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 .
The application of Sachdeva et al. for a “trajectory and intend prediction” filed on April 24, 2025 has been examined.
This application is a CON of 18/257,182, filed on June 13, 2023, now US# 12,367,725.
This application claims priority to a 371 of PCT/EP2021/084586, which is filed on December 7, 2021.
The PCT/EP2021/084586 has a PRO of 63/125,044 which is filed on December 14, 2020.
Claims 1-20 are pending.
Specification
The disclosure is objected to because of the following informalities: Under cross references to related applications CON status needs to be updated. Serial number CON of 18/257,182, filed on June 13, 2023, now US# 12,367,725.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 11-15, 17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Child et al. (US# 10,127,754) in view of Stuntebeck et al. (Pub. No. US 2016/0196414).
Referring to claim 1, Child et al. disclose a method for access control (column 1 line 43 to column 4 line 19; see Figures 1-13), comprising:
receiving, by one or more processors (410) (i.e. an identification module 410 of a barrier control module 110-a), credentials for a user to access an access control device (110-a) (i.e. determining an identity of a first user outside a home. As described above, according to embodiment, the identity of the first user may be determined in a variety of ways and using a number of modules, sensors, and other devices. Some embodiments may utilize at least one camera and the identity of the first user may be based at least in part on visual data of the user captured by the at least one camera, as well as by other scanners and devices) (column 29 lines 59 to 67; column 30 lines 58 to 67; see Figures 10-13);
determining a confidence level of a user behavior model trained for the user (i.e. he method 1300 may include a plurality of queries. In one embodiment, algorithms, comparisons, calculations, and/or other operations placing greater or lesser weight on particular queries (e.g., those relating to changeable features) and keeping track of the number of correct queries may assist in determining whether a threshold confidence level is satisfied) (column 31 line 1 to 9; see Figure 13);
restricting access to the access control device to a short-range communication protocol when the confidence level is below a threshold (i.e. a door may remain in a locked state until correct responses to the queries satisfy a threshold confidence or certainty level) (column 31 lines 9 to 11; see Figure 13).
However, Child et al. did not explicitly disclose collecting user behavior information during a training period;
updating the user behavior model based on the collected user behavior information; and
in response to determining that the updated user behavior model has achieved the confidence level above the threshold, enabling access to the access control device using a long-range communication protocol.
In the same field of endeavor of an access control system, Stuntebeck et al. teach that collecting user behavior information during a training period (i.e. a certain amount of variability may be permitted. For example, the movement pattern may be recorded by a user raising the device eighteen inches and then rotating the device 270 degrees) (page 5 paragraph 0046; see Figures 1 and 2);
updating the user behavior model based on the collected user behavior information (i.e. user 310 may manipulate user device 320 by a first motion 380(A), such as raising user device 320, and a second motion 380(B), such as rotating user device 320 clockwise. These motions may be tracked and/or recorded by accelerometer 340. In some embodiments, the actions of user 310 may be tracked by camera 360 and/or motion capture device 330) (page 6 paragraph 0051; see Figure 3); and
in response to determining that the updated user behavior model has achieved the confidence level above the threshold, enabling access to the access control device using a long-range communication protocol (i.e. the first motion 380(A) and second motion 380(B) may be compared to a recorded authentication movement associated with user 310 to determine if a request to unlock the device should be granted) (page 6 paragraph 0051; see Figure 3) in order to increase degrees of complexity to make attempts to impersonate the authorized user more difficult.
At the time of the effective filing date of the current application, it would have been obvious to a person of ordinary skill in the art to recognize the need for a method of having the first and second motions compared to the recorded authentication movement associated with the user with some percentage of different from the recorded movement for unlock device taught by Stuntebeck et al. in the determining the identity of the user relating to the first user satisfies a threshold level of certainty to unlock the locking device of Child et al. because having the first and second motions compared to the recorded authentication movement associated with the user with some percentage of different from the recorded movement would provide additional security level for controlling access to the home.
