An SSID-based trajectory collision method and system

Abstract

The present invention provides a trajectory collision method and system based on SSID. The method includes: updating a common SSID information library; inputting historical SSID information of a device to be matched; inputting historical SSID information of a device to be searched; calculating the SSID confidence between the device to be matched and the device to be searched; and outputting the trajectory collision result of the device to be matched according to the confidence ranking. It can quickly and efficiently implement information matching between devices, improve the accuracy of the result on the basis of general trajectory collision results, effectively prevent / solve the occurrence of potential events endangering public safety, and can be generally applicable to trajectory collision between different electronic devices, peer analysis between various electronic devices, such as Bluetooth and Bluetooth, Bluetooth and Wi-Fi, Wi-Fi and video, video and video, video and Bluetooth, etc.; the application scenarios include various wireless scenarios indoors and outdoors, and the application fields can be extended to voice recognition, face recognition, big data analysis, etc.

Description

Technical Field

[0001] The present invention relates to the technical field of trajectory collision, and in particular to a method and system for trajectory collision based on SSID.

Background Art

[0002] Generally, the commonly used trajectory collision method is to save the longitude and latitude of the target position, and calculate according to the longitude and latitude provided by the user through the spherical distance formula. The formula is:

[0003] 。

[0004] Calculate the spherical distance for all coordinate information within the time range, sort according to the magnitude of the spherical distance, and find the coordinate information with the smallest distance, which is the information most similar to the coordinate information to be matched. The principle of this scheme is simple, but in the implementation process, due to the huge amount of calculation, the timeliness of the collision result is very poor, the efficiency is low, and the meaning of the collision is lost.

[0005] WIFI probes can obtain the corresponding MAC information and historical SSID information by detecting devices within the coverage area. By analyzing the positioning algorithm for the MAC information, the position information can be estimated. The WiFi positioning system periodically scans the surrounding electronic devices with wireless network card functions through WiFi probes. The information it scans includes not only the RSSI signal strength information and time information of the MAC, but also the historical SSID information. Most systems only utilize the RSSI signal strength information and time information of the scanned MAC to perform coordinate positioning; the scanned historical SSID information is not reasonably utilized, resulting in a great waste of SSID information.

Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a method and system for trajectory collision based on SSID, which can quickly and efficiently achieve information matching between devices, improve the accuracy of the result on the general trajectory collision result, effectively prevent / solve the occurrence of potential public safety hazard events, and can be generally applicable to trajectory collisions between different electronic devices, peer analysis between various electronic devices, such as Bluetooth and Bluetooth, Bluetooth and wifi, wifi and video, video and video, video and Bluetooth, etc.; the application scenarios include various wireless scenarios indoors and outdoors, and the application fields can be extended to speech recognition, face recognition, big data analysis, etc.

[0007] To solve the above technical problems, on the one hand, an embodiment of the present invention provides a trajectory collision method based on SSID, including: updating the public SSID information library; inputting the historical SSID information of the device to be matched; inputting the historical SSID information of the device to be searched; calculating the SSID confidence level P between the device to be matched and the device to be searched; ranking according to the SSID confidence level P, and outputting the trajectory collision result of the device to be matched.

[0008] Preferably, updating the public SSID information library includes: scanning SSID information with a wifi probe, summarizing and analyzing the scanned SSID information, and screening out the commonly used SSID information from it.

[0009] Preferably, calculating the SSID confidence level P between the device to be matched and the device to be searched includes:

[0010] where M represents the number of the same public SSIDs, N represents the number of the same private SSIDs, SSID public represents the public SSID, and SSID private represents the private SSID.

[0011] Preferably, before ranking according to the SSID confidence level P and outputting the trajectory collision result of the device to be matched, it further includes: recording the confidence level information of the device to be searched.

[0012] Preferably, the screening rule for screening out the commonly used SSID information includes: sorting according to the SSID detection times, and selecting the top-ranked SSID information as the public SSID.

[0013] Preferably, the screening rule for screening out the commonly used SSID information includes: screening according to keywords.

[0014] Preferably, the top-ranked SSID information includes the top 10 to 20 ranked SSID information.

[0015] Preferably, the method combines the trajectory collision result based on the location to confirm the device to be matched.

[0016] Preferably, using the trajectory collision result based on the location to confirm the device to be matched includes: inputting the trajectory stream data to be matched; performing time slicing on the input trajectory stream data; determining whether there is input trajectory stream data within the time slice; if so, proceed to the next step; if not, continue to process the next time slice and return to the previous step at the same time; screening out the matching information that meets the conditions within the time slice; updating the matching times of each matching information.

