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 .
Response to Amendment
Applicant's response to the last Office Action, filed on 1/7/2026 has been entered and made of record.
Response to Arguments
Applicant's arguments with respect to claims 1, 6, 15 have been considered but are moot in view of the new grounds of rejection.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
In its recent decision, Alice Corporation Pty. Ltd. v. CLS Bank International, et al. {“Alice Corp.’’), the Supreme Court made clear that it applies the framework set forth in Mayo Collaborative Services v. Prometheus Laboratories, Inc., 566 U.S._(2012) {Mayo), to analyze claims directed towards laws of nature and abstract idea. Alice Corp. also establishes that the same analysis applies for all categories of claims (e.g., product and process claims). The basic inquiries to determine subject matter eligibility remain the same as explained in MPEP 2106(1). First, determine whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. Next, determine if the claim is directed towards a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea). The two-part test provided in Alice Corp. to determine whether a claim directed towards an abstract idea is statutory under § 101 requires an evaluation to determined 1) whether the claims is directed to an abstract idea and 2) if an abstract idea is present in the claim, whether the claim amounts to significantly more than the abstract idea itself. Examples of abstract ideas reference in Alice Corp. include:
- Fundamental economic principles
- Certain methods of organizing human activities
- An idea of itself
- Mathematical relationships/formulas
In accordance with judicial precedent, the 2019 Revised Patent Subject Matter Eligibility Guidance sets forth a procedure to determine whether a claim is ‘‘directed to’’ a judicial exception. Under the procedure, if a claim recites a judicial exception (a law of nature, a natural phenomenon, or an abstract idea), it must then be analyzed to determine whether the recited judicial exception is integrated into a practical application of that exception. A claim is not ‘‘directed to’’ a judicial exception, and thus is patent eligible, if the claim as a whole integrates the recited judicial exception into a practical application of that exception. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.
Step 1 - Statutory Category
The claims 1-20 recite a process including receiving image surveillance data of a restricted area, identifying a person associated with an event, determining the location of the person, determining a characteristic of the person, and triggering an alert referencing the characteristic of the person, therefore it recites at least one of the enumerated categories, a process, eligible subject matter in 35 USC 101. Accordingly, claims 1-20 satisfy Step 1.
Step 2A(i) -Focus of the Claim
As a result, the claims 1-20 will be reviewed under Step 2A(i) to determine whether the claim is directed to one of the judicially recognized exceptions (i.e., a law of nature, a natural phenomenon, or an abstract idea). Alice, 573 U.S. at 217. As part of this inquiry, we must "look at the 'focus of the claimed advance over the prior art' to determine if the claim's 'character as a whole' is directed to excluded subject matter." Affinity Labs of Tex., LLC v. DIRECTV, LLC, 838 F.3d 1253, 1257 (Fed. Cir. 2016) (citations omitted). The claims recite triggering an audio alert indicating a characteristic of a person associated with an event, and after the alert determining the person has moved, thus the organization of human activity such as surveillance of human behavior.
The court have ruled that receiving and authenticating identity data to permit access was abstract since the functions were claimed generically rather than offering a "'concrete, specific solution" See Prisnz Technologies LLC v. T-Afobile USA, 696 F. App'x 1014 (Fed. Cir.2017). Abstract ideas include the concepts of collecting data, recognizing certain data within the collected data set, storing the data in memory, and notifying the user of the results. Content Extraction & Transmission LLC v. Wells Fargo Bank, N.A. Ass 'n, 776 F.3d 1343, 1347 (Fed. Cir. 2014); see also Smart Sys. Innovations, LLC v. Chicago Transit Auth., 873 F.3d 1364, 1372 (Fed. Cir. 2017) (concluding "claims directed to the collection, storage, and recognition of data are directed to an abstract idea"). Moreover, the reviewing court has concluded that acts of parsing, comparing, storing, and editing data are abstract ideas. Berkheimer v. HP Inc., 890 F.3d 1369, 1370 (Fed. Cir. 2018). In addition, the collection of information and analysis of information ( e.g., recognizing certain data within the dataset, such as rules) are also abstract ideas. Elec. Power Grp., LLC v. Alstom SA., 830 F.3d 1350, 1353 (Fed. Cir. 2016). Similarly, "collecting, displaying, and manipulating data" is an abstract idea. Intellectual Ventures I LLC v. Capital One Fin. Corp., 850 F.3d 1332, 1340 (Fed. Cir. 2017); see also SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161, 1167 (Fed. Cir. 2018) ("[M]erely presenting the results of abstract processes of collecting and analyzing information ... is abstract as an ancillary part of such collection and analysis").
