CN114758476A - Activity information monitoring method, device, system, equipment and storage medium - Google Patents

Abstract

The application provides an activity information monitoring method, an apparatus, a system, equipment and a storage medium, wherein the method comprises the following steps: receiving a plurality of probe beams of a beam generator for periodically scanning a target environment, wherein the beam directions of the plurality of probe beams are different, and a moving object is included in the target environment; acquiring current channel characteristics in the target environment according to the plurality of detection beams; determining difference information between the current channel characteristics and original channel characteristics in the target environment, wherein the original channel characteristics are channel characteristics when no moving object exists in the target environment; and monitoring whether the moving object moves or not according to the difference information. The method and the device have the advantages that the active information of the moving object is detected by actively and periodically emitting the detection beams in different directions in the target environment, the problem of signal dead angles caused by uneven distribution of wireless signals can be greatly reduced, and the reliability and the accuracy of activity detection are improved.

Description

Activity information monitoring method, apparatus, system, device and storage medium

technical field

The present application relates to the field of communication technologies, and in particular, to a method, apparatus, system, device and storage medium for monitoring activity information.

Background technique

With the aging of society, home care for the elderly has become a focus of attention. Many elderly people fall at home alone, endangering their lives and health because they are not detected and rescued in time. Existing monitoring methods include wearing sensors and installing cameras in the home, both of which have serious shortcomings. Wearing sensors will fail because the elderly do not carry sensors with them; the installation of camera equipment at home will be limited by objects blocking and insufficient light. In addition, the camera has the risk of network intrusion, resulting in privacy leakage.

In this case, the technology of human activity perception using WiFi network has been paid much attention. When someone moves indoors, the human body will reflect and scatter the wireless signal, causing the original signal propagation environment to change. These disturbances will be reflected in the OFDM (Orthogonal Frequency Division Multiplexing, Orthogonal Frequency Division Multiplexing) subcarriers received by the receiver. In terms of amplitude and phase changes, and different motion states of the human body have different characteristics of OFDM sub-carrier disturbance, these disturbance characteristics can be extracted by the deep learning method of artificial intelligence, so as to identify various motion states of the human body, such as walking, sitting and fall. This technology is called Channel State Information (CSI) technology. It has been reported that the existing WiFi network is used to realize the perception of human activity, which makes the WiFi network not only used for communication interconnection, but also applied to Family elder care.

Existing wireless sensing methods based on commercial WiFi networks still have shortcomings. Due to the occlusion of wireless signals by indoor walls and various furniture items, the indoor signal distribution is uneven, and there are many places with weak signals. When the human body moves to these places, the reflected and stray signals are weak and easily overwhelmed by background noise. In addition, the WiFi network is gradually evolving to the WiFi 6 network in the 5G frequency band. Compared with the 2.4G WiFi, the coverage of the WiFi 6 network is smaller, and after using the MU MIMO technology, the wireless signals are more concentrated in some specific beam directions, resulting in a more distributed indoor wireless signal. Non-uniform, more prone to signal dead angle. However, human activity perception requires high-precision CSI signal change characteristics, and weak human body reflection signals lead to false alarms and missed alarms in CSI detection.

SUMMARY OF THE INVENTION

The purpose of the embodiments of the present application is to provide an activity information monitoring method, device, system, equipment and storage medium, which can detect the activity information of a moving object by actively and periodically transmitting detection beams in different directions into the target environment, which can greatly Reduce the signal dead angle problem caused by uneven distribution of wireless signals, and improve the reliability and accuracy of activity detection.

A first aspect of the embodiments of the present application provides a method for monitoring activity information, including: receiving a plurality of detection beams that periodically scan a target environment by a beam generator, wherein the beam directions of the multiple detection beams are different, and the The target environment includes moving objects; according to the plurality of sounding beams, the current channel characteristics in the target environment are acquired; the difference information between the current channel characteristics and the original channel characteristics in the target environment is determined, wherein the The original channel feature is the channel feature when there is no moving object in the target environment; whether the moving object moves is monitored according to the difference information.

In one embodiment, a scanning period for periodically scanning the target environment includes: a normal communication time slot and a beam scanning time slot that are independent of each other.

In an embodiment, before the receiving a plurality of detection beams that periodically scan the target environment, the method further includes: when there is no moving object in the target environment, receiving a periodic scan of the target environment. Multiple learning beams, wherein the beam directions of the multiple learning beams are different; and acquiring the original channel characteristics in the target environment according to the multiple learning beams.

In one embodiment, the plurality of learning beams are beams sent out by the beam generator in a plurality of beam scanning time slots, wherein each of the beam scanning time slots sends out a plurality of the learning beams; the Acquiring the original channel characteristics in the target environment according to the multiple learning beams includes: determining the transmission channel characteristics corresponding to each beam scanning time slot according to the channel state information corresponding to the multiple learning beams , and the obtained channel feature set is used as the original channel feature in the target environment.

In one embodiment, monitoring whether the moving object moves according to the difference information includes: judging whether the maximum value of the difference information is greater than a preset threshold; when the maximum value of the difference information is greater than the preset threshold When the moving object is determined to move, and the beam generator is notified of the direction of the target beam, the direction of the target beam is the direction of the detection beam corresponding to the maximum value of the difference information; multiple tracking beams emitted by the device in the target environment; determining whether the moving object moves according to the multiple tracking beams.

In one embodiment, the plurality of tracking beams at least include: a target beam in the direction of the target beam, a first tracking beam whose angle with the direction of the target beam is a first preset angle, and a first tracking beam with the direction of the target beam. The direction included angle of the target beam is a second tracking beam with a second preset angle; the determining whether the moving object moves according to the multiple tracking beams includes: channel state information corresponding to the multiple tracking beams , determine which direction of the multiple tracking beams has the largest beam disturbance; if the beam disturbance of the target beam is the largest, it is determined that the moving object has not moved; if the beam disturbance of the first tracking beam is the largest, determine the The moving object moves in the direction of the first tracking beam; if the beam disturbance of the second tracking beam is the largest, it is determined that the moving object moves in the direction of the second tracking beam.

In an embodiment, the determining whether the moving object moves according to the multiple tracking beams further includes: when the beam with the largest disturbance is not the target beam, sending a beam adjustment request to the beam generator, so that the beam generator transmits the tracking beam according to the beam with the largest current beam disturbance in the next beam scanning time slot.

