DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-5, 7-12, 14-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to the judicial exception of mental process type abstract idea (concepts performable in the human mind, including an observation, evaluation, judgement, and opinion) without significantly more.
Independent claim 1 recites, “identifying license plate information of a license plate; associating the license plate information with a parking spot; storing the license plate information in association with the parking spot; and checking the license plate information in association with the parking spot against a parking facility monitoring system”. Similarly, independent claim 12 recites, “identify license plate information of a license plate; associate the license plate information with a parking spot; store the license plate information in association with the parking spot; and check the license plate information in association with the parking spot against a parking facility monitoring system”.
The noted subject matter of claims 1 and 12 refer to identifying license plate information of a license plate, associating the license plate information with a parking spot of a parking facility, storing the license plate information in association with the parking spot, and checking the stored license plate information in association with the parking spot; which are described with a high level of generality which a person may practically perform in the human mind and the use of a physical aid such as pen and paper by viewing and recognizing the license plate information of a vehicle parked in a parking spot, storing the information by mentally memorizing the license plate information associated with the parking spot or recording the information with pen and paper, and performing mental comparisons with previously monitored parking facility records. Thus, the broadest reasonable interpretation, in light of the specification, of the claimed subject matter directs to performing mental observations and evaluations, falling within the “mental processes” grouping of abstract ideas.
The judicial exception of claim 12 is further not integrated into a practical application because the additional claim limitations of, “one or more memories; and one or more processors coupled with the one or more memories” describe the use of generic computing elements to implement the noted abstract idea with a high level of generality, such that the claims amounts merely implementing the abstract idea on generic computing elements. See MPEP 2106.04(d), MPEP 2106.05(b), and MPEP 2106.05(f). Furthermore, in consideration of the claim 12 additional elements as a combination, the additional elements continue to merely implement the abstract idea on generic computing elements, and thus do not provide significantly more than the noted judicial exception.
Claims 2-5 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional recited claim subject matter of,
“navigating through the parking facility to perform the identifying license plate information of the license plate based on a trigger” (claim 2);
“the trigger is caused by an anomaly” (claim 3);
“the anomaly is associated with at least one of an entry and exit timing event or the license plate” (claim 4); and
“the trigger is based on at least one of a manual user selection or a schedule, or is associated with the parking spot” (claim 5);
refer to additional steps of the noted mental process type abstract idea that are described with a high level of generality such that a person may continue to practically perform the broadest reasonable interpretation of the claimed steps within the human mind. See MPEP 2106.04(a)(2) III. In regards to the claim 2-5 subject matter, a person can walk through a parking facility, where navigating the parking facility and identifying license plate information of parked vehicles are performed mentally in response to vehicles entering to park at or leaving a parking spot in the parking facility. See MPEP 2106.04(a)(2) III. and MPEP 2106.04(a)(2) III. B. If the additional claim elements merely recite another judicial exception, that is insufficient to integrate the judicial exception into a practical application. See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017). See MPEP 2106.04 II. A. 2.
Claims 2-5 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the above noted additional claim limitations, similarly as discussed above, continue to merely encompass performing respective additional steps of the mental processes type abstract idea, and are insufficient to provide significantly more than the noted judicial exceptions. See MPEP 2106.04 II. A. 2. Furthermore, in consideration of the claims 2-5 additional elements as a combination, the additional elements continue to merely perform respective additional steps of the mental process activity, and do not provide significantly more than the noted judicial exception.
Claims 7, 9, 11, and 14 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional claimed subject matter of
“transmitting an alert, alarm, or notification to the parking facility monitoring system if checking the license plate information against the parking facility monitoring system results in a discrepancy” (claims 7 and 14);
“maintaining one or more parking space counts, wherein each of the one or more parking space counts is associated with a number of parking spaces in a specified area of the parking facility; and transmitting the one or more parking space counts to the parking facility monitoring system to maintain an accurate population count of vehicles at the parking facility” (claim 9); and
“checking whether the license plate information matches previously stored license plate information in association with the parking spot; and updating the license plate information stored in association with the parking spot by removing and/or replacing previously stored license plate information if the license plate information has changed” (claim 11) describe functions at a high level of generality for maintaining and updating a record for parking spaces and associated license plate information and for transmitting data associated with the parking spaces record data, which amount to performing computer functions (e.g. receiving and transmitting data, electronic recordkeeping, and storing and retrieving information in memory) that have been recognized by the courts as well-understood, routine, and conventional functions. See MPEP 2106.05(d).
