Mobile WiFi identification method, electronic equipment and storage medium

Abstract

The invention relates to the technical field of wireless communication, in particular to a mobile WiFi identification method, electronic equipment and a storage medium, and the method comprises the steps: obtaining a plurality of pieces of position information of each mobile WiFi sample in an initial time period, obtaining a plurality of first moving distances, screening out a plurality of second moving distances, carrying out the normalization processing, and obtaining a plurality of second moving distances; obtaining a plurality of third moving distances, calculating a moving distance fluctuation degree according to the plurality of third moving distances, determining a mobile WiFi sample of which the moving distance fluctuation degree is smaller than a preset fluctuation degree threshold as a key mobile WiFi, and determining a preset time period according to the proportion of the key mobile WiFi, according to the mobile WiFi identification method and device, a plurality of pieces of position information of each target WiFi in the preset time period are collected, the maximum distance is obtained, whether the target WiFi is the mobile WiFi or not is identified according to the maximum distance, the target WiFi can be reasonably evaluated, and the mobile WiFi identification accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communications, and in particular to a mobile WiFi identification method, electronic equipment and storage medium. Background Art

[0002] With the development of WiFi technology, in addition to fixed indoor wireless access points, wireless access points with dynamically changeable deployment locations are provided in some mobile scenarios. Mobile scenarios include scenarios when users are driving, riding high-speed trains or buses, renting portable WiFi while traveling, and using user terminals to enable WiFi hotspot sharing. We call wireless access points with movable deployment locations mobile WiFi devices. In the above scenarios, when the user terminal communicates with a server located on the Internet, the server cannot reasonably and accurately identify whether the WiFi connected to the user terminal is fixed WiFi or mobile WiFi. Summary of the invention

[0003] In view of the above technical problems, the present invention provides a mobile WiFi identification method, an electronic device and a storage medium, which can reasonably evaluate the target WiFi and improve the accuracy of mobile WiFi identification.

[0004] According to a first aspect of the present invention, a mobile WiFi identification method is provided, comprising the following steps:

[0005] S100, based on a given mobile WiFi sample set D = {D1, D2, ..., D e , ..., D f}, get D e The location information of several mobile WiFi devices reported within the preset initial time period T1 is obtained based on the location information of several mobile WiFi devices. e The corresponding first moving distances, where D e is the e-th mobile WiFi sample, e=1, 2, ..., f, f is the number of mobile WiFi samples, and the first moving distance refers to the distance between any two adjacent mobile WiFi location information.

[0006] S200, from D e Several second moving distances are selected from the corresponding several first moving distances, and the several second moving distances are normalized to between 0 and 10 to obtain several third moving distances; the second moving distance refers to any first moving distance except the maximum first moving distance and the minimum first moving distance.

[0007] S300, according to a plurality of third moving distances, calculate the moving distance fluctuation degree, and when the moving distance fluctuation degree is less than a preset fluctuation degree threshold, set De Identified as critical mobile WiFi.

[0008] S400, when the ratio of the number of key mobile WiFis to f is greater than a preset ratio threshold, the initial time period T1 is determined as the preset time period T; otherwise, T1-ΔT is replaced with a new T1, and the steps S001-S004 are returned to execute until the preset time period T is determined, or when T1<T0, T0 is determined as the preset time period T, wherein ΔT is the preset first time threshold, and T0 is the preset second time threshold.

[0009] S500, based on a preset target WiFi set A={A1,A2,……,A i , ..., A m}, get A i Several WiFi location information corresponding to the preset time period T, A i It refers to the i-th target WiFi, i=1, 2, ..., m, and m is the number of target WiFi.

[0010] S600, for A i The corresponding WiFi location information within the preset time period T is obtained, and the target distance corresponding to each two WiFi location information is obtained. i Corresponding target distances.

[0011] S700, determine A i The maximum distance among the corresponding target distances, and when the maximum distance is greater than the preset distance threshold δ, A i Identified as mobile WiFi.