In one embodiment, acquiring the current channel characteristics in the target environment according to the multiple sounding beams includes: calculating the current channel characteristics in the target environment by using the following formula:

Wherein, h _j is the current channel characteristics corresponding to the multiple probe beams under the ith beam scanning time slot, N is the number of waves of the multiple probe beams, N is a positive integer; M is each The number of subcarriers included in the sounding beam, M is a positive integer; CSI _N,M is the channel state information corresponding to the Mth subcarrier of the Nth sounding beam.

In one embodiment, the difference information is an amplitude difference; the determining the difference information between the current channel feature and the original channel feature in the target environment includes: calculating the amplitude difference by using the following formula:

为第i个波束扫描时隙下，所述原始信道特征中第p个所述探测波束的子载波对应的平均信道状态信息；δ_p为第i个波束扫描时隙下，第p个所述探测波束方向上的所述当前信道特征与所述原始信道特征之间的幅度差异。Wherein, CSI _p,j is the channel state information corresponding to the jth subcarrier of the pth sounding beam under the ith beam scanning time slot, j∈(0, M);

is the average channel state information corresponding to the subcarrier of the p-th probe beam in the original channel characteristics under the ith beam scanning time slot; δ _p is the ith beam scanning time slot, the p-th A magnitude difference between the current channel characteristic and the original channel characteristic in the direction of the detection beam.

A second aspect of an embodiment of the present application provides an activity information monitoring device, including: a first receiving module configured to receive a plurality of detection beams used by a beam generator to periodically scan a target environment, wherein the plurality of detection beams The beam direction of the target environment is different, and the target environment includes moving objects; the first acquisition module is used to obtain the current channel characteristics in the target environment according to the plurality of detection beams; the determination module is used to determine the current channel characteristics. Difference information with the original channel feature in the target environment, wherein the original channel feature is the channel feature when there is no moving object in the target environment; a monitoring module, configured to monitor the Whether the moving object has moved.

In one embodiment, a scanning period for periodically scanning the target environment includes: a normal communication time slot and a beam scanning time slot that are independent of each other.

In one embodiment, the method further includes: a second receiving module, configured to receive the target environment when there is no moving object in the target environment before receiving the plurality of detection beams that periodically scan the target environment. A plurality of learning beams that periodically scan the target environment, wherein the beam directions of the plurality of learning beams are different; a second acquisition module is used to secondly acquire all the information in the target environment according to the plurality of learning beams Describe the original channel characteristics.

In one embodiment, the plurality of learning beams are beams sent out by the beam generator in a plurality of beam scanning time slots, wherein each of the beam scanning time slots sends out a plurality of the learning beams; the The second acquisition module is configured to: determine the corresponding transmission channel feature under each of the beam scanning time slots according to the channel state information corresponding to the multiple learning beams, and the obtained channel feature set is used as the channel feature set in the target environment. original channel characteristics.

In one embodiment, the monitoring module is configured to: determine whether the maximum value of the difference information is greater than a preset threshold; when the maximum value of the difference information is greater than the preset threshold, determine that the moving object moves , and notify the beam generator of the direction of the target beam, the direction of the target beam is the direction of the detection beam corresponding to the maximum value of the difference information; a plurality of tracking beams; determining whether the moving object moves according to the plurality of tracking beams.

In one embodiment, the plurality of tracking beams at least include: a target beam in the direction of the target beam, a first tracking beam whose angle with the direction of the target beam is a first preset angle, and a first tracking beam with the direction of the target beam. The direction included angle of the target beam is a second tracking beam with a second preset angle; the monitoring module is further configured to: according to the channel state information corresponding to the multiple tracking beams, determine which direction of the multiple tracking beams The beam disturbance is the largest; if the beam disturbance of the target beam is the largest, it is determined that the moving object does not move; if the beam disturbance of the first tracking beam is the largest, it is determined that the moving object occurs in the direction of the first tracking beam Move; if the beam disturbance of the second tracking beam is the largest, it is determined that the moving object moves in the direction of the second tracking beam.

In one embodiment, the monitoring module is further configured to send a beam adjustment request to the beam generator when the maximum beam disturbance is not the target beam, so that the beam generator scans the next beam in the next time slot. The tracking beam is transmitted according to the beam with the largest current beam disturbance.

In one embodiment, the first obtaining module is configured to: calculate the current channel characteristics in the target environment using the following formula:

Wherein, h _j is the current channel characteristics corresponding to the multiple probe beams under the ith beam scanning time slot, N is the number of waves of the multiple probe beams, N is a positive integer; M is each The number of subcarriers included in the sounding beam, M is a positive integer; CSI _N,M is the channel state information corresponding to the Mth subcarrier of the Nth sounding beam.

In one embodiment, the difference information is an amplitude difference; the determining module is configured to: calculate the amplitude difference using the following formula:

为第i个波束扫描时隙下，所述原始信道特征中第p个所述探测波束的子载波对应的平均信道状态信息；δ_p为第i个波束扫描时隙下，第p个所述探测波束方向上的所述当前信道特征与所述原始信道特征之间的幅度差异。Wherein, CSI _p,j is the channel state information corresponding to the jth subcarrier of the pth sounding beam under the ith beam scanning time slot, j∈(0, M);

is the average channel state information corresponding to the subcarrier of the p-th probe beam in the original channel characteristics under the ith beam scanning time slot; δ _p is the ith beam scanning time slot, the p-th A magnitude difference between the current channel characteristic and the original channel characteristic in the direction of the detection beam.

A third aspect of the embodiments of the present application provides an activity information monitoring system, including: a beam generator configured to periodically transmit a plurality of detection beams to a target environment, wherein the beam directions of the plurality of detection beams are different, and the The target environment includes moving objects; the activity detector is installed in the target environment and used to receive the plurality of sounding beams, and use the activity information monitoring method according to any one of claims 1-9 to monitor Whether the moving object has moved.

A fourth aspect of the embodiments of the present application provides an electronic device, including: a memory for storing a computer program; and a processor for executing the method of the first aspect of the embodiments of the present application and any one of the embodiments thereof.

