U.S. patent application number 15/631986 was filed with the patent office on 2018-12-27 for methods and systems for high density rfid part scanning.
The applicant listed for this patent is The Boeing Company. Invention is credited to Jack Fredrickson, William David Kelsey, Edward Li, Brian James Smith, Kevin Yong Ung, John Jiang Yu.
Application Number | 20180373969 15/631986 |
Document ID | / |
Family ID | 64692326 |
Filed Date | 2018-12-27 |
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United States Patent
Application |
20180373969 |
Kind Code |
A1 |
Ung; Kevin Yong ; et
al. |
December 27, 2018 |
METHODS AND SYSTEMS FOR HIGH DENSITY RFID PART SCANNING
Abstract
A method for high density radio frequency identifier (RFID)
scanning is provided. The method includes receiving a plurality of
response signals from a plurality of RFID components. Where each of
the plurality of response signals includes a part number and a
serial number associated with the RFID component. The method also
includes receiving, from a location device, a location of the
scanning device. For each of the plurality of RFID components, the
method includes determining a component location, the serial
number, and the part number based on a corresponding response
signal, comparing the component location to an expected location of
the RFID component, determining a level of correlation between the
serial number associated with the corresponding response signal and
a stored serial number associated with the part number, and
calculating a confidence score based on the corresponding
comparison and the level of correlation.
Inventors: |
Ung; Kevin Yong; (Bellevue,
WA) ; Fredrickson; Jack; (Kirkland, WA) ;
Kelsey; William David; (Issaquah, WA) ; Yu; John
Jiang; (Seattle, WA) ; Li; Edward; (Seattle,
WA) ; Smith; Brian James; (Bellevue, WA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
The Boeing Company |
Chicago |
IL |
US |
|
|
Family ID: |
64692326 |
Appl. No.: |
15/631986 |
Filed: |
June 23, 2017 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 10/00 20130101;
G01S 5/0247 20130101; G06K 17/0022 20130101; G01S 5/02 20130101;
G01S 5/0284 20130101 |
International
Class: |
G06K 17/00 20060101
G06K017/00; G01S 5/02 20060101 G01S005/02 |
Claims
1. A system for high density radio frequency identifier (RFID)
scanning comprising: an RFID scanning device programmed to transmit
an RFID interrogation signal and receive a plurality of response
signals from a plurality of RFID tagged components; a location
device programmed to determine a location of said RFID scanning
device; an RFID analysis computer device in communication with said
RFID scanning device and said location device, said RFID analysis
computer device comprising at least one processor in communication
with at least one memory device, said RFID analysis computer device
programmed to: store a plurality of data for a plurality of RFID
tagged components including part numbers, serial numbers, and
expected locations for each of the plurality of RFID tagged
components; instruct said RFID scanning device to transmit an RFID
interrogation signal; receive, from said RFID scanning device, a
plurality of response signals from a plurality of RFID tagged
components, wherein each of the plurality of response signals
includes a part number and a serial number associated with the RFID
tagged component; and receive, from said location device, a
location of said RFID scanning device when said RFID scanning
device receives the plurality of response signals; for each of the
plurality of RFID tagged components, said RFID analysis computer
device is further programmed to: determine a component location,
the serial number, and the part number based on a corresponding
response signal of the plurality of response signals; compare the
component location to an expected location of the RFID tagged
component; determine a level of correlation between the serial
number associated with the corresponding response signal for the
RFID tagged component and a stored serial number associated with
the part number; and calculate a confidence score based on the
level of correlation between the serial number associated with the
corresponding response signal for the RFID tagged component and the
stored serial number associated with the part number and based on
the comparison of the component location to the expected location;
and wherein said RFID analysis computer device is further
programmed to generate a listing of the plurality of RFID tagged
components including the associated confidence score for each of
the RFID tagged components.
2. A system in accordance with claim 1, wherein said location
device is also programmed to determine an orientation of said RFID
scanning device, and wherein said RFID analysis computer device is
further programmed to: receive, from said location device, the
orientation of said RFID scanning device; and determine the
component location based on the location and the orientation of
said RFID scanning device.
3. A system in accordance with claim 2, wherein the plurality of
response signals include a signal strength, and wherein said RFID
analysis computer device is further programmed to determine the
component location based on the signal strength of the
corresponding response signal.
4. A system in accordance with claim 3, wherein said RFID analysis
computer device is further programmed to: store a layout of a
vehicle, wherein said RFID scanning device is a mobile device
located inside the vehicle; determine the location of said RFID
scanning device in the vehicle; and for each of the plurality of
RFID tagged components, determine the location of an RFID tagged
component of the plurality of RFID tagged components in the vehicle
based on the location in the vehicle of said RFID scanning device,
the orientation of said RFID scanning device, and signal strength
of the response signal associated with said RFID tagged
component.
5. A system in accordance with claim 1, wherein said RFID analysis
computer device is further configured to: store a plurality of
designed RFID tagged components designed to be installed in a
vehicle; compare the component location of the RFID tagged
component with the plurality of designed RFID tagged components;
determine a designed RFID tagged component designated to be at the
component location based on the comparison; determine whether the
part number of the RFID tagged component matches the designed RFID
tagged component; and if the determination is that the part number
matches the designed RFID tagged component, indicate that the RFID
is properly installed.
6. A system in accordance with claim 5, wherein said RFID analysis
computer device is further configured to: if the determination is
that the part number does not match the designed RFID tagged
component, transmit an alarm to a user.
7. A system in accordance with claim 5, wherein said RFID analysis
computer device is further programmed to: store a plurality of
potential part numbers for each of the plurality of designed RFID
tagged components; and compare the part number to the plurality of
potential part numbers to determine if a match is found.
8. A system in accordance with claim 5, wherein said RFID analysis
computer device is further programmed to: store an algorithm for a
potential part number for each of the plurality of designed RFID
tagged components; and compare the part number to the algorithm to
determine if a match is found.
9. A system in accordance with claim 1, wherein said RFID analysis
computer device is further configured to: parse the plurality of
response signals by part number; determine the part number
associated with more than one response; and determine a plurality
of serial numbers associated with the part number based on the more
than one response.
10. A system in accordance with claim 1, wherein the stored serial
number corresponds to an RFID tagged component with the part number
that was in a previously delivered vehicle of a similar
configuration, and wherein said RFID analysis computer device is
further configured to: compare the serial number associated with
the corresponding response signal for the RFID tagged component to
the stored serial number to determine an extent of a match between
the serial number and the stored serial number; and determine the
level of correlation between the serial number and the stored
serial number associated with the part number based on the extent
of the match.
11. A method for high density radio frequency identifier (RFID)
scanning, the method implemented using a computing device
comprising at least one processor in communication with at least
one memory device, the computing device in communication with an
RFID scanning device and a location device associated with the RFID
scanning device, the method comprising: storing a plurality of data
for a plurality of RFID tagged components including part numbers,
serial numbers, and expected locations for each of the plurality of
RFID tagged components; instructing the RFID scanning device to
transmit an RFID interrogation signal; receiving, from the RFID
scanning device, a plurality of response signals from a plurality
of RFID tagged components, wherein each of the plurality of
response signals includes a part number and a serial number
associated with the RFID tagged component; receiving, from a
location device, a location of the RFID scanning device when the
RFID scanning device received the plurality of response signals;
for each of the plurality of RFID tagged components, determining a
component location, the serial number, and the part number based on
a corresponding response signal of the plurality of response
signals; for each of the plurality of RFID tagged components,
comparing the component location to an expected location of the
RFID tagged component; for each of the plurality of RFID tagged
components, determining a level of correlation between the serial
number associated with the corresponding response signal for the
RFID tagged component and a stored serial number associated with
the part number; for each of the plurality of RFID tagged
components, calculating a confidence score based on the level of
correlation between the serial number associated with the
corresponding response signal for the RFID tagged component and the
stored serial number associated with the part number and based on
the comparison of the component location to the expected location;
and generating a listing of the plurality of RFID tagged components
including the associated confidence score for each of the RFID
tagged components.
