CN117647772A - Object motion type detection method, device, computer equipment and storage medium - Google Patents

Abstract

The present application relates to a method, an apparatus, a computer device, a storage medium and a computer program product for detecting a motion class of an object. The method comprises the following steps: acquiring RFID signal data sent by an RFID tag arranged on a target object to be detected in a movement within a preset time interval; acquiring the dispersion of the RFID signal data, and determining that a target object has a motion state in a preset time interval under the condition that the dispersion is larger than a preset dispersion threshold value; acquiring a target time interval in which a target object is in a motion state in a preset time interval; and obtaining the motion state type of the target object according to the ending time point of the target time interval, the first RFID signal data positioned in front of the target time interval in the RFID signal data and the second RFID signal data positioned behind the target time interval. By adopting the method, the motion category of the article can be accurately identified.

Description

Object motion type detection method, device, computer equipment and storage medium

Technical Field

The present application relates to the field of motion detection technology, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for detecting a motion class of an object.

Background

With the development of motion detection technology, a technology of detecting the motion of an object by a passive device appears, and the technology is widely applied to warehouse cargo management. At present, RFID tags are attached to a large number of warehouse materials in the same warehouse environment, and then antennas in the warehouse are used for scanning, so that warehouse materials are counted.

However, in the current situation of goods taking and goods handling in a warehouse, a code scanning machine or a wireless in-out warehouse registration system is mostly used for identification statistics, but no better identification method exists for the movement type of the goods in the warehouse.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a method, an apparatus, a computer device, a computer-readable storage medium, and a computer program product for detecting a motion class of an object, which address the above-mentioned technical problem that there is no better method for identifying a motion class of an object in a warehouse.

In a first aspect, the present application provides a method for detecting a motion class of an object, including:

acquiring RFID signal data sent by an RFID tag arranged on a target object to be detected in a movement within a preset time interval;

acquiring the dispersion of the RFID signal data, and determining that the target object has a motion state in the preset time interval under the condition that the dispersion is larger than a preset dispersion threshold value;

Acquiring a target time interval in which the target object is in a motion state in the preset time interval;

and obtaining the motion state type of the target object according to the ending time point of the target time interval, the first RFID signal data positioned in front of the target time interval in the RFID signal data and the second RFID signal data positioned behind the target time interval.

In one embodiment, the obtaining the motion state type of the target object according to the ending time point of the target time interval, the first RFID signal data located before the target time interval in the RFID signal data, and the second RFID signal data located after the target time interval includes: acquiring an ending time point of the preset time interval; determining the motion state type of the target object as a first motion state type representing that the target object is taken under the condition that the ending time point of the target time interval is positioned before the ending time point of the preset time interval; and under the condition that the ending time point of the target time interval is the same as the ending time point of the preset time interval, obtaining the motion state type of the target object according to the first RFID signal data and the second RFID signal data.

In one embodiment, the RFID signal data is acquired by non-overlapping antennas in at least two spaces; the obtaining the motion state category of the target object according to the first RFID signal data and the second RFID signal data includes: according to the first RFID signal data and the second RFID signal data acquired by each antenna, the change degree of the RFID signal data acquired by each antenna is obtained; under the condition that the change degree of each RFID signal data is smaller than or equal to a preset change degree threshold value, determining the motion state type of the target object as a second motion state type representing that the target object is shielded; and under the condition that the change degree of the RFID signal data collected by any antenna is larger than the preset change degree threshold, determining the motion state type of the target object as a third motion state type representing that the target object is moved.

In one embodiment, after the acquiring the dispersion of the RFID signal data, the method further includes: and under the condition that the dispersion is smaller than or equal to the preset dispersion threshold value, determining that the target object is in a static state in the preset time interval.

In one embodiment, the acquiring the dispersion of the RFID signal data includes: performing smoothing processing on the RFID signal data to obtain smoothed RFID signal data; the smoothing process includes: any one of a moving average smoothing process and a gaussian smoothing process; and acquiring the moving standard deviation of the smoothed RFID signal data, and taking the moving standard deviation as the dispersion of the RFID signal data.