A fifth aspect of an embodiment of the present application provides a non-transitory electronic device-readable storage medium, including: a program, when run by an electronic device, causes the electronic device to execute the first aspect of the embodiment of the present application and any of the above. The method of an embodiment.

The activity information monitoring method, device, system, device and storage medium provided by the present application periodically transmit detection beams in different directions into the target environment through the wave velocity generator, and then according to the channel characteristics of the received multiple detection beams and the target The original channel characteristics of the environment are compared, the difference information between the two is determined, and the activity information of the moving object is detected based on the difference information. In this way, when the beam is detected actively, there will be no phenomenon that depends on the strength distribution of the wireless signal in the prior art. , which can greatly reduce the signal dead angle problem caused by the uneven distribution of wireless signals, and improve the reliability and accuracy of activity detection.

Description of drawings

In order to explain the technical solutions of the embodiments of the present application more clearly, the following briefly introduces the accompanying drawings that need to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, therefore It should not be regarded as a limitation of the scope. For those of ordinary skill in the art, other related drawings can also be obtained from these drawings without any creative effort.

FIG. 1 is a schematic structural diagram of an electronic device according to an embodiment of the application;

2A is a schematic structural diagram of an activity information monitoring system according to an embodiment of the application;

2B is a schematic structural diagram of an activity information monitoring system according to an embodiment of the application;

2C is a schematic diagram of a timing relationship between a live normal service process and a scanning time slot according to an embodiment of the present application;

3 is a schematic flowchart of a method for monitoring activity information according to an embodiment of the present application;

4 is a schematic flowchart of a method for monitoring activity information according to an embodiment of the present application;

FIG. 5 is a schematic structural diagram of an activity information monitoring apparatus according to an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application. In the description of the present application, the terms "first", "second" and the like are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

As shown in FIG. 1 , this embodiment provides an electronic device 1 , including: at least one processor 11 and a memory 12 . In FIG. 1 , one processor is used as an example. The processor 11 and the memory 12 are connected by the bus 10 . The memory 12 stores instructions that can be executed by the processor 11, and the instructions are executed by the processor 11, so that the electronic device 1 can execute all or part of the processes of the methods in the following embodiments, so as to periodically send the instructions to the target environment by actively and periodically. Sending detection beams in different directions to detect the activity information of moving objects can greatly reduce the signal dead angle problem caused by uneven distribution of wireless signals, and improve the reliability and accuracy of activity detection.

In one embodiment, the electronic device 1 may be a gateway device, a mobile phone, a tablet computer, a notebook computer, a desktop computer, or a large computing system composed of multiple computers.

Please refer to FIG. 2A, which is an activity information monitoring system 200 according to an embodiment of the application, including: a beam generator 201 and an activity detector 202, wherein the beam generator 201 is used to periodically transmit a plurality of detection beams to the target environment, The beam directions of the multiple detection beams are different, and the target environment includes moving objects. The activity detector 202, installed in the target environment, is used for receiving a plurality of sounding beams, and adopts all or part of the process of the method in the following embodiments to monitor whether the moving object moves. The target environment can be a specified indoor scene, such as a room. The moving object can be a living creature, such as a human or an animal, or a device that can perform mechanical activities, such as an intelligent robot. The beam generator 201 can be implemented based on a wireless communication device, for example, the beam generator 201 can be implemented by a WiFi access point (Access Point, AP for short), and the activity detector 202 can be implemented by a device accessing the wireless network through the WiFi access point. .

As shown in FIG. 2B , it is assumed that the WiFi access point is used as the beam generator 201, and the client device that accesses the wireless network through the WiFi access point is used as the activity detector 202. Taking the “fall” of human activity as the monitoring object as an example, The activity information monitoring system may specifically include: a WiFi beam generator (WiFi6Beam Generator, WBG for short) and a human fall detector (Human Fall Detector, HFD for short).

The WBG adds a beam scan control unit (Beam Scan Controller, BSC for short) to a WiFi6 access point (Access Point, AP for short).

HFD is formed by adding a Fall Recognition Unit (FRU) to the WiFi6 client (Station).

Under the control of the BSC, the AP on the WBG side scans the target environment with a directional sounding beam in a specific time slot according to a certain period. On the HFD side, the Station is responsible for receiving WiFi signals, obtaining physical layer symbols through signal processing, and sending them to the FRU for processing. The FRU performs pattern recognition on the input signal to determine whether a fall event occurs. The message interaction between the human body fall detector HFD and WBG is carried out through WiFi communication.

In an embodiment, a scanning period for periodically scanning the target environment includes: a normal communication time slot and a beam scanning time slot that are independent of each other.

In practical scenarios, in order to improve the sensitivity and reliability of system perception, the beam generator WBG adds a dedicated scanning time slot in addition to the normal communication process. In the beam scanning time slot, the AP is not used for normal WiFi communication services, that is, it does not initiate various uplink and downlink communication services, and only serves as a probe signal source for beam directional transmission. The scanning period Tall and the beam scanning time slot length Tscan are configured by the BSC to the AP.

As shown in FIG. 2C , it is a time sequence relationship diagram of a normal business process and a beam scanning time slot, scanning is performed once in each cycle T _all , T _com is the normal communication duration, and T _scan is the duration of one scan. The AP sends out a directional beam in each beam scanning time slot, and the sent signal is received and processed by the human body fall detector HFD through the direct line of sight or the reflection path of the object.

The existing sensing method is to detect the disturbance of human activities to the normal communication activities of the WiFi network, and there will be signal fluctuations caused by various factors in the normal communication process, such as the increase or decrease of access devices, changes in device locations, changes in communication rates and transmission. The adjustment of the beam direction, etc., all affect the accuracy of human activity detection. However, this embodiment suspends normal communication services when detecting human activity is possible, which improves the detection accuracy and reliability.

The activity information monitoring method according to the embodiment of the present application is described in further detail below with reference to the legends.

Please refer to FIG. 3 , which is an activity information monitoring method according to an embodiment of the present application. The method can be executed by the electronic device 1 shown in FIG. 1 as an activity monitor, and can be applied to the activity information shown in FIGS. 2A-2C . In the monitoring system scenario, the activity information of moving objects can be detected by actively and periodically transmitting detection beams in different directions into the target environment, which can greatly reduce the problem of signal dead spots caused by uneven distribution of wireless signals and improve the reliability of activity detection. sex and accuracy. The method includes the following steps:

Step 301: Receive multiple probe beams that the beam generator periodically scans the target environment.