Referring to claim 11, Child et al. in view of Stuntebeck et al. disclose the method of claim 1, Stuntebeck et al. disclose further comprising: determining whether received user behavior information satisfies a minimum parameter of user behavior information (i.e. when the user later performs the authentication movement to unlock the device, they may only raise the device sixteen inches and/or may rotate the device three hundred degrees. A configurable setting may allow for some percentage of differential from the recorded movement-a larger differential percentage may comprise a less strict security policy, while a smaller differential percentage may comprise a stricter security policy) (page 5 paragraph 0046).
Referring to claim 12, Child et al. in view of Stuntebeck et al. disclose the method of claim 11, Stuntebeck et al. disclose further comprising: in response to determining that the received user behavior information satisfies the minimum parameter of user behavior information, allowing the access control device to perform an operation (i.e. the method 200 may advance to stage 235 where the computing device may unlock and/or grant access to the requested resources 132 if the user is determined to be authenticated at stage 220 ) (page 6 paragraph 0049; see Figures 2 and 3).
Referring to claim 13, Child et al. in view of Stuntebeck et al. disclose the method of claim 12, Stuntebeck et al. disclose further comprising: in response to determining that the received user behavior information fails to satisfy the minimum parameter of user behavior information, preventing the access control device from performing the operation (i.e. If the user is determined not to be authenticated at stage 220, method 200 may advance to stage 230 where the computing device may capture information about the attempt to unlock. For example, client device 120 may take a picture of an unauthorized user attempting to unlock the device and/or may capture other biometric and/or environmental information) (page 6 paragraph 0049; see Figures 2 and 3).
Referring to claim 14, Child et al. in view of Stuntebeck et al. disclose the method of claim 11, Stuntebeck et al. disclose wherein the minimum parameter comprises a threshold quantity of specified types of user behavior information (i.e. the authentication may be time and/or location dependent. For example, client device 120 may require a different authentication movement during working hours or at a public location. In some embodiments, the authentication movement may comprise a directional factor as a secondary criterion, such as requiring part of the movement to be in a northward direction, which may be detected by a compass component of client device 120) (page 6 paragraphs 0047-0048; see Figure 3).
Referring to claim 15, Child et al. in view of Stuntebeck et al. disclose the method of claim 11, Stuntebeck et al. disclose further comprising generating user behavior information by encoding a feature vector that includes identifying times and locations at which the user operates different types of access control devices (i.e. the authentication may be time and/or location dependent. For example, client device 120 may require a different authentication movement during working hours or at a public location. In some embodiments, the authentication movement may comprise a directional factor as a secondary criterion, such as requiring part of the movement to be in a northward direction, which may be detected by a compass component of client device 120) (page 6 paragraphs 0047-0048; see Figure 3).
Referring to claims 17 and 20, Child et al. in view of Stuntebeck et al. disclose a system and a non-transitory computer readable medium comprising non-transitory computer-readable instructions for performing operations, although different in scope from the claim 1, the claims 17 and 20 contains similar limitations in that the claim 1 already addressed above therefore claims 17 and 20 are also rejected for the same obvious reasons given with respect to claim 1.
Claims 2, 10, 16 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Child et al. (US# 10,127,754) in view of Stuntebeck et al. (Pub. No. US 2016/0196414) as applied to claims 1 and 17, and further in view of Pirch et al. (US# 11,405,784).
Referring to claim 2, Child et al. in view of Stuntebeck et al. disclose the method of claim 1, however, Child et al. in view of Stuntebeck et al. did not explicitly disclose further comprising: receiving an observed trajectory of the user; and
processing the observed trajectory by a machine learning model to generate a plurality of predicted trajectories, a first predicted trajectory of the plurality of predicted trajectories representing a first future path the user will follow from the observed trajectory and a second predicted trajectory of the plurality of predicted trajectories representing a second future path the user will follow from the observed trajectory.
