WO2020093828A1

WO2020093828A1 - Method and apparatus for identifying whether device is located in target area, and electronic device

Info

Publication number: WO2020093828A1
Application number: PCT/CN2019/110011
Authority: WO
Inventors: 傅春霖; 姜世琦; 杨磊
Original assignee: 阿里巴巴集团控股有限公司
Priority date: 2018-11-09
Filing date: 2019-10-08
Publication date: 2020-05-14
Also published as: TW202019219A; CN110035392B; CN110035392A; TWI718620B

Abstract

Embodiments of the present invention provide a method and apparatus for identifying whether a device is located in a target area, and an electronic device. The method comprises: collecting sample signal features of a test device in the target area, and constructing a sample signal feature library of the target area; collecting signal features of a device to be identified; comparing the signal features of said device with the sample signal feature library of the target area; and if the comparison is successful, determining that said device is located in the target area.

Description

Identification method and device for whether equipment is located in target area and electronic equipment

Technical field

The embodiments of the present specification relate to the field of Internet technologies, and in particular, to a method and apparatus for identifying whether a device is located in a target area and an electronic device.

Background technique

In some public scenarios, it is usually necessary to accurately identify the information on the flow of people in the target area. There are two main traditional solutions. One is to directly detect the flow of people through the camera, but the disadvantage is that the detection range is limited and the cost is relatively high. User information and statistics on the flow of people in the target area. However, in the latter solution, due to the fact that the signal environment in real physical scenes is very different, such as being blocked by obstacles and other factors, it is easy to fail to recognize whether the device is in the target area, that is, it is impossible to accurately identify whether the device is in the target Regional issues.

Therefore, a solution for accurately identifying whether the mobile device is in the target area needs to be provided.

Summary of the invention

An embodiment of this specification provides a method and apparatus for identifying whether a device is located in a target area and an electronic device:

According to a first aspect of the embodiments of the present specification, a method for identifying whether a device is located in a target area is provided. The method includes:

Collect the sample signal characteristics of the test equipment in the target area and construct a sample signal characteristic library of the target area;

Collect the signal characteristics of the equipment to be identified;

Comparing the signal characteristics of the device to be identified with the sample signal characteristic library of the target area;

If the comparison is successful, it is determined that the device to be identified is located in the target area.

According to a second aspect of the embodiments of the present specification, there is provided a device for identifying whether a device is located in a target area, and the device includes:

The first collection unit collects sample signal characteristics of the test equipment in the target area, and constructs a sample signal characteristic library of the target area;

The second collection unit collects the signal characteristics of the device to be identified;

A comparison unit, comparing the signal characteristics of the device to be identified with the sample signal characteristic library of the target area;

The identification unit determines that the device to be identified is located in the target area when the comparison is successful.

According to a fifth aspect of the embodiments of the present specification, an electronic device is provided, including:

processor;

Memory for storing processor executable instructions;

Wherein, the processor is configured as a method for identifying whether any one of the above devices is located in the target area.

The embodiment of the present specification provides a scheme for identifying whether a device is located in a target area. In the preprocessing stage: based on the sample signal characteristics of the test device in the collected target area, and constructing the target area based on the sample signal characteristics Sample signal feature library; because the test equipment is always located in the target area at this stage, the sample signal features at each position of the target area can be collected. In this way, in the subsequent identification, as long as the signal characteristics of the device to be identified are consistent with the sample signal characteristics in the sample signal feature library, it can be explained that the position of the device to be identified is consistent with the position of the sample signal feature compared, and because of the test The device is always in the target area, so the device to be identified is also in the target area.

It is worth noting that the solution provided in this manual, on the one hand, because the test equipment and the equipment to be identified are both affected by the same environmental factors, the difference in the comparison is only reflected in the location difference, thus avoiding the impact of various environmental factors; The recognition accuracy is high. On the other hand, the pre-processing stage only needs to mark positive samples (that is, signal features located in the target area), and does not need to pay attention to the negative samples (that is, signal features located outside the target area). It is simple and quick to implement.