In this step, the beam directions of the multiple detection beams are different, and the target environment includes a moving object, and the moving object may be a person or an animal. Suppose the target environment is a room and the moving object is an old man in the room. In order to monitor the activities of the elderly in real time, the room can be periodically scanned by the beam generator, that is, multiple probe beams in different directions are periodically transmitted into the room by the beam generator.

Step 302: Acquire current channel characteristics in the target environment according to multiple sounding beams.

In this step, the detection beam will be interfered by objects in the room during the propagation process in the room, and the transmission paths of the detection beam in different directions are different. The sounding beams have characteristics corresponding to the transmission channels in their respective directions. The activity detector can analyze the channel characteristics of the received sounding beams to obtain the current channel characteristics corresponding to each sounding beam.

Step 303: Determine the difference information between the current channel feature and the original channel feature in the target environment.

In this step, the original channel feature is the channel feature when there is no moving object in the target environment. That is to say, the original channel feature is the channel feature in an unoccupied room, and the original channel feature when there is no one in the room can be acquired by performing periodic beam scanning on the unoccupied room for several times in advance. Since the beam propagation process is interfered by objects on the propagation path, the beam generator sends out the same detection beam scan under two conditions of people and no people in the same room, and the detection beam propagation characteristics received by the activity detector will be different. The difference can be represented by the difference information between the current channel feature corresponding to when there are people in the room and the original channel feature information corresponding to when there is no one in the room. However, since the channel characteristics in this embodiment are obtained based on a specific beam scanning process, more accurate channel difference information can be obtained.

Step 304: Monitor whether the moving object moves according to the difference information.

In this step, the difference information between the current channel feature corresponding to when there are people in the room and the original channel feature information corresponding to when there is no one in the room can accurately represent the behaviors of moving objects in the room. The behavior of moving objects in the target environment can be accurately detected through the channel feature difference information obtained by the beam scanning method.

The above activity information monitoring method uses the wave velocity generator to periodically transmit detection beams in different directions into the target environment, and then compares the channel characteristics of the received multiple detection beams with the original channel characteristics of the target environment to determine the relationship between the two. Difference information, based on the difference information to detect the activity information of the moving object, in this way, when the beam is detected actively, there is no phenomenon that depends on the distribution of the strength of the wireless signal in the prior art, which can greatly reduce the uneven distribution of the wireless signal. Signal dead angle problem, improve the reliability and accuracy of behavioral activity detection.

In one embodiment, taking a person as a moving object as an example, the human activity monitoring process can be divided into three stages: 1. The learning process of the unmanned environment. 2. Human activity tracking process. 3. Fall detection alarm process. The activity information monitoring method according to the embodiment of the present application is described in further detail below with reference to the legends.

Please refer to FIG. 4 , which is an activity information monitoring method according to an embodiment of the present application. The method can be executed by the electronic device 1 shown in FIG. 1 as an activity monitor, and can be applied to the activity information shown in FIGS. 2A-2C . In the monitoring system scenario, the activity information of moving objects can be detected by actively and periodically transmitting detection beams in different directions into the target environment, which can greatly reduce the problem of signal dead spots caused by uneven distribution of wireless signals and improve the reliability of activity detection. sex and accuracy. The method includes the following steps:

Step 401: When there is no moving object in the target environment, receive a plurality of learning beams that periodically scan the target environment.

In this step, the beam directions of the multiple learning beams are different, and the multiple learning beams are beams sent by the beam generator in multiple beam scanning time slots, wherein each beam scanning time slot sends multiple learning beams.

First, the learning process of the unmanned environment is carried out, that is, the familiarization process of the activity information monitoring system to the wireless transmission channel of the unmanned room. Taking the activity information monitoring system shown in Figure 2B as an example, before performing periodic scanning, the WBG transmits the scanning beam (ie learning beam) parameters to the human body fall detector HFD through the WiFi connection, and the transmitted parameters include at least: 1. Scanning beam number N. 2. The start time of the scan time slot Tscan. 3. Scanning period length Tall. 4. The number of scan cycles m required to complete one room scan, whereby the HFD can obtain in advance the number of beams sent by AP in each scan time slot and the direction of each beam.

The WiFi6 AP uses a 20MHz bandwidth OFDMA (Orthogonal Frequency Division Multiple Access) signal as a learning beam for transmission in each scanning time slot. The OFDMA signal includes N RU (Resource Unit, resource unit), each An RU consists of M subcarriers, and each RU transmits simultaneously using a different beam (Beam) direction.

下一扫描时隙所有波束方向旋转

角度，即第i+1扫描时隙N个波束方向表示为

再下一个扫描时隙所有波束方向继续旋转

角度，如此经过m＝[K/N](表示K/N的取整)次扫描后完成一次对整个房间的波束扫描，每次扫描，人体跌落检测器HFD的Station单元接收N个波束的信号。Let the N beam directions of the i-th scanning time slot be expressed as

Rotation of all beam directions for the next scan slot

The angle, that is, the N beam direction of the i+1th scanning slot is expressed as

All beam directions continue to rotate in the next scan slot

angle, so after m=[K/N] (representing the rounding of K/N), a beam scan of the entire room is completed. Each scan, the Station unit of the human body fall detector HFD receives the signals of N beams .

After that, the beam scanning of the entire room can be started again, and the beam scanning of the room can be completed after m scanning time slots.

细分的从参数，K越大，波束能量将更加汇聚，扫描时间就会增加，所以实际场景中，K的选取要确保扫描波束具有足够的强度，保证探测的正确性。可以根据实际WiFi AP的天线数目，以及扫描波束宽度和扫描方向调整能力确定，此外也需要考虑目标环境的大小。The above K value will be

For the subdivision parameters, the larger the K is, the more concentrated the beam energy will be, and the scanning time will increase. Therefore, in the actual scene, the selection of K should ensure that the scanning beam has sufficient intensity to ensure the correctness of detection. It can be determined according to the number of antennas of the actual WiFi AP, as well as the scanning beam width and scanning direction adjustment ability. In addition, the size of the target environment needs to be considered.

Step 402: Acquire original channel features in the target environment according to the multiple learning beams.