The process of receiving images of persons in restricted area, and outputting an alert is a method of organizing human activity, as considered under MPEP § 2106.04(a)(2)(II), Certain Methods of Organizing Human Activity. Therefore, claims 1-20 recite an abstract idea.
Step 2A(ii) -Practical Application
Limitations that are indicative of integration into a practical application when recited in a claim with a judicial exception include:
Improvements to the functioning of a computer, or to any other technology or technical field, as discussed in MPEP 2106.05(a);
Applying or using a judicial exception to affect a particular treatment or prophylaxis for disease or medical condition – see Vanda Memo
Applying the judicial exception with, or by use of, a particular machine, as discussed in MPEP 2106.05(b);
Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP 2106.05(c); and
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP 2106.05(e) and the Vanda Memo issued in June 2018.
Limitations that are not indicative of integration into a practical application when recited in a claim with a judicial exception include:
Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f);
Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP 2106.05(g); and
Generally linking the use of the judicial exception to a particular technological environment or field of use, as discussed in MPEP 2106.05(h).
In this instance, this judicial exception is not integrated into a practical application because the claims merely detect persons in images, locate and identify the persons, identify characteristics of the persons, output information and trigger an audio alert. The claims do not provide an improvement to the functionality of a computer or image analysis technical field; the claims are not implemented with or used with a particular machine; the claims do not transform an article to a different state or thing when locating an object in images and triggering an audio alert; and the claims do not provide a meaningful way of analyzing image regions in the image analysis technical environment.
Step 2B - Inventive Concept
As set forth under MPEP § 2106.05( d), only if a claim: (1) recites a judicial exception; and (2) does not integrate that exception into a practical application, do we then look under Step 2B to determine; (3) whether the claim adds a specific limitation beyond the judicial exception that is not "well-understood, routine, conventional activity" (WURC) in the field; or (4) simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
Having determined claims 1-20 is directed to an abstract idea that is not integrated into a practical application, we now evaluate whether the additional elements, whether examined alone or as an ordered combination, add a specific limitation that is not well-understood, routine, or conventional activity in the field, or simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the abstract idea. See generally Revised Guidance.
It is possible that a claim that does not ‘‘integrate’’ a recited judicial exception is nonetheless patent eligible. For example, the claim may recite additional elements that render the claim patent eligible even though a judicial exception is recited in a separate claim element. Along these lines, the Federal Circuit has held claims eligible at the second step of the Alice/Mayo test because the additional elements recited in the claims provided ‘‘significantly more’’ than the recited judicial exception (e.g., because the additional elements were unconventional in combination).
Limitations reference in Alice Corp. that may be enough to quality as “significantly more” when recited in a claim with an abstract idea include, as nonexclusive examples:
- Improvements to another technology or technical field
- Improvements to the functioning of the computer itself
- Meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment
Examples that are not enough to quality as “significantly more” when recited in a claim with an abstract idea include, as non-limiting or non-exclusive example:
- Adding the words “apply it” (or an equivalent) with an abstract idea, or mere instructions to implement an abstract idea on a computer
- Requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry
The additional elements recited in claims 1-20 are well-understood, routine, and conventional steps in image analysis and ruled based surveillance. The claims 1-20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims are directed to viewing images and determining location of people.
Additionally, as noted in MPEP § 2106.05(d)(II), the courts have previously recognized that using computer processors and memories to collect data and keep records, perform repetitive calculations, and/or receive/send data are well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP § 2106.05(d)(II)(i)-(iv)). See also Berkheimer, 881 F.3d at 1366 (acts of parsing, comparing, storing, and editing data are abstract ideas); SAP Am., Inc. v. Investpic, LLC, 890 F.3d 1016, 1021 (Fed. Cir. 2018) ("[M]erely presenting the results of abstract processes of collecting and analyzing information ... is abstract as an ancillary part of such collection and analysis"); Intellectual Ventures I, 850 F .3d at 1340 ("[C]ollecting, displaying, and manipulating data" is an abstract idea); Smart Sys. Innovations, 873 F .3d at 1372 (concluding "claims directed to the collection, storage, and recognition of data are directed to an abstract idea.").
