A target positioning method and system

Abstract

The present invention relates to a target positioning method and system. The method includes the following steps: multiple wearable devices perform MAC address acquisition; select the target to be positioned from the acquired MAC addresses; determine the signal strength of the target to be positioned detected by the wearable devices, and based on the comparison result of the signal strength, determine the area where the target to be positioned is relative to the wearable devices; determine the target to be positioned from the area. Implementing the present invention does not require large-scale pre-device layout. By carrying or wearing movable devices, the target activity area can be updated and narrowed in real time according to the tracking and positioning analysis results and self-analysis results feedback by the detection devices in a timely manner, and finally accurate positioning can be achieved. At the same time, the use of wearable devices to track and position moving targets makes both device layout and positioning methods more flexible.

Description

Technical Field

[0001] The present invention relates to positioning technology, and more particularly, to a method and system for target positioning. Background Art

[0002] In existing security monitoring technologies, there are solutions for monitoring and tracking specific devices. Generally, WIFI probes are used to monitor the MAC addresses of key sensitive devices recorded. The traditional positioning and tracking method is to deploy a tracking and positioning system in advance in key areas. This system generally includes detection devices and a data analysis platform. The detection devices collect data on the multi-dimensional feature information of people in the covered area, and the data analysis platform performs real-time tracking and analysis on the detected multi-dimensional feature information.

[0003] When a target person appears, the detection device feeds the detected data back to the data analysis platform. The data analysis platform locates and tracks the target person, and then feeds the positioning result back to the on-site arrest personnel. The arrest personnel lock and arrest the target according to the result fed back by the analysis platform. In actual situations, due to the limited coverage area of the detection device and the existence of coverage blind spots, when the target escapes from the covered area, it has a great impact on the continuity of tracking, and at the same time increases the difficulty of on-site arrest. Commonly used positioning algorithms include the location fingerprint positioning algorithm, which requires fingerprint collection in the covered area and regular update of the fingerprint database. Its workload is huge, time-consuming and laborious, and it is not conducive to promotion for large-scale application scenarios. Summary of the Invention

[0004] In view of the problems in the prior art that the pre-deployed solution has a limited coverage area and blind spots, and a large deployment workload, the present invention proposes a method and system for positioning a moving target using a movable device.

[0005] In the first aspect of the present invention, there is provided a target positioning method, including:

[0006] S100. Multiple wearable devices perform MAC address collection;

[0007] S200. Select a target to be positioned from the collected MAC addresses;

[0008] S300. Determine the signal strength of the target to be positioned detected by the wearable device, and based on the comparison result of the signal strength, determine the area where the target to be positioned is relative to the wearable device;

[0009] S400. Determine the target to be positioned from the area.

[0010] Preferably, the wearable device is a smart helmet.

[0011] Preferably, in the step S100, there are at least 3 wearable devices, and the 3 wearable devices are not on the same straight line.

[0012] Preferably, the step S300 further includes:

[0013] Determine the equal-signal points on the connection line of the positions of adjacent wearable devices, connect each pair of all wearable devices and the equal-signal points, divide into multiple signal comparison regions, and determine the area where the target to be located is relative to the area where the wearable devices are located according to the signal comparison results detected by the wearable devices.

[0014] Preferably, the step S400 further includes:

[0015] When the target to be located cannot be determined from the area, the wearable device moves to the area where the wearable device is located and re-executes step S300.

[0016] Preferably, the step S200 includes:

[0017] Determine whether the collected MAC address is in the blacklist database. When the MAC address is in the blacklist database, select it as the target to be located.

[0018] In the second aspect of the present invention, a target positioning system is provided, including a cloud platform and multiple wearable devices, and the multiple wearable devices are communicatively connected to the cloud platform;

[0019] The wearable device is used to collect the MAC address and send it to the cloud platform;

[0020] The cloud platform selects the target to be located from the collected MAC addresses, determines the signal strength of the target to be located detected by the wearable device, and determines the area where the target to be located is relative to the area where the wearable device is located according to the comparison result of the signal strength;

[0021] The cloud platform sends the area where the target is located to the wearable device, and the wearer of the wearable device determines the target to be located from the area.