In this step, the drop detector HFD can analyze the channel characteristics of the received learning beam, and obtain the corresponding original channel characteristics of the room when no one is present.

In an embodiment, step 402 may specifically include: according to the channel state information corresponding to the multiple learning beams, determining the corresponding transmission channel characteristics under each beam scanning time slot, and the obtained channel characteristic set is used as the original channel characteristics in the target environment. .

In this step, the Station unit of the drop detector HFD receives the signals of N learning beams, and each learning beam contains M subcarriers, with a total of N*M subcarriers. The symbols obtained after demodulation are processed by the FRU, and the channel state information CSI value of each subcarrier can be obtained, which is expressed by amplitude and phase. For example, the CSI of the kth subcarrier is expressed as:

where _Ak is the amplitude of the k-th sub-carrier symbol, and θ _k is the phase of the sub-carrier symbol.

The N*M CSI obtained by the ith scanning time slot FRU describe the wireless transmission channel characteristics of the time slot, which can be expressed by the transmission channel characteristic matrix h _i as:

Wherein, CSI _N,M is the channel state information corresponding to the Mth subcarrier of the Nth scanning beam. Each row in the matrix represents the channel characteristics of a beam direction, which is composed of M sub-carrier CSI values of the beam, and the entire matrix represents the characteristics of the radio channel in N beam directions in the ith scanning time slot.

然后对这些矩阵对应项进行累计平均，实现降噪滤波，最终得到该房间无人情况下稳定的原始信道特征

其中

表示对h_i的平均结果。In the learning process of the unmanned environment, after m scanning time slots WBG completes the beam scanning of the room, the wireless channel characteristics of the entire room can be expressed as: H _all = {h ₁ ,h ₂ ,...h _i ...,h _m }. This is the wireless channel characteristic matrix sequence obtained by a single room scan. In order to eliminate the influence of ambient background noise and temperature changes, multiple room scans can be used to obtain multiple _Halls , such as

Then, the corresponding items of these matrices are accumulated and averaged to realize noise reduction filtering, and finally the stable original channel characteristics when the room is unoccupied are obtained.

in

represents the average result for _hi .

Step 403: Receive multiple probe beams that the beam generator periodically scans for the target environment.

In this step, the beam directions of the multiple detection beams are different, and the target environment includes a moving object, and the moving object may be a person or an animal. Suppose the target environment is a room and the moving object is an old man in the room. In order to monitor the activities of the elderly in real time, the room can be periodically scanned by the beam generator, that is, multiple probe beams in different directions are periodically transmitted into the room by the beam generator. The transmission engineering and parameter setting of the sounding beam can similarly refer to the transmission process of the learning beam in the above step 401 .

Step 404: Acquire current channel characteristics in the target environment according to multiple sounding beams. For details, refer to the description of step 302 in the above embodiment.

In an embodiment, based on the example of step 402, the Station unit of the drop detector HFD receives the signals of N learning beams, and each learning beam includes M subcarriers, for a total of N*M subcarriers. The method of calculating the original channel characteristics in step 402 can be used to calculate the current channel characteristics in the target environment by using formula (1):

Here, h _i may represent the current channel characteristics corresponding to the multiple sounding beams under the ith beam scanning time slot, N is the number of waves of the multiple sounding beams, and N is a positive integer. M is the number of subcarriers included in each sounding beam, and M is a positive integer. CSI _N,M is the channel state information corresponding to the Mth subcarrier of the Nth sounding beam.

Step 405: Determine the difference information between the current channel feature and the original channel feature in the target environment. For details, refer to the description of step 303 in the above embodiment.

In one embodiment, the difference information is an amplitude difference. Step 405 may specifically include: using the following formula to calculate the amplitude difference:

为第i个波束扫描时隙下，原始信道特征中第p个探测波束的子载波对应的平均信道状态信息。δ_p为第i个波束扫描时隙下，第p个探测波束方向上的当前信道特征与原始信道特征之间的幅度差异，即扰动幅度。Wherein, CSI _p,j is the channel state information corresponding to the jth subcarrier of the pth sounding beam under the ith beam scanning time slot, j∈(0, M).

is the average channel state information corresponding to the sub-carrier of the p-th sounding beam in the original channel characteristics under the i-th beam scanning time slot. δ _p is the amplitude difference between the current channel characteristics and the original channel characteristics in the direction of the p-th detection beam under the i-th beam scanning time slot, that is, the disturbance amplitude.

Step 406: Determine whether the maximum value of the difference information is greater than a preset threshold. If yes, go to step 407 .

In this step, the preset threshold _ΔH can be set based on the disturbance data of the wireless signal based on the movement of the human body in the space in the actual scene. For example, it can be calculated based on an empirical database when the disturbance amplitude of the wireless signal is large, indicating that there is human movement. The perturbation amplitude that just can characterize the movement of the human body is taken as the preset threshold _ΔH . In formula (2), δp represents the perturbation amplitude of the _p -th beam. The FRU unit of HFD calculates the perturbation amplitude set of N beams {δ ₁ ,δ ₂ ,δ ₃ ...δ _N }, and the maximum value in the set is equal to Compared with the preset threshold _ΔH , if the maximum value is greater than _ΔH , it means that someone has moved in the room, and go to step 407;

Step 407: Determine that the moving object moves, and notify the beam generator of the target beam direction.

In this step, the direction of the target beam is the direction of the sounding beam corresponding to the maximum value of the difference information. If the maximum value in the set sequence is greater than the preset threshold _ΔH , the WBG reports the target beam number corresponding to the maximum value. After the WBG receives the message, it stops the current beam scanning process and starts the beam tracking process.

Step 408: Receive multiple tracking beams emitted by the beam generator in the target environment.

In this step, the plurality of tracking beams at least include: a target beam in the direction of the target beam, a first tracking beam whose angle with the direction of the target beam is a first preset angle, and a direction with the target beam whose angle is a second A second tracking beam at a preset angle. For the transmission mode of the tracking beam, reference may be made to the transmission mode of the learning beam in the above step 401 .