BRIEF DESCRIPTION

1 is a flowchart of a method for identifying whether a device is located in a target area according to an embodiment of the present specification;

2 is a schematic diagram of a moving track of a test device provided by an embodiment of this specification;

3 is a hardware structure diagram of a device for identifying whether a device is located in a target area according to an embodiment of the present specification;

4 is a schematic block diagram of a device for identifying whether a device is located in a target area according to an embodiment of the present specification.

detailed description

Exemplary embodiments will be described in detail here, examples of which are shown in the drawings. When referring to the drawings below, unless otherwise indicated, the same numerals in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this specification. Rather, they are merely examples of devices and methods consistent with some aspects of this specification as detailed in the appended claims.

The terminology used in this specification is for the purpose of describing particular embodiments only, and is not intended to limit this specification. The singular forms "a", "said" and "the" used in this specification and the appended claims are also intended to include most forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" as used herein refers to and includes any or all possible combinations of one or more associated listed items.

It should be understood that although the terms first, second, third, etc. may be used to describe various information in this specification, the information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this specification, the first information may also be referred to as second information, and similarly, the second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "when" or "in response to a determination".

In order to solve the above problems, this specification provides a method for identifying whether the device is located in the target area. The following can be introduced with reference to the example shown in FIG. 1. The method can be applied to the server that identifies whether the device is located in the target area Server), the method may include the following steps:

Step 110: Collect the sample signal features of the test equipment in the target area, and construct a sample signal feature library of the target area.

In the pre-processing stage, the server can collect the sample signal features of the test device in the target area, and construct a sample signal feature library of the target area based on the sample signal features of the test device.

In this embodiment, the tester may hold the test device and move back and forth within the target area, and the movement track may include all positions of the target area.

FIG. 2 is a schematic diagram of the movement trajectory of the test device in the target area provided by the specification. The range of the target area 21 in FIG. 2 is a circular area, and a device signal acquisition device 22 is provided in the target area 21; the tester can walk around the target area 21 with the test device 23 in hand to form a moving trajectory 24 . Please note that the movement trajectory 24 cannot exceed the range of the target area 21, and the area involved in the movement trajectory 24 preferably covers all the range areas of the target area 21.

In an embodiment, the device signal collection device 22 may include a WiFi probe.

The WiFi probe is a device that can collect signals from surrounding devices. Specifically, as long as a WiFi device is within the listening range of the WiFi probe, when this WiFi device (whether it is a terminal, router, or other WiFi device) sends any frame, no matter which receiver it is sent to, WiFi The probe can be intercepted; and the WiFi probe can also analyze some information of the MAC layer and the physical layer of this frame, such as the MAC address, frame type, and signal strength of the sending and receiving devices.

Please note that the probe is transparent to surrounding WiFi devices. The probe does not need to have any interaction with surrounding devices, and itself does not need to emit any WiFi signal. In other words, as long as the device's WiFi is turned on, whether it is connected to a WiFi hotspot or not, it can be detected by the WiFi probe.

It should be noted that the WiFi probe can only collect the detected MAC address of the device and other MAC layer information, such as the target MAC, transmission channel, frame type, signal strength, connected hotspot name, etc .; some of the devices Identity information such as mobile phone numbers and information related to Internet access (including QQ numbers, WeChat, etc.) cannot be collected by WiFi probes; this avoids exposing user privacy.

In one case, the WiFi probe may be an integrated router AP, that is, the router AP may provide WiFi connection in the surrounding area, and may also collect signal characteristics of devices in the surrounding area.

In another case, the WiFi probe may be an independent device that separately collects signal characteristics of devices in the surrounding area.

Step 120: Collect signal characteristics of the device to be identified.

Taking a WiFi probe as an example, the sample signal characteristics of the test equipment collected in the target area in the above steps may specifically include:

Collect the sample signal characteristics of the test equipment in the target area through the WiFi probe;

Correspondingly, the step 120 collecting signal characteristics of the device to be identified may specifically include:

Collect the signal characteristics of the device to be identified through a WiFi probe.

The beginning of this step is the formal identification stage, which is used to identify whether the device to be identified is located in the target area.

The device to be identified may refer to a device newly detected by the WiFi probe, which has not yet identified whether it is located in the target area; therefore, subsequent steps are required to determine whether the device to be identified is located in the target area.

In an embodiment, after the step 120, the method further includes:

Acquiring the MAC address of the device to be identified corresponding to the signal characteristic;

The signal characteristics of the same MAC address are determined as the signal characteristics of the same device to be identified.

