Method and device for intelligently determining moving state of object based on wireless local area network

Abstract

The invention discloses a method and a device for intelligently determining a moving state of an object based on a wireless local area network. The method comprises the following steps: acquiring subcarrier data corresponding to a target object in a target area based on the wireless local area network; inputting the subcarrier data and a preset accumulation time length into a predetermined energy accumulation model for energy accumulation calculation to obtain an energy accumulation result corresponding to the subcarrier data; and determining the moving state of the target object according to the energy accumulation result corresponding to the subcarrier data and at least one predetermined state judgment condition. Therefore, by implementing the method and the device, the energy accumulation result of the subcarrier data can be accurately calculated, and the accuracy of determining the channel state characteristics represented by the energy accumulation result is improved; and according to the energy accumulation result and at least one predetermined state determination condition, whether the current state of the target object accords with the channel state influence feature is accurately evaluated, so that the determination accuracy of the moving state of the target object can be improved.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and in particular to a method and device for intelligently determining the movement state of an object based on a wireless local area network. Background Art

[0002] At present, CSI (channel state indication) technology can evaluate the data transmitted by wireless local area networks (mainly for data link and communication) and obtain the corresponding channel frequency characteristics, thereby identifying the movement of objects (people and / or objects).

[0003] However, in real life, when using CSI to identify the movement of objects, there are many factors that hinder the implementation of industrialization, such as: the channel status needs to be calibrated frequently, the calibration process needs to exclude the movement of people or objects, the router or sub-device will adjust the RF front-end parameters in real time according to the communication environment, the router or sub-device is moved by the user, and large objects in the environment are moved manually, etc. Changes in all of the above factors can easily lead to errors in the evaluation of channel frequency characteristics, resulting in misidentification of object movement.

[0004] It can be seen that it is particularly important to propose a technical solution to improve the accuracy of determining the movement state of an object. Summary of the invention

[0005] The present invention provides a method and device for intelligently determining the mobile state of an object based on a wireless local area network, which can improve the accuracy of evaluating the channel state characteristics of subcarrier data, thereby improving the accuracy of determining the mobile state of a target object.

[0006] In order to solve the above technical problems, the first aspect of the present invention discloses a method for intelligently determining the movement state of an object based on a wireless local area network, the method comprising:

[0007] Collecting subcarrier data corresponding to a target object in a target area based on a wireless local area network, wherein the subcarrier data corresponding to the target object is data reflected and / or absorbed and / or diffracted after a signal is sent to the target area based on the wireless local area network and collides with the target object;

[0008] Inputting the subcarrier data and the preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtaining an energy accumulation result corresponding to the subcarrier data, wherein the energy accumulation model is used to count the distribution of the change value of the subcarrier data within the accumulation time, and the energy accumulation result is used to represent the channel state characteristics of the wireless local area network for the target object within the accumulation time;

[0009] The mobile state of the target object is determined based on the energy accumulation result corresponding to the subcarrier data and at least one predetermined state judgment condition, and the state judgment condition is used to indicate whether the current state of the target object meets the channel state characteristics that affect the wireless local area network in the target area.

[0010] As an optional implementation manner, in the first aspect of the present invention, determining the movement state of the target object according to the energy accumulation result corresponding to the subcarrier data and at least one predetermined state determination condition includes:

[0011] Calculating the confidence of the energy accumulation result corresponding to the subcarrier data according to a predetermined confidence calculation condition, wherein the confidence is used to indicate the credibility of the probability that the target object moves;

[0012] Inputting the energy accumulation result corresponding to the subcarrier data and the confidence of the energy accumulation result into a predetermined confidence screening model for screening, and obtaining a target energy accumulation result whose confidence is greater than or equal to a preset confidence;

[0013] The moving state of the target object is determined according to the target energy accumulation result and at least one predetermined state determination condition.

[0014] As an optional implementation, in the first aspect of the present invention, the preset cumulative duration includes a first preset cumulative duration and / or a second preset cumulative duration, and the first preset cumulative duration is less than the second preset cumulative duration;

[0015] And, the step of inputting the subcarrier data and the preset accumulation duration into a predetermined energy accumulation model to perform energy accumulation calculation to obtain an energy accumulation result corresponding to the subcarrier data includes:

[0016] Inputting the subcarrier data and the first preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtaining a first type of energy accumulation result corresponding to the subcarrier data, wherein the first type of energy accumulation result is used to indicate that the channel state characteristic of the wireless local area network is a dynamic channel state characteristic; and / or,

[0017] The subcarrier data and the second preset accumulation time are input into the energy accumulation model to perform energy accumulation calculation, and a second type of energy accumulation result corresponding to the subcarrier data is obtained, and the second type of energy accumulation result is used to indicate that the channel state characteristics of the wireless local area network are static channel state characteristics.

[0018] As an optional implementation, in the first aspect of the present invention, determining the movement state of the target object according to the target energy accumulation result and at least one predetermined state determination condition includes:

[0019] When the target energy accumulation result includes the first type of energy accumulation result, determining the variability of the subcarrier data according to the first type of energy accumulation result, the variability being used to evaluate the authenticity of the probability that the target object in the target area moves;

[0020] Inputting the first type of energy accumulation result into a preset motion signal recognition model for recognition to obtain the motion signal of the subcarrier data;

[0021] The movement state of the target object is determined according to the variability of the subcarrier data and the motion signal of the subcarrier data.

[0022] As an optional implementation manner, in the first aspect of the present invention, the step of inputting the first type of energy accumulation result into a preset motion signal recognition model for recognition to obtain the motion signal of the subcarrier includes:

[0023] Determining a confidence region of the first type of energy accumulation result according to the confidence calculation condition;

[0024] Filter out the target energy that overflows the confidence region from the first type of energy accumulation results;

[0025] The target energy is input into a preset motion signal recognition model for identification to obtain the motion signal of the subcarrier data, wherein the motion signal of the subcarrier data includes a valid signal and / or an invalid signal, wherein the valid signal is used to indicate that the wireless local area network's perception of the moving state of the target object is valid, and the invalid signal is used to indicate that the wireless local area network's perception of the moving state of the target object is invalid.

[0026] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0027] When the energy accumulation result of the subcarrier data includes the first type of energy accumulation result and the second type of energy accumulation result, comparing the second type of energy accumulation result with the first type of energy accumulation result to obtain a comparison result;

[0028] According to the comparison result, the static existence status of the target object in the target area is determined, and the static existence status includes one or more combinations of the number of the target objects, the spatial position of the target objects, the shape of the target objects and the surface area of ​​the target objects.