其中

就是HFD上报扰动最大的目标波束方向，

就是无人房间扫描时波束扫描步长，

为第一追踪波束的方向，

为第二追踪波束的方向。由于AP的发送能量汇聚在定向波束上，当被人体反射和杂散时可获得较大的探测信号。In an embodiment, taking 3 tracking beams as an example, the AP divides the OFDMA subcarriers into 3 RUs under the control of the BSC, each RU includes M' subcarriers, and uses beams in different directions to transmit 3 RUs. The 3 beam directions are marked as

in

is the direction of the target beam with the largest disturbance reported by HFD,

is the beam scanning step size when scanning an unmanned room,

is the direction of the first tracking beam,

is the direction of the second tracking beam. Since the transmitted energy of the AP is concentrated on the directional beam, a larger detection signal can be obtained when it is reflected and strayed by the human body.

Step 409: Determine whether the moving object moves according to the multiple tracking beams.

In this step, the three tracking beams in step 408 can be used to continuously track the movement direction of the human body. The energy of the tracking beam is concentrated in the directional direction, and a large detection signal can be obtained when it is reflected and strayed by the human body, so it can accurately determine whether the moving object is moving.

In an embodiment, step 409 may specifically include: determining, according to the channel state information corresponding to the multiple tracking beams, which direction of the multiple tracking beams has the largest beam disturbance. If the beam disturbance of the target beam is the largest, it is determined that the moving object does not move. If the beam disturbance of the first tracking beam is the largest, it is determined that the moving object moves in the direction of the first tracking beam. If the beam disturbance of the second tracking beam is the largest, it is determined that the moving object moves in the direction of the second tracking beam.

Specifically, HFD receives signals from 3 beams, and each beam contains M' subcarriers. The activity detection matrix formed by 3*M' CSI can be expressed as:

The principle of formula (3) is the same as formula (1), wherein CSI _N,M' is the channel state information corresponding to the M'th subcarrier of the Nth scanning beam, where N=3.

The FRU of the HFD uses the formula (2) to calculate the disturbance amplitudes δ _p (p=1, 2, 3) of the three tracking beams respectively according to the information of the formula (3). If δ ₂ is the largest, it means that the detected human body does not move, then notify the beam generator to keep the current three tracking beam directions unchanged in the next scanning time slot, that is,

的追踪波束移动，则通知波束发生器下个扫描时隙3个追踪波束方向调整为

If δ ₁ is the largest, it means that the angle of the human body is

If the tracking beam moves, the beam generator will be notified to adjust the directions of the 3 tracking beams in the next scanning time slot to

的波束移动，则通知波束发生器下个扫描时隙3个追踪波束方向调整为

If δ ₃ is the largest, it means that the human body is facing the angle

If the beam moves, the beam generator will be notified to adjust the directions of the 3 tracking beams in the next scanning time slot to

In one embodiment, step 409 specifically further includes: when the maximum beam disturbance is not the target beam, sending a beam adjustment request to the beam generator, so that the beam generator transmits the beam with the maximum current beam disturbance in the next beam scanning time slot. Track the beam.

That is, in the above beam tracking process, if the direction of the tracking beam needs to be adjusted, the HFD will send a "beam adjustment request" message to the WBG, and the AP will transmit three tracking beams according to the new beam direction in the next scanning time slot under the control of the BSC. Through the above beam adjustment method, the continuous tracking of human activities is realized. Since the AP always concentrates the transmitted energy in the moving direction of the human body, the signal received by the HFD has a high signal-to-noise ratio, which improves the reliability of the system detection results.

Step 410: When the movement law of the moving object conforms to the falling law, an alarm is issued.

In this step, if a fall event occurs, the three tracking beam disturbance amplitude values δ _p (p=1, 2, 3) of the matrix h' in formula (3) in several consecutive scanning time slots during the fall of the human body The change will show a special law, and the three beam disturbance values _δp of the matrix h' in the scanning time slot after the fall are lower than the threshold _ΔL , that is, the situation of re-approaching the unmanned environment. According to the above characteristics, the FRU of HFD can identify the occurrence of falling events through artificial intelligence deep learning algorithms, such as SVM (vector machine), standard deviation, signal strength offset, signal entropy, mean absolute deviation MAD, etc. Identify the occurrence of a fall event. Then the HFD sends an alarm instruction to the WBG, and the WBG pushes the alarm information to the remote server through the Internet, notifying the family or nursing staff to come to the rescue.

The above-mentioned activity information monitoring method utilizes WiFi6 wireless network to realize indoor human activity perception, and finds fall events in time. Due to the use of directional beams that aggregate the transmit power and the beam tracking method, the activity detector can receive human disturbance signals with a higher signal-to-noise ratio. In addition, the detection is carried out in the dedicated scanning time slot, which eliminates various interferences generated in the communication process. It can be seen that the solution of this embodiment has higher sensitivity and reliability than the existing WiFi sensing method.

The activity information monitoring method of the present application is described in detail below in conjunction with examples of actual scenarios:

Assume that the WiFi beam generator WBG is placed on one side of the house, and the human fall detector HFD is placed on the other side opposite the AP against the wall. The AP of WBG has 4 external antennas, and the antenna spacing is 0.5λ (λ is the wavelength of the radio frequency signal). According to the antenna theory, the array aperture L=2λ, and the single beam 3dB lobe width is obtained as:

下一个扫描时隙波束旋转

经过3次扫描完成整个房间的无线信道扫描，得到该房屋内的原始信道特征。In the process of learning the unmanned environment using the methods from steps 401 to 402, the OFDM signal transmitted by the AP has a total of 234 subcarriers, which are divided into 6 RUs, each RU includes 39 subcarriers, and 6 RUs use 6 subcarriers. transmit in different beam directions. Let the first learning beam direction of the i-th time slot be the φ _{i th} , then the six learning beam directions are

Next scan slot beam rotation

After 3 scans, the wireless channel scanning of the entire room is completed, and the original channel characteristics in the room are obtained.

Then, according to the characteristics of human activities, combined with the scanning time slot setting method as shown in FIG. 2C , the scanning period T _all is set to be 500 milliseconds, and the scanning time slot length T _scan is 10 milliseconds. This parameter can be adjusted according to the actual traffic flow of communication services. For example, when the elderly are alone at home during the day, the indoor WiFi communication services are less, and more time can be allocated for beam scanning to shorten the scanning period, thereby improving the response speed and accuracy of system detection.