[0017] On the other hand, an embodiment of the present invention discloses a trajectory collision system based on SSID. The system includes a positioning device and a server, and the above-mentioned trajectory collision method of the system.

[0018] Compared with the prior art, the above technical solution has the following advantages: It can quickly and efficiently achieve information matching between devices, improve the accuracy of the results on the basis of general trajectory collision results, effectively prevent / solve the occurrence of potential public safety hazard events, and can be generally applicable to trajectory collisions between different electronic devices, peer analysis between various electronic devices, such as Bluetooth and Bluetooth, Bluetooth and Wi-Fi, Wi-Fi and video, video and video, video and Bluetooth, etc.; the application scenarios include various wireless scenarios indoors and outdoors, and the application fields can be extended to voice recognition, face recognition, big data analysis, etc.

BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0020] Figure 1 It is a flowchart of the trajectory collision method based on SSID of the present invention.

[0021] Figure 2 It is a flowchart of the trajectory collision based on location.

[0022] Figure 3 It is a structural diagram of the trajectory collision system based on SSID of the present invention.

[0023] Figure 4 It is Figure 3 The storage schematic diagram of the positioning server in

DETAILED DESCRIPTION

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0025] SSID is the abbreviation of Service Set Identifier, which means: Service Set Identification. SSID technology can divide a wireless local area network into several sub-networks that require different authentication. Each sub-network requires independent authentication. Only users who pass the authentication can enter the corresponding sub-network, preventing unauthorized users from entering the network. The SSID can have up to 32 characters. By setting different SSIDs on the wireless network card, different networks can be accessed. The SSID is usually broadcast by the AP, and the SSIDs in the current area can be viewed through the scanning function of the AP. For security reasons, the SSID can be set not to be broadcast. In this case, users need to manually set the SSID to enter the corresponding network. Simply put, the SSID is the name of a local area network. Only computers with the same SSID value can communicate with each other.

[0026] Embodiment 1

[0027] Figure 1 It is the flow chart of the trajectory collision method based on SSID of the present invention. As Figure 1 shown, (1) Maintain / update the public SSID information library. The public SSID information library can be aggregated by manual collection, that is, going to public places to collect or query on the Internet. It can also be collected automatically by summarizing and analyzing the SSID information scanned by the wifi probe, and screening out the commonly used SSID information from it. The screening principles include:

[0028] a. Sort according to the SSID detection times, and select the SSID information with the top ranking as the public / commonly used SSID. For example, the top 10 or top 20 can be selected.

[0029] b. Screen according to keywords. For example, the commonly used operator SSIDs are: CMCC, ChinaNet, etc., and the SSIDs in public places are: airport, KFC, Starbucks, etc.

[0030] Regularly update the SSID information library. Optionally, regularly update the maintained public SSID information library to the induction function list of the probe, which can improve the induction function of the probe and increase the MAC acquisition rate of the probe.

[0031] (2) Input the historical SSID information of the device to be matched.

[0032] (3) Input the historical SSID information of the device to be searched.

[0033] (4) Calculate the confidence levels of the SSID information in (2) and (3).

[0034] Historical SSID information can be directly collected by the probe device. The number of devices with the same SSID is calculated as the basis for judgment. The more the number of the same devices, the greater the probability that these two devices have appeared in multiple areas simultaneously in history. The confidence level P can be expressed as: p = N, where N represents the number of devices with the same SSID.

[0035] Expandable. Since the names of some public SSIDs are the same in different areas, for example, the common SSID name of KFC is KFC, and the SSIDs of all KFCs across the country are the same. If only the number of the same SSIDs is calculated, the result will be misleading to some extent. Therefore, different confidence level coefficients can be set for public and private SSIDs. The confidence level coefficient of public SSIDs is lower than that of private SSIDs to reduce the reference value of public SSIDs. The confidence level can be expressed as M represents the number of devices with the same public SSID, N represents the number of devices with the same private SSID, SSID public represents the public SSID, SSID private represents the private SSID.

[0036] (5) Record the confidence level information of each device to be searched.

[0037] Calculate the SSID confidence levels of all devices in the area and the device to be matched in the manner of step (4).

[0038] (6) Output and store the collision results.

