CN112085134B - Airport luggage identification system and method based on radio frequency identification - Google Patents
Airport luggage identification system and method based on radio frequency identification Download PDFInfo
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Abstract
The invention provides an airport luggage identification method and system based on RFID (radio frequency identification devices), which are used for solving the problems that airport luggage identification is inaccurate and cannot be identified when phases are lost in the prior art. According to the luggage identification method, the RFID reader-writer records reading time and phase information, the DI light control module controls the snapshot camera based on judgment of whether luggage passes through or not, the luggage is photographed, and a time window of the luggage passing through the antenna is calculated; when the phase information is normal, calculating the zero point moment of the current luggage, matching and binding the luggage photo corresponding to the zero point, and displaying the luggage information and the photo; and when the data is abnormal, eliminating the abnormal phase, judging that the matching fails, and only displaying the current luggage information. The method solves the problem of airport luggage identification when abnormal conditions such as inaccurate phase information acquisition, no phase data set passing through zero point and the like occur, accurately calculates the zero point time, improves the accuracy of calculating the zero point time, and improves the luggage matching accuracy and the working efficiency.
Description
Technical Field
The invention belongs to the field of radio frequency identification and baggage tracking, and particularly relates to an airport baggage identification system and method based on radio frequency identification.
Background
Radio Frequency Identification (RFID) is a non-contact Identification technology based on an electronic tag and a reader/writer, and is widely applied to the fields of logistics, aviation, identity Identification and the like. Wherein the package tracking of the aviation passengers is also realized by RFID. An RFID system on an airport baggage carousel provides the correct baggage information for upper applications by identifying and sequencing RFID tags that pass through the baggage. Accurate tracking of baggage is only ensured when tag identification and sequencing are both correct.
In the prior art, when the RFID system finishes collecting the baggage data on the conveyer belt, the tags are generally identified and sorted based on the inverse synthetic aperture radar technology. The inverse synthetic aperture radar method sequences tags based on the phase of the dynamic tag (reader antenna stationary) return signal. However, when the phase data of the baggage collected by the system is not complete, for example, the computed zero point time is inaccurate due to the periodic ambiguity of the phase, because the signal blocks the phase data only traveling to the zero point position, or only the phase data far away from the zero point position, or the phase data separating the baggage from the conveyor belt in the read-only area of the reader-writer antenna, or due to human intervention; meanwhile, when the baggage flows from the main conveyor to the branch conveyor to its unpacking process, a discontinuity of the phase is also caused.
Fig. 1 is a schematic diagram of the operation of a prior art RFID system on an airport baggage conveyor. As shown in fig. 1, when the reader/writer of the RFID system reads the tag of the article C directly facing the antenna on the conveyor belt through the antenna, the luggage C is located closest to the reader/writer antenna, and is the zero point of the luggage C, and this time is the zero point time of the luggage C. However, since the receiving range of the antenna is wide, when the distance between the luggage is short, the tags of the articles B and D before and after C may be read, and thus it is impossible to know which tag is currently facing the antenna and the information of the article to which the tag is attached, thereby causing an operation error.
When the phase information acquisition is inaccurate, the problems of luggage data matching error, inaccurate zero point time calculation and the like can be caused. And for the phase data set which does not pass through the zero point, the zero point moment cannot be calculated, the labels on the luggage cannot be identified or the sorting is wrong, so that the luggage sorting error on the conveyor belt is caused.
Disclosure of Invention
In view of the above defects in the prior art, embodiments of the present invention provide a system and a method for identifying airport baggage based on radio frequency identification, which improve the accuracy of zero point resolving, and further improve the correct matching rate of baggage and baggage photo.