In one embodiment, the RFID signal data includes intensity data and phase data of an RFID signal transmitted by the RFID tag in a preset time interval; the acquiring the dispersion of the RFID signal data, and determining that the target object has a motion state in the preset time interval if the dispersion is greater than a preset dispersion threshold value, includes: acquiring the dispersion of the intensity data and the dispersion of the phase data; and determining that the target object has a motion state in the preset time interval under the condition that the dispersion of the intensity data is larger than a preset intensity dispersion threshold value or the dispersion of the phase data is larger than a preset phase dispersion threshold value.

In a second aspect, the present application further provides a motion class detection device for an object, including:

the data acquisition module is used for acquiring RFID signal data sent by the RFID tag arranged on the target object to be detected in a movement within a preset time interval;

the motion state determining module is used for acquiring the dispersion of the RFID signal data and determining that the target object has a motion state in the preset time interval under the condition that the dispersion is larger than a preset dispersion threshold value;

the time interval acquisition module is used for acquiring a target time interval in which the target object is in a motion state in the preset time interval;

and the motion type judging module is used for obtaining the motion state type of the target object according to the ending time point of the target time interval, the first RFID signal data positioned in front of the target time interval in the RFID signal data and the second RFID signal data positioned behind the target time interval.

In a third aspect, the present application also provides a computer device comprising a memory storing a computer program and a processor implementing the method according to any one of the embodiments of the present application when the computer program is executed.

In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of any of the embodiments of the present application for motion class detection of an object.

In a fifth aspect, the present application also provides a computer program product comprising a computer program which, when executed by a processor, performs the detection of a motion class of an object of the method according to any of the embodiments of the present application.

The method, the device, the computer equipment, the storage medium and the computer program product for detecting the motion category of the object have the following beneficial effects in the process of detecting the motion category of the object: firstly, acquiring RFID signal data transmitted by an RFID tag arranged on a target object to be detected in a movement within a preset time interval; then acquiring the dispersion of the RFID signal data, and determining that a target object has a motion state in a preset time interval under the condition that the dispersion is larger than a preset dispersion threshold value; acquiring a target time interval in which the target object is in a motion state in a preset time interval; and finally, obtaining the motion state type of the target object according to the ending time point of the target time interval, the first RFID signal data before the target time interval in the RFID signal data and the second RFID signal data after the target time interval. According to the scheme, signal data sent by the RFID tag in the preset time interval are obtained, then the dispersion of the RFID signal data is obtained, when the dispersion of the RFID signal data is larger than a threshold value, the movement state of a target object in the preset time interval is determined, then the target time interval in which the target object is in the movement state is obtained, and the movement state type of the target object is analyzed and obtained according to the ending time point of the target time interval, the first RFID signal data and the second RFID signal data, so that the real-time monitoring and classification of the movement state type of the target object are realized.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for a person having ordinary skill in the art.

FIG. 1 is a diagram of an application environment for a method of motion class detection of an object in one embodiment;

FIG. 2 is a flow chart of a method for detecting a motion class of an object in one embodiment;

FIG. 3 is a schematic flow chart of a method for detecting a motion class of an object to obtain a motion state class of the target object in one embodiment;

FIG. 4 is a schematic flow chart of a method for detecting a motion class of an object according to another embodiment;

FIG. 5 is a flow chart of a method for detecting a motion class of an object to obtain dispersion of RFID signal data in one embodiment;

FIG. 6 is a schematic flow chart of a method for detecting a motion class of an object according to an embodiment, wherein the method determines that a motion state exists in a target object within a preset time interval;

FIG. 7 is a flow chart of a motion class detection step of an object in one embodiment;

FIG. 8 is a schematic diagram of antenna and RFID tag deployment for a method of motion class detection of an object in one embodiment;

FIG. 9 is a discrete data plot of single antenna versus RFID tag location data for a method of motion class detection of an object in one embodiment;

FIG. 10 is a schematic diagram of RFID data of a method for detecting a motion class of an object before convolution smoothing using a Gaussian method in a period in one embodiment;

FIG. 11 is a schematic diagram of RFID data of a method for detecting a motion class of an object according to an embodiment after convolution smoothing using a Gaussian method in a period;