12. A method in accordance with claim 11, wherein the location
device is also programmed to determine an orientation of the RFID
scanning device, and wherein said method further comprises:
receiving, from the location device, the orientation of the RFID
scanning device; and determining the component location based on
the location and the orientation of the RFID scanning device.
13. A method in accordance with claim 12, wherein the plurality of
response signals include a signal strength, and wherein said method
further comprises determining the component location based on the
signal strength of the corresponding response signal.
14. A method in accordance with claim 13 further comprising:
storing a layout of a vehicle, wherein the RFID scanning device is
a mobile device located in the vehicle; determining the location of
the RFID scanning device in relation to the vehicle; and for each
of the plurality of RFID tagged components, determining the
location of the RFID tagged component in the vehicle based on the
location in relation to the vehicle of the RFID scanning device,
the orientation of the RFID scanning device, and signal strength of
the response signal associated with the RFID tagged components.
15. A method in accordance with claim 11, wherein said method
further comprises: storing a plurality of designed RFID tagged
components designed to be installed in a vehicle; comparing the
component location of the RFID tagged component with the plurality
of designed RFID tagged components; determining a designed RFID
tagged component designated to be at the component location based
on the comparison; determining whether the part number of the RFID
tagged component matches the designed RFID tagged component; and if
the determination is that the part number matches the designed RFID
tagged component, indicating that the RFID is properly
installed.
16. A method in accordance with claim 15 further comprising if the
determination is that the part number does not match the designed
RFID tagged component, transmitting an alarm to a user.
17. A method in accordance with claim 15 further comprising:
storing a plurality of potential part numbers for each of the
plurality of designed RFID tagged components; and comparing the
part number to the plurality of potential part numbers to determine
if a match is found.
18. A method in accordance with claim 15 further comprising:
storing an algorithm for a potential part number for each of the
plurality of designed RFID tagged components; and comparing the
part number to the algorithm to determine if a match is found.
19. A method in accordance with claim 11, wherein said method
further comprises: parsing the plurality of response signals by
part number; determining the part number associated with more than
one response; and determining a plurality of serial numbers
associated with the part number based on the more than one
response.
20. A computer device for high density radio frequency identifier
(RFID) scanning comprising at least one processor in communication
with at least one memory device, said at least one processor
programmed to: store a plurality of data for a plurality of RFID
tagged components including part numbers, serial numbers, and
expected locations for each of the plurality of RFID tagged
components; instruct an RFID scanning device to transmit an RFID
interrogation signal; receive, from the RFID scanning device, a
plurality of response signals from a plurality of RFID tagged
components, wherein each of the plurality of response signals
includes a part number and a serial number associated with the RFID
tagged component; receive, from a location device, a location of
the RFID scanning device when the RFID scanning device received the
plurality of response signals; for each of the plurality of RFID
tagged components, determine a component location, the serial
number, and the part number based on a corresponding response
signal of the plurality of response signals; for each of the
plurality of RFID tagged components, compare the component location
to an expected location of the RFID tagged component; for each of
the plurality of RFID tagged components, determine a level of
correlation between the serial number associated with the
corresponding response signal for the RFID tagged component and a
stored serial number associated with the part number; for each of
the plurality of RFID tagged components, calculate a confidence
score based on the level of correlation between the serial number
associated with the corresponding response signal for the RFID
tagged component and the stored serial number associated with the
part number and based on the comparison of the component location
to the expected location; and generate a listing of the plurality
of RFID tagged components including the associated confidence score
for each of the RFID tagged components.
Description
BACKGROUND
[0001] The field of the invention relates generally to high density
radio frequency identifier (RFID) part scanning, and more
specifically, to scanning and identifying a plurality of closely
located parts based on RFID tags.
[0002] Known RFID systems utilize RFID readers and RFID tags. The
RFID reader interrogates an RFID tag by transmitting a radio signal
to the tag and receiving a response radio signal from the tag. The
radio response signal may include information about an object to
which the RFID tag is attached. Accordingly, by interrogating a
plurality of RFID tags, information about a plurality of objects
can be retrieved relatively quickly.
[0003] However, depending on a location of the RFID tag and/or RFID
reader, different power levels may be needed to detect different
RFID tags. At least some known RFID readers allow a user to
manually change the power level until an RFID tag is detected.
However, using such a trial and error process to detect RFID tags
may be time-consuming, and may result in missing (i.e., not
detecting) one or more RFID tags. Accordingly, in some assemblies,
such as vehicles, items are often manually checked rather than
using automated RFID systems. However, manually checking items,
such as safety equipment and/or maintenance equipment, generally is
more time-consuming and/or labor-intensive. Further, manually
checking items may result in human error, making manual checks
limited in their reliability.
[0004] In the known systems, detecting singular RFID tags requires
an individual read per part, which can be very time consuming.
These systems also work in environments where parts with RFID tags
are installed away from other tagged parts. However, in some
vehicles, some areas include a high density of parts with RFID
tags. Furthermore some parts have metallic surface which can also
affect reading RFID tags in a high density area. These conditions
may cause a frequency multi-path situation, which may make
selecting individual tags difficult and increase the difficulty of
adjusting the RF scanning window to capture just one tag at a
time.
BRIEF DESCRIPTION
[0005] In one aspect, a system for high density radio frequency
identifier (RFID) scanning is provided. The system includes a
scanning device capable of transmitting an interrogation signal and
receiving a plurality of response signals from a plurality of RFID
components, a location device capable of determining a location of
the scanning device, and a RFID analysis computer device in
communication with the scanning device and the location device. The
RFID analysis computer device includes at least one processor in
communication with at least one memory device. The RFID analysis
computer device is programmed to receive, from the scanning device,
a plurality of response signals from a plurality of RFID
components. Each of the plurality of response signals includes a
part number and a serial number associated with the RFID component.
The RFID analysis computer device is also programmed to receive,
from the location device, a location of the scanning device when
the scanning device received the plurality of response signals. For
each of the plurality of RFID components, the RFID analysis
computer device is further programmed to determine a component
location, a serial number, and a part number based on a
corresponding response signal of the plurality of response signals,
compare the component location to an expected location of the RFID
component, determine a level of correlation between the serial
number associated with the corresponding response signal for the
RFID component and a stored serial number associated with the part
number, and calculate a confidence score based on the level of
correlation between the serial number associated with the
corresponding response signal for the RFID component and the stored
serial number associated with the part number. In addition, the
RFID analysis computer device is programmed to generate a listing
of the plurality of RFID components including the associated
confidence score for each of the RFID components.
[0006] In another aspect, a method for high density radio frequency
identifier (RFID) scanning is provided. The method includes
receiving, from a scanning device, a plurality of response signals
from a plurality of RFID components. Each of the plurality of
response signals includes a part number and a serial number
associated with the RFID component. The method also includes
receiving, from a location device, a location of the scanning
device when the scanning device received the plurality of response
signals. For each of the plurality of RFID components, the method
further includes determining a component location, a serial number,
and a part number based on a corresponding response signal of the
plurality of response signals, comparing the component location to
an expected location of the RFID component, determining a level of
correlation between the serial number associated with the
corresponding response signal for the RFID component and a stored
serial number associated with the part number, and calculating a
confidence score based on the level of correlation between the
serial number associated with the corresponding response signal for
the RFID component and the stored serial number associated with the
part number. In addition, the method includes generating a listing
of the plurality of RFID components including the associated
confidence score for each of the RFID components.