[0029] As an optional implementation, in the first aspect of the present invention, before inputting the subcarrier data and the preset accumulation duration into a predetermined energy accumulation model for energy accumulation calculation to obtain the energy accumulation result corresponding to the subcarrier data, the method further includes:

[0030] Inputting the subcarrier data into a predetermined preprocessing model for preprocessing to obtain preprocessed subcarrier data, and triggering the execution of the operation of inputting the subcarrier data and a preset accumulation time into a predetermined energy accumulation model for energy accumulation calculation to obtain an energy accumulation result of the subcarrier data, the subcarrier data being the preprocessed subcarrier data;

[0031] Among them, the preprocessing model is used to perform signal shaping and / or jitter removal on the subcarrier data through a preset filtering method, and the filtering method includes a combination of one or more of a low-frequency filtering method, a bandpass filtering method, a median filtering method, a pattern filtering method, and an artificial neural network signal filtering method.

[0032] A second aspect of the present invention discloses a device for intelligently determining the movement state of an object based on a wireless local area network, the device comprising:

[0033] A collection module, used for collecting subcarrier data corresponding to a target object in a target area based on a wireless local area network, wherein the subcarrier data corresponding to the target object is data reflected and / or absorbed and / or diffracted after a signal is sent to the target area based on the wireless local area network and collides with the target object;

[0034] A calculation module, used for inputting the subcarrier data and the preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtaining an energy accumulation result corresponding to the subcarrier data, wherein the energy accumulation model is used for counting the distribution of the change value of the subcarrier data within the accumulation time, and the energy accumulation result is used for representing the channel state characteristics of the wireless local area network for the target object within the accumulation time;

[0035] A determination module is used to determine the mobile state of the target object based on the energy accumulation result corresponding to the subcarrier data and at least one predetermined state determination condition, wherein the state determination condition is used to indicate whether the current state of the target object meets the channel state characteristics that affect the wireless local area network in the target area.

[0036] As an optional implementation, in the second aspect of the present invention, the determination module determines the movement state of the target object according to the energy accumulation result corresponding to the subcarrier data and at least one predetermined state determination condition, specifically including:

[0037] Calculating the confidence of the energy accumulation result corresponding to the subcarrier data according to a predetermined confidence calculation condition, wherein the confidence is used to indicate the credibility of the probability that the target object moves;

[0038] Inputting the energy accumulation result corresponding to the subcarrier data and the confidence of the energy accumulation result into a predetermined confidence screening model for screening, and obtaining a target energy accumulation result whose confidence is greater than or equal to a preset confidence;

[0039] The moving state of the target object is determined according to the target energy accumulation result and at least one predetermined state determination condition.

[0040] As an optional implementation, in the second aspect of the present invention, the preset cumulative duration includes a first preset cumulative duration and / or a second preset cumulative duration, and the first preset cumulative duration is less than the second preset cumulative duration;

[0041] And, the calculation module inputs the subcarrier data and the preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and the method of obtaining the energy accumulation result corresponding to the subcarrier data specifically includes:

[0042] Inputting the subcarrier data and the first preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtaining a first type of energy accumulation result corresponding to the subcarrier data, wherein the first type of energy accumulation result is used to indicate that the channel state characteristic of the wireless local area network is a dynamic channel state characteristic; and / or,

[0043] The subcarrier data and the second preset accumulation time are input into the energy accumulation model to perform energy accumulation calculation, and a second type of energy accumulation result corresponding to the subcarrier data is obtained, and the second type of energy accumulation result is used to indicate that the channel state characteristics of the wireless local area network are static channel state characteristics.

[0044] As an optional implementation, in the second aspect of the present invention, the determination module determines the movement state of the target object according to the target energy accumulation result and at least one predetermined state determination condition, specifically including:

[0045] When the target energy accumulation result includes the first type of energy accumulation result, determining the variability of the subcarrier data according to the first type of energy accumulation result, the variability being used to evaluate the authenticity of the probability that the target object in the target area moves;

[0046] Inputting the first type of energy accumulation result into a preset motion signal recognition model for recognition to obtain the motion signal of the subcarrier data;

[0047] The movement state of the target object is determined according to the variability of the subcarrier data and the motion signal of the subcarrier data.

[0048] As an optional implementation manner, in the second aspect of the present invention, the determination module inputs the first type of energy accumulation result into a preset motion signal recognition model for recognition, and the manner in which the motion signal of the subcarrier is obtained specifically includes:

[0049] Determining a confidence region of the first type of energy accumulation result according to the confidence calculation condition;

[0050] Filter out the target energy that overflows the confidence region from the first type of energy accumulation results;

[0051] The target energy is input into a preset motion signal recognition model for identification to obtain the motion signal of the subcarrier data, wherein the motion signal of the subcarrier data includes a valid signal and / or an invalid signal, wherein the valid signal is used to indicate that the wireless local area network's perception of the moving state of the target object is valid, and the invalid signal is used to indicate that the wireless local area network's perception of the moving state of the target object is invalid.

[0052] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0053] A comparison module, configured to, when the energy accumulation result of the subcarrier data includes the first type of energy accumulation result and the second type of energy accumulation result, compare the second type of energy accumulation result with the first type of energy accumulation result to obtain a comparison result;

[0054] The determination module is further used to determine the static presence of the target object in the target area based on the comparison result, and the static presence includes one or more combinations of the number of the target objects, the spatial position of the target objects, the shape of the target objects and the surface area of ​​the target objects.

[0055] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0056] a preprocessing module, configured to input the subcarrier data into a predetermined preprocessing model for preprocessing before the calculation module inputs the subcarrier data and the preset accumulation time into a predetermined energy accumulation model for energy accumulation calculation to obtain the energy accumulation result corresponding to the subcarrier data, and to trigger the calculation module to execute the operation of inputting the subcarrier data and the preset accumulation time into a predetermined energy accumulation model for energy accumulation calculation to obtain the energy accumulation result of the subcarrier data, wherein the subcarrier data is the preprocessed subcarrier data;

[0057] Among them, the preprocessing model is used to perform signal shaping and / or jitter removal on the subcarrier data through a preset filtering method, and the filtering method includes a combination of one or more of a low-frequency filtering method, a bandpass filtering method, a median filtering method, a pattern filtering method, and an artificial neural network signal filtering method.

[0058] The third aspect of the present invention discloses another device for intelligently determining the movement state of an object based on a wireless local area network, the device comprising:

[0059] A memory storing executable program code;

[0060] a processor coupled to the memory;

[0061] The processor calls the executable program code stored in the memory to execute the method for intelligently determining the movement status of an object based on a wireless local area network disclosed in the first aspect of the present invention.

[0062] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute the method for intelligently determining the movement status of an object based on a wireless local area network disclosed in the first aspect of the present invention.