[0039] Rank the results in (5) according to the confidence level. The higher the ranking, the greater the probability that these two devices have appeared in multiple areas simultaneously in history.

[0040] It should be noted that:

[0041] a. This solution can achieve the simultaneous collision of multiple SSID information in a parallel manner.

[0042] b. There may be multiple collision results. Through the online operation method, as time goes by, the number of track collisions of the same attributes will gradually become prominent.

[0043] Regularly maintain and update the collision results. Through long-term data operation and analysis, the SSID matching information of different devices can be obtained.

[0044] Expandable. Since the track collision of SSIDs is based on area collision and the result is relatively rough, the track collision result based on location can be combined with the collision result based on SSID to improve the reliability of the final collision result. The track collision method based on location is as shown in the appendix Figure 2 as follows Figure 2It is a flow chart of trajectory collision based on location. Its positioning results mainly include coordinate and time information. Taking latitude and longitude coordinates as an example, the positioning result is (mac, lat, lng, time). The collision method is as follows:

[0045] (1) Input the trajectory stream data to be matched

[0046] (2) Perform time slicing on the input trajectory stream data

[0047] (3) Determine whether there is input trajectory stream data within this time slice

[0048] If there is, go to step (4); if not, continue to process the next time slice and perform step (3) simultaneously.

[0049] (4) Screen out the matching information that meets the conditions within the time slice

[0050] Within this time slice, find the trajectory information that is closest to the input trajectory stream data from all the trajectory stream data to be searched, and obtain the matching information set within this time slice.

[0051] Analysis can be carried out according to distance / region / similarity, etc. For distance, it is judged based on whether two trajectories are within the distance threshold, taking spherical distance and Euclidean distance as examples; for region, it is judged based on whether two trajectories belong to the same region; for similarity, it is judged based on whether two trajectories are similar. The data calculation / screening here includes various methods, which can be through direct calculation or through the idea of position hashing for rapid data screening.

[0052] (5) Update the matching times of each matching information

[0053] Update the matching times of the information matched in time and space in (4).

[0054] Taking the set of matched macs as an example, if the matched mac already exists, add 1 to the original matching times; if it does not exist, the matching times is 1.

[0055] (6) Determine whether all time slices have been traversed

[0056] If not all time slices have been traversed, process the next time slice and perform step (3), otherwise go to step (8).

[0057] (8) Output the collision result

[0058] Embodiment 2

[0059] The WiFi probe device can scan all electronic devices within a certain area, integrate and summarize the signal strength (RSSI) of the captured MACs, run a positioning algorithm, and perform real-time positioning analysis on the marked MACs to obtain the real-time position information (p, t) of the marked MACs, where p represents the position information and t represents the time corresponding to the current position.

[0060] Figure 3 This is the structure diagram of the trajectory collision system based on SSID of the present invention. As Figure 3 shown, the trajectory collision system based on SSID consists of a WiFi probe device, a POE module, a database server, and a positioning server.

[0061] Among them, the uses of the WiFi probe device include:

[0062] (1) The built-in induction module emits SSIDs with a high connection frequency to induce devices to connect and increase the probability of capturing MACs.

[0063] (2) Full-channel scanning to capture device MACs without missing packets.

[0064] (3) Encrypt and transmit information such as the signal strength and connection time difference of the marked MACs to the position calculation server for accurate position calculation.

[0065] (4) Obtain the historical SSID information of the device.

[0066] The POE module powers the WiFi probe device and at the same time transmits data back to the database server.

[0067] The database server serves as a database for storing MAC addresses, runs a MAC address comparison program, quickly compares the MACs captured by the WiFi probe device, transmits the successfully compared data to the positioning server, and updates and stores information such as the connection duration, connection time, and position of the devices with marked MACs, and simulates the movement path of the devices with marked MACs.

[0068] The positioning server runs a positioning algorithm, calculates the positions of the marked MACs, and transmits them to the database server to update the database of the marked MACs. The storage schematic diagram of the positioning server is as shown in the appendix Figure 4 shown.

[0069] Figure 4 This is Figure 3 the storage schematic diagram of the positioning server in. The storage format of the positioning server is that each line of data represents the ID of the device to be positioned, the MAC address of the device to be positioned, the device name of the device to be positioned, the X coordinate of the device to be positioned, the Y coordinate of the device to be positioned, and the reporting time.