In order to achieve the above purpose, the embodiment of the invention adopts the following technical scheme:
in a first aspect, an embodiment of the present invention provides an RFID-based airport baggage identification method, where the RFID-based airport baggage identification method includes the following steps:
step S1, when the luggage passes through the identification area of the RFID antenna from the conveyor belt, the RFID reader-writer reads the RFID label information of the current luggage for many times through the RFID antenna, and records the reading time and the phase information;
step S2, the DI light control module arranged at the antenna judges whether luggage passes through, when luggage passes through, the process goes to step S3; when no luggage passes, the process proceeds to step S5;
step S3, the DI light control module triggers the snapshot camera to take a picture of the luggage, and the time window [ t ] of the luggage passing through the RFID antenna is calculated according to the interval of the luggage triggering the DI light control module1,t2]；
Step S4, the time window [ t ]1,t2]Adding the data into a cache array;
step S5, the RFID reader-writer judges whether the phase information of the label can not be read in a preset time period; if yes, the step S6 is executed, otherwise, the reading time and the phase information are continuously recorded, and the step S1 is executed;
step S6, preprocessing the reading time and phase information, and judging whether the data is abnormal; when there is an abnormality in the data, proceed to step S10; when the data is normal, proceed to step S7;
step S7, calculating the zero point time t of the current luggage0；
Step S8, judging the zero point time t of the current luggage0Whether the time window is in the corresponding time window in the cache array; if the corresponding time window exists in the cache array, judging that the luggage corresponding to the zero point has a corresponding luggage photo, and entering step S9, otherwise, judging that the corresponding luggage photo does not exist, and entering step S10;
step S9, binding the RFID label information of the luggage to which the zero point belongs with the corresponding photo, and displaying the photo and the luggage information;
in step S10, if it is determined that the matching has failed, the current baggage information is displayed.
In the foregoing solution, the step S6 of determining whether the data is abnormal further includes the following steps:
step S61, calculating a correlation coefficient r of the reading time and the phase information;
step S62, judging whether the absolute value of the correlation coefficient r is smaller than sf _ thr; if the phase data is smaller than sf _ thr, judging that the phase data is normal; otherwise, go to step S63; wherein sf _ thr is a correlation coefficient threshold;
step S63, calculating precision Sy of the regression equation according to the correlation coefficient r;
step S64, calculating a quadratic term coefficient a after quadratic curve fitting by using a least square method;
step S65, determine whether the inequality Sy > syc _ thr and a <0 holds; if yes, determining that the phase data is normal; if the equality is not satisfied, judging that the phase data is abnormal, and rejecting the phase data; wherein syc _ thr is the precision threshold.
In the above scheme, the process of calculating the correlation coefficient r is as follows:
unwrapping the phase information and calculating the difference delta phi between adjacent phase pointsiAnd accumulating the phase difference data one by one to obtain all the real phase values phimAs in formula (1):
in the formula (1), f (Delta phi)i) The expression is as follows:
from time data t obtained by the reader/writeriAnd unwrapped phase data phiiCalculating a linear correlation r as shown in formula (3):
in the formula (3), the reaction mixture is,
n is the total number of phase data.
In the above scheme, in the step S65, the trend of the phase data is determined according to the positive and negative of the quadratic term coefficient; if the quadratic term coefficient a is positive, the trend of the phase data is descending first and then ascending; if the quadratic coefficient a is negative, the trend of the phase data is first rising and then falling.
In the scheme, whether the data is abnormal or not is judged in step S6, the phase data is analyzed through a machine learning method, and when the data is abnormal, the abnormal luggage phase data is removed.
In the above scheme, step S7 calculates the zero point time, the movement track and the movement speed of the baggage on the conveyor belt are known, the tag is read many times when the tag reads the area through the reader, and the reading time and the phase information of each time are recorded; and resolving real-time phase information in a position interval corresponding to the time period according to the obtained starting time and the obtained ending time, comparing the real-time phase information with the phase information read by the reader-writer, and finally calculating the time when the label passes through the zero point.
In the above scheme, step S7 uses a real-time phase fingerprint algorithm to calculate the zero point time t of the current baggage0。
In the above scheme, in the real-time phase fingerprint algorithm, the zero point moment of the RFID tag is t0The zero point distance is h, the conveyor speed is known as v, and the x-axis coordinate of the tag read at the ith time is xi＝v(ti-t0) The distance from the antenna is:
the phase difference due to distance is:
for all i, satisfy:
in a second aspect, an embodiment of the present invention further provides an RFID-based airport baggage identification system, where the identification system includes: the system comprises an RFID identification module consisting of an RFID reader-writer, an RFID antenna and an RFID label, a data preprocessing module, a zero point moment resolving module, a DI light control module, a snapshot camera, a data logic binding module and a result display module; wherein,
the RFID antenna is the front end of an RFID reader-writer, is arranged above a conveyor belt for conveying luggage in an airport and is used for reading RFID label information in a conveyor belt identification area;
the reader-writer is connected with the data preprocessing module and used for sending the RFID label information read by the RFID antenna to the data preprocessing module;
the data preprocessing module is connected with the zero point moment resolving module and used for preprocessing the RFID tag data and sending the preprocessed data to the zero point moment resolving module;
the DI light control module is connected with the snapshot camera, and both the DI light control module and the snapshot camera are arranged above the airport luggage conveyer belt and used for controlling the camera to execute snapshot action;
the zero point moment resolving module and the snapshot camera are simultaneously connected with the data logic binding module, and the zero point moment resolving module is used for resolving the preprocessed RFID tag information to obtain the zero point moment of the current luggage and sending the resolved zero point moment to the data logic binding module; the snapshot camera is used for executing snapshot actions according to the instruction of the DI light control module and sending the captured images to the data logic binding module;
the data logic binding module is connected with the result display module and is used for matching the zero point time and the image, executing binding when the matching is successful and sending binding information to the result display module; sending the luggage information to a result display module when the matching fails;
and the result display module is used for displaying the received binding information and/or the received luggage information.