[0022] Preferably, there are at least 3 wearable devices, and the at least 3 wearable devices are not on the same straight line.

[0023] Preferably, the wearable device is a smart helmet.

[0024] Preferably, the cloud platform includes a blacklist database. When the collected MAC address exists in the blacklist database, the cloud platform selects it as the target to be located.

[0025] With the solution of the present invention, there is no need for large-scale pre-arrangement of equipment. Personnel can carry or wear movable devices to timely update and narrow the target activity area according to the tracking and positioning analysis results and self-analysis results feedback by the detection devices, and finally achieve precise positioning. At the same time, wearable devices are used to track and position moving targets, making both the equipment layout and the positioning method more flexible. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings forming a part of this application are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0027] Figure 1 It is a schematic diagram of dividing the MAC area according to a preferred embodiment of the present invention;

[0028] Figure 2 It is a flowchart of the positioning method according to a preferred embodiment of the present invention;

[0029] Figure 3 It is a flowchart of tracking a target according to a preferred embodiment of the present invention;

[0030] Figure 4 It is a schematic diagram of the positioning system according to a preferred embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0032] It should be pointed out that unless otherwise specified, all technical and scientific terms used in this application have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.

[0033] In the present invention, unless otherwise stated, the orientation words such as "up, down, top, bottom" are usually in the direction shown in the drawings, or in the vertical, perpendicular or gravitational direction of the component itself; similarly, for the convenience of understanding and description, "inside, outside" refer to the inside and outside relative to the contour of each component itself, but the above orientation words do not limit the present invention.

[0034] As Figure 1 shown is a schematic diagram of the target positioning solution according to a preferred embodiment of the present invention. In this embodiment, 3 wearable devices are used, namely wearable device A, wearable device B and wearable device C. The three devices are distinguished by three different asterisks in Figure 1 The positions of the three devices at a certain moment are POS A, POS B and POS C , the positions of the three wearable devices can be obtained by setting GPS chips in the devices. Each wearable device is carried by a staff member.

[0035] In this embodiment, the three devices are smart helmets, which are built-in with multiple electronic modules to achieve different functions. In this embodiment, only the WIFI probe is taken as an example. When a WIFI probe module is set in the smart helmet, it can detect the MAC addresses of nearby Internet devices (such as smartphones).

[0036] The three smart helmets act as movable WIFI probes to Figure 1 detect the MAC address of the tracking target in A 、RSSI B 、RSSI C . Comparing these three strength values, for example, the comparison result in this embodiment is RSSI A < RSSI B 、RSSI C > RSSI B 、RSSI A < RSSI c . Since the RSSI value will be measured larger when the distance to the smart helmet is closer, by comparing the intensities detected by two different smart helmets, it is possible to determine which helmet the target is more "close" to. For example, in this embodiment, RSSI A < RSSI B , so the target is closer to the smart helmet represented by B.

[0037] In order to determine the area where the target is located by comparing RSSI, first, the RSSI intensity of the areas where the three smart helmets are located is weighted and divided. In a preferred solution, the RSSI equal-value points of two adjacent smart helmets are selected. The significance of this equal-value point is that if the target MAC is located at this position, the two smart helmets detect the same RSSI intensity, and the area is divided by connecting the line with the third smart helmet. Specifically, as shown by the three dotted lines in Figure 1 , the three dotted lines together with the pairwise connections of the three smart helmets divide the entire area into multiple sub-areas. According to the comparison result of RSSI, RSSI A < RSSI B 、RSSIC >RSSI B 、RSSI A <RSSI c It can be determined that the target area at this time is the shaded area.

[0038] After obtaining the range of the above-mentioned shaded area at a certain moment, the wearers of the three smart helmets can move towards the shaded area, and re-execute the above positioning method at the next moment to obtain a new positioning area. By gradually approaching, the target can be finally locked.

[0039] In this embodiment, equivalent RSSI points are used to divide the area. This division scheme is not unique. For example, the middle position points of the three smart helmets can also be connected to divide multiple judgment areas; or the intensity distribution of RSSI and the position midpoint can be combined for weighted calculation and then used as weighted equivalent RSSI points for connection to divide multiple judgment areas.