In the process of tracking the human activity in the manner from step 408 to step 409, 3 tracking beams are used, and the RU of each tracking beam includes 78 subcarriers. If the variation law of the three tracking beam disturbance amplitude values δ _p (p=1, 2, 3) of the matrix h' in several consecutive scanning time slots conforms to the fall characteristic, and the beam disturbance amplitude value δ _p of the subsequent scanning time slots is low At the trigger threshold, it is determined that a human body fall event occurs. The alarm information sent by the HFD can be pushed to the remote server through the WBG to remind the relevant personnel to come to the rescue.

In the above activity information monitoring method, the WiFi6 AP periodically sends a directional beam in a specific time slot, and adjusts the beam direction step by step to complete the scan of the room. Since the transmitted energy of the AP is concentrated on the directional beam, a larger detection signal can be obtained when it is reflected and strayed by the human body. In addition, the existing sensing method is to detect the disturbance of human activities to the normal communication activities of the WiFi network, and there will be signal fluctuations caused by various factors in the normal communication process, such as the increase or decrease of access devices, changes in device locations, changes in communication rates and The adjustment of the transmit beam direction, etc., all affect the accuracy of human activity detection. However, the embodiment of the present application suspends normal communication services when detecting human activity, designs a dedicated scanning time slot for perception detection, prevents external interference, and improves detection accuracy and reliability. Through the wireless environment learning process of beam scanning, the signal dead angle is eliminated and the measurement quality of the entire room channel environment is improved. It can effectively solve the shortcomings of the existing WiFi indoor sensing technology, use the WiFi6 network to realize indoor human activity perception, and effectively solve the nursing problem of the elderly at home alone.

Please refer to FIG. 5 , which is an activity information monitoring apparatus 500 according to an embodiment of the present application. The apparatus can be applied to the electronic device 1 shown in FIG. 1 , and can be applied to the activity information monitoring system scenarios shown in FIGS. 2A-2C . In order to detect the activity information of moving objects by actively and periodically transmitting detection beams in different directions into the target environment, it can greatly reduce the problem of signal dead spots caused by uneven distribution of wireless signals, and improve the reliability and accuracy of activity detection. sex. The device includes: a first receiving module 501, a first acquiring module 502, a determining module 503 and a monitoring module 504, and the principle relationships of each module are as follows:

The first receiving module 501 is configured to receive multiple detection beams that are periodically scanned by the beam generator on the target environment, wherein the beam directions of the multiple detection beams are different, and the target environment includes moving objects.

The first obtaining module 502 is configured to obtain the current channel characteristics in the target environment according to the multiple sounding beams.

The determining module 503 is configured to determine the difference information between the current channel feature and the original channel feature in the target environment, wherein the original channel feature is the channel feature when there is no moving object in the target environment.

The monitoring module 504 is configured to monitor whether the moving object moves according to the difference information.

In an embodiment, a scanning period for periodically scanning the target environment includes: a normal communication time slot and a beam scanning time slot that are independent of each other.

In one embodiment, it further includes: a second receiving module 505, configured to receive a periodic scanning of the target environment when there is no moving object in the target environment before receiving the plurality of detection beams that periodically scan the target environment. The scanned multiple learning beams, wherein the beam directions of the multiple learning beams are different. The second obtaining module 506 is configured to secondly obtain the original channel characteristics in the target environment according to the plurality of learning beams.

In one embodiment, the plurality of learning beams are beams emitted by the beam generator in a plurality of beam scanning time slots, wherein each beam scanning time slot emits a plurality of learning beams. The second obtaining module 506 is configured to: determine the corresponding transmission channel feature under each beam scanning time slot according to the channel state information corresponding to the multiple learning beams, and use the obtained channel feature set as the original channel feature in the target environment.

In one embodiment, the monitoring module 504 is configured to: determine whether the maximum value of the difference information is greater than a preset threshold. When the maximum value of the difference information is greater than the preset threshold, it is determined that the moving object moves, and the beam generator is notified of the direction of the target beam, where the direction of the target beam is the direction of the detection beam corresponding to the maximum value of the difference information. Receive multiple tracking beams from the beam generator within the target environment. Determine if a moving object is moving based on multiple tracking beams.

In one embodiment, the plurality of tracking beams at least include: a target beam in the direction of the target beam, a first tracking beam whose angle is a first preset angle with the direction of the target beam, and a first tracking beam whose direction with the target beam is the first angle. Two second tracking beams with preset angles. The monitoring module 504 is further configured to: determine, according to the channel state information corresponding to the multiple tracking beams, which direction of the multiple tracking beams has the largest beam disturbance. If the beam disturbance of the target beam is the largest, it is determined that the moving object does not move. If the beam disturbance of the first tracking beam is the largest, it is determined that the moving object moves in the direction of the first tracking beam. If the beam disturbance of the second tracking beam is the largest, it is determined that the moving object moves in the direction of the second tracking beam.

In one embodiment, the monitoring module 504 is further configured to: when the maximum beam disturbance is not the target beam, send a beam adjustment request to the beam generator, so that the beam generator is in the next beam scanning time slot according to the current beam with the largest beam disturbance. Transmit tracking beams.

In one embodiment, the first obtaining module 502 is used to calculate the current channel characteristics in the target environment by using the following formula:

Among them, hi is the current channel characteristics corresponding to the multiple probe beams under the _ith beam scanning time slot, N is the number of waves of the multiple probe beams, and N is a positive integer. M is the number of subcarriers included in each sounding beam, and M is a positive integer. CSI _N,M is the channel state information corresponding to the Mth subcarrier of the Nth sounding beam.

In one embodiment, the difference information is an amplitude difference. The determining module 503 is used to calculate the amplitude difference using the following formula:

为第i个波束扫描时隙下，原始信道特征中第p个探测波束的子载波对应的平均信道状态信息。δ_p为第i个波束扫描时隙下，第p个探测波束方向上的当前信道特征与原始信道特征之间的幅度差异。Wherein, CSI _p,j is the channel state information corresponding to the jth subcarrier of the pth sounding beam under the ith beam scanning time slot, j∈(0, M).

is the average channel state information corresponding to the sub-carrier of the p-th sounding beam in the original channel characteristics under the i-th beam scanning time slot. δ _p is the amplitude difference between the current channel feature and the original channel feature in the direction of the p-th probe beam under the i-th beam scanning time slot.