The invention has the following beneficial effects:
the method solves the problem of airport luggage identification when abnormal conditions such as inaccurate phase information acquisition, no phase data set passing through zero point and the like occur, accurately calculates the zero point time, improves the accuracy of calculating the zero point time, and improves the luggage matching accuracy and the working efficiency.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic representation of the operation of a prior art RFID system on an airport baggage conveyor;
FIG. 2 is a schematic flow chart of an RFID-based airport baggage identification method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a data preprocessing flow according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an airport baggage identification system based on RFID in an embodiment of the present invention.
Detailed Description
The technical problems, aspects and advantages of the invention will be apparent from the following detailed description, which proceeds with reference to the accompanying drawings, when taken in conjunction with the accompanying exemplary embodiments. The following exemplary embodiments are merely illustrative of the present invention and are not to be construed as limiting the invention. It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Fig. 2 shows a flowchart of an RFID-based airport baggage identification method according to an embodiment of the present invention. As shown in fig. 2, the method for identifying airport baggage based on RFID includes the following steps:
and step S1, when the luggage passes through the identification area of the RFID antenna from the conveyor belt, the RFID reader-writer reads the RFID label information of the current luggage for multiple times through the RFID antenna, and records the reading time and the phase information.
In this step, the RFID antenna is used as an input terminal of the RFID reader to read information in the RFID tag. The RFID antenna and the RFID reader-writer are arranged on the identification station on the conveyor belt; the RFID tag is attached to the luggage to be identified.
Step S2, the DI light control module arranged at the antenna judges whether luggage passes through, when luggage passes through, the process goes to step S3; when no baggage passes, the process proceeds to step S5. In this step, when luggage passes through, the DI light control module is triggered, so that the luggage is judged to pass through.
Step S3, the DI light control module triggers the snapshot camera to take a picture of the luggage, and the time window [ t ] of the luggage passing through the RFID antenna is calculated according to the interval of the luggage triggering the DI light control module1,t2]。
Step S4, the time window [ t ]1,t2]And adding the information into a cache array for matching the luggage real object photo with the luggage information.
Step S5, the RFID reader-writer judges whether the phase information of the label can not be read in a preset time period; if so, the process proceeds to step S6, otherwise, the read time and phase information are recorded, and the process proceeds to step S1.
Step S6, preprocessing the read time and phase information; judging whether the data is abnormal or not, and if so, turning to the step S10; when the data is normal, the flow proceeds to step S7.
Step S7, calculating the zero point time t of the current luggage0。
Step S8, judging the zero point time t of the current luggage0And if the corresponding time window exists in the cache array, judging that the luggage corresponding to the zero point has a corresponding luggage photo, and entering step S9, otherwise, judging that the corresponding luggage photo does not exist, and entering step S10.
And step S9, binding the RFID label information of the luggage to which the zero point belongs with the corresponding photo, and displaying the photo and the luggage information.
In step S10, if it is determined that the matching has failed, the current baggage information is displayed.
The displaying process, including displaying the photograph and baggage information or displaying only current baggage information, may be performed as a single step S11.
Preferably, as shown in fig. 3, the step S6 of determining whether there is an abnormality in the data further includes the following steps:
in step S61, a correlation coefficient r of the read time and the phase information is calculated.