[0070] Embodiment III

[0071] Assume that the maintained common SSID information library is

[0072] Number SSID Name 1 KFC Free WiFi 2 CMCC 3 China-Net

[0073] The device historical SSID information is as follows:

[0074] Number MAC Historical SSID List 1 <![CDATA[MAC1]]> KFC Free WiFi, CMCC, mywifi, KC, TP-LINK-1, China-Net 2 <![CDATA[MAC2]]> CMCC, airport, myapple, KC, mywifi 3 <![CDATA[MAC3]]> CMCC, KFC Free WiFi, China-Net, TP-LINK-1, myhuawei 4 <![CDATA[MAC4]]> KFC Free WiFi, myoppo, CMCC

[0075] Calculate the confidence levels of devices 2, 3, and 4 with respect to device 1. The results obtained by the method of the same number of SSIDs are {MAC2: 3, MAC3: 4, MAC4: 2}. It can be seen that the confidence level of MAC3 is relatively high.

[0076] According to the method of calculating confidence levels with different coefficients:

[0077] Set α = 0.1, and the results obtained are:

[0078] MAC2 = 0.1×1 + 0.9×2 = 1.9;

[0079] MAC3 = 0.1×3 + 0.9×1 = 1.2;

[0080] MAC4 = 0.1×2 = 0.2;

[0081] It can be seen that the confidence level of MAC2 is relatively high.

[0082] Assume that the location-based trajectory collision results are: {MAC2: 10, MAC3: 5, MAC4: 8}. Combining it with the results based on SSIDs for analysis, after information matching in multiple dimensions, the probability that device MAC2 appears in multiple regions with MAC1 at historical moments is relatively large. It can be seen that the confidence level of MAC2 is the highest.

[0083] As can be seen from the above description, by using the SSID-based trajectory collision method and system according to the present invention, information matching between devices can be achieved quickly and efficiently, the accuracy of the results is improved on the basis of general trajectory collision results, potential public safety hazard events can be effectively prevented / solved, and it can be generally applicable to trajectory collisions between different electronic devices, peer analysis between various electronic devices, such as Bluetooth and Bluetooth, Bluetooth and Wi-Fi, Wi-Fi and video, video and video, video and Bluetooth, etc.; the application scenarios include various wireless scenarios indoors and outdoors, and the application fields can be extended to speech recognition, face recognition, big data analysis, etc.

[0084] The above has introduced the embodiments of the present invention in detail. Specific examples are used herein to elaborate on the principles and implementation manners of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A trajectory collision method based on SSID, characterized in that, Including: Update the public SSID information library; Input the historical SSID information of the device to be matched; Input the historical SSID information of the device to be searched; Calculate the SSID confidence P between the device to be matched and the device to be searched; Calculating the SSID confidence level P between the device to be matched and the device to be searched for includes: where M represents the number of devices with the same public SSID, N represents the number of devices with the same private SSID, SSID public represents the public SSID, and SSID private represents the private SSID; Rank according to the SSID confidence P and output the trajectory collision result of the device to be matched; Among them, the method combines the trajectory collision result based on location to confirm the device to be matched; the trajectory collision result based on location to confirm the device to be matched includes: Input the trajectory stream data to be matched; Perform time slicing on the input trajectory stream data; Judge whether there is input trajectory stream data in this time slice; If so, proceed to the next step; if not, continue to process the next time slice and return to the previous step at the same time; Filter out the matching information that meets the conditions in the time slice; Update the matching times of each matching information.

2. The method for trajectory collision based on SSID according to claim 1, wherein Updating the public SSID information library includes: Scan the SSID information with a wifi probe, summarize and analyze the scanned SSID information, and filter out the commonly used SSID information from it.

3. The method for trajectory collision based on SSID according to claim 1, wherein Before ranking according to the SSID confidence P and outputting the trajectory collision result of the device to be matched, it also includes: Record the confidence information of the device to be searched.

4. The method for trajectory collision based on SSID according to claim 2, characterized in that The screening rule for filtering out the commonly used SSID information includes: sorting according to the SSID detection times, and selecting the top-ranked SSID information as the public SSID.

5. The method for trajectory collision based on SSID according to claim 2, wherein The screening rule for filtering out the commonly used SSID information includes: filtering according to keywords.

6. The method for trajectory collision based on SSID according to claim 4, wherein The top-ranked SSID information includes the top 10-20 ranked SSID information.

7. A trajectory collision system based on SSID, characterized in that, The system includes a positioning device and a server, and the system executes the method described in any one of claims 1-6.

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