The claims state processing circuitry. However, the claims merely implement the judicial exception using generic computer elements to perform well-understood, routine, and conventional activities previously known to the industry, specified at a high level of generality. See FairWarning, 839 F.3d at 1096 ("[T]he use of generic computer elements like a microprocessor or user interface do not alone transform an otherwise abstract idea into patent eligible subject matter."); see also OIP Techs., 788 F.3d at 1363 (claims reciting, inter alia, sending messages over a network, gathering statistics, using a computerized system to automatically determine an estimated outcome, and presenting offers to potential customers found to merely recite "'well-understood, routine conventional activit[ies],' either by requiring conventional computer activities or routine data-gathering steps").
Claims 1, 3, 6-8, and 14-17 recite a machine learning model to identify persons and associated events. According to the MPEP Section 2106, simply mentioning "machine learning" in a patent claim is generally not enough to guarantee patentable subject matter; the claims must clearly define a specific, practical application of machine learning that goes beyond a generic or abstract idea, often requiring detailed description of the training process, data inputs, and specific outputs to avoid rejection under Section 101 for being too abstract. The machine learning language in the claims does not go beyond the abstract idea of identifying events in images.
In claims 1-20, the steps of receiving images and outputting detection results is not an improvement to a fundamental practice and/or method of organizing human activity. The claims do not include additional elements that are sufficient to amount to significantly more than generalized steps well-known and routine in the art such as image detection and object localization. Therefore, claims 1-20 are directed to patent-ineligible abstract idea that is not integrated into a practical application, with steps that do not add significantly more to the abstract idea. Claims 1-20 are ineligible. The Examiner suggests the applicant further define the audio alert devices as described in paragraphs 0021-0022 of specification, and machine learning model as described in paragraph 0044 of specification.
Claim Rejections - 35 USC § 103
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 1-3, 6-10, 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over Sinha et al. (US 11,308,775) in view of Amir (US 2024/0331517) (WO2022144876 published 7/7/2022).
Regarding claim 1, Sinha teaches a system, comprising:
at least one device comprising processing circuitry configured to: receive surveillance video associated with a restricted area of a premises (see col. 7 lines 42-67, Sinha discusses surveillance system capturing video data of restricted and retail locations);
identify, by applying at least one machine learning model to the surveillance video, a triggering event associated with the restricted area (see col. 2 lines 25-36, Sinha discusses a convolutional neural network to process the time series of video frames to detecting events);
in response to the triggering event, apply the at least one machine learning model to the surveillance video to: identify a person associated with the triggering event (see col. 14 lines 18-26, Sinha discusses person recognition (e.g., facial recognition) technique to match the person associated with a given first alert with a person exiting the retail environment; person recognition may be based on other attributes such as clothing color);
identify a visually observable characteristic of the person associated with the triggering event, the visually observable characteristic of the person being derived from the surveillance video (see col. 14 lines 18-26, col. 18 lines 8-10, Sinha discusses performing person recognition (e.g., facial recognition) technique on surveillance video to match the person associated with a given first alert with a person exiting the retail environment; person recognition may be based on other attributes such as clothing color; see col. 15 lines 13-67, Sinha discusses detecting suspicious activity and when a person exits the region without paying for an item).
Amir teaches to determine a location of the person within the restricted area (see para. 0377, Amir discusses detecting when a human intruder violates a restricted region);
generate a first audio message referencing the visually observable characteristic of the person and the location of the person within the restricted area, the first audio message configured to instruct the person to leave the restricted area of the premises (see para. 0377, Amir discusses detecting when a human violates a restricted region, audio message alarm is triggered, telling human to leave the area);
cause audio playback of the first audio message (see para. 0402, Amir discusses increasing the audio message to the intruder to leave the area); and
after audio playback of the first audio message, determine the person has moved outside the restricted area (see para. 0404, Amir discusses monitoring intruder in the area).
Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha with Amir to derive at the invention of claim 1. The result would have been expected, routine, and predictable in order to perform human detection and security surveillance.