Claims 7, 9, 11, and 14 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the above noted additional claim limitations, similarly as discussed above, continue to merely encompass performing functions that have been recognized by the courts as well-understood, routine, and conventional functions, and are insufficient to provide significantly more than the noted judicial exceptions. See MPEP 2106.05(d). Furthermore, in consideration of the claims 7, 9, 11, and 14 additional elements as a combination, the additional elements continue to merely perform functions recognized as well-understood, routine, and conventional functions, and do not provide significantly more than the noted judicial exception.
Claims 8, 10, and 15 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional claimed subject matter of
“capturing one or more images of the license plate; and performing character recognition on the one or more images” (claims 8 and 15); and
“the license plate information is reviewable by a user of the parking facility monitoring system” (claim 10) describe data gathering steps and selecting particular data source or type of data to be manipulated, such that the claims merely add insignificant extra-solution activity to the judicial exceptions. See MPEP 2106.04(d) and MPEP 2106.05(g).
Claims 8, 10, and 15 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the above noted additional claim limitations, similarly as discussed above, continue to merely encompass performing additional insignificant extra solution activity to the noted abstract idea activity, and are insufficient to provide significantly more than the noted judicial exceptions. See MPEP 2106.05(g). Furthermore, in consideration of the claims 8, 10, and 15 additional elements as a combination, the additional elements continue to merely perform additional insignificant extra solution activity to the noted abstract idea activity, and do not provide significantly more than the noted judicial exception.
Examiner notes that claims 6, 13, and 16 recite additional features of “wherein navigating through the parking facility comprises the robot running an obstacle avoidance program equipped with artificial intelligence(AI)/machine learning (ML)” (claims 6 and 13) and “one or more robots, wherein each of the one or more robots comprises: one or more cameras; one or more mobility subsystems; one or more memories; and one or more processors that are individually or in combination configured to: identify license plate information of a license plate; associate the license plate information with a parking spot; store the license plate information in association with the parking spot; and communicate with the parking facility monitoring station to check the stored license plate information in association with the parking spot” (claim 16), where the consideration of the additional claim elements as a combination requires the integral use of a particular robot machine to perform the functions of the above noted abstract idea judicial exception, such that the claim as a whole amounts to significantly more than the noted abstract idea judicial exception. See MPEP 2106.04(d) and MPEP 2106.05(b)
Thus, claims 6, 13, and 16-20 are directed to statutory eligible subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-16 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (US 10,311,731), herein Li.
Regarding claim 1, Li discloses a method of using a robot to validate a license plate recognition check at a parking facility (see Li col. 5, ln. 30-55, where an autonomous data machine (ADM) is employed to autonomously navigate and monitor parking areas to provide relevant parking information), comprising:
identifying license plate information of a license plate (see Li col. 9, ln. 30 – col. 10, ln. 45, where license plate detection is performed to collect license plate information, where one or more cameras may be used for license plate detection; see Li col. 11, ln. 65- col. 12, ln. 15, where license plates of vehicles are detected and read);
associating the license plate information with a parking spot (see Li col. 11, ln. 65- col. 12, ln. 50, where information relating to one or more parking spaces within the parking area is collected, including occupancy information for the parking space, where occupancy information includes information relating to a vehicle occupying the parking space, e.g. license plate; see also Li col. 14, ln. 60- col. 15, ln. 15, where detected license plate information can improve the accuracy of occupancy information regarding a parking space);
storing the license plate information in association with the parking spot (see Li col. 7, ln. 45-60, where data received from the sensors of the ADM are processed by a processing module and stored within memory, where sensor data can be processed by suitable computer vision algorithms to perform target identification and tracking, and optical character recognition; see Li col. 11, ln. 65- col. 12, ln. 15, where license plates of vehicles can be detected and read, and the collected license plate information is compared to other information; see Li col. 17, ln. 40-50, where information for a parking space can be updated with repeat scans of the vehicle and/or license plate of the parking space; and see Li col. 27, ln. 10-25, where a vehicle identifier such as the license plate can be viewed and displayed with information about the vehicle’s location, e.g. parking space number); and
checking the license plate information in association with the parking spot against a parking facility monitoring system (see Li col. 11, ln. 65- col. 12, ln. 15, where the collected license plate information is communicated to a remote entity and compared to other information, e.g. a list or database of known license plates).
