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 .
Detailed Action
The following action is in response to the communication(s) received on 11/28/2023.
As of the claims filed 11/28/2023:
Claims 1-11 are pending.
Claims 1 and 11 are independent claims.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 09/11/2024 were filed in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Such claim limitation(s) is/are:
In claim 1: “a first electronic device configured to…”; “a computing unit…”; “an artificial intelligence module configured to…”; “an event aggregation module configured to…”;
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 5-10 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 5-8 recite “and/or”. It is unclear whether the claims must be read as “and” (thus requiring all the joined limitations) or “or”. For purposes of examination, “and/or” is interpreted as “or”.
Claims 9 and 10 recite the limitation "the language module". There is insufficient antecedent basis for this limitation in the claim.
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 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 recites A behavior analysis system, thus a machine, one of the four statutory categories of patentable subject matter (Step 1). However, Claim 1 further recites:
detect a first behavior event from the first monitoring message, which is an evaluation or judgement that can be performed in the human mind;
an event aggregation module configured to aggregate the first behavior event to generate an event aggregation report, which is an evaluation or judgement that can be performed in the human mind;
generate a behavior summary based on the event aggregation report, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1.Under Step 2A Prong 2, the claim recites:
a first electronic device configured to capture image data of a scene to obtain a first monitoring message, which is merely an insignificant extra-solution activity of data gathering, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application;
a computing unit, in communication with the first electronic device, comprising: an artificial intelligence module , as the performance of an abstract idea on a computer is not more than instructions to 'apply it' on a computer, which by MPEP 2106.05(f) cannot integrate an abstract idea into a practical application;
configured to receive the first monitoring message, which is merely an insignificant extra-solution activity of data gathering, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application;
an event aggregation module configured to..., as the performance of an abstract idea on a computer is not more than instructions to 'apply it' on a computer, which by MPEP 2106.05(f) cannot integrate an abstract idea into a practical application;
and a language model configured to..., as the performance of an abstract idea on a computer is not more than instructions to 'apply it' on a computer, which by MPEP 2106.05(f) cannot integrate an abstract idea into a practical application;
and a user equipment, in communication with the first electronic device and the computing unit, configured to display the behavior summary; wherein the behavior summary is in a form of natural language, which is merely an insignificant extra-solution activity of displaying results, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application.
Thus, the claim is directed towards and abstract idea.
Further, the additional element(s), alone or in combination, do not provide significantly more than the abstract idea itself, because the activity of data gathering (MPEP 2106.05(g)) cannot provide significantly more, as storing and retrieving information in memory is well understood, routine, and conventional (MPEP 2106.05(d)(II)(iv)); the activity of displaying results (MPEP 2106.05(g)) cannot provide significantly more, as displaying results is well understood, routine, and conventional (Tuncel [p.17 right ¶2] To prevent the audience from getting bored while reading a scientific article, some of the data should be expressed in a visual format in graphics… Peer-reviewers frequently look at tables…) (MPEP 2106.05(d)); implementation on a computer (MPEP 2106.05(f)) cannot provide significantly more. The combination of these additional elements does not provide an inventive concept; thus, the claim remains ineligible.
Claim 2, dependent on 1, further recites
detect a second behavior event from the second monitoring message, which is an evaluation or judgement that can be performed in the human mind;
aggregate the first behavior event and the second behavior event to generate the event aggregation report, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1. Under Step 2A Prong 2, the claim recites:
a second electronic device, in communication with the computing unit and the user equipment, configured to sense motion data of a pet to obtain a second monitoring message, which is merely an insignificant extra-solution activity of data gathering, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application.
Thus, the claim is directed towards and abstract idea.
Further, the additional element(s), alone or in combination, do not provide significantly more than the abstract idea itself, because the activity of data gathering (MPEP 2106.05(g)) cannot provide significantly more, as storing and retrieving information in memory is well understood, routine, and conventional (MPEP 2106.05(d)(II)(iv)). The combination of these additional elements does not provide an inventive concept; thus, the claim remains ineligible.
Claim 3, dependent on 2, further recites
the first behavior event and the second behavior event each comprise a combination of one or more precise behavior events and one or more non-precise behavior events, which is merely a detail of an abstract idea (aggregate the first behavior event and the second behavior event).
Thus, the claim recites an abstract idea under Step 2A Prong 1. Under Step 2A Prong 2 and Step 2B, the claim recites: no additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself; thus, the claim remains ineligible.