[0063] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0064] In an embodiment of the present invention, subcarrier data corresponding to a target object in a target area is collected based on a wireless local area network, and the subcarrier data corresponding to the target object is data based on a signal sent by the wireless local area network to the target area and reflected and / or absorbed and / or diffracted after the signal collides with the target object; the subcarrier data and a preset accumulation time are input into a predetermined energy accumulation model to perform energy accumulation calculation, and an energy accumulation result corresponding to the subcarrier data is obtained, the energy accumulation model is used to count the distribution of the change value of the subcarrier data within the accumulation time, and the energy accumulation result is used to represent the channel state characteristics of the wireless local area network for the target object within the accumulation time; the mobile state of the target object is determined according to the energy accumulation result corresponding to the subcarrier data and at least one predetermined state determination condition, and the state determination condition is used to represent whether the current state of the target object meets the channel state characteristics that affect the wireless local area network in the target area. It can be seen that the implementation of the present invention can collect subcarrier data of target objects in the target area based on the wireless local area network, and input the subcarrier data and the preset accumulation time into the preset energy accumulation model to perform energy accumulation calculation, and accurately calculate the energy accumulation result corresponding to the subcarrier data, which can improve the accuracy of determining the channel state characteristics represented by the energy accumulation result; and, based on the energy accumulation result and at least one predetermined state judgment condition, accurately evaluate whether the current state of the target object meets the characteristics that affect the channel state, which can improve the accuracy of determining the mobile state of the target object. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0066] Figure 1 It is a schematic diagram of a scenario to which a method for intelligently determining the movement state of an object based on a wireless local area network disclosed in an embodiment of the present invention is applicable;

[0067] Figure 2 It is a flow chart of a method for intelligently determining the movement state of an object based on a wireless local area network disclosed in an embodiment of the present invention;

[0068] Figure 3 It is a flow chart of another method for intelligently determining the movement state of an object based on a wireless local area network disclosed in an embodiment of the present invention;

[0069] Figure 4 It is a schematic diagram of the distribution of a first type of energy accumulation result and a second type of energy accumulation result of a single subcarrier data disclosed in an embodiment of the present invention;

[0070] Figure 5 It is a schematic diagram of the distribution of the long-term energy accumulation results of multiple subcarrier data disclosed in an embodiment of the present invention;

[0071] Figure 6 It is a schematic diagram of the distribution of short-term energy accumulation results of multiple subcarrier data disclosed in an embodiment of the present invention;

[0072] Figure 7 It is a schematic diagram of a change in a short-term energy accumulation result caused by movement of a target object disclosed in an embodiment of the present invention;

[0073] Figure 8 It is a schematic diagram of the distribution of a confidence filtering of a short-term energy accumulation result disclosed in an embodiment of the present invention;

[0074] Fig. 9 It is a structural schematic diagram of a device for intelligently determining the movement state of an object based on a wireless local area network disclosed in an embodiment of the present invention;

[0075] Fig.10 It is a structural schematic diagram of another device for intelligently determining the movement state of an object based on a wireless local area network disclosed in an embodiment of the present invention;

[0076] Fig.11 It is a structural schematic diagram of another device for intelligently determining the movement state of an object based on a wireless local area network disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0077] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or end including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or ends.

[0079] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0080] The present invention discloses a method and device for intelligently determining the mobile state of an object based on a wireless local area network, which can collect subcarrier data of a target object in a target area based on a wireless local area network, and input the subcarrier data and a preset accumulation time into a preset energy accumulation model for energy accumulation calculation, accurately calculate the energy accumulation result corresponding to the subcarrier data, accurately evaluate the characteristic content of the channel state characteristics of the subcarrier data according to the energy accumulation result and at least one state judgment condition determined in advance, and improve the evaluation accuracy of the channel state characteristics of the subcarrier data, thereby improving the accuracy of determining the mobile state of the target object. The following are detailed descriptions respectively.

[0081] In order to better understand the method and device for intelligently determining the mobile state of an object based on a wireless local area network described in the present invention, firstly, the scenario to which the method for intelligently determining the mobile state of an object based on a wireless local area network is applicable is described. Specifically, taking a home scenario as an example, the scenario schematic diagram can be as follows: Figure 1 As shown, Figure 1 FIG. 1 is a schematic diagram of a scenario to which a method for intelligently determining the movement state of an object based on a wireless local area network disclosed in an embodiment of the present invention is applicable. Figure 1 As shown, the scenario diagram takes a home scene as an example of the target area. A wireless router is placed in the home scene, and the home scene has a test object (i.e., a target object). When the subcarrier signal (such as Figure 1 After the multipath signal 1, multipath signal 2 and direct signal in the home scene collide with the object under test, the data in the subcarrier signal will change accordingly. Furthermore, a terminal device can be placed in the home scene, wherein the wireless router can send the subcarrier signal to the terminal device, and the terminal device can intelligently determine the movement state of the target object based on the subcarrier data carried in the received subcarrier signal.

[0082] It should be noted that Figure 1 The scene diagram shown is only for showing one of the scenes applicable to the method and device for intelligently determining the movement state of an object based on a wireless local area network, and is not used to limit other scenes applicable to the method and device for intelligently determining the movement state of an object based on a wireless local area network, and Figure 1 The wireless routers and objects under test involved in Figure 1The scenario diagram shown does not limit the shape and size of the wireless router, and the shape and size of the object under test; Figure 1 There is no restriction on whether the terminal devices and other related objects involved exist and their existence forms.

[0083] The above describes an example of one scenario to which the method and device for intelligently determining the movement state of an object based on a wireless local area network are applicable. The following describes the method and device for intelligently determining the movement state of an object based on a wireless local area network in detail.

[0084] Embodiment 1

[0085] See also Figure 2 , Figure 2 1 is a flow chart of a method for intelligently determining the movement state of an object based on a wireless local area network disclosed in an embodiment of the present invention. Figure 2 The method for intelligently determining the movement state of an object based on a wireless local area network can be applied to a device for intelligently determining the movement state of an object based on a wireless local area network, wherein the device may include a determination device or a determination server, wherein the determination server may include a cloud server or a local server, which is not limited in the embodiments of the present invention. Figure 2 As shown, the method for intelligently determining the movement state of an object based on a wireless local area network may include the following operations:

[0086] 101. Collect subcarrier data corresponding to a target object in a target area based on a wireless local area network.

[0087] In an embodiment of the present invention, the subcarrier data corresponding to the target object is data that is reflected and / or absorbed and / or diffracted based on a signal sent to the target area by the wireless local area network and after the signal collides with the target object. Among them, the signal sent by the wireless local area network to the target area can be a subcarrier signal, and the number of subcarrier signals can be one or more, and each subcarrier signal can reflect and / or absorb and / or diffract the corresponding subcarrier data after colliding with the target object. Optionally, the target object can be an object other than inherent objects such as walls, ceilings, floors, etc. in the target area. Optionally, the target object can include living objects and / or non-living objects. Optionally, living objects can include humans and / or animals, and non-living objects can include furniture and / or smart home devices (such as: sweepers), which are not limited in the embodiment of the present invention.