FIG. 12 is a discrete data plot of dual antenna versus RFID tag location data for a method of motion class detection of an object in one embodiment;

FIG. 13 is a schematic diagram of a determination flow of a method for detecting a motion class of an object in one embodiment;

FIG. 14 is a block diagram of a motion class detection device for an object in one embodiment;

fig. 15 is an internal structural view of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

The method for detecting the motion category of the object, provided by the embodiment of the application, can be applied to an application environment shown in fig. 1. Wherein the terminal 102 communicates with the RFID tag 104 using an antenna. The data storage system may store data that needs to be processed. Firstly, a terminal 102 acquires RFID signal data sent by an RFID tag arranged on a target object to be detected in a movement within a preset time interval; then acquiring the dispersion of the RFID signal data, and determining that a target object has a motion state in a preset time interval under the condition that the dispersion is larger than a preset dispersion threshold value; acquiring a target time interval in which the target object is in a motion state in a preset time interval; and finally, obtaining the motion state type of the target object according to the ending time point of the target time interval, the first RFID signal data before the target time interval in the RFID signal data and the second RFID signal data after the target time interval. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices, and portable wearable devices, where the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart vehicle devices, and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like.

In an exemplary embodiment, as shown in fig. 2, a method for detecting a motion class of an object is provided, and the method is applied to the terminal 102 in fig. 1 for illustration, and includes the following steps 202 to 208. Wherein:

step 202, acquiring RFID signal data sent by an RFID tag arranged on a target object to be detected in a movement within a preset time interval.

The RFID tag is a UHF RFID (ultra high frequency passive radio frequency) tag and is widely used for warehouse management; the preset time interval refers to a time period set in advance.

Specifically, the scanner for reading the signal emitted by the RFID tag is an industrial control integrated machine of the UHF tag scanner, and UHF signals can be received and transmitted after being connected with the UHF antenna. RFID tags may be data transmitted and identified by radio signals without direct contact. The preset time interval can be set according to specific requirements and scenes, for example, an hour, a day or a week, and the like, and the motion detection and the data acquisition of the target object are performed in the preset time interval.

Step 204, acquiring the dispersion of the RFID signal data, and determining that the target object has a motion state in a preset time interval under the condition that the dispersion is larger than a preset dispersion threshold value.

The dispersion refers to the dispersion degree of a group of data, and can be measured by calculating standard deviation or variance, and the preset dispersion threshold refers to a preset value during RFID tag data processing, which is used for judging whether the dispersion degree of RFID tag signal data reaches a certain expected level.

Specifically, the dispersion is used to analyze the degree of change in the RFID signal data to determine whether the target object is in motion.

Step 206, obtaining a target time interval in which the target object is in a motion state within a preset time interval.

The target time interval refers to a time period when the target object is in a motion state, and can be obtained through analysis and processing of RFID signal data. Within the target time interval, the motion state and behavior of the target object may be determined.

Step 208, obtaining the motion state type of the target object according to the ending time point of the target time interval, the first RFID signal data before the target time interval in the RFID signal data, and the second RFID signal data after the target time interval.

The first RFID signal data refer to the intensity and phase data of the target object before starting movement, and the second RFID signal data refer to the intensity and phase data of the target object after finishing movement; the motion state category refers to dividing the motion state of the target object into different categories, such as static, shielding, moving and the like, according to the ending time point of the target time interval and the change condition of front and rear RFID signal data.

In the method for detecting the motion category of the object, RFID signal data sent by an RFID tag arranged on a target object to be detected in a motion mode in a preset time interval is firstly obtained; then acquiring the dispersion of the RFID signal data, and determining that a target object has a motion state in a preset time interval under the condition that the dispersion is larger than a preset dispersion threshold value; acquiring a target time interval in which the target object is in a motion state in a preset time interval; and finally, obtaining the motion state type of the target object according to the ending time point of the target time interval, the first RFID signal data before the target time interval in the RFID signal data and the second RFID signal data after the target time interval. According to the scheme, signal data sent by the RFID tag in the preset time interval are obtained, then the dispersion of the RFID signal data is obtained, when the dispersion of the RFID signal data is larger than a threshold value, the movement state of a target object in the preset time interval is determined, then the target time interval in which the target object is in the movement state is obtained, and the movement state type of the target object is analyzed and obtained according to the ending time point of the target time interval, the first RFID signal data and the second RFID signal data, so that the real-time monitoring and classification of the movement state type of the target object are realized.