[0007] In yet another aspect, a computer device for high density
radio frequency identifier (RFID) scanning is provided. The
computer device includes at least one processor in communication
with at least one memory device. The at least one processor is
programmed to receive, from a scanning device, a plurality of
response signals from a plurality of RFID components. Each of the
plurality of response signals includes a part number and a serial
number associated with the RFID component. The at least one
processor is also programmed to receive, from a location device, a
location of the scanning device when the scanning device received
the plurality of response signals. For each of the plurality of
RFID components, the at least one processor is programmed to
determine a component location, a serial number, and a part number
based on a corresponding response signal of the plurality of
response signals, compare the component location to an expected
location of the RFID component, determine a level of correlation
between the serial number associated with the corresponding
response signal for the RFID component and a stored serial number
associated with the part number, and calculate a confidence score
based on the level of correlation between the serial number
associated with the corresponding response signal for the RFID
component and the stored serial number associated with the part
number. The at least one processor is further programmed to
generate a listing of the plurality of RFID components including
the associated confidence score for each of the RFID
components.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] FIGS. 1-11 show example embodiments of the methods and
systems described herein.
[0009] FIG. 1 is a schematic diagram of an exemplary RFID
system.
[0010] FIG. 2 is a block diagram of an exemplary RFID reader that
may be used with the system shown in FIG. 1.
[0011] FIG. 3 is a simplified block diagram of an example RFID
analysis system used for analyzing RFID signals received
simultaneously from a plurality of plurality of RFID tags
accordance with FIG. 1.
[0012] FIG. 4 illustrates an example configuration of a client
system shown in FIG. 3, in accordance with one embodiment of the
present disclosure.
[0013] FIG. 5 illustrates an example configuration of a server
system shown in FIG. 3, in accordance with one embodiment of the
present disclosure.
[0014] FIG. 6 is a flow chart of a process for creating a list of
"as-designed" parts expected to be installed in a vehicle using the
systems shown in FIGS. 1 & 3.
[0015] FIG. 7 is a flow chart of a process for creating a list of
"as-delivered" parts expected to be installed in a vehicle using
the systems shown in FIGS. 1 & 3.
[0016] FIG. 8 is a flow chart of a process for creating a list of
scanned parts detecting in a vehicle using the systems shown in
FIGS. 1 & 3.
[0017] FIG. 9 is a flow chart of a process for pattern matching the
"as-designed," "as-delivered," and scanned parts in a vehicle using
the systems shown in FIGS. 1 & 3.
[0018] FIG. 10 is a flow chart of a process for high density radio
frequency identifier (RFID) scanning using the systems shown in
FIGS. 1 & 3.
[0019] FIG. 11 is a diagram of components of one or more example
computing devices that may be used in the systems shown in FIGS. 1
& 3.
[0020] Unless otherwise indicated, the drawings provided herein are
meant to illustrate features of embodiments of this disclosure.
These features are believed to be applicable in a wide variety of
systems comprising one or more embodiments of this disclosure. As
such, the drawings are not meant to include all conventional
features known by those of ordinary skill in the art to be required
for the practice of the embodiments disclosed herein.
DETAILED DESCRIPTION
[0021] The implementations described herein relate to radio
frequency identifier ("RFID") part scanning, and more specifically,
to scanning, identifying, and verifying a plurality of closely
located parts with RFID tags. More specifically, an RFID analysis
computer device (also known as an RFID analysis server) analyzes
received RFID signals to locate and identify the parts in an area
with a high concentration of RFID tags. The RFID analysis computer
device compares the identified parts to potential parts at that
location to confirm that the proper parts are identified.
[0022] Described herein are computer systems such as the RFID
analysis computer devices and related computer systems. As
described herein, all such computer systems include a processor and
a memory. However, any processor in a computer device referred to
herein may also refer to one or more processors wherein the
processor may be in one computing device or in a plurality of
computing devices acting in parallel. Additionally, any memory in a
computer device referred to herein may also refer to one or more
memories wherein the memories may be in one computing device or in
a plurality of computing devices acting in parallel.
[0023] As used herein, a processor may include any programmable
system including systems using micro-controllers, reduced
instruction set circuits (RISC), application specific integrated
circuits (ASICs), logic circuits, and any other circuit or
processor capable of executing the functions described herein. The
above examples are not intended to limit in any way the definition
and/or meaning of the term "processor."
[0024] As used herein, the term "database" may refer to either a
body of data, a relational database management system (RDBMS), or
to both. As used herein, a database may include any collection of
data including hierarchical databases, relational databases, flat
file databases, object-relational databases, object-oriented
databases, and any other structured or unstructured collection of
records or data that is stored in a computer system. The above
examples are not intended to limit in any way the definition and/or
meaning of the term database. Examples of RDBMS's include, but are
not limited to, Oracle.RTM. Database, MySQL, IBM.RTM. DB2,
Microsoft.RTM. SQL Server, Sybase.RTM., and PostgreSQL. However,
any database may be used that enables the systems and methods
described herein. (Oracle is a registered trademark of Oracle
Corporation, Redwood Shores, Calif.; IBM is a registered trademark
of International Business Machines Corporation, Armonk, N.Y.;
Microsoft is a registered trademark of Microsoft Corporation,
Redmond, Wash.; and Sybase is a registered trademark of Sybase,
Dublin, Calif.)
[0025] In one embodiment, a computer program is provided, and the
program is embodied on a computer readable medium. In an example
embodiment, the system is executed on a single computer system,
without requiring a connection to a server computer. In a further
embodiment, the system is being run in a Windows.RTM. environment
(Windows is a registered trademark of Microsoft Corporation,
Redmond, Wash.). In yet another embodiment, the system is run on a
mainframe environment and a UNIX.RTM. server environment (UNIX is a
registered trademark of X/Open Company Limited located in Reading,
Berkshire, United Kingdom). The application is flexible and
designed to run in various different environments without
compromising any major functionality. In some embodiments, the
system includes multiple components distributed among a plurality
of computing devices. One or more components may be in the form of
computer-executable instructions embodied in a computer-readable
medium.
[0026] As used herein, an element or step recited in the singular
and preceded with the word "a" or "an" should be understood as not
excluding plural elements or steps, unless such exclusion is
explicitly recited. Furthermore, references to "example embodiment"
or "one embodiment" of the present disclosure are not intended to
be interpreted as excluding the existence of additional embodiments
that also incorporate the recited features.
[0027] As used herein, the terms "software" and "firmware" are
interchangeable, and include any computer program stored in memory
for execution by a processor, including RAM memory, ROM memory,
EPROM memory, EEPROM memory, and non-volatile RAM (NVRAM) memory.
The above memory types are examples only and thus, are not limiting
as to the types of memory usable for storage of a computer
program.
[0028] Furthermore, as used herein, the term "real-time" refers to
at least one of the time of occurrence of the associated events,
the time of measurement and collection of predetermined data, the
time to process the data, and the time of a system response to the
events and the environment. In the embodiments described herein,
these activities and events occur substantially
instantaneously.
[0029] The systems and processes are not limited to the specific
embodiments described herein. In addition, components of each
system and each process can be practiced independent and separate
from other components and processes described herein. Each
component and process also can be used in combination with other
assembly packages and processes.
[0030] FIG. 1 is a schematic diagram of an exemplary
radio-frequency identification (RFID) system 100 that includes an
RFID reader 102 and at least one RFID tag 104 attached to and/or
included as part of an object 106. In the exemplary implementation,
RFID reader 102 is a portable, handheld reader. Alternatively, RFID
reader 102 is a fixed reader that is mounted and/or installed in an
operating environment, such as a vehicle. RFID reader 102 includes
a display 108 for displaying information and a user input device
110, such as a keyboard, for receiving input from a user.
[0031] RFID reader 102 is configured to transmit an interrogation
radio signal at a plurality of power levels, as described in detail
herein. Further, RFID reader 102 is configured to integrate
position data and configuration data to determine confirm the
location of one or more objects 106 including RFID tags 104, as
described in detail herein.
[0032] Interrogating RFID tag 104 using RFID reader 102 enables
identification of object 106. To interrogate RFID tag 104, RFID
reader 102 transmits an interrogation radio signal. The
interrogation radio signal is capable of being transmitted at a
plurality of power levels, as described in detail herein. In the
exemplary embodiment, the interrogation radio signal is transmitted
at a maximum power level. Further, RFID reader 102 is configured to
integrate position data and configuration data to confirm the
location of one or more RFID tags 104, and accordingly the
corresponding object 106, as described in detail herein.