Claim 4, dependent on 2, further recite no additional abstract ideas. However: Under Step 2A Prong 2, the claim recites:
the first electronic device is further configured to capture video data and audio data of the scene to obtain the first monitoring message, which is merely an insignificant extra-solution activity of data gathering, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application;
and the second electronic device is further configured to sense environmental data of an environment in which the pet is located to obtain the second monitoring message, which is merely an insignificant extra-solution activity of data gathering, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application.
Thus, the claim is directed towards and abstract idea.
Further, the additional element(s), alone or in combination, do not provide significantly more than the abstract idea itself, because the activity of data gathering (MPEP 2106.05(g)) cannot provide significantly more, as storing and retrieving information in memory is well understood, routine, and conventional (MPEP 2106.05(d)(II)(iv)). The combination of these additional elements does not provide an inventive concept; thus, the claim remains ineligible.
Claim 5, dependent on 2, further recites
determine whether the first monitoring message comprises at least one motion and/or at least one sound, and the second electronic device is further configured to determine whether the second monitoring message comprises at least one motion and/or at least one sound, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1. Under Step 2A Prong 2 and Step 2B, the claim recites: no additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself; thus, the claim remains ineligible.
Claim 6, dependent on 2, further recites
determine whether the first monitoring message and/or the second monitoring message comprise at least one motion and/or at least one sound, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1. Under Step 2A Prong 2 and Step 2B, the claim recites: no additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself; thus, the claim remains ineligible.
Claim 7, dependent on 5, further recites
determines whether the at least one motion and/or at least one sound in the first monitoring message and/or the second monitoring message is associated with a target object in response to the determination that the first monitoring message and/or the second monitoring message comprising the at least one motion and/or the at least one sound, which is an evaluation or judgement that can be performed in the human mind;
detects the first behavior event from the first monitoring message and detects the second behavior event from the second monitoring message in response to the determination that the at least one motion and/or at least one sound in the first monitoring me, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1. Under Step 2A Prong 2 and Step 2B, the claim recites: no additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself; thus, the claim remains ineligible.
Claim 8, dependent on 6, further recites
determines whether the at least one motion and/or at least one sound in the first monitoring message and/or the second monitoring message is associated with a target object in response to the determination that the first monitoring message and/or the second monitoring message comprising the at least one motion and/or the at least one sound, which is an evaluation or judgement that can be performed in the human mind;
detects the first behavior event from the first monitoring message and detects the second behavior event from the second monitoring message in response to the determination that the at least one motion and/or at least one sound in the first monitoring me, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1. Under Step 2A Prong 2 and Step 2B, the claim recites: no additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself; thus, the claim remains ineligible.
Claim 9, dependent on 1, further recites
generates the behavior summary based on the event aggregation report and the reference information, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1.Under Step 2A Prong 2, the claim recites:
the computing unit further comprising: a knowledge module, in communication with the language module, as the performance of an abstract idea on a computer is not more than instructions to 'apply it' on a computer, which by MPEP 2106.05(f) cannot integrate an abstract idea into a practical application;
configured to provide reference information, which is merely an insignificant extra-solution activity of data transfer, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application.
Thus, the claim is directed towards and abstract idea.
Further, the additional element(s), alone or in combination, do not provide significantly more than the abstract idea itself, because the activity of data transfer (MPEP 2106.05(g)) cannot provide significantly more, as receiving or transmitting data over a network is well understood, routine, and conventional (MPEP 2106.05(d)(II)(i), buySAFE, Inc. v. Google, Inc); implementation on a computer (MPEP 2106.05(f)) cannot provide significantly more. The combination of these additional elements does not provide an inventive concept; thus, the claim remains ineligible.
Claim 10, dependent on 1, further recites
generate a behavior suggestion based on the event aggregation report, the reference information, and the behavior summary, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1. Under Step 2A Prong 2, the claim recites:
and the user equipment displays the behavior summary and the behavior suggestion, which is merely an insignificant extra-solution activity of displaying results, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application.
Thus, the claim is directed towards and abstract idea.
Further, the additional element(s), alone or in combination, do not provide significantly more than the abstract idea itself, because the activity of displaying results (MPEP 2106.05(g)) cannot provide significantly more, as displaying images and results is well understood, routine, and conventional (Tuncel [p.17 right ¶2] To prevent the audience from getting bored while reading a scientific article, some of the data should be expressed in a visual format in graphics… Peer-reviewers frequently look at tables…) (MPEP 2106.05(d)). The combination of these additional elements does not provide an inventive concept; thus, the claim remains ineligible.