In the same field of endeavor of an access control system, Pirch et al. teach that further comprising: receiving an observed trajectory of the user (i.e. a cameras, noise sensors (microphones), and environmental sensors such as thermometers and barometers may be used to provide information for the PACS to identify intent. For example, a camera may be used to assist in identifying which turnstile a user intends to enter. The temperature outside may affect the paths or habits of users) (column 10 lines 36 to 44; see Figures 3-4 and 10); and
processing the observed trajectory by a machine learning model to generate a plurality of predicted trajectories, a first predicted trajectory of the plurality of predicted trajectories representing a first future path the user will follow from the observed trajectory and a second predicted trajectory of the plurality of predicted trajectories representing a second future path the user will follow from the observed trajectory (i.e. an operation 1006 to determine the user intends to access the asset based on a data set generated derived from the second wireless connection. The PACS may determine location information from the second wireless connection by using UWB. The second wireless connection may include information from the key device, such as sensor data from sensors of the key device. The data set may include data both provided from the key device and derived from the second wireless connection that may be used to determine the intent of the user) (column 17 lines 47 to 56; see Figure 10) in order to predict and determine the user intends to access the asset.
At the time of the effective filing date of the current application, it would have been obvious to a person of ordinary skill in the art to recognize the need for a method of determining the user intends to access the asset based on the data set generated from wireless connection taught by Pirch et al. in the determining the identity of the user and user’s position relative to the barrier for determine user intent to open the barrier to unlock the locking device of Child et al.in view of Stuntebeck et al. because determining the user intends to access the asset based on the data set generated from wireless connection would provide accurate prediction of the user intent to unlock the locking device.
Referring to claim 10, Child et al. in view of Stuntebeck et al. disclose the method of claim 1, Pirch et al. disclose further comprising encoding an observed trajectory of the user, wherein a machine learning model is applied to the encoded observed trajectory of the user (i.e. the trained machine learning model is trained with data sets collected from a plurality of users. The data sets may include movement data for the plurality of users within a range of the asset. The data sets may include movement data from the plurality of users. The information received from the wireless key device may include movement data of the user collected from an accelerometer of the wireless key device) (column 17 line 57 to column 18 line 14).
Referring to claim 16, Child et al. in view of Stuntebeck et al. disclose the method of claim 1, Stuntebeck et al. disclose further comprising: generating user behavior information by a machine learning model; and generating user intent to operate the access control device by an additional machine learning model (i.e. for a particular asset or secure entry point, location and movement data for how different people approach and move toward the secure entry point when entering the secure entry point and data for when people do not enter the secure entry point may be used to train the machine learning model. This training may provide for the machine learning model to recognize how people may move and angles of their approach, when their intent is to enter the secure entry point. The data sets may include a time of day timestamp and the data set of the user may be timestamped. Including the time in the training of the machine learning model may indicate different patterns and actions based on the time of day) (column 17 line 57 to column 18 line 14).
Referring to claim 18, Child et al. in view of Stuntebeck et al. disclose the system of claim 17, although different in scope from the claim 2, the claim 18 contains similar limitations in that the claim 2 already addressed above therefore claim 18 also rejected for the same obvious reasons given with respect to claim 2.
Allowable Subject Matter
Claims 3-9 and 19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Referring to claims 3 and 19, the following is a statement of reasons for the indication of allowable subject matter: the prior art fails to suggest limitations further comprising:
adjusting the plurality of predicted trajectories based on the user behavior model to determine user intent to operate the access control device;
determining that the access control device is within a threshold range of a given one of the plurality of predicted trajectories; and
in response to determining that the access control device is within the threshold range of the given one of the plurality of predicted trajectories, performing an operation associated with the access control device.
Claims 4-9 depend either directly or indirectly upon independent claim 3; therefore, these claims are also allowed by virtue of their dependencies.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Refer to the enclosed PTO-892 for details.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NAM V NGUYEN whose telephone number is 571-272-3061. Fax number is (571) 273-3061. The examiner can normally be reached on 8:00AM-5:00PM Monday to Friday.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Quan-Zhen Wang can be reached on 571-272-3114. The fax phone numbers for the organization where this application or proceeding is assigned are 571-273-8300 for regular communications.
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/NAM V NGUYEN/
Primary Examiner, Art Unit 2685
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