Although Li does not explicitly disclose all features within the same embodiment, Li further teaches that the disclosed embodiments are provided by examples and numerous variations, changes, and substitutions will occur to those skilled in the art without departing from the invention, and that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention (see Li col. 36, ln. 15-25). Thus, one of ordinary skill in the art, in view of the suggested disclosed features of the embodiments of Li, would have found it obvious and led to combine the disclosed features and arrive at the claimed invention. This modification is rationalized as some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention.In this instance, Li provides the suggested teachings that the feature of the various disclosed embodiments, where one of ordinary skill in the art may modify and combine the features of the disclosed embodiments to the same embodiment. One of ordinary skill in the art would have reasonable expectation of success of combining the disclosed features in the same embodiment for employing the disclosed autonomous data machine to navigate and monitor a parking facility.
Regarding claim 2, please see the above rejection of claim 1. Li discloses the method of claim 1, further comprising:
navigating through the parking facility to perform the identifying license plate information of the license plate based on a trigger (see Li col. 11, ln. 65- col. 12, ln. 15, where the ADM autonomously navigates within a parking area to detect and read license plates of vehicles; see Li col. 17, ln. 40-50, where the ADM can detect when vehicles are moving in or out of parking spaces and store information regarding these parking spaces, and the ADM can adjust its movement path within the parking area so as to repeat the scan of the vehicle and/or license plate of the previously identified parking space).
Regarding claim 3, please see the above rejection of claim 2. Li discloses the method of claim 2, wherein the trigger is caused by an anomaly (see Li col. 17, ln. 40-50, where the ADM can detect when vehicles are moving in or out of parking spaces and store information regarding these parking spaces, and the ADM can adjust its movement path within the parking area so as to repeat the scan of the vehicle and/or license plate of the previously identified parking space).
Regarding claim 4, please see the above rejection of claim 3. Li discloses the method of claim 3, wherein the anomaly is associated with at least one of an entry and exit timing event or the license plate (see Li col. 17, ln. 40-50, where the ADM can detect when vehicles are moving in or out of parking spaces and store information regarding these parking spaces, and the ADM can adjust its movement path within the parking area so as to repeat the scan of the vehicle and/or license plate of the previously identified parking space).
Regarding claim 5, please see the above rejection of claim 2. Li discloses the method of claim 2, wherein the trigger is based on at least one of a manual user selection or a schedule, or is associated with the parking spot (see Li col. 13, ln. 5-15, where the movement path of the ADM can be a loop and can be traveled repeatedly at a specified frequency to provide periodic updates to the parking information obtained from the parking area ).
Regarding claim 6, please see the above rejection of claim 2. Li discloses the method of claim 2, wherein navigating through the parking facility comprises the robot running an obstacle avoidance program equipped with artificial intelligence(AI)/machine learning (ML) (see Li col. 7, ln. 45 – col. 8, ln. 5, where the data received from the sensors on the ADM are used to facilitate autonomous navigation including obstacle detection and the controller controls various operation aspects of the ADM such as propulsion, navigation, sensing, data processing; see Li col. 13, ln. 35-60, where the ADM can be designed to avoid potential collisions or obstructing vehicles when navigating the parking area and utilize various obstacle detection sensors and adjust its motion as needed to avoid colliding with and/or obstructing a vehicle or human; see Li col. 35, ln. 55 – col. 36, ln. 15, where one or more processors of a computer system can execute code stored upon storage media and computer readable media to implement the disclosed teachings).
Regarding claim 7, please see the above rejection of claim 1. Li discloses the method of claim 1, further comprising:
transmitting an alert, alarm, or notification to the parking facility monitoring system if checking the license plate information against the parking facility monitoring system results in a discrepancy (see Li col. 17, ln. 25 – ln. 50, where the license plate information may be used to detect whether a vehicle is the same or a different type than a designation for a parking space and the ADM may provide an alert when the parking space is occupied by a different vehicle type; see Li col. 26, ln. 25-50, where an alert may be provided when a vehicle on a black list excluded from parking in the parking area is detected in the parking area).