In this step, the process of calculating the correlation coefficient r is as follows:
first to unwrap the phase information. The phase value of the RFID obtained by the reader-writer has the 2 pi period ambiguity problem, namely, the periodic repetition occurs every 2 pi phases. The adjacent phase points are differentiated to obtain a difference result delta phii(ii) a Judging whether the difference result changes within the range of 2 pi or not, further correcting the phase difference data, and accumulating the phase difference data one by one to obtain all real phase values, as shown in a formula (1):
in the formula (1), f (Delta phi)i) The expression is as follows:
next, a correlation coefficient r of the phase data over time is calculated. From time data t obtained by the reader/writeriAnd unwrapped phase data phiiCalculating the linear correlation thereof as in formula (3):
in the formula (3), the reaction mixture is,
n is the total number of phase data.
In step S62, it is determined whether the absolute value of the correlation coefficient r is smaller than sf _ thr. If the phase data is smaller than sf _ thr, the phase data is normal; otherwise, go to step S63; wherein sf _ thr is a correlation coefficient threshold.
In step S63, the precision Sy of the regression equation is calculated based on the correlation coefficient r. The precision of the regression equation reflects the degree of fit of the data points to the regression line.
In step S64, a quadratic coefficient a after quadratic curve fitting is calculated by the least square method.
Step S65, determining whether the inequality Sy > syc _ thr and a <0 are true, if true, determining that the phase data is normal; if the equality is not satisfied, the phase data is judged to be abnormal, and the phase data is removed. Wherein syc _ thr is the precision threshold.
In this step, the trend of the phase data is judged according to the positive and negative of the quadratic term coefficient. If the quadratic term coefficient a is positive, the trend of the phase data is descending first and then ascending; if the quadratic coefficient a is negative, the trend of the phase data is first rising and then falling. Since normal time-varying phase data is rising first and then falling. Whether the phase data is normal or not can be judged according to the positive and negative of the quadratic term coefficient a.
Preferably, in step S6, it is determined whether the data is abnormal, and the phase data may be analyzed by a machine learning method (e.g., logistic regression, decision tree, etc.), and when there is an abnormality, the phase data of the non-conforming baggage is removed, so as to obtain an accurate zero point time, thereby improving the correct matching rate between the physical baggage photo and the baggage. The machine learning method comprises an offline stage and an online stage, wherein the offline stage comprises the following steps: the training data are phase data of the luggage which normally passes through and does not pass through the reader-writer antenna respectively, and then the training data are used for training the model of the luggage; an online stage: and analyzing the luggage phase data in real time by using the trained model, and judging whether the luggage phase data in the time period is proper or not.
As described above, step S7 calculates the zero point time, the movement locus and the movement speed of the tag are known on the conveyor belt, the tag is read a plurality of times while the tag is read by the reader/writer, and the read time and the return phase information of each time are recorded. And then resolving real-time phase fingerprint information in an interval from 0 to h according to the obtained starting time and the obtained ending time, comparing the real-time phase fingerprint information with the phase information read by the reader-writer, and finally calculating the time of the tag passing through the zero point.
As described above, step S7 uses the real-time phase fingerprinting algorithm to calculate the zero point time t of the current baggage0. In the real-time phase fingerprint algorithm, the zero point moment of the RFID label is t0The zero point distance is h, the conveyor speed is known as v, and the x-axis coordinate of the tag read at the ith time is xi＝v(ti-t0) The distance from the antenna is:
the phase difference due to distance is:
for all i, satisfy:
fig. 4 shows a schematic structural diagram of an RFID-based airport baggage identification system provided by an embodiment of the present invention. As shown in fig. 4, the RFID-based airport baggage identification system is used to implement the RFID-based airport baggage identification method in the above embodiments. The recognition system includes: the system comprises an RFID identification module consisting of an RFID reader-writer, an RFID antenna and an RFID label, a data preprocessing module, a zero point moment resolving module, a DI light control module, a snapshot camera, a data logic binding module and a result display module.
The RFID antenna is the front end of an RFID reader-writer, is arranged above a conveyor belt for conveying luggage in an airport and is used for reading RFID label information in a conveyor belt identification area;
the reader-writer is connected with the data preprocessing module and used for sending the RFID label information read by the RFID antenna to the data preprocessing module;
the data preprocessing module is connected with the zero point moment resolving module and used for preprocessing the RFID tag data and sending the preprocessed data to the zero point moment resolving module;
the DI light control module is connected with the snapshot camera, and both the DI light control module and the snapshot camera are arranged above the airport luggage conveyer belt and used for controlling the camera to execute snapshot action;
the zero point moment resolving module and the snapshot camera are simultaneously connected with the data logic binding module, and the zero point moment resolving module is used for resolving the preprocessed RFID tag information to obtain the zero point moment of the current luggage and sending the resolved zero point moment to the data logic binding module; the snapshot camera is used for executing snapshot actions according to the instruction of the DI light control module and sending the captured images to the data logic binding module;
the data logic binding module is connected with the result display module and is used for matching the zero point time and the image, executing binding when the matching is successful and sending binding information to the result display module; when the matching fails, the RFID label information of the luggage is sent to a result display module;
and the result display module is used for displaying the received binding information and/or RFID label information.