In an exemplary embodiment, the obtaining the motion state type of the target object according to the ending time point of the target time interval, the first RFID signal data before the target time interval in the RFID signal data, and the second RFID signal data after the target time interval, as shown in fig. 3, includes:

s302, acquiring an ending time point of a preset time interval.

The ending time point refers to an ending time point of the preset time interval.

Specifically, the preset time interval is used for detecting the motion of the target object and collecting data, and the ending time point marks the end of the preset time interval. First, a specific time range of a preset time interval is required to be defined, and then an ending time point of the time range is acquired.

S304, determining the motion state type of the target object as a first motion state type representing that the target object is taken under the condition that the ending time point of the target time interval is before the ending time point of the preset time interval.

Specifically, when the ending time point of the target time interval is earlier than the ending time point of the preset time interval, the motion state type of the target object can be judged to be a first motion state type representing that the target object is taken, which indicates that the target object is taken in the preset time interval.

S306, under the condition that the ending time point of the target time interval is the same as the ending time point of the preset time interval, the motion state type of the target object is obtained according to the first RFID signal data and the second RFID signal data.

The first RFID signal data refer to initial signal data of the RFID tag of the target object in the target time interval, and the second RFID signal data refer to signal data after the RFID tag of the target object in the target time interval generates motion.

In this embodiment, when the ending time point of the target time interval is the same as the ending time point of the preset time interval, the confirmation of the motion state type of the target object is completed through the first RFID signal data and the second RFID signal data. By analyzing the first RFID signal data and the second RFID signal data, the motion state type of the target object can be deduced, so that the motion state type of the target object can be accurately monitored and classified.

In an exemplary embodiment, the RFID signal data is acquired by at least two antennas that are not overlapped in space; the obtaining the motion state category of the target object according to the first RFID signal data and the second RFID signal data, as shown in fig. 4, includes:

S402, according to the first RFID signal data and the second RFID signal data acquired by each antenna, the change degree of the RFID signal data acquired by each antenna is obtained.

Wherein the antenna refers to a means for receiving and transmitting RFID signals; the RFID signal data refers to data sent by an RFID tag, and comprises identification information and other related information of the tag; the degree of change refers to whether the RFID signal data has obvious change before moving relative to the target object at different time points or different positions, and the reference value of the obvious degree can be the percentage of the target object before the relative movement, so as to judge the movement state of the target object.

S404, determining the motion state type of the target object as a second motion state type representing that the target object is blocked under the condition that the change degree of each RFID signal data is smaller than or equal to a preset change degree threshold value.

The preset change degree threshold value refers to a preset threshold value of the change degree of the RFID signal data and is used for judging the motion state of the target object; the second occluded state of motion category refers to the state of motion category in which the target object is due to occlusion.

Specifically, when the degree of change of each RFID signal data is less than or equal to the preset degree of change threshold, the motion state type of the target object may be determined as the second motion state type representing that the target object is blocked.

S406, determining the motion state type of the target object as a third motion state type representing that the target object is moved under the condition that the change degree of the RFID signal data acquired by any antenna is larger than a preset change degree threshold value.

The moved third motion state category refers to a motion state category of the target object due to being moved.

Specifically, when the degree of change of the RFID signal data collected by any antenna is greater than a preset degree of change threshold, the motion state type of the target object may be determined as a third motion state type representing that the target object is moved.

In the embodiment, automatic monitoring and classification are realized by quantifying and analyzing the change degree of the data, the labor cost is reduced, and the RFID technology can realize real-time monitoring and recording of the position and the state of the object and more accurately judge the motion state of the target object.

In one embodiment, after the acquiring the dispersion of the RFID signal data, the method further includes: and under the condition that the dispersion is smaller than or equal to a preset dispersion threshold value, determining that the target object is in a static state in a preset time interval.

In this embodiment, the motion state of the target object can be more accurately determined by analyzing and judging the dispersion of the RFID signal data, and more reliable data support is provided for judging the motion state type of the target object.