Regarding claim 8, please see the above rejection of claim 1. Li discloses the method of claim 1, wherein identifying license plate information of the license plate comprises:
capturing one or more images of the license plate (see Li col. 10, ln. 1-15, where cameras are used for license plate detection to capture images and the images are analyzed to provide automated license plate recognition); and
performing character recognition on the one or more images (see Li col. 7, ln. 49-60, where data received from sensors can be processed by suitable computer vision algorithms to perform optical character recognition; see Li col. 9, ln. 30-50, where license plate detection may include alphanumeric characters).
Regarding claim 9, please see the above rejection of claim 1. Li discloses the method of claim 1, further comprising:
maintaining one or more parking space counts, wherein each of the one or more parking space counts is associated with a number of parking spaces in a specified area of the parking facility (see Li col. 21, ln. 25–ln. 40, where an indication of utilization for the parking spaces can be provided, and may indicate the number of parking spaces out of a total number of parking spaces in the sector are utilized); and
transmitting the one or more parking space counts to the parking facility monitoring system to maintain an accurate population count of vehicles at the parking facility (see Li col. 19, ln. 28–ln. 60, where the parking information can be transmitted by the ADM to existing parking information system).
Regarding claim 10, please see the above rejection of claim 1. Li discloses the method of claim 1, wherein the license plate information is reviewable by a user of the parking facility monitoring system (see Li col. 19, ln. 25 – col. 20, ln. 30, where parking information can be transmitted by the ADM to existing parking information system, and a use can view the information on a user interface (UI); see Li col. 27, ln. 10-25, where a vehicle identifier such as the license plate can be viewed by a user).
Regarding claim 11, please see the above rejection of claim 1. Li discloses the method of claim 1, further comprising:
checking whether the license plate information matches previously stored license plate information in association with the parking spot (see Li col. 11, ln. 65- col. 12, ln. 15, where the collected license plate information is compared to other information, e.g. a list or database of known vehicles; see Li col. 17, ln. 50 –ln. 60, where the ADM can store information regarding scanned parking spaces and repeat the scan of the vehicle and/or license plate of the previously identified parking spaces); and
updating the license plate information stored in association with the parking spot by removing and/or replacing previously stored license plate information if the license plate information has changed (see Li col. 17, ln. 50 –ln. 60, where information for a parking space can be updated with repeat scans of the vehicle and/or license plate of the parking space).
Regarding claim 12, it recites an apparatus performing the method of claim 1. Li teaches an apparatus performing the method of claim 1 (see Li col. 7, ln. 20 - col. 8, ln. 50, where an autonomous data machine (ADM) is disclosed to perform the disclosed teachings for autonomously navigating and monitoring parking areas to provide relevant parking information). Please see above for detailed claim analysis, with the exception to the following further limitations:
one or more memories (see Li col. 35, ln. 55 – col. 36, ln. 15, where storage media and computer readable media for containing code are disclosed); and
one or more processors coupled with the one or more memories, wherein the one or more processors are configured, individually or in combination, to perform the method of claim 1 (see Li col. 35, ln. 55 – col. 36, ln. 15, where one or more processors of a computer system can execute code stored upon storage media and computer readable media to implement the disclosed teachings).
Please see the above rejection for claim 1, as the rationale to combine the teachings of Li is similar, mutatis mutandis.
Regarding claim 13, see above rejection for claim 12. It is an apparatus claim reciting similar subject matter as claim 6. Please see above claim 6 for detailed claim analysis as the limitations of claim 13 are similarly rejected.
Regarding claim 14, see above rejection for claim 12. It is an apparatus claim reciting similar subject matter as claim 7. Please see above claim 7 for detailed claim analysis as the limitations of claim 14 are similarly rejected.
Regarding claim 15, see above rejection for claim 12. It is an apparatus claim reciting similar subject matter as claim 8. Please see above claim 8 for detailed claim analysis as the limitations of claim 15 are similarly rejected.