Claim 11 recites A behavioral analysis method, thus a process, one of the four statutory categories of patentable subject matter. However, Claim 11 recites precisely the abstract ideas and additional elements of Claim 1. Therefore, Step 2A Prong 1, Step 2A Prong 2, and Step 2B analyses remain the same. Claim 11 is rejected as subject-matter ineligible for reasons set forth in the rejections of Claim 1.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-9 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Boteju et al., “Deep Learning Based Dog Behavioural Monitoring System” (hereinafter Boteju), further in view of Noguera-Arnaldos et al., “im4Things: An Ontology-Based Natural Language Interface for Controlling Devices in the Internet of Things” (hereinafter Noguera-Arnaldos ).
Regarding Claim 1, Boteju teaches:
A behavior analysis system, comprising: a first electronic device configured to capture image data of a scene to obtain a first monitoring message; (Boteju [p.83, fig.1]
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[p.4 left ¶3,4] As shown in Section C in Fig. 1, the resting activity is measured using the CCTV camera and the results are compared with the data regarding the breed and activity levels obtained from Section A and Section B. In Section D, the barking activity is observed using the audio feature enabled in the CCTV camera device.) (Note: the CCTV camera corresponds to the first electronic device; video component (with audio) corresponds to the first monitoring message)
a computing unit, in communication with the first electronic device, comprising: an artificial intelligence module configured to receive the first monitoring message and detect a first behavior event from the first monitoring message; (Boteju [fig.1 (C); (D)] Trained dog barking classifier using Deep Learning; Identify Barking Behavior;
[abstract] Transfer learning with ResNet50, Inception V3, and support vector machines have been used to recognize and classify the activities of the dogs.) (Note: identifying the barking behavior using deep learning corresponds to detecting the first behavior event)
an event aggregation module configured to aggregate the first behavior event to generate an event aggregation report; (Boteju [fig.1, bottom right] If there’s a change / Signs of unusual behavior -> Notify the change ) (Note: signs of unusual changed behavior based on the aggregated factors corresponds to the event aggregation report)
and a user equipment, in communication with the first electronic device and the computing unit, configured to display the behavior summary… (Boteju [p.1 left ¶1] Projecting the above-mentioned trends, this study proposes a novel method where the user is able to identify the breed of the dog and address issues related to dogs through an application that can be installed on the owners’ smartphone.)
Boteju does not teach, but Noguera-Arnaldos further teaches:
and a language model configured to generate a behavior summary based on the event aggregation report; … wherein the behavior summary is in a form of natural language (Noguera-Arnaldos [p.7 ¶2] Besides the above-mentioned process, the im4Things bot is also able to notify the users about the home appliance’s state changes. Therefore, once a home appliance’s alert is triggered, the im4Things bot sends to the im4Things Cloud service a natural language expression concerning the situation. Then, the im4Things Cloud service notifies the users subscribed to the home appliance. Finally, it is worth mentioning that im4Things system allows users to control home appliances from the local network and remote locations.) (Note: the natural language expression corresponds to the behavior summary in the form of natural language)
Noguera-Arnaldos and Boteju are analogous to the present invention because both are from the same field of endeavor of app-based event monitoring methods. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the method of generating natural language expression regarding the triggered alert from Noguera-Arnaldos into Boteju’s dog behavior monitoring system. The motivation would be to “notify the users about the… state changes.” (Noguera-Arnaldos, abstract)
Regarding Claim 2, Boteju/Noguera-Arnaldos respectively teaches and incorporates the claimed limitations and rejections of Claim 1. Boteju, via Boteju/Noguera-Arnaldos further, teaches:
The behavior analysis system according to claim 1, further comprising: a second electronic device, in communication with the computing unit and the user equipment, configured to sense motion data of a pet to obtain a second monitoring message; (Boteju [p.74 left last ¶] As shown in Fig. 3, the input device in the component is the MPU6050 sensor which contains an integrated accelerometer and gyroscope along with a Node Micro Controller Unit (NodeMCU) Wi-Fi development board. The accelerometer measures proper acceleration (‘g-force’) whereas the gyroscope indicates orientation. ) (Note: the wearable sensor corresponds to the second electronic device; the acceleration measurement corresponds to the second monitoring message)
wherein the artificial intelligence module is configured to receive the second monitoring message and detect a second behavior event from the second monitoring message; (Boteju [p.87 left last ¶] The comparison of the obtained activity (Walking and Running time per day based on breed) and resting levels (Time spent in the lying position) was done with the data obtained from the official Wag Walking site [22]. This is a significant outcome of this research. The system is able to successfully identify the breed of the dog and analyze the behavior (Walk, Run, Rest, Bark) of the pet dog and abnormalities to notify its user in a restricted setting of their own home with the use of a wearable MPU6050 sensor which is attached to the dog collar and CCTV camera.) (Note: the detected abnormalities based on the behavior corresponds to the second behavior event)
and the event aggregation module is configured to aggregate the first behavior event and the second behavior event to generate the event aggregation report. (Boteju [p.83, fig.1]
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) (Note: the video component comprising the analyzed resting behavior corresponds to the first behavior event; either notifying or generating the behavior report corresponds to aggregating the first behavior event and the second behavior event)
Regarding Claim 3, Boteju/Noguera-Arnaldos respectively teaches and incorporates the claimed limitations and rejections of Claim 2. Boteju, via Boteju/Noguera-Arnaldos, further teaches:
The behavior analysis system according to claim 2, wherein the first behavior event and the second behavior event each comprise a combination of one or more precise behavior events and one or more non-precise behavior events. (Boteju [p.82 bottom left; fig.1 sections C and D] C) Resting Pattern Recognition - Analyze the resting behavior pattern of the dog based on breed and age. D) Barking Pattern Recognition - Analyze the unusual barking behavior patterns of the dog using computer vision and audio analysis.