Further, in one embodiment, the acquiring the dispersion of the RFID signal data, as shown in fig. 5, includes:

s502, performing smoothing on the RFID signal data to obtain smoothed RFID signal data; the smoothing process includes: any one of a moving average smoothing process and a gaussian smoothing process.

The moving average smoothing process is to calculate a group of data arranged according to time sequence or sequence, calculate an average value by taking a data width interval n, and let the following data enter and the front data exit in the calculation process so as to ensure that the data width interval used for calculating the average value is constant to n. The gaussian smoothing is a derivative of the moving average smoothing, and the data in the moving average smoothing is weighted to conform to normal distribution. And the method is consistent with the processing of moving average smoothing, the average value is calculated by taking the data width interval n in the process of calculating the average value, the subsequent data is allowed to enter in the process of calculating, and the front data is exited, wherein the difference is that n data are normally weighted, the data weight close to the center of the interval is high, the data weight close to the edge is low, and the front and rear weight distribution accords with the normal distribution.

S504, obtaining the moving standard deviation of the RFID signal data after the smoothing processing, and taking the moving standard deviation as the dispersion of the RFID signal data.

The moving standard deviation refers to data used for counting deviation between a data sequence and a mean value of the data sequence, and the standard deviation is calculated on the data in a data width interval n in a sliding mode to obtain a relatively real-time standard deviation.

In the embodiment, the acquired RFID signal data is subjected to smoothing processing to reduce noise and fluctuation in the data, so that more stable data is obtained, and the fluctuation condition of the RFID signal data can be reflected more accurately by taking the moving standard deviation as a dispersion index, so that the motion state of the target object is judged, the data can be effectively processed and analyzed, and a reliable data base is provided for the subsequent judgment of the motion state type of the target object.

In one embodiment, the RFID signal data includes intensity data and phase data of an RFID signal transmitted by the RFID tag in a preset time interval; the acquiring the dispersion of the RFID signal data, and determining that the target object has a motion state in the preset time interval if the dispersion is greater than the preset dispersion threshold, as shown in fig. 6, includes:

s602, acquiring the dispersion of the intensity data and the dispersion of the phase data;

Specifically, after the intensity data and the phase data in the RFID signal data are combined, the motion state type of the target object needs to be comprehensively judged. If the judgment is carried out only according to the intensity data, the precision is low, when the medium between the RFID tag and the antenna is changed, the change amount of the intensity data is small, and the type of the motion state of the target object cannot be judged rapidly, so that the judgment is carried out together by relying on the phase data; if the judgment is only performed according to the phase data, and when the target object moves to the periodic point, the motion state type of the target object cannot be judged, and the judgment is performed by referring to the intensity data.

S604, determining that the target object has a motion state in a preset time interval when the dispersion of the intensity data is greater than a preset intensity dispersion threshold or the dispersion of the phase data is greater than a preset phase dispersion threshold.

Specifically, in the plurality of RFID tags, it may be determined that the target object has a motion state if the dispersion of the intensity data in the acquired RFID signal data is greater than a threshold value or the dispersion of the phase data is greater than a threshold value.

In this embodiment, the dispersion degree of the intensity data and the dispersion degree of the phase data are calculated, so that the dispersion degree of the two data can be obtained respectively, the fluctuation condition and the change trend of the signal can be known, the dispersion degree of the intensity data and the dispersion degree of the phase data can be analyzed, and the motion state of the target object can be determined more accurately by combining a preset dispersion degree threshold value.

In order to better understand the above-mentioned process of detecting the motion category of the object, a specific flow of detecting the motion category of the object of the present application is described in detail below with reference to fig. 7, which includes the following steps:

s702, disposing an antenna and an RFID tag in an area to be positioned.

As shown in fig. 8, two antennas with non-repeating positions are provided, the transmitting frequency of the antennas is set to be a unique fixed value, the fixed frequency is 922.250MHz, the data information on the RFID tag is read, and the reading speed is set to be 5Hz. The read data is formatted, and five variables of time, tag ID, strength RSSI, phase and antenna serial number are separated. Data processing is carried out according to the antenna serial numbers and the time, the scanning time of the two antennas is aligned, and time dislocation is prevented; and separating the data according to the antenna serial numbers, and putting all the data under the same antenna together.