[0033] When RFID tag 104 receives the transmitted radio signal from
RFID reader 102, RFID tag 104 emits a response radio signal.
Specifically, the RFID tag 104 includes a receiver (not shown) for
receiving the interrogation radio signal, and a transmitter (not
shown) for transmitting the response radio signal. The response
radio signal includes identification information related to object
106. For example, the response radio signal may include a unique
tag serial number, an expiration date of object 106, a stock number
of object 106, a lot or batch number of object 106, a position
and/or location of object 106, and/or other information pertinent
to object 106.
[0034] Object 106 may be any article for which it is desirable to
obtain information about the article. For example, in some
implementations, system 100 is implemented onboard a moving
vehicle, such as aircraft 10 (shown in FIG. 1). In an aircraft
operating environment, object 106 may be aircraft maintenance
equipment, aircraft safety equipment, and/or other aircraft
articles. For example, object 106 could be a seat, seatbelt, a
flotation device, an oxygen mask, a fire extinguisher, a drinks
cart, a piece of avionics equipment, and/or any other suitable
article.
[0035] The response radio signal transmitted from one or more RFID
tags 104 is received by RFID reader 102. In the exemplary
implementation, RFID reader 102 transmits the received radio
response signal to a computer system (not shown) running software
for extracting the identification information from the response
radio signal. Alternatively, RFID reader 102 may include suitable
software extracting the identification information from the radio
response signal.
[0036] In the exemplary implementation, RFID tag 104 is a passive
RFID tag that uses radio energy in the interrogation radio signal
to generate and emit the response radio signal. Alternatively, RFID
tag 104 may be an active RFID tag that includes a battery that
periodically transmits the response radio signal. Further, RFID tag
104 may be read-only or read/write, in which data can be written
into RFID tag 104.
[0037] Although FIG. 1 shows only three RFID tag 104 attached to
one object 106, it will be appreciated that system 100 may include
any number of RFID tags 104 each attached to a respective object.
Accordingly, RFID reader 102 is capable of reading a plurality of
RFID tags 104 to acquire identification information for a plurality
of objects 106.
[0038] The detection range of RFID reader 102 depends on a power
level of the transmitted interrogation signal. That is, the higher
the power level, the further away RFID reader 102 can detect RFID
tags 104. Accordingly, in the exemplary implementation, the power
level is controlled to the maximum level to facilitate efficient
and accurate detection of the largest plurality of RFID tags 104
possible at once, as described in detail herein.
[0039] In the exemplary implementation, RFID reader 102 is in
communication with a configuration database 120 and a position
system 122. By integrating data received from configuration
database 120 and position system 122, when RFID reader 102 detects
an RFID tag 104, RFID reader 102 can confirm the location of RFID
tag 104, as described in detail herein.
[0040] FIG. 2 is a block diagram of RFID reader 102 that may be
used with RFID system 100 (shown in FIG. 1). In the exemplary
implementation, RFID reader 102 includes a transmitter/receiver
module 202, a control module 204, a user interface module 208, and
a communications module 210.
[0041] Transmitter/receiver module 202 transmits interrogation
radio signal and receives response radio signal from RFID tag 104
(shown in FIG. 1). In the exemplary implementation,
transmitter/receiver module 202 is capable of transmitting and
interrogation radio signals at a plurality of power levels.
[0042] Control module 204 instructs transmitter/receiver module 202
to transmit the interrogation radio signal at a specified power
level. In the exemplary embodiment, control module 204 is
configured to instruct transmitter/receiver module 202 to transmit
the interrogation radio signal at the maximum power level. In some
embodiments, control module 204 may adjust the power level to
prevent interference or other issues with reading a plurality of
RFID tags 104. In the exemplary implementation, control module 204
includes at least one memory device 220 and a processing device 222
that is coupled to memory device 220 for executing instructions. In
some implementations, executable instructions are stored in memory
device 220. Control module 204 performs one or more operations
described herein by programming processing device 222. For example,
processing device 222 may be programmed by encoding an operation as
one or more executable instructions and by providing the executable
instructions in memory device 220.
[0043] Processing device 222 may include one or more processing
units (e.g., in a multi-core configuration). Further, processing
device 222 may be implemented using one or more heterogeneous
processor systems in which a main processor is present with
secondary processors on a single chip. As another illustrative
example, processing device 222 may be a symmetric multi-processor
system containing multiple processors of the same type. Further,
processing device 222 may be implemented using any suitable
programmable circuit including one or more systems and
microcontrollers, microprocessors, reduced instruction set circuits
(RISC), application specific integrated circuits (ASIC),
programmable logic circuits, field programmable gate arrays (FPGA),
and any other circuit capable of executing the functions described
herein. Processing device 222 determines what power level control
module 204 should instruct transmitter/receiver module 202 to
transmit interrogation radio signals at.
[0044] Memory device 220 is one or more devices that enable
information such as executable instructions and/or other data to be
stored and retrieved. Memory device 220 may include one or more
computer readable media, such as, without limitation, dynamic
random access memory (DRAM), static random access memory (SRAM), a
solid state disk, and/or a hard disk. Memory device 220 may be
configured to store, without limitation, application source code,
application object code, source code portions of interest, object
code portions of interest, configuration data, execution events
and/or any other type of data.
[0045] User interface module 208 includes an input device 240, such
as user input device 110 (shown in FIG. 2). Input device 240 may
include a toggle switch, a touchscreen, keypad and/or keyboard,
and/or mouse that enables a user to enter information and interact
with RFID reader 102. A user can use input device 240 to select
which object 106 (and corresponding RFID tag 104) RFID reader 102
should attempt to detect. Further, using input device 240, a user
can manually input a location of the RFID reader 102.
[0046] In the exemplary implementation, user interface module 208
also includes a display device 242, such as display 108 (shown in
FIG. 1) that enables a user to view information pertinent to the
operation of RFID reader 102. For example, display device 242 may
display the current location of RFID reader 102, the current
interrogation radio signal power level, and/or the currently
detected RFID tag 104/object 106. Display device 242 may include,
for example, a cathode ray tube (CRT), a liquid crystal display
(LCD), an organic LED (OLED) display, and/or an "electronic ink"
display. In some implementations, a touch screen functions as both
display device 242 and input device 240.
[0047] Communications module 210 transmits and receives data for
RFID reader 102. Communications module 210 transmits and receives
data using any suitable communications medium, including, but not
limited to, a wired and/or wireless network, an Iridium satellite
network, radio, 3G, Controller Pilot Data Link (CPDL), and Tactical
Digital Information Links (TADIL). In the exemplary implementation,
communications module 210 transmits and receives data to and from
configuration database 120 and position system 122 (both shown in
FIG. 2). For example, communications module 210 may communicate
with position system 122 to determine a location of RFID reader
102. Further, communications module 210 may receive configuration
data, such as a configuration of aircraft 10, from configuration
database 120.
[0048] Data transmitted and/or received by communications module
210 may also include identification information received from RFID
tag 104 (shown in FIG. 1). In implementations where RFID reader 102
is located onboard a vehicle, communications module 210 may
facilitate communications and integration between RFID reader 102
and one or more vehicle systems. For example, in at least some
implementations, communications module 210 communicates with one or
more aircraft flight and/or navigation systems.
[0049] FIG. 3 is a simplified block diagram of an example RFID
analysis system 200 used for analyzing RFID signals received
simultaneously from a plurality of RFID tags 104 (shown in FIG. 1).