For a detailed description of the above-mentioned activity information monitoring apparatus 500, please refer to the description of the relevant method steps in the above-mentioned embodiment.

The embodiment of the present invention further provides a non-transitory electronic device 1 readable storage medium, including: a program, when running on the electronic device 1, enables the electronic device 1 to execute all or part of the processes of the methods in the foregoing embodiments . Wherein, the storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a flash memory (Flash Memory), a hard disk (Hard Disk Drive, Abbreviation: HDD) or solid-state drive (Solid-State Drive, SSD), etc. The storage medium may also include a combination of the aforementioned kinds of memories.

Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, various modifications and variations can be made by those skilled in the art without departing from the spirit and scope of the present invention, such modifications and variations falling within the scope of the appended claims within the limited range.

Claims (13)

1. An activity information monitoring method, comprising:

receiving a plurality of probe beams of a periodic scanning target environment by a beam generator, wherein the beam directions of the plurality of probe beams are different, and a moving object is included in the target environment;

acquiring current channel characteristics in the target environment according to the plurality of detection beams;

determining difference information between the current channel characteristics and original channel characteristics within the target environment, wherein the original channel characteristics are channel characteristics in the absence of a moving object within the target environment;

and monitoring whether the moving object moves or not according to the difference information.

2. The method of claim 1, wherein during a scan cycle in which the target environment is periodically scanned, comprising: a normal communication time slot and a beam scanning time slot independent of each other.

3. The method of claim 1, further comprising, prior to said receiving a plurality of probe beams periodically scanning a target environment:

receiving a plurality of learning beams that periodically scan the target environment when no moving object is present in the target environment, wherein the plurality of learning beams have different beam directions;

and acquiring the original channel characteristics in the target environment according to the plurality of learning beams.

4. The method of claim 3, wherein the plurality of learning beams are beams emitted by the beam generator in a plurality of beam scanning time slots, wherein a plurality of the learning beams are emitted in each of the beam scanning time slots; the obtaining the original channel characteristics in the target environment according to the plurality of learning beams includes:

and determining the corresponding transmission channel characteristics under each beam scanning time slot according to the channel state information corresponding to the plurality of learning beams, and taking the obtained channel characteristic set as the original channel characteristics in the target environment.

5. The method of claim 1, wherein monitoring whether the moving object moves according to the difference information comprises:

judging whether the maximum value of the difference information is larger than a preset threshold value or not;

when the maximum value of the difference information is larger than the preset threshold value, determining that the moving object moves, and informing a target beam direction to the beam generator, wherein the target beam direction is the direction of the detection beam corresponding to the maximum value of the difference information;

receiving a plurality of tracking beams emitted by the beam generator within the target environment;

determining whether the moving object moves according to the plurality of tracking beams.

6. The method of claim 5, wherein the plurality of tracking beams comprises at least: a target wave beam in the direction of the target wave beam, a first tracking wave beam with a direction included angle with the target wave beam as a first preset angle, and a second tracking wave beam with a direction included angle with the target wave beam as a second preset angle; the determining whether the moving object moves according to the plurality of tracking beams includes:

determining which direction of the plurality of tracking beams has the largest beam disturbance according to the channel state information corresponding to the plurality of tracking beams;

if the beam disturbance of the target beam is maximum, determining that the moving object does not move;

if the beam disturbance of the first tracking beam is maximum, determining that the moving object moves towards the direction of the first tracking beam;

and if the beam disturbance of the second tracking beam is maximum, determining that the moving object moves towards the direction of the second tracking beam.

7. The method of claim 6, wherein said determining whether said moving object is moving from said plurality of tracking beams further comprises:

and when the beam disturbance is not the target beam with the maximum beam disturbance, sending a beam adjustment request to the beam generator so that the beam generator emits a tracking beam according to the beam with the maximum beam disturbance at the next beam scanning time slot.

8. The method of claim 1, wherein said obtaining current channel characteristics within said target environment from said plurality of probe beams comprises:

calculating said current channel characteristics within said target environment using the formula:

wherein h is_iThe current channel characteristics corresponding to the plurality of detection beams in the ith beam scanning time slot are obtained, wherein N is the number of wave numbers of the plurality of detection beams, and N is a positive integer; m is the number of subcarriers included in each sounding beam, and M is a positive integer; CSI_N,MAnd the channel state information corresponds to the mth subcarrier of the nth sounding beam.

9. The method of claim 8, wherein the difference information is an amplitude difference; said determining difference information between said current channel characteristics and original channel characteristics within said target environment, comprising:

the amplitude difference is calculated using the following formula:

wherein, CSI_p,jChannel state information corresponding to the jth subcarrier of the pth detection beam in the ith beam scanning time slot, wherein j belongs to (0, M);

average channel state information corresponding to a subcarrier of a p-th sounding beam in the original channel characteristics at an ith beam scanning time slot; delta_pThe amplitude difference between the current channel characteristic and the original channel characteristic in the p-th probe beam direction at the i-th beam scanning time slot.

10. An activity information monitoring device, comprising:

the device comprises a first receiving module, a second receiving module and a third receiving module, wherein the first receiving module is used for receiving a plurality of detection beams which are used for periodically scanning a target environment by a beam generator, the beam directions of the plurality of detection beams are different, and a moving object is included in the target environment;

a first obtaining module, configured to obtain, according to the multiple sounding beams, a current channel characteristic in the target environment;

a determining module, configured to determine difference information between the current channel characteristics and original channel characteristics in the target environment, where the original channel characteristics are channel characteristics when no moving object exists in the target environment;

and the monitoring module is used for monitoring whether the mobile object moves or not according to the difference information.

11. An activity information monitoring system, comprising:

a beam generator for periodically emitting a plurality of probe beams to a target environment, wherein the plurality of probe beams have different beam directions and a moving object is included in the target environment;

an activity detector installed in the target environment for receiving the plurality of probe beams and monitoring whether the moving object moves by using the activity information monitoring method according to any one of claims 1 to 9.

12. An electronic device, comprising:

a memory to store a computer program;

a processor to execute the computer program to implement the method of any one of claims 1 to 9.

13. A non-transitory electronic device readable storage medium, comprising: program which, when run by an electronic device, causes the electronic device to perform the method of any one of claims 1 to 9.

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