[0012] According to a second aspect of the present invention, a non-transitory computer-readable storage medium is provided, wherein at least one instruction or at least one program is stored in the storage medium, and the at least one instruction or the at least one program is loaded and executed by a processor to implement the above-mentioned mobile WiFi identification method.

[0013] According to a third aspect of the present invention, there is provided an electronic device comprising a processor and the above-mentioned non-transitory computer-readable storage medium.

[0014] The present invention has at least the following beneficial effects:

[0015] The present invention provides a mobile WiFi identification method. First, a plurality of location information of each mobile WiFi sample within a preset initial time period is obtained, and a plurality of first moving distances are obtained. A plurality of second moving distances are selected from the plurality of first moving distances and normalized to obtain a plurality of third moving distances. The moving distance fluctuation degree is calculated according to the plurality of third moving distances. Through the normalization process, the moving distances can be normalized to a unified range, so that the calculated moving distance fluctuation degree is more reasonable. The mobile WiFi sample whose moving distance fluctuation degree is less than a preset fluctuation degree threshold is determined as a key mobile WiFi. A preset time period is determined according to the proportion of the key mobile WiFi, so that the determined preset time period is more reasonable. While reducing the length of the preset time period, sufficient location information data can be collected, which is conducive to accurately identifying more mobile WiFi. Finally, a plurality of location information of each target WiFi within the preset time period is collected and a maximum distance is obtained. Whether the target WiFi is a mobile WiFi is identified according to the maximum distance. Through the determined preset time period, a plurality of moving situations of the target WiFi can be relatively comprehensively collected, and the moving range of the target WiFi within the preset time period is obtained, which is conducive to reasonably and reliably evaluating whether the WiFi is a mobile WiFi and accurately identifying the mobile WiFi. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 The present invention provides a flowchart of a mobile WiFi identification method. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0019] The embodiment of the present invention provides a mobile WiFi identification method, such as Figure 1 As shown, the method comprises the following steps:

[0020] S100, based on a given mobile WiFi sample set D = {D1, D2, ..., De , ..., D f}, get D e The location information of several mobile WiFi devices reported within the preset initial time period T1 is obtained based on the location information of several mobile WiFi devices. e The corresponding first moving distances, where D e is the e-th mobile WiFi sample, e=1, 2, ..., f, and f is the number of mobile WiFi samples.

[0021] Furthermore, the first moving distance refers to the distance between any two adjacent mobile WiFi location information.

[0022] Specifically, D e The number of mobile WiFi location information reported within the preset initial time period T1 is D e A number of geohash values ​​reported within the preset initial time period T1.

[0023] Preferably, the preset initial time period T1 is not less than 20 days.

[0024] S200, from D e Several second moving distances are selected from the corresponding several first moving distances, and the several second moving distances are normalized to between 0 and 10 to obtain several third moving distances; the second moving distance refers to any first moving distance except the maximum first moving distance and the minimum first moving distance.

[0025] As mentioned above, since the moving distances of mobile WiFi devices at adjacent time points are generally similar, but considering the problem of unreasonable moving distances caused by position drift or other situations, the maximum moving distance and the minimum moving distance are deleted, and the remaining moving distances are normalized to a unified range, so that the calculated moving distance fluctuation degree is more reasonable, which is conducive to determining a reasonable number of mobile WiFi.

[0026] S300, calculating the movement distance fluctuation degree according to the plurality of third movement distances, and when the movement distance fluctuation degree is less than a preset fluctuation degree threshold, setting D e Identified as critical mobile WiFi.

[0027] Specifically, the moving distance fluctuation degree S meets the following conditions:

[0028] Among them, x k is the kth new moving distance, is the average distance of several new moving distances.

[0029] As mentioned above, when the fluctuation degree of the moving distance is less than the preset fluctuation degree threshold, it indicates that the moving distance of the mobile WiFi samples between each adjacent time point is similar. For example, the moving distance of the vehicle-mounted WiFi at the same time point is roughly the same. In this way, some unstable WiFi with position drift or the device users choosing other travel modes can be screened out, so that the judged key mobile WiFi is a reasonable mobile WiFi, which is conducive to the subsequent determination of whether the setting of the preset time period is reasonable based on the number of reasonable mobile WiFis.