In the example embodiment, system 300 may be used for detecting and
cataloging RFID tags 104 from areas that are densely populated with
RFID tags 104 and objects 106, such as the avionics bay of an
aircraft. As described below in more detail, a RFID analysis
computer device 310 is configured to receive, from the scanning
device 305, a plurality of response signals from a plurality of
RFID components 106. Each of the plurality of response signals
includes a part number and a serial number associated with the RFID
component 106. RFID analysis computer device 310 is also configured
to receive a location of a scanning device 305 when scanning a
plurality of RFID components 106. For each of the plurality of RFID
components, RFID analysis computer device 310 is also configured to
determine a component location, a serial number, and a part number
based on a corresponding response signal of the plurality of
response signals. For each of the plurality of RFID components,
RFID analysis computer device 310 is further configured to compare
the component location to an expected location of the RFID
component 106. For each of the plurality of RFID components, RFID
analysis computer device 310 is also configured to determine a
level of correlation between the serial number associated with the
corresponding response signal and a stored serial number associated
with the part number. In addition, RFID analysis computer device
310 is configured to calculate a confidence score for each RFID
component 106 based on the corresponding comparison. And RFID
analysis computer device 310 is also configured to generate a
listing of the plurality of RFID components 106 including the
associated confidence score.
[0050] In the example embodiment, an RFID scanner 305, such as RFID
reader 102 (shown in FIG. 1), is in communication with RFID
analysis computer device 310. In some embodiments, RFID scanner 305
is an individual part that is attached to a user computer device
(not shown), where RFID scanner 305 communicates with RFID analysis
computer device 310 through user computer device. In these
embodiments, user computer device is a computer that include a web
browser or a software application to enable user computer device to
access RFID analysis computer device 310 using the Internet or a
network. More specifically, user computer devices are
communicatively coupled to RFID analysis computer device 310
through many interfaces including, but not limited to, at least one
of a network, such as the Internet, a local area network (LAN), a
wide area network (WAN), or an integrated services digital network
(ISDN), a dial-up-connection, a digital subscriber line (DSL), a
cellular phone connection, and a cable modem. User computer devices
can be any device capable of accessing the Internet, or another
network, including, but not limited to, a desktop computer, a
laptop computer, a personal digital assistant (PDA), a cellular
phone, a smartphone, a tablet, a phablet, or other web-based
connectable equipment. In other embodiments, RFID scanner 305 is
directly wired to RFID analysis computer device 310. In still
further embodiments, RFID analysis computer device 310 includes a
plurality of computer devices connected through many interfaces to
allow RFID scanner 305 to read signals from RFID tags 104 and
analyze those signals as described herein.
[0051] RFID analysis computer device 310 includes one or more
computer devices configured to perform as described herein. In the
example embodiment, RFID analysis computer device 310 includes one
or more server systems configured to communicate with RFID scanner
305 and location computer device 325. In some embodiments, RFID
analysis computer device 310 is remote from at least one of RFID
scanner 305, database server 315, and location computer device 325
and communicates with the remote computer device (either RFID
scanner 305, database server 315, and location computer device 325)
through the Internet. More specifically, RFID analysis computer
device 310 is communicatively coupled to the Internet through many
interfaces including, but not limited to, at least one of a
network, such as a local area network (LAN), a wide area network
(WAN), or an integrated services digital network (ISDN), a
dial-up-connection, a digital subscriber line (DSL), a cellular
phone connection, and a cable modem. RFID analysis computer device
310 can be any device capable of accessing the Internet, or another
network, including, but not limited to, a desktop computer, a
laptop computer, a personal digital assistant (PDA), a cellular
phone, a smartphone, a tablet, a phablet, or other web-based
connectable equipment.
[0052] A database server 315 is communicatively coupled to a
database 220 that stores data. In one embodiment, database 320
includes as-designed configurations, as-delivered configurations,
location information, part numbers, and serial numbers. In the
example embodiment, database 320 is stored remotely from RFID
analysis computer device 310. In some embodiments, database 320 is
decentralized. In the example embodiment, a person can access
database 320 via a user computer device by logging onto RFID
analysis computer device 310, as described herein.
[0053] Location computer devices 325 include any device or
combination of devices capable of determining the location of RFID
scanner 305. In the example embodiment, RFID scanner 305 includes a
location, a height from the ground, and a direction of orientation.
When RFID scanner 305 transmits an interrogation radio signal,
location computer device 325 is capable of determining where in a
vehicle RFID scanner 305 and the direction that RFID scanner 305 is
pointed. Location computer device 325 is further configured to
communicate that determined location and orientation to RFID
analysis computer device 310 to determine one or more RFID tags 104
of one or more objects 106 that should respond to RFID scanner's
interrogation radio signal. In the example embodiment, location
computer device 325 is in communication with RFID analysis computer
device 310. In the exemplary embodiment, location computer device
325 may include, for example, a global positioning system (GPS)
sensor, a sensor located within RFID scanner 305 (e.g., an active
RFID tag), a multilateration navigation system, accelerometer,
and/or an inertial reference unit (IRU). To determine the location
and/or orientation of RFID scanner 305, RFID analysis computer
device 310 may communicate with location computer device 325
continuously, periodically, upon a user request input using user
interface module 208, and/or whenever RFID scanner 305 transmits an
interrogation radio signal. More specifically, location computer
device 325 is communicatively coupled to RFID analysis computer
device 310 through many interfaces including, but not limited to,
at least one of the Internet, a network, such as a local area
network (LAN), a wide area network (WAN), or an integrated services
digital network (ISDN), a dial-up-connection, a digital subscriber
line (DSL), a cellular phone connection, and a cable modem.
[0054] FIG. 4 illustrates an example configuration of a client
system shown in FIG. 3, in accordance with one embodiment of the
present disclosure. User computer device 402 is operated by a user
401. User computer device 402 may include, but is not limited to,
RFID reader 102 (shown in FIG. 1), RFID scanner 305, RFID analysis
computer device 310, and location computer device 325 (all shown in
FIG. 3). User computer device 402 includes a processor 405 for
executing instructions. In some embodiments, executable
instructions are stored in a memory area 410. Processor 405 may
include one or more processing units (e.g., in a multi-core
configuration). Memory area 410 is any device allowing information
such as executable instructions and/or transaction data to be
stored and retrieved. Memory area 410 may include one or more
computer-readable media.
[0055] User computer device 402 also includes at least one media
output component 415 for presenting information to user 401. Media
output component 415 is any component capable of conveying
information to user 401. In some embodiments, media output
component 415 includes an output adapter (not shown) such as a
video adapter and/or an audio adapter. An output adapter is
operatively coupled to processor 405 and operatively coupleable to
an output device such as a display device (e.g., a cathode ray tube
(CRT), liquid crystal display (LCD), light emitting diode (LED)
display, or "electronic ink" display) or an audio output device
(e.g., a speaker or headphones). In some embodiments, media output
component 415 is configured to present a graphical user interface
(e.g., a web browser and/or a client application) to user 401. A
graphical user interface may include, for example, one or more
potential tags associated with an RFID signal. In some embodiments,
user computer device 402 includes an input device 420 for receiving
input from user 401. User 401 may use input device 420 to, without
limitation, select and/or enter a part number associated with the
RFID signal. Input device 420 may include, for example, a keyboard,
a pointing device, a mouse, a stylus, a touch sensitive panel
(e.g., a touch pad or a touch screen), a gyroscope, an
accelerometer, a position detector, a biometric input device,
and/or an audio input device. A single component such as a touch
screen may function as both an output device of media output
component 415 and input device 420.
[0056] User computer device 402 may also include a communication
interface 425, communicatively coupled to a remote device such as
RFID analysis computer device 310 (shown in FIG. 3). Communication
interface 425 may include, for example, a wired or wireless network
adapter and/or a wireless data transceiver for use with a mobile
telecommunications network.
[0057] Stored in memory area 410 are, for example,
computer-readable instructions for providing a user interface to
user 401 via media output component 415 and, optionally, receiving
and processing input from input device 420. The user interface may
include, among other possibilities, a web browser and/or a client
application. Web browsers enable users, such as user 401, to
display and interact with media and other information typically
embedded on a web page or a website from RFID analysis computer
device 310. A client application allows user 401 to interact with,
for example, RFID analysis computer device 310. For example,
instructions may be stored by a cloud service and the output of the
execution of the instructions sent to the media output component
415.