[0088] 102. Input the subcarrier data and the preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtain an energy accumulation result corresponding to the subcarrier data.

[0089] In the embodiment of the present invention, the energy accumulation model is used to count the distribution of the change values ​​of the subcarrier data within the accumulation time, and the energy accumulation result is used to represent the channel state characteristics of the wireless local area network for the target object within the accumulation time.

[0090] 103. Determine a moving state of the target object according to an energy accumulation result corresponding to the subcarrier data and at least one predetermined state determination condition.

[0091] In the embodiment of the present invention, the state determination condition is used to indicate whether the current state of the target object meets the channel state characteristics that affect the wireless local area network in the target area.

[0092] It should be noted that there is a certain time delay when identifying the movement of the target object, that is, after the target object enters the target area, an effective output response will not be obtained immediately, but a certain observation time is required. When it is determined according to the predetermined state judgment conditions that the current state of the target object does meet the channel state characteristics that affect the wireless LAN in the target area, the output response will officially take effect.

[0093] In the embodiment of the present invention, optionally, the current state (movement state) of the target object may include a stationary state and / or a motion state. Specifically, when the target object is a person, the stationary state may include at least one of a sleeping state, a sitting state, a eating state, and a tea drinking state, and the motion state may include a slow motion state (e.g., a walking state) or a fast motion state (e.g., a running state), and the state parameters of the motion state may include a combination of one or more of the target object's motion speed, the target object's motion direction, the target object's motion duration, and the target object's position parameter, which is not limited in the embodiment of the present invention.

[0094] Specifically, if it is detected that the channel characteristics of each subcarrier signal in multiple subcarrier signals include channel state characteristics corresponding to subcarrier data reflected and / or absorbed and / or diffracted when the subcarrier signal collides with the same target object (for example, a person), it can be determined that the current state of the person is a motion state, and then based on the intervals (distance intervals and / or time intervals) of all subcarrier signals, the person's movement speed can be determined, and based on the person's movement speed and the collected movement states corresponding to the person at different movement speeds, the person's target movement state can be determined.

[0095] It can be seen that the method for intelligently determining the mobile state of an object based on a wireless local area network described in the embodiment of the present invention can collect subcarrier data of a target object in a target area based on a wireless local area network, and input the subcarrier data and a preset accumulation time into a preset energy accumulation model for energy accumulation calculation, and accurately calculate the energy accumulation result corresponding to the subcarrier data, which can improve the accuracy of determining the channel state characteristics represented by the energy accumulation result; and, based on the energy accumulation result and at least one predetermined state judgment condition, accurately evaluate whether the current state of the target object meets the characteristics that affect the channel state, which can improve the accuracy of determining the mobile state of the target object.

[0096] In an optional embodiment, after determining the movement state of the target object according to the energy accumulation result corresponding to the subcarrier data and at least one predetermined state determination condition in the above step 103, the method may further include:

[0097] Performing curve fitting on the energy accumulation result corresponding to the subcarrier data to obtain a curve fitting result of the subcarrier data;

[0098] According to the curve fitting result, determine the change trend of the subcarrier data;

[0099] Selecting historical subcarrier data with the highest similarity to the change trend of subcarrier data from a preset subcarrier database as reference subcarrier data matching the above subcarrier data, wherein the preset database stores the change trends of multiple historical subcarrier data, and each historical subcarrier data is data collected by the wireless local area network when there is a historical object in the target area, wherein the type of the historical object is consistent with that of the target object;

[0100] Acquire a reference movement state corresponding to the reference subcarrier data, where the reference movement state is a reference movement state of the reference object determined when the reference subcarrier data exists in the target area;

[0101] The movement state of the target object is calibrated according to the reference movement state corresponding to the reference subcarrier data to obtain a calibrated movement state.

[0102] It can be seen that this optional embodiment can accurately filter out the target subcarrier data with the highest similarity to the change trend of the subcarrier data from the historical subcarrier data in the preset subcarrier database, and accurately calibrate the movement state of the target object according to the reference movement state corresponding to the acquired target subcarrier data, thereby improving the calibration accuracy of the movement state of the target object, thereby being able to obtain a more accurate movement state of the target object.

[0103] Embodiment 2

[0104] See also Figure 3 , Figure 3 1 is a flow chart of a method for intelligently determining the movement state of an object based on a wireless local area network disclosed in an embodiment of the present invention. Figure 3 The method for intelligently determining the movement state of an object based on a wireless local area network can be applied to a device for intelligently determining the movement state of an object based on a wireless local area network, wherein the device may include a determination device or a determination server, wherein the determination server may include a cloud server or a local server, which is not limited in the embodiments of the present invention. Figure 3 As shown, the method for intelligently determining the movement state of an object based on a wireless local area network may include the following operations:

[0105] 201. Collect subcarrier data corresponding to a target object in a target area based on a wireless local area network.

[0106] 202. Input the subcarrier data and the preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtain an energy accumulation result corresponding to the subcarrier data.

[0107] In the embodiment of the present invention, the specific technical details and technical terminology of step 201 and step 202 can refer to the description of step 101 and step 102 in the first embodiment, and will not be repeated here.

[0108] 203. Calculate the confidence of the energy accumulation result corresponding to the subcarrier data according to the predetermined confidence calculation condition.

[0109] In the embodiment of the present invention, the confidence level is used to indicate the credibility of the probability that the target object moves.

[0110] In the embodiment of the present invention, specifically, calculating the confidence of the energy accumulation result corresponding to the subcarrier data according to the predetermined confidence calculation condition may include:

[0111] Performing curve fitting on the energy accumulation result corresponding to the subcarrier data to obtain a normal distribution curve of the energy accumulation result;

[0112] Determine the confidence interval of the energy accumulation result according to the predetermined confidence calculation conditions;

[0113] Obtaining the initial likelihood of each value in the confidence interval of the energy accumulation result;

[0114] The average value of the initial likelihood of all values ​​is calculated to obtain the target likelihood of the energy accumulation result, which is used as the confidence of the energy accumulation result corresponding to the subcarrier data.

[0115] It can be seen that this optional embodiment can perform curve fitting on the energy accumulation result corresponding to the subcarrier data, accurately obtain the normal distribution curve of the energy accumulation result, and accurately determine the confidence interval of the energy accumulation result according to the preset confidence calculation conditions, calculate the initial possibility of each of all the acquired values, and accurately obtain the confidence of the energy accumulation result corresponding to the subcarrier data, which can improve the calculation accuracy and reliability of the confidence of the energy accumulation result.

[0116] 204. Input the energy accumulation result corresponding to the subcarrier data and the confidence of the energy accumulation result into a predetermined confidence screening model for screening, and obtain a target energy accumulation result with a confidence greater than or equal to a preset confidence.