According to the airport luggage identification system, accurate zero-point time information is obtained through luggage phase data acquired by the RFID identification module and processed by the data preprocessing module and the zero-point time resolving module; meanwhile, the luggage passes through the DI light control module, so that the camera snapshot module is triggered to shoot the luggage, and luggage photo information is stored; and then, the luggage real photo and the luggage data are matched through the data logic binding module, so that the accuracy of luggage identification is improved, the efficiency of a manual processing link is improved, and the automatic intelligent identification of the luggage is realized.
Each module in the embodiment can be realized by a CPU or a programmable logic controller PLC; the storage or caching involved therein is implemented by means of a removable hard disk, ROM or RAM.
It should be noted that, the airport baggage identification system based on RFID in this embodiment corresponds to the airport baggage identification method based on RFID in the foregoing embodiment, and the description and the limitation of the identification method are also applicable to the identification system in this embodiment, and are not repeated herein.
The embodiments in the present specification are described in a progressive manner, and the same or similar parts in the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for apparatus or system embodiments, since they are substantially similar to method embodiments, they are described in relative terms, as long as they are described in partial descriptions of method embodiments. The above-described embodiments of the apparatus and system are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
While the foregoing is directed to the preferred embodiment of the present invention, it is understood that the invention is not limited to the exemplary embodiments disclosed, but is made merely for the purpose of providing those skilled in the relevant art with a comprehensive understanding of the specific details of the invention. It will be apparent to those skilled in the art that various modifications and adaptations of the present invention can be made without departing from the principles of the invention and the scope of the invention is to be determined by the claims.
Claims (8)
1. An airport luggage identification method based on RFID is characterized by comprising the following steps:
step S1, when the luggage passes through the identification area of the RFID antenna from the conveyor belt, the RFID reader-writer reads the RFID label information of the current luggage for many times through the RFID antenna, and records the reading time and the phase information;
step S2, the DI light control module arranged at the antenna judges whether luggage passes through, when luggage passes through, the process goes to step S3; when no luggage passes, the process proceeds to step S5;
step S3, the DI light control module triggers the snapshot camera to take a picture of the luggage, and the time window [ t ] of the luggage passing through the RFID antenna is calculated according to the interval of the luggage triggering the DI light control module1,t2]；
Step S4, the time window [ t ]1,t2]Adding the data into a cache array;
step S5, the RFID reader-writer judges whether the phase information of the label can not be read in a preset time period; if yes, the step S6 is executed, otherwise, the reading time and the phase information are continuously recorded, and the step S1 is executed;
step S6, preprocessing the reading time and phase information, and judging whether the data is abnormal; when there is an abnormality in the data, proceed to step S10; when the data is normal, proceed to step S7;
step S7, calculating the zero point time t of the current luggage0；
Step S8, judging the zero point time t of the current luggage0Whether the time window is in the corresponding time window in the cache array; if the corresponding time window exists in the cache array, judging that the luggage corresponding to the zero point has a corresponding luggage photo, and entering step S9, otherwise, judging that the corresponding luggage photo does not exist, and entering step S10;
step S9, binding the RFID label information of the luggage to which the zero point belongs with the corresponding photo, and displaying the photo and the luggage information;
in step S10, if it is determined that the matching has failed, the current baggage information is displayed.
2. The RFID-based airport baggage identification method of claim 1, wherein the step of determining whether the data is abnormal in step S6 further comprises the steps of:
step S61, calculating a correlation coefficient r of the reading time and the phase information;
step S62, judging whether the absolute value of the correlation coefficient r is smaller than sf _ thr; if the phase data is smaller than sf _ thr, judging that the phase data is normal; otherwise, go to step S63; wherein sf _ thr is a correlation coefficient threshold;
step S63, calculating precision Sy of the regression equation according to the correlation coefficient r;
step S64, calculating a quadratic term coefficient a after quadratic curve fitting by using a least square method;
step S65, determine whether the inequality Sy > syc _ thr and a <0 holds; if yes, determining that the phase data is normal; if the equality is not satisfied, judging that the phase data is abnormal, and rejecting the phase data; wherein syc _ thr is the precision threshold.