S704, acquiring and processing phase data and intensity data of the RFID tag on the target object to be detected in a moving mode.

Electromagnetic waves emitted by the RFID tag physically have three key physical parameters of frequency, intensity and phase, and when the electromagnetic waves are received by the tag scanner, the specific values of the intensity and the phase of the electromagnetic waves can be detected by the RFID tag scanner. The frequency is fixed frequency, and the fixed frequency is selected to influence the phase judgment; the intensity is directly related to the distance between the RFID tag and the antenna, and is influenced by shielding; the phase is related to the propagation path length of the electromagnetic wave between the tag and the antenna and the medium on the path.

For any static RFID tag, the intensity and phase information read by the antenna in a scanning way are constant, and when a moving object exists around the object or is manually moved, the intensity and phase of electromagnetic waves emitted by the RFID tag are interfered. When interfered, the intensity and phase of the received electromagnetic wave change from a single value at rest to a random discrete value. After the artificial activity (picking up the tag or walking around the tag) is completed, if the antenna can scan the tag as well, its intensity and phase will settle to another stable value. When multiple antennas exist, the responses of different antennas to motion are completely different, and the movement condition of an object can be directly judged by utilizing the antenna responses of different spaces through the phenomenon, as shown in the table 1.

TABLE 1 identification of RFID tag information by a single antenna

In table 1, P is a measured phase value, R is a measured intensity value, and Px and Rx represent a state of uncertainty of a specific value, because the intensity and phase value of the RFID tag change randomly due to factors such as space state of the tag and refraction and reflection of electromagnetic wave during the process of shielding or moving the RFID tag, and the data is discrete in a period of time, as shown in fig. 9.

S706, smoothing the phase data and the intensity data, and obtaining two groups of smoothed data of intensity and phase by using a moving average smoothing method.

And the RFID tag is scanned in a high density mode in a fixed period, the scanning frequency is 5-30 Hz, and the higher the scanning frequency is, the better the strength and phase information of the read tag are. Before the data in the period is convolved and smoothed by using a Gaussian method, as shown in fig. 10, the smoothed data is subjected to Fourier analysis by using a fast Fourier method, noise frequencies are searched by using the obtained frequency data, and the noise frequency band is subjected to filtering processing by using a simple filter, so that smoothed data in an input signal is obtained. Whether the signal intensity and the phase of the object are effectively changed or not can be judged, and when the change is found, the collected data is judged through multiple antennae at the same time, and whether the object is moved or shielded is declared.

S708, the raw data of the two antennas are used to make moving standard deviations, the obtained standard deviation data are smoothed, and the moving average is used to smooth, so as to obtain two groups of dispersion smoothed data.

All the movement cases are covered in the table above and are different from each other. In terms of time, different situations can occur in a period of sampling time, but each motion condition is independently analyzed, and each possible state is found to be an independent state, which is the basis for the motion judgment to be independently judged, namely, the logic deduction can be carried out:

For example, after sampling the intensity and phase data of an RFID, it is found that the intensity and phase of the tag stabilize at two unequal intensity and phase values P1+notep2, R1 is not equal to R2, namely that the object is moved to another position or is blocked by a certain object; for another example, after sampling the intensity and phase data of a section of RFID, it is found that the intensity and phase of the object tag are respectively stable, and the object tag is suddenly and randomly dithered until the sampling is finished, which can indicate that the object is taken, or that the object having motion all around the object has random interference on its signal, as shown in table 2:

table 2 identification of RFID tag information by two antennas

As shown in fig. 12, the phase change and intensity change data of the one-time taking action of the dual antennas can be observed through the scanning gap to obtain three moving actions of the object, and the blocked and moved positions can be obtained to have completely different characteristics on the data expression of the two antennas, and when the motion judgment is carried out, the two days are analyzed

The intensity and phase data of the line can fully infer the motion state of the object.

S710, comparing the relation between the dispersion and the threshold value, and judging the motion type of the target object.