In this embodiment, in practical applications, the server generally collects the signal characteristics of multiple devices to be identified at the same time, so it is necessary to distinguish the signal characteristics of these different devices; each device has a unique MAC address, so By identifying the MAC address of the device corresponding to the signal feature, and combining the signal features based on the MAC address, the signal feature of the same MAC address is determined as the signal feature of the same device to be identified.

Step 130: Compare the signal features of the device to be identified with the sample signal feature library of the target area.

In an embodiment, the signal features include signal feature vectors;

The comparison of the signal characteristics of the device to be identified with the sample signal characteristic library of the target area specifically includes:

Calculating the similarity between the signal feature vector of the device to be identified and the sample signal feature vector in the sample signal feature library of the target area;

When any calculated similarity exceeds a threshold, it is determined that the comparison is successful.

In an embodiment, the vector refers to a quantity with direction and magnitude, so the signal feature vector also has magnitude and direction. When comparing signal feature vectors, you can compare whether the size and direction of the signal feature vectors are similar or the same as the size and direction of the sample signal feature vectors.

In an embodiment, the calculating the similarity may refer to calculating the Euclidean distance between two vectors; that is, calculating the Euclidean distance between the signal feature vector of the device to be identified and the sample signal feature vector; when there is any calculation When the Euclidean distance is less than the threshold, the comparison is successful.

Step 140: When the comparison is successful, determine that the device to be identified is located in the target area.

The embodiment of the present specification provides a scheme for identifying whether a device is located in a target area. In the preprocessing stage: based on the sample signal characteristics of the test device in the collected target area, and based on the sample signal characteristics, the Sample signal feature library; because the test equipment is always located in the target area at this stage, the sample signal features at each position of the target area can be collected. In this way, in the subsequent identification, as long as the signal characteristics of the device to be identified are consistent with the signal characteristics in the sample signal feature library, it can be explained that the position of the device to be identified is consistent with the position of the sample signal feature compared, and because of the test equipment It is always in the target area, so the device to be identified is also in the target area.

In an embodiment, the step 110 may specifically include:

Collect the sample signal characteristics of the test equipment at various positions in the target area;

Aggregate according to the time stamps of the sample signal features, and sample signal features of the same time stamp are aggregated into sample signal feature groups;

Store the aggregated sample signal feature group in the sample signal feature library;

Correspondingly, after step 120, the method may further include:

Aggregate according to the time stamps of the signal features, and the signal features of the same time stamp are aggregated into signal feature groups;

The step 130 may specifically include:

Compare the signal feature set with the sample signal feature set in the sample signal feature library.

In this specification, the time stamp may indicate the time interval in which the sample signal characteristics are collected. The server can continuously collect sample signal characteristics, and determine the time stamp of the sample signal characteristics according to the time interval at which the sample signal characteristics are collected.

For example, suppose the server sets a time zone every 5 seconds, that is, set a time stamp every 5 seconds; take the collected 0-5 seconds as time stamp 1, 6-10 seconds as time stamp 2; if a sample signal When the feature collection time is at the 4th second, the time stamp corresponding to the sample signal feature can be determined to be 1; if the sample signal feature collection time is at the 7th second, then the time stamp corresponding to the sample signal feature can be determined to be 2 .

Similarly, the time stamp of the signal feature of the device to be identified can also be expressed as the time interval when the signal feature is collected.

In practical applications, the position of the device to be identified may not be accurately located through the comparison of individual signal features, and positioning accuracy can be greatly improved through a continuous set of signal features. Through this embodiment, the signal feature group of the device to be identified is integrated as a whole, and compared with the sample signal special group in the sample signal feature library (the sample signal special group is also a whole). Identification accuracy.

In an embodiment, before the aggregation is performed according to the time stamps of the signal characteristics, and the signal features of the same time stamp are aggregated into the signal characteristic group, the method may further include:

The aggregation is performed according to the time stamps of the signal features, and the signal features of the same time stamp are aggregated into a signal feature group, which specifically includes:

For the signal characteristics of the same device to be identified, aggregation is performed according to the time stamps of the signal characteristics, and the signal characteristics of the same time stamp are aggregated into signal characteristic groups.