[0117] In an embodiment of the present invention, optionally, when the confidence (confidence level) is greater than or equal to 95%, it can be considered that the channel state characteristics (samples) corresponding to the energy accumulation result can represent the channel state characteristics of all similar energy accumulation results in the target area. Among them, the similar energy accumulation result is an energy accumulation result whose similarity with the energy accumulation result is greater than or equal to a preset similarity (for example: 80%). Optionally, the similarity may include a combination of one or more of the similarity of the accumulation time length, the similarity of the amplitude change value of the subcarrier data, and the similarity of the amplitude change rate of the subcarrier data, etc., which is not limited in the embodiment of the present invention.

[0118] 205. Determine the movement state of the target object according to the target energy accumulation result and at least one predetermined state determination condition.

[0119] In the embodiment of the present invention, optionally, the movement state of the target object may include the movement state of the target object in each accumulated time duration in all accumulated time durations.

[0120] It can be seen that the method for intelligently determining the mobile state of an object based on a wireless local area network described in the embodiment of the present invention can collect subcarrier data of a target object in a target area based on a wireless local area network, and input the subcarrier data and the preset accumulation time into a preset energy accumulation model for energy accumulation calculation, accurately calculate the energy accumulation result corresponding to the subcarrier data, and improve the accuracy of determining the channel state characteristics represented by the energy accumulation result; and, according to the energy accumulation result and at least one state judgment condition determined in advance, accurately evaluate whether the current state of the target object meets the characteristics that affect the channel state, and improve the accuracy of determining the mobile state of the target object. In addition, it is also possible to accurately calculate the confidence of the energy accumulation result corresponding to the subcarrier data according to the predetermined hunger confidence calculation condition, so that the target energy accumulation result with a confidence greater than or equal to the preset confidence can be accurately screened out from the energy accumulation result, and the screening accuracy and reliability of the target energy accumulation result can be improved.

[0121] In an optional embodiment, the preset cumulative duration may include a first preset cumulative duration and / or a second preset cumulative duration, and the first preset cumulative duration is smaller than the second preset cumulative duration.

[0122] Furthermore, in the above step 202, the subcarrier data and the preset accumulation duration are input into a predetermined energy accumulation model to perform energy accumulation calculation, and the energy accumulation result corresponding to the subcarrier data is obtained, which may include:

[0123] Inputting the subcarrier data and the first preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtaining a first type of energy accumulation result corresponding to the subcarrier data; and / or,

[0124] The subcarrier data and the second preset accumulation time are input into the energy accumulation model to perform energy accumulation calculation, and a second type of energy accumulation result corresponding to the subcarrier data is obtained.

[0125] In an embodiment of the present invention, the first type of energy accumulation result is used to indicate that the channel state characteristics of the wireless local area network are dynamic channel state characteristics, wherein the dynamic channel state characteristics are a scale for determining whether a target object in space is moving; the second type of energy accumulation result is used to indicate that the channel state characteristics of the wireless local area network are static channel state characteristics, wherein the static channel state characteristics are a scale for a combination of one or more of counting the number of people, identifying the movement of an object, and determining the static existence of an object.

[0126] like Figure 4 FIG. 1 is a schematic diagram showing the distribution of a first type of energy accumulation result and a second type of energy accumulation result of a single subcarrier data disclosed in an embodiment of the present invention, wherein: Figure 4The long-term energy accumulation distribution in is the distribution of the change value of the subcarrier data represented by the second type of energy accumulation result. Figure 4 The short-term energy accumulation distribution in is the distribution of the change value of the subcarrier data represented by the first type of energy accumulation result.

[0127] Specifically, Figure 5 and Figure 6 As shown, Figure 5 is a schematic diagram of the distribution of long-term energy accumulation results of multiple subcarrier data disclosed in an embodiment of the present invention, Figure 6 is a schematic diagram of the distribution of short-term energy accumulation results of multiple subcarrier data disclosed in an embodiment of the present invention, Figure 5 and Figure 6 The white parts represent the corresponding energy accumulation results in their respective figures.

[0128] It can be seen that this optional embodiment can input subcarrier data and different accumulation durations into a predetermined energy accumulation model to perform energy accumulation calculations, accurately obtain different types of energy accumulation results, and improve the calculation accuracy and reliability of different types of energy accumulation results.

[0129] In another optional embodiment, in the above step 205, determining the moving state of the target object according to the target energy accumulation result and at least one predetermined state determination condition may include:

[0130] When the target energy accumulation result includes a first type of energy accumulation result, determining the variability of the subcarrier data according to the first type of energy accumulation result;

[0131] Inputting the first type of energy accumulation result into a preset motion signal recognition model for recognition to obtain a motion signal of the subcarrier data;

[0132] The moving state of the target object is determined based on the variability of the subcarrier data and the motion signal of the subcarrier data.

[0133] In the embodiment of the present invention, the variability is used to evaluate the authenticity of the probability of the target object moving in the target area. Figure 4 As shown, Figure 4 The two dotted curves in are distribution curves of short-term energy accumulation results recorded at different times. Specifically, by screening out the top of the distribution curve through the confidence selection module, and comparing the drift of the tops of the two curves, the variability value of the subcarrier in the time period can be obtained. By evaluating the variability of all subcarrier data, the authenticity judgment value of the target object's movement state can be obtained. For example, Figure 7is a schematic diagram of a change in a short-term energy accumulation result caused by the movement of a target object disclosed in an embodiment of the present invention, Figure 7 The drift of all subcarriers before and after this specific time period (the time period when the target object moves) is shown in FIG.

[0134] It can be seen that this optional embodiment can accurately determine the volatility of the subcarrier data based on the short-term energy accumulation result, and input the short-term energy accumulation result into a preset motion signal recognition model for recognition, so as to accurately obtain the motion signal of the subcarrier data, and then accurately determine the movement state of the target object based on the accurately determined subcarrier data volatility and motion signal, thereby improving the accuracy and reliability of determining the movement state of the target object.

[0135] In this optional embodiment, as an optional implementation, inputting the first type of energy accumulation result into a preset motion signal recognition model for recognition to obtain the motion signal of the subcarrier may include:

[0136] According to the confidence calculation conditions, the confidence region of the first type of energy accumulation result is determined;

[0137] Filter out the target energy that exceeds the confidence region from the first type of energy accumulation results;

[0138] The target energy is input into a preset motion signal recognition model for identification to obtain a motion signal of the subcarrier data. The motion signal of the subcarrier data includes a valid signal and / or an invalid signal. The valid signal is used to indicate that the wireless local area network's perception of the target object's movement state is valid, and the invalid signal is used to indicate that the wireless local area network's perception of the target object's movement state is invalid.