Regarding claim 16, Li discloses a system for validating a license plate recognition check at a parking facility, comprising:
a license plate recognition check subsystem (see Li col. 9, ln. 30- col. 10, ln. 5, where one or more sensors can be used for license plate detection and an external device in communication with the ADM may be capable of license plate detection);
a parking facility monitoring station (see Li col. 19, ln. 25- col. 20, ln. 10, where the information collected parking information can be integrated or combined with an existing parking information system, where a user may monitor the parking area at a security operations center); and
one or more robots (see Li col. 7, ln. 20 - col. 8, ln. 50, where an autonomous data machine (ADM) is disclosed to perform the disclosed teachings for autonomously navigating and monitoring parking areas to provide relevant parking information), wherein each of the one or more robots comprises:
one or more cameras (see Li col 10,ln. 35-40, where the ADM includes one or more cameras);
one or more mobility subsystems (see Li col. 5, ln. 55 - col. 6, ln. 15, where the ADM includes a suitable propulsion system for navigating the environment);
one or more memories (see Li col. 35, ln. 55 – col. 36, ln. 15, where storage media and computer readable media for containing code are disclosed); and
one or more processors (see Li col. 35, ln. 55 – col. 36, ln. 15, where one or more processors of a computer system can execute code stored upon storage media and computer readable media to implement the disclosed teachings) that are individually or in combination configured to:
identify license plate information of a license plate (see Li col. 9, ln. 30 – col. 10, ln. 45, where license plate detection is performed to collect license plate information, where one or more cameras may be used for license plate detection; see Li col. 11, ln. 65- col. 12, ln. 15, where license plates of vehicles are detected and read);
associate the license plate information with a parking spot (see Li col. 11, ln. 65- col. 12, ln. 50, where information relating to one or more parking spaces within the parking area is collected, including occupancy information for the parking space, where occupancy information includes information relating to a vehicle occupying the parking space, e.g. license plate; see also Li col. 14, ln. 60- col. 15, ln. 15, where detected license plate information can improve the accuracy of occupancy information regarding a parking space);
store the license plate information in association with the parking spot (see Li col. 7, ln. 45-60, where data received from the sensors of the ADM are processed by a processing module and stored within memory, where sensor data can be processed by suitable computer vision algorithms to perform target identification and tracking, and optical character recognition; see Li col. 11, ln. 65- col. 12, ln. 15, where license plates of vehicles can be detected and read, and the collected license plate information is compared to other information; see Li col. 17, ln. 40-50, where information for a parking space can be updated with repeat scans of the vehicle and/or license plate of the parking space; and see Li col. 27, ln. 10-25, where a vehicle identifier such as the license plate can be viewed and displayed with information about the vehicle’s location, e.g. parking space number); and
communicate with the parking facility monitoring station to check the stored license plate information in association with the parking spot (see Li col. 11, ln. 65- col. 12, ln. 15, where the collected license plate information is communicated to a remote entity and compared to other information, e.g. a list or database of known license plates).
Although Li does not explicitly disclose all features within the same embodiment, Li further teaches that the disclosed embodiments are provided by examples and numerous variations, changes, and substitutions will occur to those skilled in the art without departing from the invention, and that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention (see Li col. 36, ln. 15-25). Thus, one of ordinary skill in the art, in view of the suggested disclosed features of the embodiments of Li, would have found it obvious and led to combine the disclosed features and arrive at the claimed invention. This modification is rationalized as some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention.In this instance, Li provides the suggested teachings that the feature of the various disclosed embodiments, where one of ordinary skill in the art may modify and combine the features of the disclosed embodiments to the same embodiment. One of ordinary skill in the art would have reasonable expectation of success of combining the disclosed features in the same embodiment for employing the disclosed autonomous data machine to navigate and monitor a parking facility.
Regarding claim 18, please see the above rejection of claim 16. Li discloses the system of claim 16, wherein the parking facility monitoring station comprises:
one or more databases (see Li col. 12, ln. 1-25, where a list or database of known license plates is disclosed; see Li col. 19, ln. 40-55, where the parking information can be transmitted to a remote computing system, e.g. a server);
one or more graphical user interfaces (see Li col. 20, ln. 5-30, where the parking information can be presented on a user interface (UI)); and
one or more processors that are individually or in combination configured to: display parking information via the graphical user interface for review by a user (see Li col. 19, ln. 40 - col. 20, ln. 30, where the parking information can be presented to a user on a UI of a display system of a computing system).