[0030] S400, when the ratio of the number of key mobile WiFis to f is greater than a preset ratio threshold, the initial time period T1 is determined as the preset time period T; otherwise, T1-ΔT is replaced with a new T1, and the steps S001-S004 are returned to execute until the preset time period T is determined, or when T1<T0, T0 is determined as the preset time period T, wherein ΔT is the preset first time threshold, and T0 is the preset second time threshold.

[0031] As mentioned above, when the reasonable proportion of mobile WiFi determined is small, it indicates that the initial time period is not reasonable enough. Since the longer the time, the greater the difference in the location change of mobile WiFi, the duration of the time period should be shortened, and when shortening the duration, it is necessary to ensure that sufficient location information data is collected, so that the determined preset time period is more reasonable and more mobile WiFi can be accurately identified.

[0032] S500, based on a preset target WiFi set A={A1,A2,……,A i , ..., A m}, get A i Several WiFi location information corresponding to the preset time period T, A i It refers to the i-th target WiFi, i=1, 2, ..., m, and m is the number of target WiFi.

[0033] In another embodiment, the preset time period T is set by a person skilled in the art according to actual needs. For example, the preset time period T is a number of consecutive days before the current time point; in an actual usage scenario, it can be set to 16 days to meet the number of WiFi collection days analyzed by the beacon library.

[0034] As mentioned above, since the travel speeds of mobile WiFi devices are inconsistent in different scenarios, a reasonable time period needs to be selected. By determining the preset time period, several movement situations of the target WiFi can be collected more comprehensively, and the movement range of the target WiFi within the preset time period can be obtained, which is conducive to a reasonable and reliable evaluation of whether the WiFi is a mobile WiFi, and is conducive to accurately identifying the mobile WiFi.

[0035] S600, for A i The corresponding WiFi location information within the preset time period T is obtained, and the target distance corresponding to each two WiFi location information is obtained. i Corresponding to several target distances; it can be understood that: the target distance is calculated for any two WiFi location information.

[0036] As described above, by calculating the distance between any two WiFi location information, the farthest distance moved by each target WiFi within the moving range within the preset time period can be obtained, providing a basis for determining whether each target WiFi is a mobile WiFi.

[0037] S700, confirm A i The maximum distance among the corresponding target distances, and when the maximum distance is greater than the preset distance threshold δ, A i Identified as mobile WiFi.

[0038] In another specific implementation, the following steps are further included after S600:

[0039] S001, according to A i The maximum distance among the corresponding target distances is obtained from the preset initial WiFi cluster B = {B1, B2, ..., B j , ..., B n} to determine the target WiFi cluster and i Insert into the target WiFi cluster; where B j is the preset j-th initial WiFi cluster, j=1, 2, ..., n, and n is the number of initial WiFi clusters; it can be understood that after the target WiFi is inserted into the empty initial WiFi cluster, it is updated to the target WiFi cluster.

[0040] Specifically, B1-B n The initial state of B1-B is empty and n The corresponding distance interval is set continuously from small to large; it can be understood as: B j The upper limit of the corresponding distance interval is j+1 The lower limits of the corresponding distance intervals are connected.

[0041] Specifically, step S001 also includes the following steps:

[0042] S0011, according to A i The maximum distance among the corresponding target distances, from B1-B n The distance interval in which the maximum distance lies is determined in the corresponding distance interval.

[0043] S0012, determine the initial WiFi cluster corresponding to the distance interval where the maximum distance is located as the target WiFi cluster. i The corresponding maximum distance is 4km, and the distance interval corresponding to B2 is (3km, 6km], so A i Place in B2.

[0044] Furthermore, B j The corresponding distance interval is ((j-1)×δ, j×δ].

[0045] Preferably, δ=3 km. In a specific implementation, since the distance between base stations is mostly around 3 km, δ is set to 3 km.