[0058] FIG. 5 illustrates an example configuration of a server
system shown in FIG. 3, in accordance with one embodiment of the
present disclosure. Server computer device 501 may include, but is
not limited to, database server 315, RFID analysis computer device
310, and location computer device 325 (all shown in FIG. 3). Server
computer device 501 also includes a processor 505 for executing
instructions. Instructions may be stored in a memory area 510.
Processor 505 may include one or more processing units (e.g., in a
multi-core configuration).
[0059] Processor 505 is operatively coupled to a communication
interface 515, such that server computer device 501 is capable of
communicating with a remote device such as another server computer
device 501, RFID scanner 305, location computer device 325, or RFID
analysis computer device 310 (all shown in FIG. 3). For example,
communication interface 515 may receive location information from
location computer devices 305 via the Internet.
[0060] Processor 505 may also be operatively coupled to a storage
device 534. Storage device 534 is any computer-operated hardware
suitable for storing and/or retrieving data, such as, but not
limited to, data associated with database 320 (shown in FIG. 3). In
some embodiments, storage device 534 is integrated in server
computer device 501. For example, server computer device 501 may
include one or more hard disk drives as storage device 534. In
other embodiments, storage device 534 is external to server
computer device 501 and may be accessed by a plurality of server
computer devices 501. For example, storage device 534 may include a
storage area network (SAN), a network attached storage (NAS)
system, and/or multiple storage units such as hard disks and/or
solid state disks in a redundant array of inexpensive disks (RAID)
configuration.
[0061] In some embodiments, processor 505 is operatively coupled to
storage device 534 via a storage interface 520. Storage interface
520 is any component capable of providing processor 505 with access
to storage device 534. Storage interface 520 may include, for
example, an Advanced Technology Attachment (ATA) adapter, a Serial
ATA (SATA) adapter, a Small Computer System Interface (SCSI)
adapter, a RAID controller, a SAN adapter, a network adapter,
and/or any component providing processor 505 with access to storage
device 534.
[0062] Processor 505 executes computer-executable instructions for
implementing aspects of the disclosure. In some embodiments,
processor 505 is transformed into a special purpose microprocessor
by executing computer-executable instructions or by otherwise being
programmed. For example, processor 505 is programmed with the
instructions such as are illustrated below.
[0063] FIG. 6 is a flow chart of a process 600 for creating a list
of "as-designed" parts expected to be installed in a vehicle using
the systems 100 and 300 (shown in FIGS. 1 & 3). In the example
embodiment, process 600 is performed by RFID analysis computer
device 310 (shown in FIG. 3).
[0064] In the example embodiment, a user is in possession of a
mobile computer device that includes RFID scanner 305. In the
example embodiment, the mobile computer device is RFID analysis
computer device 305. In other embodiments, the mobile computer
device is in communication with RFID analysis computer device 310.
In the example embodiment, the user aims 605 RFID scanner 305 at a
plurality of objects 106 that are tagged with RFID tags 104. In at
least one embodiment, the tagged objects 106 are aircraft parts on
an airplane to be inspected.
[0065] RFID analysis computer device 310 computes 615 the
orientation and location of RFID scanner 305 based on sensors on
the mobile device. In the example embodiment, a layout of the
vehicle is stored in a database, such as database 320 (shown in
FIG. 3). RFID analysis computer device 310 converts 620 the
orientation and location into the orientation and location of the
RFID scanner 305 onboard the vehicle. For example, RFID analysis
computer device 310 may determine that RFID scanner 305 is in the
forward galley of an aircraft and is pointed towards the starboard
side of the aircraft.
[0066] In the example embodiment, RFID analysis computer device 310
is in communication with database 320 which is storing an
"as-designed" configuration 630 of the vehicle. In this embodiment,
"as-designed" configuration 630 includes information about the
parts and components of the vehicle based on the design by the
engineers. This information includes, but is not limited to, part
manufacturers, part numbers, and installation locations on the
vehicle.
[0067] Based on the location of RFID scanner 305, RFID analysis
computer device 310 retrieves 625 from database 320 the parts that
are designed to be installed in proximity to RFID scanner's
location in the vehicle. RFID analysis computer device 310 then
ranks the parts based on their distance from the location of RFID
scanner 305. RFID analysis computer device 310 creates 635 a list
of the parts that in proximity to RFID scanner 305 and updates a
contextual database for this vehicle with the list.
[0068] In some embodiments, RFID analysis computer device 310
virtually replicates the vehicle and simulates scanning of the
parts by having RFID scanner 305 in different positions and
orientations in the vehicle to generate the lists of parts
associated with each location.
[0069] FIG. 7 is a flow chart of a process 700 for creating a list
of "as-delivered" parts expected to be installed in a vehicle using
the systems 100 and 300 (shown in FIGS. 1 & 3). In the example
embodiment, process 700 is performed by RFID analysis computer
device 310 (shown in FIG. 3).
[0070] In the example embodiment, RFID analysis computer device 310
is in communication with database 320 (shown in FIG. 3) which is
storing an "as-delivered" configuration 640 of the vehicle. In this
embodiment, "as-delivered" configuration 640 includes information
about the parts and components of the vehicle that was collected
from past vehicles that have been completed and potentially
previously delivered to customers. This information includes, but
is not limited to, serial numbers, dates of manufacture, part
manufacturers, part numbers, and installation locations on the
vehicle.
[0071] Based on the location of RFID scanner 305, RFID analysis
computer device 310 retrieves 645 from database 320 the parts that
have been installed in proximity to RFID scanner's location in the
vehicle in the past. RFID analysis computer device 310 then ranks
the parts based on their distance from the location of RFID scanner
305. RFID analysis computer device 310 creates 650 a list of the
parts that in proximity to RFID scanner 305 and updates a
contextual database for this vehicle with the list.
[0072] Accordingly, at this point, the contextual database includes
information about the parts that were designed to be in proximity
to RFID scanner's location in the vehicle and information about the
parts that have been installed in proximity to RFID scanner's
location in past vehicles. In some further embodiments, RFID
analysis computer device 310 includes information about parts that
were installed in this vehicle in the past, such as those detected
in a previous scan or inspection of the vehicle.
[0073] FIG. 8 is a flow chart of a process 800 for creating a list
of scanned parts detecting in a vehicle using the systems 100 and
300 (shown in FIGS. 1 & 3). In the example embodiment, process
800 is performed by RFID analysis computer device 310 (shown in
FIG. 3).
[0074] In the example embodiment, the user retrieves 655 the
"as-designed" configuration 630 of the vehicle and instructs 655
RFID scanner 305 to scan at maximum RF power. RFID scanner 305
transmits an interrogation radio signal at maximum RF power and
receives responses from the plurality of RFID tags 104. RFID
scanner 305 transmits that scanned data 610 (the plurality of
response radio signals) to RFID analysis computer device 310.
[0075] RFID analysis computer device 310 parses 660 the scanned
data 610 from the RFID tags 104 to determines part information,
such as, but not limited to, manufacturers, part numbers, part
serial numbers, and dates of manufacture. RFID analysis computer
device 310 ranks 665 the parts by proximity to RFID scanner 305. In
some embodiments, RFID analysis computer device 310 uses techniques
such as Time Difference of Arrival (TDOA) and Received Signal
Strength Indicator (RSSI) to determine the distance of the
corresponding part relative to RFID scanner 305.
[0076] In the example embodiment, RFID analysis computer device 310
sorts 670 the ranked list of parts by part number and updates the
contextual database with this ranked list. For each scanned part,
RFID analysis computer device 310 lists 675 the number of parts
that have the same part number and updates the contextual database
with this list.
[0077] FIG. 9 is a flow chart of a process 900 for pattern matching
the "as-designed," "as-delivered," and scanned parts in a vehicle
using the systems 100 and 300 (shown in FIGS. 1 & 3). In the
example embodiment, process 900 is performed by RFID analysis
computer device 310 (shown in FIG. 3).
[0078] In the example embodiment, RFID analysis computer device 310
sets 905 a variable n to one (1) for all parts on the scanned part
list. RFID analysis computer device 310 performs process 900 to
analyze all of the parts on the scanned parts list.