[0040] In the above example, the scheme of collecting by the device multiple times at different times and gradually approaching the positioning area to lock the target is adopted. In other feasible implementation schemes, more wearable devices are used for cooperation: any combination of three smart helmets performs the above area division scheme to obtain a judgment area; the judgment areas of multiple combinations are overlapped and judged to obtain a more accurate area with a smaller coverage area, and then the target in this area is positioned. Those skilled in the art can understand that the above scheme can be combined with the previous positioning embodiment and the two work together in coordination.

[0041] The process of adopting the positioning scheme of the above embodiment is as Figure 2 shown:

[0042] In step S100, multiple wearable devices collect MAC addresses; in this step, the wearable devices can be smart helmets, and a WiFi probe module is installed in the smart helmets to collect the MAC addresses of devices within the nearby range.

[0043] In step S200, the MAC addresses obtained in step S100 are analyzed, and the targets to be positioned are selected from all the collected MAC addresses; in this step, the method of setting a blacklist / whitelist on the cloud platform or server can be used to select the targets to be positioned. For example, the devices corresponding to the MAC addresses on the blacklist need to be positioned, the MAC addresses on the whitelist are ignored, and for other MAC addresses, artificial intelligence judgment is performed according to the behavior trajectory. Specifically, the blacklist and whitelist can be shown in Table 1 and Table 2.

[0044] Table 1

[0045]

[0046] Table 2

[0047]

[0048] Table 1, each row represents a device to be located, including its MAC address, device type, reason for being blacklisted and data update time. Table 2 only records the MAC address, device type and data update time.

[0049] S300. For the device corresponding to the selected MAC address, determine its relative position area relative to at least three wearable devices according to the RSSI strength obtained in at least three wearable devices. In order to be able to determine the divided relative position area, it is necessary to ensure that the three wearable devices selected in this step are not in a straight line. If the selected devices are in a straight line, another group of wearable devices need to be reselected to obtain a spatial triangular area. Or when the three selected wearable devices are in a straight line, the wearers of the wearable devices move their positions by themselves so that the changed positions are not in a straight line.

[0050] S400. Determine whether the target can be located from the position area in step S300. If the target cannot be located, re-execute step S300 until the location target can be determined within the obtained position area.

[0051] To make the positioning result more accurate, the present invention provides a positioning method of another embodiment, and its process is as Figure 3 shown. First, the wearable devices equipped with WiFi probe modules periodically collect the MAC addresses of various surrounding devices, and upload the collected relevant data to the cloud platform analysis system for judgment and detection to confirm whether the collected MAC needs to be focused on.

[0052] For the above-mentioned collected MAC, when it is not in the list that needs to be focused on (such as Table 1 of the present application), the operation of entering the corresponding time and other information detected by it into the information database is performed, so that in the subsequent analysis of the behavior pattern information database, it can be obtained through artificial intelligence analysis whether the MAC needs to be focused on. And if the collected MAC needs to be focused on, subsequent positioning steps are performed.

[0053] Each wearable device continuously detects the target MAC, and obtains the RSSI value of the MAC during the detection process. Since the distance between each wearable device and the MAC is different, the RSSI strengths detected by each device for the MAC are not the same. After receiving the relevant RSSI values, the cloud platform analysis system determines the area where the target MAC is located in combination with the geographical locations of each device. Specifically, the area is obtained by using the method asFigure 2 Perform according to the corresponding steps.

[0054] After the users of each wearable device obtain the positioning area calculated by the cloud platform, they approach this positioning area to further narrow down the positioning area and finally achieve precise positioning and tracking. When each wearable device fails to accurately locate, it is necessary to re-detect the MAC to obtain a new positioning area.

[0055] After fully executing the above steps, under an ideal positioning result, there is only one target within the positioning area, that is, the capture of the target MAC is achieved.

[0056] Adopting the above positioning steps, there is no need to pre-arrange a large number of probes on-site. By virtue of the flexible mobility of the wearable devices, positioning and capture can be carried out in any scenario through the collaborative work of the backend cloud platform.