[0139] In the embodiment of the present invention, specifically, Figure 8 As shown, Figure 8 It is a schematic diagram (white part) of the distribution of a confidence-filtered short-term energy accumulation result disclosed in an embodiment of the present invention. It can be seen that the short-term energy accumulation with confidence is the part close to the peak of the short-term energy accumulation curve, and the area is determined by the confidence setting value. Figure 8 The gray part shown is the real-time motion signal. The movement of the target object in space, including the jitter caused by the equipment, will bring about signal offset, causing the signal to deviate and overflow outside the confidence area. The overflow part can be used for motion pattern recognition.

[0140] It can be seen that this optional implementation method can determine the confidence region of the short-term energy accumulation result according to the confidence calculation conditions, and accurately screen out the target energy that overflows the confidence region from the short-term energy accumulation result, and input the accurately screened target energy into the preset motion signal recognition model for identification, so as to accurately obtain the motion signal of the subcarrier data, which can improve the recognition accuracy of the motion signal.

[0141] In this optional embodiment, as another optional implementation, the method may further include:

[0142] When the energy accumulation result of the subcarrier data includes a first type of energy accumulation result and a second type of energy accumulation result, comparing the second type of energy accumulation result with the first type of energy accumulation result to obtain a comparison result;

[0143] According to the comparison result, the static existence of the target objects in the target area is determined, and the static existence includes one or more combinations of the number of target objects, the spatial position of the target objects, the shape of the target objects, and the surface area of ​​the target objects.

[0144] In the embodiment of the present invention, optionally, the static presence of the target object in the target area can be determined by comparing the change trend of the two types of energy accumulation results stored in the predetermined data. Specifically, when the change trend of the first type of energy accumulation result represented by the comparison result is a step-like change compared to the second type of energy accumulation result, the change in the number of target objects can be determined, which is not limited in the embodiment of the present invention.

[0145] It can be seen that this optional implementation can obtain a comparison result by comparing the first type of energy accumulation results with the second type of energy accumulation results, and based on the comparison result, accurately determine the static existence of the target object in the target area, thereby improving the accuracy of determining the static existence of the target object.

[0146] In another optional embodiment, before inputting the subcarrier data and the preset accumulation duration into a predetermined energy accumulation model to perform energy accumulation calculation in the above step 202 and obtaining the energy accumulation result corresponding to the subcarrier data, the method may further include:

[0147] The subcarrier data is input into a predetermined preprocessing model for preprocessing to obtain preprocessed subcarrier data, and the operation of triggering the execution of inputting the subcarrier data and a preset accumulation time into a predetermined energy accumulation model for energy accumulation calculation to obtain an energy accumulation result of the subcarrier data is performed. The subcarrier data is the preprocessed subcarrier data.

[0148] In an embodiment of the present invention, the preprocessing model is used to perform signal shaping and / or jitter removal on subcarrier data through a preset filtering method, and the filtering method includes a combination of one or more of a low-frequency filtering method, a bandpass filtering method, a median filtering method, a pattern filtering method, and an artificial neural network signal filtering method, which is not limited in the embodiment of the present invention.

[0149] It can be seen that this optional embodiment can preprocess the subcarrier data through a predetermined preprocessing model, accurately obtain the preprocessed subcarrier data, and trigger subsequent energy accumulation calculation of the preprocessed subcarrier data, which can improve the filtering accuracy of the subcarrier data, thereby reducing the impact of clutter on subsequent energy accumulation calculations, and further helps to improve the accuracy of determining the movement state of the target object.

[0150] Embodiment 3

[0151] See also Fig. 9 , Fig. 9 1 is a schematic diagram of a structure of a device for intelligently determining the movement state of an object based on a wireless local area network disclosed in an embodiment of the present invention. Fig. 9 The apparatus for intelligently determining the movement state of an object based on a wireless local area network may include a determination device or a determination server, wherein the determination server may include a cloud server or a local server, which is not limited in the embodiment of the present invention. Fig. 9 As shown, the device for intelligently determining the movement state of an object based on a wireless local area network may include:

[0152] The acquisition module 301 is used to acquire subcarrier data corresponding to the target object in the target area based on the wireless local area network. The subcarrier data corresponding to the target object is data reflected and / or absorbed and / or diffracted after the signal is sent to the target area based on the wireless local area network and collides with the target object.

[0153] The calculation module 302 is used to input the subcarrier data and the preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtain the energy accumulation result corresponding to the subcarrier data. The energy accumulation model is used to count the distribution of the change value of the subcarrier data within the accumulation time, and the energy accumulation result is used to represent the channel state characteristics of the wireless local area network for the target object within the accumulation time.

[0154] The determination module 303 is used to determine the movement state of the target object according to the energy accumulation result corresponding to the subcarrier data and at least one predetermined state determination condition, and the state determination condition is used to determine whether the target object meets the mode that affects the channel state characteristics.

[0155] It can be seen that the device for intelligently determining the movement state of an object based on a wireless local area network described in the embodiment of the present invention can collect subcarrier data of a target object in a target area based on a wireless local area network, and input the subcarrier data and a preset accumulation time into a preset energy accumulation model for energy accumulation calculation, and accurately calculate the energy accumulation result corresponding to the subcarrier data, which can improve the accuracy of determining the channel state characteristics represented by the energy accumulation result; and, based on the energy accumulation result and at least one predetermined state judgment condition, accurately evaluate whether the current state of the target object meets the characteristics that affect the channel state, which can improve the accuracy of determining the movement state of the target object.

[0156] In an optional embodiment, the determination module 303 determines the movement state of the target object according to the energy accumulation result corresponding to the subcarrier data and at least one predetermined state determination condition, and the method may specifically include:

[0157] Calculating the confidence of the energy accumulation result corresponding to the subcarrier data according to the pre-determined confidence calculation condition, where the confidence is used to indicate the credibility of the probability that the target object moves;

[0158] Inputting the energy accumulation result corresponding to the subcarrier data and the confidence of the energy accumulation result into a predetermined confidence screening model for screening, and obtaining a target energy accumulation result whose confidence is greater than or equal to a preset confidence;

[0159] The moving state of the target object is determined according to the target energy accumulation result and at least one predetermined state determination condition.

[0160] It can be seen that this optional embodiment can accurately calculate the confidence of the energy accumulation result corresponding to the subcarrier data according to the predetermined confidence calculation conditions, so that the target energy accumulation result with a confidence greater than or equal to the preset confidence can be accurately screened out from the energy accumulation results, thereby improving the screening accuracy and reliability of the target energy accumulation results.

[0161] In another optional embodiment, the preset cumulative duration may include a first preset cumulative duration and / or a second preset cumulative duration, and the first preset cumulative duration is smaller than the second preset cumulative duration.