Regarding claim 19, please see the above rejection of claim 18. Li discloses the system of claim 18, wherein the parking information comprises one or more of a total parking space occupancy count, a total parking space vacancy count, a robot status indicator, an alert, an alarm, a notification, license plate information, and parking spot information (see Li col. 20, ln. 5-25, where parking information can be presented on a UI, including location of parking spaces, availability or occupancy of parking spaces, vehicle and license plate information of occupying vehicles, and parking space statistics and utilization; see Li col. 21, ln. 25-40 where an indication of utilization can be provided about how much a corresponding sector is utilized, and can indicate the number of parking spaces out of a total number of parking spaces in the sector were utilized; see Li col. 26, ln. 25-50, where an alert may be provided when a vehicle on a black list excluded from parking in the parking area is detected in the parking area; see Li col. 32, ln. 40-55, where a map may show the position of an ADM within a parking structure).
Regarding claim 20, please see the above rejection of claim 16. Li discloses the system of claim 16, wherein the one or more robots autonomously patrol the parking facility (see Li col. 5, ln. 30-55, where the ADM are employed to autonomously navigate and monitor parking areas).
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Li as applied to claim 16 above, and further in view of Hong et al. (KR 20220071771), herein Hong.
Regarding claim 17, please see the above rejection of claim 16. Li discloses the system of claim 16, wherein the license plate recognition check subsystem comprises:
a parking spot presence counter configured to determine the presence of a vehicle in a parking spot (see Li col. 12, ln. 25-40, where the ADM can collect occupancy information regarding whether a parking space is occupied; see Li col. 21, ln. 25-40 where an indication of utilization can be provided about how much a corresponding sector is utilized, and can indicate the number of parking spaces out of a total number of parking spaces in the sector were utilized).
While Li teaches that an external device in communication with the ADM may be capable of license plate detection (see Li col. 9, ln. 30- col. 10, ln. 5), and that the information collected parking information can be integrated or combined with an existing parking information system, where a user may monitor the parking area at a security operations center (see Li col. 19, ln. 25- col. 20, ln. 10); Li does not explicitly disclose one or more cameras configured to capture images of a license plate upon entry and exit of the parking facility.
Hong teaches in a related and pertinent license plate identification system (see Hong Abstract), where a target vehicle license plate is detected from image data to be analyzed to obtain a vehicle number from the detected license plate and that license plate of a vehicle entering a parking lot can be recognized more clearly using the vehicle license plate recognition system (see Hong [0021]-[0022]), and that the extracted vehicle number can be used to provide a visual or auditory output of the vehicle number, determine whether entry or exit is possible based on the vehicle number, control a barrier, and/ or process fee settlement based on entry and exit times (see Hong [0074]-[0078]).
At the time of filing, one of ordinary skill in the art would have found it obvious to combine the teachings of Li with the teachings of Hong, such that images of the license plates of vehicles entering or exiting the parking facility can be captured by cameras and used to detect and license plate numbers for to be integrated and combined with existing parking information system for the operations of the parking facility.
This modification is rationalized as combining prior art elements according to known methods to yield predictable results.
Li discloses a system for employing an ADM to navigate and monitor a parking facility, where an external device in communication with the ADM may be capable of license plate detection, and that the information collected parking information can be integrated or combined with an existing parking information system, where a user may monitor the parking area at a security operations center.
Hong teaches a license plate identification system, where a target vehicle license plate is detected from image data to be analyzed to obtain a vehicle number from the detected license plate and that license plate of a vehicle entering a parking lot can be recognized more clearly using the vehicle license plate recognition system, and that the extracted vehicle number can be used to provide a visual or auditory output of the vehicle number, determine whether entry or exit is possible based on the vehicle number, control a barrier, and/ or process fee settlement based on entry and exit times.
One of ordinary skill in the art could have combined the disclosed teachings by capturing images of the license plates of vehicles entering or exiting the parking facility by cameras and the images are used to detect and license plate numbers for to be integrated and combined with existing parking information system, along with the parking information collected by the ADMs employed to navigate and monitor the parking facility, and predictably result in using the integrated and combined parking information for the operations of the parking facility.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TIMOTHY WING HO CHOI whose telephone number is (571)270-3814. The examiner can normally be reached 9:00 AM to 5:00 PM.
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/TIMOTHY CHOI/Examiner, Art Unit 2671
/VINCENT RUDOLPH/Supervisory Patent Examiner, Art Unit 2671
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