[0079] In the example embodiment, RFID analysis computer device 310
retrieves 910 the next part from the scanned part list. RFID
analysis computer device 310 checks 915 if the part number of this
part is the same as the previous part. If the part numbers are
different, then RFID analysis computer device 310 sets 920 n equal
to one for this part. If the numbers are different, then RFID
analysis computer device 310 increments 925 n by one for that
part.
[0080] RFID analysis computer device 310 confirms 930 that the
scanned part number is the same as the part number that was
designated in the "as-designed" configuration 630. If the parts are
different, RFID analysis computer device 310 flags 935 the part
numbers as being mismatched. RFID analysis computer device 310
calculates or updates 940 a confidence factor based on the
comparison of the part numbers of the scanned and "as-designed"
parts. In some embodiments, there may be a plurality of parts that
may be used at that location. For example, there may be three
different parts that the engineers determined were acceptable for
that location. In another example, a part may be upgraded over
time. In the example embodiment, RFID analysis computer device 310
calculates 940 the confidence score to determine the probability
that the scanned part is the correct part for that location. In
some embodiments, RFID analysis computer device 310 compares the
scanned part to one or more "as-delivered" configurations 640
(shown in FIG. 7) to determine the confidence factor.
[0081] RFID analysis computer device 310 assigns 950 the serial
number of the part to the "as-designed" part for that location.
RFID analysis computer device 310 also assigns the confidence
factor to the part based on all of the confidence factors
calculated for that part. In some embodiments, different confidence
factors may be weighted based on user preferences.
[0082] RFID analysis computer device 310 checks 955 to determine if
all of the parts in the scanned list have been analyzed. If there
are more parts to analyze, RFID analysis computer device 310
retrieves 910 the next part from the scanned list. If there are no
more parts to analyze, RFID analysis computer device 310 displays
960 the serial number assignments to the user. In some embodiments,
RFID analysis computer device 310 displays multiple parts with the
same part number along with the associated confidence factors. In
some further embodiments, RFID analysis computer device 310 alerts
the user if the mismatch flag was set to true.
[0083] FIG. 10 is a flow chart of a process 1000 for high density
radio frequency identifier (RFID) scanning using systems 100 and
300 (shown in FIGS. 1 & 3). In the example embodiment, process
900 is performed by RFID analysis computer device 310 (shown in
FIG. 3).
[0084] In the example embodiment, RFID analysis computer device 310
receives 1005, from a scanning device (such as RFID scanner 305
shown in FIG. 3), a plurality of response signals from a plurality
of RFID components, such as objects 106 (shown in FIG. 1). Each of
the plurality of response signals includes a part number and a
serial number associated with the RFID component 106. RFID analysis
computer device 310 receives 1010, from a location device (such as
location computer device 325 shown in FIG. 3), a location of the
scanning device 305 when the scanning device 305 received the
plurality of response signals.
[0085] For each of the plurality of RFID components, RFID analysis
computer device 310 determines 1015 a component location, a serial
number, and a part number based on a corresponding response signal
of the plurality of response signals. For each of the plurality of
RFID components, RFID analysis computer device 310 compares 1020
the component location to an expected location of the RFID
component.
[0086] For each of the plurality of RFID components, RFID analysis
computer device 310 determines 1025 a level of correlation between
the serial number associated with a response signal for an RFID
component (which includes a part number) and a stored serial number
associated with the part number. In some embodiments, RFID analysis
computer device 310 uses the received part number to look up serial
numbers associated with that part number, such as in database 320
(shown in FIG. 3). In these embodiments, database 320 stores serial
numbers associated with each part number, where each serial number
is of a RFID component 106 that was installed in a previous
vehicle, such as "as-delivered" configuration 640 (shown in FIG.
6). In these embodiments, RFID analysis computer device 310
compares the serial number received in the response signal and the
store serial number to determine if they match within certain
parameters. For example, each serial number is supposed to be
unique; therefore, RFID analysis computer device 310 compares the
serial numbers based on pattern matching. For example, where a
received response signal including a part number and serial number
is associated with an RFID component that is a passenger seat, each
passenger seat may have a unique serial number 000541XXXX where the
last four characters are unique to each seat, while the first six
sequential characters match that of stored serial numbers for seats
installed in a previous "as-delivered" vehicle. In some
embodiments, RFID analysis computer device 310 also compares the
part number receives from the response signal to a part number or a
plurality of part numbers for the component in the "as-delivered"
configuration 640 and/or the "as-designed" configuration 630 (shown
in FIG. 3). In these embodiments, the RFID component 106 may have
been upgraded from the "as-designed" configuration 630 and have a
different part number. In these embodiments, RFID analysis computer
device 310 may analyze the part number to determine the extent of
the match to determine if the correct part is being used. This
analysis may include pattern recognition and/or algorithm matching.
For example, the analysis for determining an extent of a match
and/or level of correlation, between the serial number associated
with a response signal for an RFID component and the stored serial
number, may comprise determining the number of sequential
characters in the stored serial number that match a corresponding
number of sequential characters in the serial number associated
with a response signal. In the example embodiment, the closer the
correlation between the received serial number and the stored
serial number, the higher the level of correlation.
[0087] RFID analysis computer device 310 calculates 1030 a
confidence score for each RFID component based on the corresponding
comparison of the location and the level of correlation. For
example, the calculation of the confidence score may comprise a
percentage that is based on the number of characters that match
between the serial number associated with a response signal and the
stored serial number. The calculation of the confidence score may
also comprise a weighting or percentage that is based on the level
of correlation or proximity of the determined RFID component
location to an expected location of the RFID component. For
example, a weighting reflecting a high level of correlation may
correspond to a proximity within 6 inches, a weighting reflecting a
low level of correlation may correspond to a proximity greater than
12 inches, with a medium level of correlation corresponding to a
proximity between 6 and 12 inches from the expected location of the
RFID component. RFID analysis computer device 310 generates 1035 a
listing of the plurality of RFID components including the
associated confidence score.
[0088] In some embodiments, the location device 325 is also capable
of determining an orientation of the scanning device 305. In these
embodiments, RFID analysis computer device 310 receives, from the
location device 325, the orientation of the scanning device 305.
RFID analysis computer device 310 determines the plurality of
component locations based on the location and the orientation of
the scanning device 305. In some further embodiments, each of the
plurality of response signals include a signal strength. RFID
analysis computer device 310 determines the component location
based on the signal strength of the corresponding response
signal.
[0089] In some still further embodiments, RFID analysis computer
device 310 stores a layout of a vehicle, where the scanning device
305 is a mobile device located in the vehicle. RFID analysis
computer device 310 determines the location of the scanning device
305 in relation to the vehicle. For each of the plurality of RFID
components, RFID analysis computer device 310 determines the
location of the RFID component in the vehicle based on the location
in relation to the vehicle of the scanning device 305, the
orientation of the scanning device 305, and signal strength of the
response signal associated with RFID component.
[0090] In some embodiments, each of the plurality of response
signals includes a part number associated with the RFID component.
RFID analysis computer device 310 stores a plurality of designed
RFID components designed to be installed in the vehicle. RFID
analysis computer device 310 compares the component location of the
RFID component with the plurality of designed RFID components. RFID
analysis computer device 310 determines a designed RFID component
designated to be at the component location based on the comparison.
RFID analysis computer device 310 determines whether the part
number of the RFID component matches the designed RFID component.
If the determination is that the part number matches the designed
RFID component, RFID analysis computer device 310 indicates that
the RFID is properly installed. If the determination is that the
part number does not match the designed RFID component, RFID
analysis computer device 310 transmits an alarm to a user.
[0091] In some embodiments, RFID analysis computer device 310
stores a plurality of potential part numbers for the designed RFID
component. RFID analysis computer device 310 compares the part
number to the plurality of potential part numbers to determine if a
match is found. In some further embodiments, RFID analysis computer
device 310 stores an algorithm for a potential part number for the
designed RFID component and compares the part number to the
algorithm to determine if a match is found.