This embodiment is similar to the foregoing embodiments. In practical applications, the server generally collects the signal characteristics of multiple devices to be identified at the same time, so it is necessary to distinguish these signal characteristics belonging to different devices. Since each device has a unique MAC address, by identifying the signal characteristics corresponding to the MAC address of the device, and combining the signal characteristics based on the MAC address, the signal characteristics of the same MAC address are determined to be the same device to be identified Signal characteristics.

In an embodiment, the signal features include signal feature vectors;

The comparison between the signal feature set and the sample signal feature set in the sample signal feature library includes:

Calculating the similarity between the signal feature vector group and the sample signal feature vector group in the sample signal feature library;

In this embodiment, multiple signal features in the feature group are compared as a whole, and the similarity calculation method is implemented in the same manner as the previous embodiment; for example, the size and direction of the overall vector can be calculated; European distance.

Corresponding to the foregoing embodiment of the method for identifying whether the device is located in the target area, this specification also provides an embodiment of the method for identifying whether the device is located in the target area. The device embodiments may be implemented by software, or by hardware or a combination of hardware and software. Taking software implementation as an example, as a logical device, it is formed by reading the corresponding computer service program instructions in the non-volatile memory into the memory through the processor of the device where it is located and running. From the hardware level, as shown in FIG. 3, it is a hardware structure diagram of the device where the identification method of the device is located in the target area, except for the processor, network interface, memory, and non-volatile shown in FIG. 3. In addition to the non-volatile memory, the device where the apparatus is located in the embodiment usually depends on the actual function of the identification method of whether the device is located in the target area, and may also include other hardware, which will not be repeated here.

Please refer to FIG. 4, which is a block diagram of a device for identifying whether a device is located in a target area according to an embodiment of the present specification. The device corresponds to the embodiment shown in FIG. 1. The device includes:

The first collection unit 310 collects sample signal characteristics of the test equipment in the target area, and constructs a sample signal characteristic library of the target area;

The second collection unit 320 collects the signal characteristics of the device to be identified;

The comparison unit 330 compares the signal characteristics of the device to be identified with the sample signal characteristic library of the target area;

The identification unit 340 determines that the device to be identified is located in the target area if the comparison is successful.

Optionally, the signal features include signal feature vectors;

The comparison unit 330 specifically includes:

A calculation subunit, calculating the similarity between the signal feature vector of the device to be identified and the sample signal feature vector in the sample signal feature library of the target area;

Determine the subunit. When there is any calculated similarity exceeding the threshold, it is determined that the comparison is successful.

Optionally, after the second collection unit 320, the device further includes:

An obtaining subunit, obtaining the MAC address of the device to be identified corresponding to the signal feature;

The merging subunits determine the signal characteristics of the same MAC address as the signal characteristics of the same device to be identified.

Optionally, the first collection unit 310 specifically includes:

A collection subunit, which collects sample signal characteristics of the test equipment at various positions in the target area;

The first aggregation subunit aggregates according to the time stamps of the sample signal features, and the sample signal features of the same time stamp are aggregated into a sample signal feature group; wherein, the time stamp represents the time interval when the sample signal features are collected;

Storage subunit, storing the aggregated sample signal feature group into the sample signal feature library;

After the second collection unit 320, the device further includes:

The second aggregation subunit aggregates according to the time stamps of the signal features, and the signal features of the same time stamp are aggregated into signal feature groups;

The comparison unit 330 specifically includes:

Optionally, before the second aggregation subunit, the device further includes:

Merging subunits, determining the signal characteristics of the same MAC address as the signal characteristics of the same device to be identified;

The second aggregation subunit specifically includes:

Optionally, the signal features include signal feature vectors;

The comparison unit 330 specifically includes:

A calculation subunit, calculating the similarity between the signal feature vector group and the sample signal feature vector group in the sample signal feature library;

Optionally, the first collection unit 310 specifically includes:

The second collection unit 320 specifically includes:

The system, device, module or unit explained in the above embodiments may be specifically implemented by a computer chip or entity, or implemented by a product with a certain function. A typical implementation device is a computer, and the specific form of the computer may be a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email sending and receiving device, and a game control Desk, tablet computer, wearable device, or any combination of these devices.

For the implementation process of the functions and functions of the units in the above device, please refer to the implementation process of the corresponding steps in the above method for details, which will not be repeated here.

As for the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to the description of the method embodiments. The device embodiments described above are only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located One place, or can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution in this specification. Those of ordinary skill in the art can understand and implement without paying creative labor.