[0046] S002, based on the number of characters corresponding to each keyword in the given first mobile WiFi keyword library, extract characters from the SSID name of each target WiFi in each target WiFi cluster according to each number of characters, and obtain a plurality of target character strings corresponding to each target WiFi.

[0047] In a specific embodiment, step S002 also includes the following steps:

[0048] S0021, according to the number of characters corresponding to each keyword in the first mobile WiFi keyword library, obtain a number of character numbers. For example, the number of characters of each keyword in the first mobile WiFi keyword library is traversed, and the number of characters counted is five, namely 2, 3, 4, 5, and 6.

[0049] S0022, for any number of characters, extract consecutive characters from the SSID name of each target WiFi according to the number of characters to obtain a number of target character strings corresponding to each target WiFi. For example, when the number of characters is 3, extract all 3 consecutive characters from the SSID name of the target WiFi, that is, when the SSID name has 8 characters in total, extract 6 target character strings in total, each of which includes 3 consecutive characters.

[0050] S0023, according to the number of keywords corresponding to each number of characters, the number of characters is sorted in descending order of the number of corresponding keywords, and the target strings corresponding to each target WiFi are sorted according to the sorting result of the number of characters to obtain a string sorting result. For example, the sorting result of the number of characters is 5-4-6-3-2. For any target WiFi, the target string with the number of characters of 5 among the target strings corresponding to the target WiFi is placed at the head of the string sorting result, and the target string with the number of characters of 2 is placed at the end of the string sorting result. It should be noted that for target strings with the same number of characters, they are sorted according to the order in which the target strings appear in the SSID name.

[0051] As described above, by extracting the string of the SSID name according to the number of characters of the keyword, the more keywords corresponding to the same number of characters, the greater the probability of successful string matching. Therefore, the extracted target strings are sorted based on the number of characters, and the target strings are matched with the keywords in turn according to the target string sorting results. This can increase the probability of successful matching at each time and also improve the matching accuracy.

[0052] S003, match the several target strings corresponding to each target WiFi with the keywords in the first mobile WiFi keyword library, and determine the target WiFi corresponding to the successfully matched target string as the first preset type of mobile WiFi; otherwise, match the several target strings corresponding to each target WiFi with the keywords in the second mobile WiFi keyword library, and determine the target WiFi corresponding to the successfully matched target string as the second preset type of mobile WiFi; it can be understood that: the matching priority of the first preset type of mobile WiFi is higher than the matching priority of the second preset type of mobile WiFi. It should be noted that, since the number of characters of the keywords obtained in the first mobile WiFi keyword library has basically included the number of characters of the keywords in the second mobile WiFi keyword library, it is sufficient to directly use the obtained several target strings to match the keywords in the second mobile WiFi keyword library. In a specific implementation, the number of characters of the keywords in the second mobile WiFi keyword library can also be counted, and the characters of the SSID name of each target WiFi in each target WiFi cluster are extracted again, and subsequent keyword matching operations are performed according to the extracted strings.

[0053] Specifically, the first preset type of mobile WiFi is a vehicle-mounted WiFi. For example, the SSID name of the vehicle-mounted WiFi includes the brand, model, and driving recorder of the vehicle.

[0054] Furthermore, the second preset type of mobile WiFi is a mobile phone hotspot. For example, the SSID name of the mobile phone hotspot includes the mobile phone model-Android, etc. In a specific implementation, a third mobile WiFi keyword library can also be set according to actual needs, and the corresponding third preset type of mobile WiFi is a portable WiFi.

[0055] As mentioned above, considering that in actual usage scenarios, some mobile WiFi SSID names include both keywords corresponding to car WiFi and keywords corresponding to mobile hotspots, in this case, the mobile WiFi all belongs to car WiFi. Therefore, when matching keywords, the matching priority of the first mobile WiFi keyword and the target string is higher than the matching priority of the second mobile WiFi keyword and the target string, which is conducive to quickly and accurately determining the type of mobile WiFi.