[0162] Furthermore, the calculation module 302 inputs the subcarrier data and the preset accumulation duration into a predetermined energy accumulation model to perform energy accumulation calculation, and the method of obtaining the energy accumulation result corresponding to the subcarrier data may specifically include:

[0163] Inputting the subcarrier data and the first preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtaining a first type of energy accumulation result corresponding to the subcarrier data, wherein the first type of energy accumulation result is used to indicate that the channel state characteristic of the wireless local area network is a dynamic channel state characteristic; and / or,

[0164] The subcarrier data and the second preset accumulation time are input into the energy accumulation model to perform energy accumulation calculation, and a second type of energy accumulation result corresponding to the subcarrier data is obtained. The second type of energy accumulation result is used to indicate that the channel state characteristics of the wireless local area network are static channel state characteristics.

[0165] It can be seen that this optional embodiment can input subcarrier data and different accumulation durations into a predetermined energy accumulation model to perform energy accumulation calculations, accurately obtain different types of energy accumulation results, and improve the calculation accuracy and reliability of different types of energy accumulation results.

[0166] In this optional embodiment, as an optional implementation, the determination module 303 determines the moving state of the target object according to the target energy accumulation result and at least one state determination condition determined in advance, which may specifically include:

[0167] When the target energy accumulation result includes a first type of energy accumulation result, determining the variability of the subcarrier data according to the first type of energy accumulation result, the variability being used to evaluate the authenticity of the probability that the target object in the target area moves;

[0168] Inputting the first type of energy accumulation result into a preset motion signal recognition model for recognition to obtain a motion signal of the subcarrier data;

[0169] The moving state of the target object is determined based on the variability of the subcarrier data and the motion signal of the subcarrier data.

[0170] It can be seen that this optional implementation can accurately determine the volatility of the subcarrier data based on the short-term energy accumulation results, and input the short-term energy accumulation results into a preset motion signal recognition model for identification, so as to accurately obtain the motion signal of the subcarrier data, and then accurately determine the movement state of the target object based on the accurately determined subcarrier data volatility and motion signal, thereby improving the accuracy and reliability of determining the movement state of the target object.

[0171] In this optional implementation, optionally, the determination module 303 inputs the first type of energy accumulation result into a preset motion signal recognition model for recognition, and the manner of obtaining the subcarrier motion signal may specifically include:

[0172] According to the confidence calculation conditions, the confidence region of the first type of energy accumulation result is determined;

[0173] Filter out the target energy that exceeds the confidence region from the first type of energy accumulation results;

[0174] The target energy is input into a preset motion signal recognition model for identification to obtain a motion signal of the subcarrier data. The motion signal of the subcarrier data includes a valid signal and / or an invalid signal. The valid signal is used to indicate that the wireless local area network's perception of the target object's movement state is valid, and the invalid signal is used to indicate that the wireless local area network's perception of the target object's movement state is invalid.

[0175] It can be seen that this optional implementation can also determine the confidence region of the short-term energy accumulation result according to the confidence calculation conditions, and accurately screen out the target energy that overflows the confidence region from the short-term energy accumulation result, and input the accurately screened target energy into the preset motion signal recognition model for identification, so as to accurately obtain the motion signal of the subcarrier data, thereby improving the recognition accuracy of the motion signal.

[0176] In this optional embodiment, as another optional implementation, as Fig.10 As shown, the device may also include:

[0177] A comparison module 304, configured to compare the second type of energy accumulation result with the first type of energy accumulation result to obtain a comparison result when the energy accumulation result of the subcarrier data includes the first type of energy accumulation result and the second type of energy accumulation result;

[0178] The determination module 303 is further used to determine the static existence of the target object in the target area according to the comparison result, and the static existence includes one or more combinations of the number of target objects, the spatial position of the target objects, the shape of the target objects and the surface area of ​​the target objects.

[0179] It can be seen that this optional implementation can obtain a comparison result by comparing the first type of energy accumulation results with the second type of energy accumulation results, and based on the comparison result, accurately determine the static existence of the target object in the target area, thereby improving the accuracy of determining the static existence of the target object.

[0180] In yet another optional embodiment, Fig.10 As shown, the device may also include:

[0181] A preprocessing module 305 is used for inputting the subcarrier data and the preset accumulation time into a predetermined energy accumulation model for energy accumulation calculation before obtaining the energy accumulation result corresponding to the subcarrier data in the calculation module 302, inputting the subcarrier data into a predetermined preprocessing model for preprocessing to obtain the preprocessed subcarrier data, and triggering the calculation module 302 to execute the operation of inputting the subcarrier data and the preset accumulation time into a predetermined energy accumulation model for energy accumulation calculation to obtain the energy accumulation result of the subcarrier data, and the subcarrier data is the preprocessed subcarrier data;

[0182] Among them, the preprocessing model is used to perform signal shaping and / or jitter removal on the subcarrier data through a preset filtering method, and the filtering method includes a combination of one or more of a low-frequency filtering method, a bandpass filtering method, a median filtering method, a pattern filtering method, and an artificial neural network signal filtering method.

[0183] It can be seen that this optional embodiment can preprocess the subcarrier data through a predetermined preprocessing model, accurately obtain the preprocessed subcarrier data, and trigger subsequent energy accumulation calculation of the preprocessed subcarrier data, which can improve the filtering accuracy of the subcarrier data, thereby reducing the impact of clutter on subsequent energy accumulation calculations, and further helps to improve the accuracy of determining the movement state of the target object.

[0184] Embodiment 4

[0185] See also Fig.11 , Fig.11 FIG. 1 is a schematic diagram of the structure of another device for intelligently determining the movement state of an object based on a wireless local area network disclosed in an embodiment of the present invention. Fig.11 As shown, the device for intelligently determining the movement state of an object based on a wireless local area network may include:

[0186] A memory 401 storing executable program codes;

[0187] a processor 402 coupled to the memory 401;

[0188] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the method for intelligently determining the movement state of an object based on a wireless local area network described in the first embodiment of the present invention or the second embodiment of the present invention.

[0189] Embodiment 5

[0190] An embodiment of the present invention discloses a computer storage medium storing computer instructions. When the computer instructions are called, they are used to execute the steps of the method for intelligently determining the movement status of an object based on a wireless local area network described in Embodiment 1 or Embodiment 2 of the present invention.

[0191] Embodiment 6

[0192] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps in the method for intelligently determining the movement status of an object based on a wireless local area network described in embodiment one or embodiment two.