[0092] In some embodiments, each of the plurality of response
signals includes a part number and a serial number associated with
the RFID component. In these embodiments, RFID analysis computer
device 310 parses the plurality of response signals by part number.
RFID analysis computer device 310 determines a part number
associated with more than one response. Then RFID analysis computer
device 310 determines a plurality of serial numbers associated with
the part number based on the more than one response.
[0093] FIG. 11 is a diagram 1100 of components of one or more
example computing devices that may be used in system 100 (shown in
FIG. 1) and system 300 (shown in FIG. 3). In some embodiments,
computing device 1110 is similar to RFID analysis computer device
310 (shown in FIG. 3). Database 1120 may be coupled with several
separate components within computing device 1110, which perform
specific tasks. In this embodiment, database 1120 includes
as-designed configurations 1122, as-delivered configurations 1124,
location information 1126, and part numbers and serial numbers
1128. In some embodiments, database 1120 is similar to database 320
(shown in FIG. 3).
[0094] Computing device 1110 includes database 1120, as well as
data storage devices 1130. Computing device 1110 also includes a
communication component 1140 for receiving 1005 a plurality of
response signals and receiving 1010 a location of a scanning device
when scanning a plurality of RFID components (shown in FIG. 10).
Computing device 1110 further includes a determining component 1150
for determining 1015 a component location, a serial number, and a
part number based on a corresponding response signal of the
plurality of response signals and determining 1025 a level of
correlation (both shown in FIG. 10). In addition, computing device
1110 includes a comparing component 1160 for comparing 1020 the
component location to an expected location of the RFID component
(shown in FIG. 10). Moreover, computing device 1110 includes a
calculating component 1170 for calculating 1030 a confidence score
for each RFID component based on the corresponding comparison
(shown in FIG. 10). Furthermore, computing device 1110 includes a
generating component 1180 for generating 1035 a listing of the
plurality of RFID components including the associated confidence
score (shown in FIG. 10). A processing component 1190 assists with
execution of computer-executable instructions associated with the
system.
[0095] A processor or a processing element may be trained using
supervised or unsupervised machine learning, and the machine
learning program may employ a neural network, which may be a
convolutional neural network, a deep learning neural network, or a
combined learning module or program that learns in two or more
fields or areas of interest. Machine learning may involve
identifying and recognizing patterns in existing data in order to
facilitate making predictions for subsequent data. Models may be
created based upon example inputs in order to make valid and
reliable predictions for novel inputs.
[0096] Additionally or alternatively, the machine learning programs
may be trained by inputting sample data sets or certain data into
the programs, such as image data, previously recognized markings,
previously identified parts, previous location analysis based on
RFID signal strength, and other data. The machine learning programs
may utilize deep learning algorithms that may be primarily focused
on pattern recognition, and may be trained after processing
multiple examples. The machine learning programs may include
Bayesian program learning (BPL), image or object recognition,
optical character recognition, pixel recognition, and/or natural
language processing--either individually or in combination. The
machine learning programs may also include natural language
processing, semantic analysis, automatic reasoning, and/or machine
learning.
[0097] In supervised machine learning, a processing element may be
provided with example inputs and their associated outputs, and may
seek to discover a general rule that maps inputs to outputs, so
that when subsequent novel inputs are provided the processing
element may, based upon the discovered rule, accurately predict the
correct output. In unsupervised machine learning, the processing
element may be required to find its own structure in unlabeled
example inputs. In one embodiment, machine learning techniques may
be used to extract data about a part, one or more markings, image
data, and/or other data.
[0098] Based upon these analyses, the processing element may learn
how to identify characteristics and patterns that may then be
applied to analyzing engineering drawings, image data, and/or other
data. For example, the processing element may learn to identify a
location of an object among a plurality of objects. The processing
element may also learn how to recognize related part numbers.
[0099] The computer-implemented methods discussed herein may
include additional, less, or alternate actions, including those
discussed elsewhere herein. The methods may be implemented via one
or more local or remote processors, transceivers, servers, and/or
sensors (such as processors, transceivers, servers, and/or sensors
mounted on vehicles or mobile devices, or associated with smart
infrastructure or remote servers), and/or via computer-executable
instructions stored on non-transitory computer-readable media or
medium. Additionally, the computer systems discussed herein may
include additional, less, or alternate functionality, including
that discussed elsewhere herein. The computer systems discussed
herein may include or be implemented via computer-executable
instructions stored on non-transitory computer-readable media or
medium.
[0100] As used herein, the term "non-transitory computer-readable
media" is intended to be representative of any tangible
computer-based device implemented in any method or technology for
short-term and long-term storage of information, such as,
computer-readable instructions, data structures, program modules
and sub-modules, or other data in any device. Therefore, the
methods described herein may be encoded as executable instructions
embodied in a tangible, non-transitory, computer readable medium,
including, without limitation, a storage device and/or a memory
device. Such instructions, when executed by a processor, cause the
processor to perform at least a portion of the methods described
herein. Moreover, as used herein, the term "non-transitory
computer-readable media" includes all tangible, computer-readable
media, including, without limitation, non-transitory computer
storage devices, including, without limitation, volatile and
nonvolatile media, and removable and non-removable media such as a
firmware, physical and virtual storage, CD-ROMs, DVDs, and any
other digital source such as a network or the Internet, as well as
yet to be developed digital means, with the sole exception being a
transitory, propagating signal.
[0101] As described above, the implementations described herein
relate to radio frequency identifier ("RFID") part scanning, and
more specifically, to scanning, identifying, and verifying a
plurality of closely located parts with RFID tags. More
specifically, an RFID analysis computer device (also known as an
RFID analysis server) analyzes received RFID signals to locate and
identify the parts in an area with a high concentration of RFID
tags. The RFID analysis computer device compares the identified
parts to potential parts at that location to confirm that the
proper parts are identified.
[0102] The above-described methods and systems for high density
RFID part scanning are cost-effective, secure, and highly reliable.
The methods and systems include receiving a location of a scanning
device when scanning a plurality of RFID components, determining a
component location based on a corresponding response signal of the
plurality of response signals for each of the plurality of RFID
components, compare the component location to an expected location
of the RFID component for each of the plurality of RFID components,
calculate a confidence score for each RFID component based on the
corresponding comparison; and generate a listing of the plurality
of RFID components including the associated confidence score.
Accordingly, the methods and systems facilitate improving the use
and efficiency of RFID scanning by reducing the number of scans
required to identify and locate a plurality of objects.
[0103] The methods and system described herein may be implemented
using computer programming or engineering techniques including
computer software, firmware, hardware, or any combination or
subset. As disclosed above, at least one technical problem with
prior systems is that there is a need for systems for a
cost-effective and reliable manner for converting engineering
drawings. The system and methods described herein address that
technical problem. The technical effect of the systems and
processes described herein is achieved by performing at least one
of the following steps: (a) receiving, from a scanning device, a
plurality of response signals from a plurality of RFID components;
(b) receiving, from a location device, a location of the scanning
device when the scanning device received the plurality of response
signals; (c) for each of the plurality of RFID components,
determining a component location based on a corresponding response
signal of the plurality of response signals; (d) for each of the
plurality of RFID components, comparing the component location to
an expected location of the RFID component; (e) calculating a
confidence score for each RFID component based on the corresponding
comparison; and (0 generating a listing of the plurality of RFID
components including the associated confidence score.
[0104] The resulting technical effect is locating, identifying, and
verifying parts with RFID tags in an area with a high density of
RFID tagged parts.
[0105] This written description uses examples to disclose various
implementations, including the best mode, and also to enable any
person skilled in the art to practice the various implementations,
including making and using any devices or systems and performing
any incorporated methods. The patentable scope of the disclosure is
defined by the claims, and may include other examples that occur to
those skilled in the art. Such other examples are intended to be
within the scope of the claims if they have structural elements
that do not differ from the literal language of the claims, or if
they include equivalent structural elements with insubstantial
differences from the literal language of the claims.
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