The determination of obviousness is predicated upon the following: One skilled in the art would have been motivated to modify Sinha in this manner in order to improve human detection and security surveillance by applying a machine learning model to identify an intruder and automatically generating an audio alarm based on the severity of a triggering event, therefore removing the need for human security personnel. Furthermore, the prior art collectively includes each element claimed (though not all in the same reference), and one of ordinary skill in the art could have combined the elements in this manner explained using known engineering design, interface and/or programming techniques, without changing a fundamental operating principle of Sinha, while the teaching of Amir continues to perform the same function as originally taught prior to being combined, in order to produce the repeatable and predictable result of identifying the identity of an visitor using a machine learning algorithm to determine the severity of a security event and eliminate the need for human security intervention. The Sinha and Amir systems perform video surveillance, therefore one of ordinary skill in the art would have reasonable expectation of success in the combination. It is for at least the aforementioned reasons that the examiner has reached a conclusion of obviousness with respect to the claim in question.
Regarding claim 2, Sinha teaches wherein the characteristic of the person associated with the triggering event comprises at least one of: an item of clothing worn by the person; a gender of the person; or a hairstyle of the person (see col. 12 lines 47-50, col. 14 lines 18-26, Sinha discusses person recognition (e.g., facial recognition) technique to match the person associated with a given first alert with a person exiting the retail environment; person recognition may be based on other attributes such as clothing color and clothing worn; see col. 15 lines 13-67, Sinha discusses detecting suspicious activity and when a person exits the region without paying for an item).
The same motivation of claim 1 is applied to claim 2. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha with Amir to derive at the invention of claim 2. The result would have been expected, routine, and predictable in order to perform human detection and security surveillance.
Regarding claim 3, Sinha and Amir teach wherein the processing circuitry is further configured to: identify, by applying the at least one machine learning model to the surveillance video, a facial characteristic of the person associated with triggering event; (see col. 14 lines 18-26, Sinha discusses person recognition (e.g., facial recognition) technique to match the person associated with a given first alert with a person exiting the retail environment; person recognition may be based on other attributes such as clothing color; see col. 15 lines 13-67, Sinha discusses detecting suspicious activity and when a person exits the region without paying for an item); and
the first audio message being based on the facial characteristic of the person associated with the triggering event (see para. 0377, Amir discusses detecting when a human violates a restricted region, audio message alarm is triggered, telling human to leave the area).
The same motivation of claim 1 is applied to claim 3. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha with Amir to derive at the invention of claim 3. The result would have been expected, routine, and predictable in order to perform human detection and security surveillance.
Regarding claim 6, Sinha teaches system, comprising: at least one device comprising processing circuitry configured to: receive surveillance video associated with an area of a premises (see col. 7 lines 42-67, Sinha discusses surveillance system capturing video data of restricted and retail locations);
identify, by applying at least one machine learning model to the surveillance video, a triggering event (see col. 2 lines 25-36, Sinha discusses a convolutional neural network to process the time series of video frames to detecting events);
in response to the triggering event, apply the at least one machine learning model to the surveillance video to: identify a person associated with the triggering event (see col. 14 lines 18-26, Sinha discusses person recognition (e.g., facial recognition) technique to match the person associated with a given first alert with a person exiting the retail environment; person recognition may be based on other attributes such as clothing color);
identify at least one non-facial and visually observable characteristic of the person associated with the triggering event, the at least one non-facial and visually observable characteristic of the person being derived from the surveillance video (see col. 14 lines 18-26, Sinha discusses person recognition (e.g., facial recognition) technique to match the person associated with a given first alert with a person exiting the retail environment; person recognition may be based on other attributes such as clothing color and size; see col. 15 lines 13-67, Sinha discusses detecting suspicious activity and when a person exits the region without paying for an item).
Amir teaches to determine a location of the person within a restricted area (see para. 0377, Amir discusses detecting when a human intruder violates a restricted region); and
generate a first audio message referencing the at least one non-facial and visually observable characteristic of the person and the location of the person within the restricted area, the first audio configured to instruct the person to leave the restricted area of the premises (see para. 0377, Amir discusses detecting when a human violates a restricted region, audio message alarm is triggered, telling human to leave the area); and
cause audio playback of the first audio message (see para. 0402, Amir discusses increasing the audio message to the intruder to leave the area; see para. 0404, Amir discusses monitoring intruder in the area).
Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha with Amir to derive at the invention of claim 6. The result would have been expected, routine, and predictable in order to perform human detection and security surveillance.
The determination of obviousness is predicated upon the following: One skilled in the art would have been motivated to modify Sinha in this manner in order to improve human detection and security surveillance by applying a machine learning model to identify an intruder and automatically generating an audio alarm based on the severity of a triggering event, therefore removing the need for human security personnel. Furthermore, the prior art collectively includes each element claimed (though not all in the same reference), and one of ordinary skill in the art could have combined the elements in this manner explained using known engineering design, interface and/or programming techniques, without changing a fundamental operating principle of Sinha, while the teaching of Amir continues to perform the same function as originally taught prior to being combined, in order to produce the repeatable and predictable result of identifying the identity of an visitor using a machine learning algorithm to determine the severity of a security event and eliminate the need for human security intervention. The Sinha and Amir systems perform video surveillance, therefore one of ordinary skill in the art would have reasonable expectation of success in the combination. It is for at least the aforementioned reasons that the examiner has reached a conclusion of obviousness with respect to the claim in question.
Regarding claim 7, Sinha and Amir teach wherein the processing circuitry is further configured to: determine, by applying the at least one machine learning model to the surveillance video, an event type associated with the triggering event (see col. 2 lines 25-36, Sinha discusses a convolutional neural network to process the time series of video frames to detecting events);
identify the person associated with the triggering event further based at least in part on the event type (see col. 2 lines 25-36, Sinha discusses a convolutional neural network to process the time series of video frames to detecting events); and
the first audio message referencing information of the event type (see para. 0377, Amir discusses detecting when a human violates a restricted region, audio message alarm is triggered, telling human to leave the area).
The same motivation of claim 6 is applied to claim 7. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha with Amir to derive at the invention of claim 7. The result would have been expected, routine, and predictable in order to perform human detection and security surveillance.
Regarding claim 8, Sinha teaches wherein the processing circuitry is further configured to: identify, by applying the at least one machine learning model to the surveillance video, an object with which the person is interacting; and the first audio message referencing the identity of the object with which the person is interacting (see col. 14 lines 5-8, Sinha discusses identifying item taken by a person).
The same motivation of claim 6 is applied to claim 8. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha with Amir to derive at the invention of claim 8. The result would have been expected, routine, and predictable in order to perform human detection and security surveillance.
Regarding claim 9, Sinha teaches wherein the at least one non-facial and visually observable characteristic of the person associated with the triggering event includes at least one of: an item of clothing worn by the person; a gender of the person; a hairstyle of the person; an identification of an object with which the person is interacting; or a type of a weapon being held by the person (see col. 14 lines 18-26, col. 18 lines 8-10, Sinha discusses person recognition (e.g., facial recognition) technique to match the person associated with a given first alert with a person exiting the retail environment; person recognition may be based on other attributes such as clothing color and clothing worn; see col. 15 lines 13-67, Sinha discusses detecting suspicious activity and when a person carries an item and exits the region without paying for an item).
The same motivation of claim 6 is applied to claim 9. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha with Amir to derive at the invention of claim 9. The result would have been expected, routine, and predictable in order to perform human detection and security surveillance.
Regarding claim 10, Sinha teaches wherein the processing circuitry is further configured to: receive biometric data associated with the triggering event; and identify the person associated with the triggering event further based at least in part on the biometric data (see col. 14 lines 18-26, Sinha discusses person recognition (e.g., facial recognition) technique to match the person associated with a given first alert with a person exiting the retail environment).
The same motivation of claim 6 is applied to claim 10. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha with Amir to derive at the invention of claim 10. The result would have been expected, routine, and predictable in order to perform human detection and security surveillance.
Regarding claim 14, Sinha and Amir teach wherein the processing circuitry is further configured to: identify, by applying the at least one machine learning model to the surveillance video, a facial and visually observable characteristic of the person associated with the triggering event (see col. 14 lines 18-26, Sinha discusses person recognition (e.g., facial recognition) technique to match the person associated with a given first alert with a person exiting the retail environment); and
the generating of the first audio message being based at least on the facial and visually observable characteristic of the person associated with the triggering event (see para. 0377, Amir discusses detecting when a human violates a restricted region, audio message alarm is triggered, telling human to leave the area).