The above FIG. 4 describes the internal functional modules and structural schematics of the method for identifying whether the device is located in the target area, and the actual execution subject may be an electronic device, including:

processor;

Memory for storing processor executable instructions;

Wherein, the processor is configured to:

Collect the signal characteristics of the equipment to be identified;

Optionally, the signal features include signal feature vectors;

Optionally, after collecting the signal characteristics of the device to be identified, the method further includes:

Optionally, collecting the sample signal characteristics of the test equipment in the target area and constructing a sample signal characteristic database of the target area specifically includes:

Aggregate according to the time stamps of the sample signal features, and sample signal features of the same time stamp are aggregated into a sample signal feature group; where the time stamp represents the time interval in which the sample signal features are collected;

After the signal characteristics of the device to be identified are collected, the method further includes:

Optionally, before the aggregation is performed according to the time stamps of the signal features, and the signal features of the same time stamp are aggregated into a signal feature group, the method further includes:

Determine the signal characteristics of the same MAC address as the signal characteristics of the same device to be identified;

Optionally, the signal features include signal feature vectors;

Optionally, the sample signal characteristics of the test equipment in the collection target area specifically include:

The collecting signal characteristics of the device to be identified specifically includes:

In the above embodiments of the electronic device, it should be understood that the processor may be a central processing unit (English: Central Processing Unit, abbreviated as: CPU), or other general-purpose processors, digital signal processors (English: Digital Signal Processor , Abbreviation: DSP), application specific integrated circuit (English: Application Specific Integrated Circuit, abbreviation: ASIC), etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc., and the aforementioned memory may be a read-only memory (English: read-only memory, abbreviation: ROM), a random access memory (English) : Random access memory (RAM for short), flash memory, hard disk or solid state drive. The steps of the method disclosed in conjunction with the embodiments of the present invention may be directly embodied and executed by a hardware processor, or may be executed and completed by a combination of hardware and software modules in the processor.

The embodiments in this specification are described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the embodiment of the electronic device, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant part can be referred to the description of the method embodiment.

After considering the description and practicing the invention disclosed herein, those skilled in the art will easily think of other embodiments of the description. This specification is intended to cover any variations, uses, or adaptive changes of this specification. These variations, uses, or adaptive changes follow the general principles of this specification and include common general knowledge or common technical means in the technical field not disclosed in this specification. . The description and examples are to be considered exemplary only, and the true scope and spirit of this description are pointed out by the following claims.

It should be understood that this specification is not limited to the precise structure that has been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of this description is limited only by the appended claims.

Claims

A method for identifying whether a device is located in a target area, the method includes:

Collect the sample signal characteristics of the test equipment in the target area and construct a sample signal characteristic library of the target area;

Collect the signal characteristics of the equipment to be identified;

Comparing the signal characteristics of the device to be identified with the sample signal characteristic library of the target area;

If the comparison is successful, it is determined that the device to be identified is located in the target area.
The method according to claim 1, wherein the signal characteristic comprises a signal characteristic vector;

The comparison of the signal characteristics of the device to be identified with the sample signal characteristic library of the target area specifically includes:

Calculating the similarity between the signal feature vector of the device to be identified and the sample signal feature vector in the sample signal feature library of the target area;

When any calculated similarity exceeds a threshold, it is determined that the comparison is successful.
The method according to claim 1, after the signal characteristics of the device to be identified are collected, the method further comprises:

Acquiring the MAC address of the device to be identified corresponding to the signal characteristic;

The signal characteristics of the same MAC address are determined as the signal characteristics of the same device to be identified.
According to the method of claim 1, the collecting the sample signal characteristics of the test equipment in the target area and constructing the sample signal characteristic library of the target area specifically includes:

Collect the sample signal characteristics of the test equipment at various positions in the target area;

Aggregate according to the time stamps of the sample signal features, and sample signal features of the same time stamp are aggregated into sample signal feature groups;

Store the aggregated sample signal feature group in the sample signal feature library;

After the signal characteristics of the device to be identified are collected, the method further includes:

Aggregate according to the time stamps of the signal features, and the signal features of the same time stamp are aggregated into signal feature groups;

The comparison of the signal characteristics of the device to be identified with the sample signal characteristic library of the target area specifically includes:

Compare the signal feature set with the sample signal feature set in the sample signal feature library.
The method according to claim 4, before the aggregation according to the time stamps of the signal characteristics and the aggregation of the signal characteristics of the same time stamp into the signal characteristic group, the method further comprises:

Acquiring the MAC address of the device to be identified corresponding to the signal characteristic;

Determine the signal characteristics of the same MAC address as the signal characteristics of the same device to be identified;

The aggregation is performed according to the time stamps of the signal features, and the signal features of the same time stamp are aggregated into a signal feature group, which specifically includes:

For the signal characteristics of the same device to be identified, aggregation is performed according to the time stamps of the signal characteristics, and the signal characteristics of the same time stamp are aggregated into signal characteristic groups.
The method according to claim 4, wherein the signal features include signal feature vectors;

The comparison between the signal feature set and the sample signal feature set in the sample signal feature library includes:

Calculating the similarity between the signal feature vector group and the sample signal feature vector group in the sample signal feature library;

When any calculated similarity exceeds a threshold, it is determined that the comparison is successful.
According to the method of claim 1, the sample signal characteristics of the test equipment in the acquisition target area specifically include:

Collect the sample signal characteristics of the test equipment in the target area through the WiFi probe;

The collecting signal characteristics of the device to be identified specifically includes:

Collect the signal characteristics of the device to be identified through a WiFi probe.
An apparatus for identifying whether a device is located in a target area, the apparatus includes:

The first collection unit collects sample signal characteristics of the test equipment in the target area, and constructs a sample signal characteristic library of the target area;

The second collection unit collects the signal characteristics of the device to be identified;

A comparison unit, comparing the signal characteristics of the device to be identified with the sample signal characteristic library of the target area;

The identification unit determines that the device to be identified is located in the target area when the comparison is successful.
The apparatus according to claim 8, wherein the signal characteristic comprises a signal characteristic vector;

The comparison unit specifically includes:

A calculation subunit, calculating the similarity between the signal feature vector of the device to be identified and the sample signal feature vector in the sample signal feature library of the target area;

Determine the subunit. When there is any calculated similarity exceeding the threshold, it is determined that the comparison is successful.
The apparatus according to claim 8, after the second collection unit, the apparatus further comprises:

An obtaining subunit, obtaining the MAC address of the device to be identified corresponding to the signal feature;

The merging subunits determine the signal characteristics of the same MAC address as the signal characteristics of the same device to be identified.
The apparatus according to claim 8, wherein the first collection unit specifically includes:

A collection subunit, which collects sample signal characteristics of the test equipment at various positions in the target area;

The first aggregation subunit aggregates according to time stamps of sample signal features, and sample signal features of the same time stamp are aggregated into sample signal feature groups;

Storage subunit, storing the aggregated sample signal feature group into the sample signal feature library;

After the second collection unit, the device further includes:

The second aggregation subunit aggregates according to the time stamps of the signal features, and the signal features of the same time stamp are aggregated into signal feature groups;

The comparison unit specifically includes:

Compare the signal feature set with the sample signal feature set in the sample signal feature library.
The apparatus according to claim 11, before the second aggregation subunit, the apparatus further comprises:

An obtaining subunit, obtaining the MAC address of the device to be identified corresponding to the signal feature;

Merging subunits, determining the signal characteristics of the same MAC address as the signal characteristics of the same device to be identified;

The second aggregation subunit specifically includes:

For the signal characteristics of the same device to be identified, aggregation is performed according to the time stamps of the signal characteristics, and the signal characteristics of the same time stamp are aggregated into signal characteristic groups.
The apparatus according to claim 11, wherein the signal features include signal feature vectors;

The comparison unit specifically includes:

A calculation subunit, calculating the similarity between the signal feature vector group and the sample signal feature vector group in the sample signal feature library;

Determine the subunit. When there is any calculated similarity exceeding the threshold, it is determined that the comparison is successful.
The apparatus according to claim 8, wherein the first collection unit specifically includes:

Collect the sample signal characteristics of the test equipment in the target area through the WiFi probe;

The second collection unit specifically includes:

Collect the signal characteristics of the device to be identified through a WiFi probe.
An electronic device, including:

processor;

Memory for storing processor executable instructions;

Wherein the processor is configured as the method according to any one of claims 1-7 above.