[0193] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0194] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0195] Finally, it should be noted that the method and device for intelligently determining the movement status of an object based on a wireless local area network disclosed in the embodiment of the present invention only discloses a preferred embodiment of the present invention, which is only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions recorded in the aforementioned embodiments can still be modified, or some of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for intelligently determining the movement status of an object based on a wireless local area network, It is characterized in that The method comprises: Collecting subcarrier data corresponding to a target object in a target area based on a wireless local area network, wherein the subcarrier data corresponding to the target object is data reflected and / or absorbed and / or diffracted after a signal is sent to the target area based on the wireless local area network and collides with the target object; Inputting the subcarrier data and the preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtaining an energy accumulation result corresponding to the subcarrier data, wherein the energy accumulation model is used to count the distribution of the change value of the subcarrier data within the accumulation time, and the energy accumulation result is used to represent the channel state characteristics of the wireless local area network for the target object within the accumulation time; The mobile state of the target object is determined based on the energy accumulation result corresponding to the subcarrier data and at least one predetermined state judgment condition, and the state judgment condition is used to indicate whether the current state of the target object meets the channel state characteristics that affect the wireless local area network in the target area.

2. The method for intelligently determining the movement state of an object based on a wireless local area network according to claim 1, It is characterized in that The determining the movement state of the target object according to the energy accumulation result corresponding to the subcarrier data and at least one predetermined state determination condition includes: Calculating the confidence of the energy accumulation result corresponding to the subcarrier data according to a predetermined confidence calculation condition, wherein the confidence is used to indicate the credibility of the probability that the target object moves; Inputting the energy accumulation result corresponding to the subcarrier data and the confidence of the energy accumulation result into a predetermined confidence screening model for screening, and obtaining a target energy accumulation result whose confidence is greater than or equal to a preset confidence; The moving state of the target object is determined according to the target energy accumulation result and at least one predetermined state determination condition.

3. The method for intelligently determining the movement state of an object based on a wireless local area network according to claim 2, It is characterized in that The preset cumulative duration includes a first preset cumulative duration and / or a second preset cumulative duration, and the first preset cumulative duration is less than the second preset cumulative duration; And, the step of inputting the subcarrier data and the preset accumulation duration into a predetermined energy accumulation model to perform energy accumulation calculation to obtain an energy accumulation result corresponding to the subcarrier data includes: Inputting the subcarrier data and the first preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtaining a first type of energy accumulation result corresponding to the subcarrier data, wherein the first type of energy accumulation result is used to indicate that the channel state characteristic of the wireless local area network is a dynamic channel state characteristic; and / or, The subcarrier data and the second preset accumulation time are input into the energy accumulation model to perform energy accumulation calculation, and a second type of energy accumulation result corresponding to the subcarrier data is obtained, wherein the second type of energy accumulation result is used to indicate that the channel state characteristics of the wireless local area network are static channel state characteristics.

4. The method for intelligently determining the movement state of an object based on a wireless local area network according to claim 3, It is characterized in that The step of determining the moving state of the target object according to the target energy accumulation result and at least one predetermined state determination condition includes: When the target energy accumulation result includes the first type of energy accumulation result, determining the variability of the subcarrier data according to the first type of energy accumulation result, the variability being used to evaluate the authenticity of the probability that the target object in the target area moves; Inputting the first type of energy accumulation result into a preset motion signal recognition model for recognition to obtain the motion signal of the subcarrier data; The movement state of the target object is determined according to the variability of the subcarrier data and the motion signal of the subcarrier data.

5. The method for intelligently determining the movement state of an object based on a wireless local area network according to claim 4, It is characterized in that The step of inputting the first type of energy accumulation result into a preset motion signal recognition model for recognition to obtain the motion signal of the subcarrier includes: Determining a confidence region of the first type of energy accumulation result according to the confidence calculation condition; Filter out the target energy that overflows the confidence region from the first type of energy accumulation results; The target energy is input into a preset motion signal recognition model for identification to obtain the motion signal of the subcarrier data, wherein the motion signal of the subcarrier data includes a valid signal and / or an invalid signal, wherein the valid signal is used to indicate that the wireless local area network's perception of the moving state of the target object is valid, and the invalid signal is used to indicate that the wireless local area network's perception of the moving state of the target object is invalid.

6. The method for intelligently determining the movement state of an object based on a wireless local area network according to any one of claims 3 to 5, It is characterized in that The method further comprises: When the energy accumulation result of the subcarrier data includes the first type of energy accumulation result and the second type of energy accumulation result, comparing the second type of energy accumulation result with the first type of energy accumulation result to obtain a comparison result; According to the comparison result, the static existence status of the target object in the target area is determined, and the static existence status includes one or more combinations of the number of the target objects, the spatial position of the target objects, the shape of the target objects and the surface area of ​​the target objects.

7. The method for intelligently determining the movement state of an object based on a wireless local area network according to any one of claims 1 to 5, It is characterized in that Before inputting the subcarrier data and the preset accumulation duration into a predetermined energy accumulation model to perform energy accumulation calculation and obtain an energy accumulation result corresponding to the subcarrier data, the method further includes: Inputting the subcarrier data into a predetermined preprocessing model for preprocessing to obtain preprocessed subcarrier data, and triggering the execution of the operation of inputting the subcarrier data and a preset accumulation time into a predetermined energy accumulation model for energy accumulation calculation to obtain an energy accumulation result of the subcarrier data, the subcarrier data being the preprocessed subcarrier data; Among them, the preprocessing model is used to perform signal shaping and / or jitter removal on the subcarrier data through a preset filtering method, and the filtering method includes a combination of one or more of a low-frequency filtering method, a bandpass filtering method, a median filtering method, a pattern filtering method, and an artificial neural network signal filtering method.

8. A device for intelligently determining the movement status of an object based on a wireless local area network, It is characterized in that The device comprises: A collection module, used for collecting subcarrier data corresponding to a target object in a target area based on a wireless local area network, wherein the subcarrier data corresponding to the target object is data reflected and / or absorbed and / or diffracted after a signal is sent to the target area based on the wireless local area network and collides with the target object; A calculation module, used for inputting the subcarrier data and the preset accumulation time into a predetermined energy accumulation model to perform energy accumulation calculation, and obtaining an energy accumulation result corresponding to the subcarrier data, wherein the energy accumulation model is used for counting the distribution of the change value of the subcarrier data within the accumulation time, and the energy accumulation result is used for representing the channel state characteristics of the wireless local area network for the target object within the accumulation time; A determination module is used to determine the mobile state of the target object based on the energy accumulation result corresponding to the subcarrier data and at least one predetermined state judgment condition, wherein the state judgment condition is used to indicate whether the current state of the target object meets the channel state characteristics that affect the wireless local area network in the target area.

9. A device for intelligently determining the movement status of an object based on a wireless local area network, It is characterized in that The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the method for intelligently determining the movement status of an object based on a wireless local area network as described in any one of claims 1 to 7.

10. A computer storage medium, It is characterized in that The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the method for intelligently determining the movement status of an object based on a wireless local area network as described in any one of claims 1 to 7.

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