The same motivation of claim 6 is applied to claim 14. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha with Amir to derive at the invention of claim 14. The result would have been expected, routine, and predictable in order to perform human detection and security surveillance.
Claim 15 is rejected as applied to claim 6 as pertaining to a corresponding method.
Claim 16 is rejected as applied to claim 7 as pertaining to a corresponding method.
Claim 17 is rejected as applied to claim 8 as pertaining to a corresponding method.
Claim 18 is rejected as applied to claim 9 as pertaining to a corresponding method.
Claims 4, 11, 13, 19 are rejected under 35 U.S.C. 103 as being unpatentable over Sinha et al. (US 11,308,775) in view of Amir (US 2024/0331517) (WO2022144876 published 7/7/2022) in view of Loke et al. (US 2023/0410512) (WO2022098305 published 5/12/2022).
Regarding claim 4, Sinha and Amir do not expressly disclose wherein the processing circuitry is further configured to: determine a severity level of the triggering event; and the generating of the first audio message being based at least in part on a vocal profile associated with the severity level.
However, Loke teaches wherein the processing circuitry is further configured to: determine a severity level of the triggering event (see para. 0083, Loke discusses defining a relationship between position information of a human detected in images and event severity); and
the generating of the first audio message being based at least in part on a vocal profile associated with the severity level (see para. 0083, Loke discusses notification system may output different messages and activate different audio and visual alarms based on the level of severity of the event).
Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha and Amir with Loke to derive at the invention of claim 4. The result would have been expected, routine, and predictable in order to perform human intruder detection and security surveillance.
The determination of obviousness is predicated upon the following: One skilled in the art would have been motivated to modify Sinha and Amir in this manner in order to improve human detection and security surveillance by applying a machine learning model to identify an intruder and automatically generating an audio alarm based on the severity of a triggering event, therefore removing the need for human security personnel. Furthermore, the prior art collectively includes each element claimed (though not all in the same reference), and one of ordinary skill in the art could have combined the elements in this manner explained using known engineering design, interface and/or programming techniques, without changing a fundamental operating principle of Sinha and Amir, while the teaching of Loke continues to perform the same function as originally taught prior to being combined, in order to produce the repeatable and predictable result of identifying the identity of an visitor using a machine learning algorithm to determine the severity of a security event associated with different audible alarms and eliminating the need for human security intervention. The Sinha, Amir, and Loke systems perform video surveillance, therefore one of ordinary skill in the art would have reasonable expectation of success in the combination. It is for at least the aforementioned reasons that the examiner has reached a conclusion of obviousness with respect to the claim in question.
Claim 11 is rejected as applied to claim 4 as pertaining to a corresponding system.
Regarding claim 13, Loke teaches wherein the processing circuitry is further configured to: detect, using additional surveillance video, a movement of the person from the area to a different area of the premises; determine a second severity level based at least in part on the movement of the person and at least one characteristic of the different area, the second severity level is one of: a higher severity level than the first severity level when the different area to which the person moved is farther from an exit of the premises than the area; or a lower severity level than the first severity level when the different area to which the person moved is closer to the exit of the premises than the area (see para. 0083, Loke discusses activating different audio alarms based on the level of severity of the event and the position of the person).
The same motivation of claim 11 is applied to claim 13. Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha and Amir with Loke to derive at the invention of claim 13. The result would have been expected, routine, and predictable in order to perform human intruder detection and security surveillance.
Claim 19 is rejected as applied to claim 11 as pertaining to a corresponding method.
Claims 5, 12, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Sinha et al. (US 11,308,775) in view of Amir (US 2024/0331517) (WO2022144876 published 7/7/2022) in view of Meganathan et al. (US 2017/0193774).
Regarding claim 5, Sinha and Amir do not expressly disclose wherein the processing circuitry is further configured to: generate an additional audio message referencing the visually observable characteristic of the person associated with the triggering event and the movement of the person outside the restricted area, the additional audio message acknowledging that the person has left at least the restricted area; and cause playback of the additional audio message.