And setting a dispersion judgment threshold value, and judging that the target object has a moving or shielding action in the antenna direction when the dispersion of a certain antenna exceeds the threshold value, and regarding the time period exceeding the threshold value as a motion state. And comparing the intensity and the phase value before and after the motion state appears by a program to obtain whether the tag is moved. Then comparing whether the other antenna moves or not in the same time, and judging whether the object is moved or shielded or not by judging whether the intensity and the phase value detected by the antenna are consistent with those before the movement; if the motion state continues until the scanning is finished, the label is considered to continue to move. By judging electromagnetic wave parameters (intensity data and phase data) of the RFID tag, and judging the variation and dispersion of the two physical data by moving average value and moving standard deviation, the state around the target object can be judged, and the type of the motion state of the target object is identified as shielding, moving or being taken. The determination procedure is shown in fig. 13.

Through the embodiment, the plurality of antennas scan the same tag at the same time, so that the scanning values of different antennas for the signal intensity and the phase of the tag at the same time can be obtained. For each point in space, the antenna has different scanning intensity, when the shielding exists on the label path or the object exists, the intensity and the phase change in the direction of one or more antennas, and the motion condition of the object can be comprehensively judged by identifying the change condition of each antenna.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides a motion category detection device for an object, which is used for realizing the motion category detection method of the object. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the motion class detection device for one or more objects provided below may refer to the limitation of the motion class detection method for an object described above, which is not repeated here.

In an exemplary embodiment, as shown in fig. 14, there is provided a motion class detection apparatus of an object, including: a data acquisition module 1401, a motion state determination module 1402, a time interval acquisition module 1403, and a motion class determination module 1404, wherein:

the data acquisition module 1401 is configured to acquire RFID signal data sent by an RFID tag disposed on a target object to be motion detected within a preset time interval.

The motion state determining module 1402 is configured to obtain a dispersion of the RFID signal data, and determine that the target object has a motion state within a preset time interval if the dispersion is greater than a preset dispersion threshold.

The time interval obtaining module 1403 is configured to obtain a target time interval in which the target object is in a motion state within a preset time interval.

The motion type determining module 1404 is configured to obtain a motion state type of the target object according to an end time point of the target time interval, first RFID signal data located before the target time interval in the RFID signal data, and second RFID signal data located after the target time interval.

In one embodiment, the motion class determination module 1404 is further configured to obtain an end time point of the preset time interval; determining the motion state type of the target object as a first motion state type representing that the target object is taken under the condition that the ending time point of the target time interval is positioned before the ending time point of the preset time interval; and under the condition that the ending time point of the target time interval is the same as the ending time point of the preset time interval, obtaining the motion state type of the target object according to the first RFID signal data and the second RFID signal data.

In one embodiment, the data obtaining module 1401 is further configured to obtain a degree of change of the RFID signal data collected by each antenna according to the first RFID signal data and the second RFID signal data collected by each antenna; under the condition that the change degree of each RFID signal data is smaller than or equal to a preset change degree threshold value, determining the motion state type of the target object as a second motion state type representing that the target object is shielded; and under the condition that the change degree of the RFID signal data collected by any antenna is larger than a preset change degree threshold, determining the motion state type of the target object as a third motion state type representing that the target object is moved.

In one embodiment, the motion state determining module 1402 is further configured to determine that the target object is in a stationary state within a preset time interval if the dispersion is less than or equal to a preset dispersion threshold.

In one embodiment, the motion state determining module 1402 is further configured to perform smoothing on the RFID signal data to obtain smoothed RFID signal data; the smoothing process includes: any one of a moving average smoothing process and a gaussian smoothing process; and acquiring the moving standard deviation of the smoothed RFID signal data, and taking the moving standard deviation as the dispersion of the RFID signal data.

In one embodiment, the motion state determining module 1402 is further configured to obtain a dispersion of intensity data and a dispersion of phase data; and determining that the target object has a motion state in a preset time interval under the condition that the dispersion of the intensity data is larger than a preset intensity dispersion threshold value or the dispersion of the phase data is larger than a preset phase dispersion threshold value.

