forms of coupling.

[0177] In addition, each functional module in each embodiment of the present application can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above integrated modules can be implemented in the form of hardware or software functional modules.

[0178] Please refer to Fig.13 , which shows a structural block diagram of an electronic device 700 provided in an embodiment of the present application. The electronic device 700 may be a vehicle system, which may be arranged in a vehicle. The electronic device 700 in the present application may include one or more of the following components: a processor 711, a memory 712, and one or more application programs, wherein the processor 711 is electrically connected to the memory 712, and the one or more program configurations are used to execute the methods described in the various embodiments of the aforementioned test method.

[0179] The processor 711 may include one or more processing cores. The processor 711 uses various interfaces and lines to connect various parts of the entire electronic device 700, and executes various functions and processes data of the electronic device 700 by running or executing instructions, programs, code sets or instruction sets stored in the memory 712, and calling data stored in the memory 712. Optionally, the processor 711 can be implemented in at least one hardware form of digital signal processing (DSP), field programmable gate array (FPGA), and programmable logic array (PLA). The processor 711 can integrate one or a combination of a central processing unit (CPU), a graphics processor (GPU), and a modem. Among them, the CPU mainly processes the operating system, user interface, and computer programs; the GPU is responsible for rendering and drawing display content; and the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 711, but may be implemented separately through a communication chip. Specifically, the method described in the above embodiments may be executed by one or more processors 711 .

[0180] For some embodiments, the memory 712 may include a random access memory (RAM) or a read-only memory (ROM). The memory 712 may be used to store instructions, programs, codes, code sets, or instruction sets. The memory 712 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function, instructions for implementing the following various method embodiments, etc. The data storage area may also store data created by the electronic device 700 during use, etc.

[0181] Please refer to Fig.14 , which shows a structural block diagram of a computer-readable medium provided in an embodiment of the present application. The computer-readable medium 800 stores program codes, which can be called by a processor to execute the method described in the above method embodiment.

[0182] The computer readable medium 800 can be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk, or a ROM. Optionally, the computer readable medium 800 includes a non-transitory computer-readable storage medium. The computer readable medium 800 has storage space for program code 810 that performs any method step in the above method. These program codes can be read from one or more computer program products or written into one or more computer program products. The program code 810 can be compressed, for example, in an appropriate form.

[0183] Please refer to Fig.15 , which shows a structural block diagram 900 of a computer program product provided by an embodiment of the present application. The computer program product 900 includes a computer program / instruction 910, and when the computer program / instruction 910 is executed by a processor, the steps of the above method are implemented.

[0184] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A positioning method, characterized in that: Applied to a mobile device, the method comprises: Based on the currently acquired radio frequency data, determining the target fence area where the mobile device is currently located and the fence type corresponding to the target fence area; Determine the target number of candidate card swiping points within the target fence area; If the fence type is a preset type and the number of targets is greater than a specified number, obtaining the motion trajectory data of the mobile device in the target fence area; Based on the motion trajectory data, a target card swiping point is determined from the plurality of candidate card swiping points.

2. The method according to claim 1, characterized in that If the fence type is a preset type and the number of targets is greater than a specified number, obtaining the motion trajectory data of the mobile device in the target fence area includes: If the target quantity is greater than a specified quantity, determining whether the fence type is a preset type; If it is a preset type, the motion trajectory data of the mobile device in the fence area is obtained.

3. The method according to claim 1, characterized in that The specified number is 1.

4. The method according to claim 1, characterized in that: The radio frequency data includes different types of communication data, each type of communication data corresponds to a different fence range, and determining the target fence area where the mobile device is currently located and the fence type corresponding to the target fence area based on the currently acquired radio frequency data includes: Determine the communication type of the communication data corresponding to the maximum fence range as the target type; Determine the target fence area where the mobile device is currently located based on the communication data of the target type in the currently acquired radio frequency data; Determining a fence type corresponding to the target fence area based on the target type; If the fence type is a preset type and the number of targets is greater than a specified number, obtaining the motion trajectory data of the mobile device in the target fence area includes: In the case where the number of targets is greater than the specified number, if the fence type is a preset type, obtaining the motion trajectory data of the mobile device in the target fence area; If it is not the preset type, based on the trend of the fence range gradually becoming smaller, the next communication type of the current target type is used as the new target type, and the operation of determining the target fence area where the mobile device is currently located and subsequent operations are returned based on the communication data of the target type in the currently acquired radio frequency data, until it is determined that the current fence type is the preset type and the number of targets is greater than the specified number.

5. The method according to claim 4, characterized in that The different types of communication data include passively monitored GPS type communication data with a gradually decreasing fence range, passively monitored cellular type communication data, passively monitored first WIFI type communication data, and actively monitored second WIFI type communication data.

6. The method according to claim 5, characterized in that The fence area corresponding to the communication data of the second WIFI type is obtained by performing similarity calculation on the temporary fence area, and the temporary fence area is the fence area corresponding to the communication data of the first WIFI type.

7. The method according to claim 5, characterized in that If the target type is not a preset type, based on the trend that the fence range gradually decreases, the next communication type of the current target type is used as the new target type, which also includes: If it is not a preset type, and the target type is the first WIFI type of passive monitoring, when it is detected that the mobile device meets the specified conditions, the next communication type of the current target type is used as a new target type.

8. The method according to claim 7, characterized in that The specified condition includes at least one of the duration of the motion state of the mobile device meeting a preset duration condition and the current time being within a preset time period.

9. The method according to claim 1, characterized in that: The step of determining a target card swiping point from a plurality of candidate card swiping points based on the motion trajectory data includes: The motion trajectory data is input into a target model corresponding to the target fence area, and a target check-in point is predicted from the plurality of candidate check-in points based on the target model.

10. The method according to claim 9, characterized in that Before determining a target card swiping point from a plurality of candidate card swiping points based on the motion trajectory data, the method further includes: Collecting training samples, wherein the training samples include motion data corresponding to motion trajectories generated by a mobile device moving to different card swiping points within a reference fence area, wherein the fence type of the reference fence area is the preset type; The training samples are input into the model for training to obtain a target model, wherein the trained target model is used to determine the possibility of the mobile device reaching each card swiping point based on the motion data of the motion trajectory.

11. A positioning device, characterized in that: Applied to a mobile device, the device comprises: a determining unit, configured to determine a target fence area where the mobile device is currently located and a fence type corresponding to the target fence area based on the currently acquired radio frequency data; A detection unit, used to determine the target number of candidate card swiping points within the target fence area; a judgment unit, configured to obtain the motion trajectory data of the mobile device in the target fence area if the fence type is a preset type and the number of targets is greater than a specified number; A prediction unit is used to determine a target check-in point from a plurality of candidate check-in points based on the motion trajectory data.

12. An electronic device, characterized in that: include: one or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory, the one or more applications are configured to be executed by the one or more processors, and the one or more applications are configured to execute the method according to any one of claims 1-10.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program codes, which can be called by a processor to execute the method according to any one of claims 1 to 10.

14. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 10 is implemented.

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