[0056] In a specific embodiment, step S003 also includes the following steps:

[0057] S0031, for any string sorting result corresponding to the target WiFi, match the target string with the keywords in the first mobile WiFi keyword library in sequence according to the sequence of the target strings in the string sorting result.

[0058] S0032: When any target string successfully matches a keyword in the first mobile WiFi keyword library, the matching of the target string is stopped, and the target WiFi corresponding to the successfully matched target string is determined as a mobile WiFi of the first preset type.

[0059] As described above, by matching the target character strings with the keywords in the order of sequence and stopping the matching of the target character strings when the match is successful, there is no need to match all the target character strings, which can improve the matching efficiency. The order of the target character strings corresponds to the order of the number of characters. When the number of characters corresponds to the more keywords, the greater the probability of successful matching. Therefore, matching according to the order of the target character strings can improve the probability of successful matching in the early stage. By matching target character strings with different numbers of characters with keywords, mobile WiFi can be quickly and accurately determined.

[0060] Furthermore, the method further comprises the following steps:

[0061] S10, obtaining an initial WiFi cluster corresponding to each target mobile WiFi; wherein the target mobile WiFi refers to any one of a mobile WiFi of a first preset type and a mobile WiFi of a second preset type.

[0062] S20, obtaining the preset WiFi cluster priority corresponding to each initial WiFi cluster in the initial WiFi cluster set B; wherein B1-B n The priorities of the corresponding preset WiFi clusters increase in sequence; it can be understood that: the larger the distance interval corresponding to the initial WiFi cluster, the greater the priority of the preset WiFi cluster corresponding to the initial WiFi cluster.

[0063] S30, sorting a plurality of target mobile WiFis according to the initial WiFi cluster corresponding to each target mobile WiFi and the preset WiFi cluster priority corresponding to each initial WiFi cluster, and obtaining the accuracy priority sorting result of the target mobile WiFis. For example, the greater the preset WiFi cluster priority corresponding to the target mobile WiFi, the greater the accuracy priority corresponding to the target mobile WiFi.

[0064] As mentioned above, since the farther the WiFi moves, the greater the probability that it belongs to mobile WiFi, a higher priority is set for the initial WiFi cluster with a large corresponding distance interval. By setting this, the accuracy of each determined mobile WiFi can be ranked, that is, the higher the priority of the corresponding initial WiFi cluster, the greater the accuracy that the target WiFi belongs to mobile WiFi, which can provide a measurement basis for the accuracy of the determined mobile WiFi.

[0065] An embodiment of the present invention also provides a non-transitory computer-readable storage medium, which can be set in an electronic device to store at least one instruction or at least one program related to implementing a method in a method embodiment. The at least one instruction or the at least one program is loaded and executed by the processor to implement the method provided in the above embodiment.

[0066] An embodiment of the present invention further provides an electronic device, comprising a processor and the aforementioned non-transitory computer-readable storage medium.

[0067] Although some specific embodiments of the present invention have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It will also be appreciated by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A mobile WiFi identification method, characterized in that: The method comprises the following steps: S100, based on a given mobile WiFi sample set D = {D1, D2, ..., D e , ..., D f }, get D e The location information of several mobile WiFi devices reported within the preset initial time period T1 is obtained based on the location information of several mobile WiFi devices. e The corresponding first moving distances, where D e is the e-th mobile WiFi sample, e=1, 2, ..., f, f is the number of mobile WiFi samples, and the first moving distance refers to the distance between any two adjacent mobile WiFi location information; S200, from D e A plurality of second moving distances are selected from the corresponding plurality of first moving distances, and the plurality of second moving distances are normalized to a range between 0 and 10 to obtain a plurality of third moving distances; the second moving distance refers to any first moving distance except the maximum first moving distance and the minimum first moving distance; S300, calculating the movement distance fluctuation degree according to the plurality of third movement distances, and when the movement distance fluctuation degree is less than a preset fluctuation degree threshold, setting D e Identified as critical mobile WiFi; S400, when the ratio of the number of key mobile WiFis to f is greater than a preset ratio threshold, determine the initial time period T1 as the preset time period T; otherwise, replace T1-ΔT with a new T1, and return to execute steps S001-S004 until the preset time period T is determined, or when T1<T0, determine T0 as the preset time period T, where ΔT is the preset first time threshold, and T0 is the preset second time threshold; S500, based on a preset target WiFi set A={A1,A2,……,A i , ..., A m }, get A i Several WiFi location information corresponding to the preset time period T, A i refers to the i-th target WiFi, i = 1, 2, ..., m, m is the number of target WiFi; S600, for A i The corresponding WiFi location information within the preset time period T is obtained, and the target distance corresponding to each two WiFi location information is obtained. i The corresponding target distances; S700, confirm A i The maximum distance among the corresponding target distances, and when the maximum distance is greater than the preset distance threshold δ, A i Identified as mobile WiFi.