[0057] To achieve the above positioning effect, the present application provides a positioning system as Figure 4 shown. The system includes a backend cloud platform and multiple front-end wearable devices. The wearable devices are communicatively connected to the backend cloud platform through wireless communication; the multiple wearable devices can be smart helmets. A WiFi probe module for detecting the MAC addresses of nearby mobile devices is provided in the wearable device, and the wearable device uploads the collected MAC information through the communication link with the cloud platform. The cloud platform is used to maintain a MAC information database, and this information database can at least include a MAC white list and a MAC black list. The cloud platform is also used to perform positioning and tracking of the target based on the MAC information uploaded from the wearable device, and send the relevant positioning and tracking information to each wearable device through the communication link with the wearable device.

[0058] The steps for the cloud platform to perform positioning and tracking of a specific MAC are as follows: First, it is necessary to retrieve the MAC data collected by three wearable devices that are not on a straight line in space at a certain moment and the position data of the wearable devices. The MAC data needs to include the RSSI intensity value corresponding to the wearable device detecting the MAC.

[0059] Use the method corresponding to the above-mentioned data for area division and selection, and send the obtained area information to each wearable device and instruct the wearer to move towards this area. Figure 1 Repeat the operations of collecting MAC data and area division and selection until the wearer can locate the target.

[0060] Repeat the operations of collecting MAC data and area division and selection until the wearer can locate the target.

[0061] Adopting the solution of this embodiment, there is no need to deploy on-site monitoring equipment in advance, and it can quickly lock the target through the collaborative work of the wearer flexibly; at the same time, since the wearer can move freely, the monitoring blind area can be reduced to the minimum as much as possible.

[0062] Obviously, the above-described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0063] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they specify the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0064] It should be noted that the terms "first", "second", etc. in the description, claims and drawings of the present application are used to distinguish similar objects and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein.

[0065] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A target positioning method, characterized in that, Including: S100. Multiple wearable devices collect MAC addresses; S200. Select a target to be located from the collected MAC addresses; S300. Determine the signal strength of the target to be located detected by the wearable device, and based on the comparison result of the signal strength, determine the area where the target to be located is relative to the wearable device; In step S100, at least 3 wearable devices are included, and the 3 wearable devices are not on the same straight line; Step S300 further includes: Determine the equal-signal points of the detection signals on the connection line between the positions of adjacent wearable devices, connect each pair of all wearable devices and the equal-signal points of the detection signals, divide into multiple signal comparison areas, and based on the signal comparison results detected by the wearable devices, determine the area where the target to be located is relative to the wearable device; S400. Determine the target to be located from the area.

2. The target positioning method according to claim 1, wherein The wearable device is a smart helmet.

3. The target positioning method according to claim 1, characterized in that Step S400 further includes: When the target to be located cannot be determined from the area, the wearable device moves to the area where the wearable device is located and re-executes step S300.

4. The target positioning method according to claim 1, characterized in that, Step S200 includes: Determine whether the collected MAC address is in the blacklist database. When the MAC address is in the blacklist database, select it as the target to be located.

5. A target positioning system, characterized in that, Including a cloud platform and multiple wearable devices, the multiple wearable devices are communicatively connected to the cloud platform; The wearable device is used to collect MAC addresses and send them to the cloud platform; The cloud platform selects a target to be located from the collected MAC addresses, determines the signal strength of the target to be located detected by the wearable device, and based on the comparison result of the signal strength, determines the area where the target to be located is relative to the wearable device; at least 3 wearable devices are provided, and the at least 3 wearable devices are not on the same straight line; The cloud platform sends the area where the target is located to the wearable device, and the wearer of the wearable device determines the target to be located from the area; the area where the target is located is determined by the following method: determine the equal-signal points of the detection signals on the connection line between the positions of adjacent wearable devices, connect each pair of all wearable devices and the equal-signal points of the detection signals, divide into multiple signal comparison areas, and based on the signal comparison results detected by the wearable devices, determine the area where the target to be located is relative to the wearable device.

6. The target positioning system according to claim 5, characterized in that, The wearable device is a smart helmet.

7. The target positioning system according to claim 5, characterized in that, The cloud platform includes a blacklist database. When the collected MAC address exists in the blacklist database, the cloud platform selects it as the target to be located.

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