3. The RFID-based airport baggage identification method of claim 2, wherein said calculating a correlation coefficient r is performed as follows:
unwrapping the phase information and calculating the difference delta phi between adjacent phase pointsiAnd accumulating the phase difference data one by one to obtain all the real phase values phimAs in formula (1):
in the formula (1), f (Delta phi)i) The expression is as follows:
from time data t obtained by the reader/writeriAnd unwrapped phase data phiiCalculating a linear correlation r as shown in formula (3):
in the formula (3), the reaction mixture is,
n is the total number of phase data.
4. The RFID-based airport baggage identification method according to claim 2, wherein in step S65, the trend of the phase data is determined according to the positive and negative of the quadratic coefficient; if the quadratic term coefficient a is positive, the trend of the phase data is descending first and then ascending; if the quadratic coefficient a is negative, the trend of the phase data is first rising and then falling.
5. The RFID-based airport baggage identification method of claim 1, wherein step S6 is performed to determine whether there is an abnormality in the data, analyze the phase data by a machine learning method, and reject the abnormal baggage phase data when there is an abnormality.
6. The RFID-based airport baggage identification method according to claim 1, wherein said step S7 calculates a zero point time, a motion trajectory and a motion speed of the baggage on the conveyor belt are known, the tag is read a plurality of times while reading the area by the reader, and the reading time and phase information of each time are recorded; and resolving real-time phase information in a position interval corresponding to the time period according to the obtained starting time and the obtained ending time, comparing the real-time phase information with the phase information read by the reader-writer, and finally calculating the time when the label passes through the zero point.
7. The RFID-based airport baggage identification method of claim 1, whereinCharacterized in that the step S7 adopts a real-time phase fingerprint algorithm to calculate the zero point time t of the current luggage0(ii) a In the real-time phase fingerprint algorithm, the zero point moment of the RFID label is t0The zero point distance is h, the conveyor speed is known as v, and the x-axis coordinate of the tag read at the ith time is xi＝v(ti-t0) The distance from the antenna is:
the phase difference due to distance is:
for all i, satisfy:
time t corresponding to solving S maximum value0Namely the zero point moment.
8. An RFID-based airport baggage identification system, the identification system comprising: the system comprises an RFID identification module consisting of an RFID reader-writer, an RFID antenna and an RFID label, a data preprocessing module, a zero point moment resolving module, a DI light control module, a snapshot camera, a data logic binding module and a result display module; wherein,
the RFID antenna is the front end of an RFID reader-writer, is arranged above a conveyor belt for conveying luggage in an airport and is used for reading RFID label information in a conveyor belt identification area;
the reader-writer is connected with the data preprocessing module and used for sending the RFID label information read by the RFID antenna to the data preprocessing module;
the data preprocessing module is connected with the zero point moment resolving module and used for preprocessing the RFID tag data and sending the preprocessed data to the zero point moment resolving module;
the DI light control module is connected with the snapshot camera, and both the DI light control module and the snapshot camera are arranged above the airport luggage conveyer belt and used for controlling the camera to execute snapshot action;
the zero point moment resolving module and the snapshot camera are simultaneously connected with the data logic binding module, and the zero point moment resolving module is used for resolving the preprocessed RFID tag information to obtain the zero point moment of the current luggage and sending the resolved zero point moment to the data logic binding module; the snapshot camera is used for executing snapshot actions according to the instruction of the DI light control module and sending the captured images to the data logic binding module;
the data logic binding module is connected with the result display module and is used for matching the zero point time and the image, executing binding when the matching is successful and sending binding information to the result display module; sending the luggage information to a result display module when the matching fails;
and the result display module is used for displaying the received binding information and/or the received luggage information.
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| CN113326707B (en) * | 2021-04-19 | 2023-04-07 | 福建新大陆自动识别技术有限公司 | Method and equipment for identifying mobile RFID (radio frequency identification) tag |
| CN114239765A (en) * | 2021-11-02 | 2022-03-25 | 上海仪电特镭宝信息科技有限公司 | Airport intelligent wearable luggage identification method based on RFID technology |
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