The respective modules in the above-described object motion class detection device may be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one exemplary embodiment, a computer device is provided, which may be a server, and the internal structure thereof may be as shown in fig. 15. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing motion class detection data of the object. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of detecting a motion class of an object.

It will be appreciated by those skilled in the art that the structure shown in fig. 15 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the computer device to which the present application is applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

In an exemplary embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor performing the steps of the method embodiments described above when the computer program is executed.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method embodiments described above.

In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.

It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use, and processing of the related data are required to meet the related regulations.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims (10)

1. A method for detecting a motion class of an object, the method comprising:

acquiring RFID signal data sent by an RFID tag arranged on a target object to be detected in a movement within a preset time interval;

acquiring the dispersion of the RFID signal data, and determining that the target object has a motion state in the preset time interval under the condition that the dispersion is larger than a preset dispersion threshold value;

Acquiring a target time interval in which the target object is in a motion state in the preset time interval;

and obtaining the motion state type of the target object according to the ending time point of the target time interval, the first RFID signal data positioned in front of the target time interval in the RFID signal data and the second RFID signal data positioned behind the target time interval.

2. The method according to claim 1, wherein the obtaining the motion state category of the target object according to the end time point of the target time interval, the first RFID signal data before the target time interval in the RFID signal data, and the second RFID signal data after the target time interval includes:

acquiring an ending time point of the preset time interval;

determining the motion state type of the target object as a first motion state type representing that the target object is taken under the condition that the ending time point of the target time interval is positioned before the ending time point of the preset time interval;

and under the condition that the ending time point of the target time interval is the same as the ending time point of the preset time interval, obtaining the motion state type of the target object according to the first RFID signal data and the second RFID signal data.

3. The method of claim 2, wherein the RFID signal data is acquired by non-overlapping antennas in at least two spaces; the obtaining the motion state category of the target object according to the first RFID signal data and the second RFID signal data includes:

according to the first RFID signal data and the second RFID signal data acquired by each antenna, the change degree of the RFID signal data acquired by each antenna is obtained;

under the condition that the change degree of each RFID signal data is smaller than or equal to a preset change degree threshold value, determining the motion state type of the target object as a second motion state type representing that the target object is shielded;

and under the condition that the change degree of the RFID signal data collected by any antenna is larger than the preset change degree threshold, determining the motion state type of the target object as a third motion state type representing that the target object is moved.

4. The method of claim 1, wherein after the obtaining the dispersion of the RFID signal data, further comprising:

and under the condition that the dispersion is smaller than or equal to the preset dispersion threshold value, determining that the target object is in a static state in the preset time interval.

5. The method of claim 1, wherein said obtaining a dispersion of said RFID signal data comprises:

performing smoothing processing on the RFID signal data to obtain smoothed RFID signal data; the smoothing process includes: any one of a moving average smoothing process and a gaussian smoothing process;

and acquiring the moving standard deviation of the smoothed RFID signal data, and taking the moving standard deviation as the dispersion of the RFID signal data.

6. The method of claim 1, wherein the RFID signal data comprises intensity data and phase data of an RFID signal transmitted by the RFID tag during a preset time interval; the acquiring the dispersion of the RFID signal data, and determining that the target object has a motion state in the preset time interval if the dispersion is greater than a preset dispersion threshold value, includes:

acquiring the dispersion of the intensity data and the dispersion of the phase data;

and determining that the target object has a motion state in the preset time interval under the condition that the dispersion of the intensity data is larger than a preset intensity dispersion threshold value or the dispersion of the phase data is larger than a preset phase dispersion threshold value.

7. A motion class detection device for an object, the device comprising:

the data acquisition module is used for acquiring RFID signal data sent by the RFID tag arranged on the target object to be detected in a movement within a preset time interval;

the motion state determining module is used for acquiring the dispersion of the RFID signal data and determining that the target object has a motion state in the preset time interval under the condition that the dispersion is larger than a preset dispersion threshold value;

the time interval acquisition module is used for acquiring a target time interval in which the target object is in a motion state in the preset time interval;

and the motion type judging module is used for obtaining the motion state type of the target object according to the ending time point of the target time interval, the first RFID signal data positioned in front of the target time interval in the RFID signal data and the second RFID signal data positioned behind the target time interval.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.