2. The mobile WiFi identification method according to claim 1, characterized in that: After step S600, the following steps are also included: S001, according to A i The maximum distance among the corresponding target distances is obtained from the preset initial WiFi cluster B = {B1, B2, ..., B j , ..., B n } to determine the target WiFi cluster and i Insert into the target WiFi cluster; where B j is the preset jth initial WiFi cluster, j = 1, 2, ..., n, n is the number of initial WiFi clusters, B1-B n The initial state of B1-B is empty and n The corresponding distance interval is set continuously from small to large; S002, based on the number of characters corresponding to each keyword in the given first mobile WiFi keyword library, extract characters from the SSID name of each target WiFi in each target WiFi cluster according to each number of characters, to obtain a plurality of target character strings corresponding to each target WiFi; S003, match the several target strings corresponding to each target WiFi with the keywords in the first mobile WiFi keyword library, and determine the target WiFi corresponding to the successfully matched target string as the first preset type of mobile WiFi; otherwise, match the several target strings corresponding to each target WiFi with the keywords in the second mobile WiFi keyword library, and determine the target WiFi corresponding to the successfully matched target string as the second preset type of mobile WiFi.

3. The mobile WiFi identification method according to claim 2, characterized in that: The step S001 also includes the following steps: S0011, according to A i The maximum distance among the corresponding target distances, from B1-B n Determine the distance interval in which the maximum distance lies in the corresponding distance interval; S0012: Determine the initial WiFi cluster corresponding to the distance interval in which the maximum distance is located as the target WiFi cluster.

4. The mobile WiFi identification method according to claim 2, characterized in that: B j The corresponding distance interval is ((j-1)×δ, j×δ].

5. The mobile WiFi identification method according to claim 1, characterized in that: The step S002 also includes the following steps: S0021, obtaining a number of character quantities according to the number of characters corresponding to each keyword in the first mobile WiFi keyword library; S0022, for any number of characters, extract consecutive characters from the SSID name of each target WiFi according to the number of characters, so as to obtain a number of target character strings corresponding to each target WiFi; S0023, sorting the character quantities in descending order according to the keyword quantities corresponding to each character quantity, and sorting the target character strings corresponding to each target WiFi according to the character quantity sorting result to obtain the character string sorting result.

6. The mobile WiFi identification method according to claim 5, characterized in that: The step S003 also includes the following steps: S0031, for any string sorting result corresponding to the target WiFi, according to the sequence of the target strings in the string sorting result, match the target string with the keywords in the first mobile WiFi keyword library in sequence; S0032: When any target string successfully matches a keyword in the first mobile WiFi keyword library, the matching of the target string is stopped, and the target WiFi corresponding to the successfully matched target string is determined as a mobile WiFi of the first preset type.

7. A non-transitory computer-readable storage medium, wherein at least one instruction or at least one program is stored in the storage medium, characterized in that: The at least one instruction or the at least one program is loaded and executed by the processor to implement the mobile WiFi identification method according to any one of claims 1 to 6.

8. An electronic device, characterized in that: The invention comprises a processor and the non-transitory computer-readable storage medium as claimed in claim 7.

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