However, Meganathan wherein the processing circuitry is further configured to: generate an additional audio message referencing the visually observable characteristic of the person associated with the triggering event and the movement of the person outside the restricted area, the additional audio message acknowledging that the person has left at least the restricted area; and cause playback of the additional audio message (see para. 0069, Meganathan discusses generating an alert when a person has entered a restricted area, and continuously tracking the person and generating an alert when the person has exited the restricted area).
Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha and Amir with Meganathan to derive at the invention of claim 5. The result would have been expected, routine, and predictable in order to perform human detection and security surveillance.
The determination of obviousness is predicated upon the following: One skilled in the art would have been motivated to modify Sinha and Amir in this manner in order to improve human detection and security surveillance by applying a machine learning model to identify an intruder and automatically generating an audio alarm based on the severity of a triggering event, therefore removing the need for human security personnel. Furthermore, the prior art collectively includes each element claimed (though not all in the same reference), and one of ordinary skill in the art could have combined the elements in this manner explained using known engineering design, interface and/or programming techniques, without changing a fundamental operating principle of Sinha and Amir, while the teaching of Meganathan continues to perform the same function as originally taught prior to being combined, in order to produce the repeatable and predictable result of identifying the identity of an visitor using a machine learning algorithm to determine the severity of a security event and eliminate the need for human security intervention. The Sinha, Amir, and Meganathan systems perform video surveillance, therefore one of ordinary skill in the art would have reasonable expectation of success in the combination. It is for at least the aforementioned reasons that the examiner has reached a conclusion of obviousness with respect to the claim in question.
Regarding claim 12, Sinha and Amir do not expressly disclose wherein the processing circuitry is further configured to: determine the person has moved outside the restricted area; generate an additional audio message referencing the at least one non-facial and visually observable characteristic of the person associated with the triggering event and the movement of the person outside the restricted area, the additional audio message acknowledging that the person has left at least the restricted area; and cause audio playback of the additional audio message.
However, Meganathan teaches wherein the processing circuitry is further configured to: determine the person has moved outside the restricted area; generate an additional audio message referencing the at least one non-facial and visually observable characteristic of the person associated with the triggering event and the movement of the person outside the restricted area, the additional audio message acknowledging that the person has left at least the restricted area (see para. 0069, Meganathan discusses generating an alert when a person has entered a restricted area, further tracking the person and generating an alert when the person has exited the restricted area); and
cause audio playback of the additional audio message (see para. 0069, Meganathan discusses generating an alert when a person has entered a restricted area, further tracking the person and generating an alert when the person has exited the restricted area).
Motivation to combine may be gleaned from the prior art considered. It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify the invention of Sinha and Amir with Meganathan to derive at the invention of claim 12. The result would have been expected, routine, and predictable in order to perform human detection and security surveillance.
The determination of obviousness is predicated upon the following: One skilled in the art would have been motivated to modify Sinha and Amir in this manner in order to improve human detection and security surveillance by applying a machine learning model to identify an intruder and automatically generating an audio alarm based on the severity of a triggering event, therefore removing the need for human security personnel. Furthermore, the prior art collectively includes each element claimed (though not all in the same reference), and one of ordinary skill in the art could have combined the elements in this manner explained using known engineering design, interface and/or programming techniques, without changing a fundamental operating principle of Sinha and Amir, while the teaching of Meganathan continues to perform the same function as originally taught prior to being combined, in order to produce the repeatable and predictable result of identifying the identity of an visitor using a machine learning algorithm to determine the severity of a security event and eliminate the need for human security intervention. The Sinha, Amir, and Meganathan systems perform video surveillance, therefore one of ordinary skill in the art would have reasonable expectation of success in the combination. It is for at least the aforementioned reasons that the examiner has reached a conclusion of obviousness with respect to the claim in question.
Claim 20 is rejected as applied to claim 12 as pertaining to a corresponding method.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KENNY A CESE whose telephone number is (571) 270-1896. The examiner can normally be reached on Monday – Friday, 9am – 4pm.
If attempts to reach the primary examiner by telephone are unsuccessful, the examiner’s supervisor, Gregory Morse can be reached on (571) 272-3838. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/Kenny A Cese/
Primary Examiner, Art Unit 2663
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