[p.87 left last ¶] The comparison of the obtained activity (Walking and Running time per day based on breed) and resting levels (Time spent in the lying position) was done with the data obtained from the official Wag Walking site [22]. This is a significant outcome of this research. The system is able to successfully identify the breed of the dog and analyze the behavior (Walk, Run, Rest, Bark) of the pet dog and abnormalities to notify its user in a restricted setting of their own home with the use of a wearable MPU6050 sensor which is attached to the dog collar and CCTV camera.) (Note: the identified behavior (such as Walk, Run, Rest, Bark) corresponds to the precise behavior events; the time spent walking, running, and lying correspond to the non-precise behavior events.)
Regarding Claim 4, Boteju/Noguera-Arnaldos respectively teaches and incorporates the claimed limitations and rejections of Claim 2. Boteju, via Boteju/Noguera-Arnaldos, further teaches:
The behavior analysis system according to claim 2, wherein: the first electronic device is further configured to capture video data and audio data of the scene to obtain the first monitoring message; (Boteju, fig.1 top right, “Video Component (with audio)”)
and the second electronic device is further configured to sense environmental data of an environment in which the pet is located to obtain the second monitoring message. (Boteju, fig.1 top left, “sensor”; p.84 left bottom, “the MPU6050 sensor which contains an integrated accelerometer and gyroscope along with a Node Micro Controller Unit (NodeMCU) Wi-Fi development board. The accelerometer measures proper acceleration (‘g-force’) whereas the gyroscope indicates orientation. Proper acceleration is not the same as coordinate acceleration (rate of change of velocity). The NodeMCU is used to obtain the readings through a Wi-Fi connection.”; the orientation and g-force of a sensor measurements are relative to its environment, thus corresponding to the environmental data of an environment)
Regarding Claim 5, Boteju/Noguera-Arnaldos respectively teaches and incorporates the claimed limitations and rejections of Claim 2. Boteju, via Boteju/Noguera-Arnaldos further teaches:
The behavior analysis system according to claim 2, wherein the first electronic device is further configured to determine whether the first monitoring message comprises at least one motion and/or at least one sound, (Boteju, fig.1 top right, “Video Component (with audio)”; inputting the audio into the Deep learning classifier corresponds to having been determined that the input comprising a sound)
and the second electronic device is further configured to determine whether the second monitoring message comprises at least one motion and/or at least one sound. (Boteju, fig.1 top left, “sensor”; p.84 left bottom, “the MPU6050 sensor which contains an integrated accelerometer and gyroscope along with a Node Micro Controller Unit (NodeMCU) Wi-Fi development board. The accelerometer measures proper acceleration (‘g-force’) whereas the gyroscope indicates orientation. Proper acceleration is not the same as coordinate acceleration (rate of change of velocity). The NodeMCU is used to obtain the readings through a Wi-Fi connection.”; the g-force corresponds to motion)
Regarding Claim 6, Boteju/Noguera-Arnaldos respectively teaches and incorporates the claimed limitations and rejections of Claim 2. Boteju, via Boteju/Noguera-Arnaldos, further teaches:
The behavior analysis system according to claim 2, wherein the artificial intelligence module is further configured to determine whether the first monitoring message and/or the second monitoring message comprise at least one motion and/or at least one sound. (Boteju, fig.1, “identify barking behavior” of the video component (first monitoring message) corresponds to comprising a sound)
Regarding Claim 7, Boteju/Noguera-Arnaldos respectively teaches and incorporates the claimed limitations and rejections of Claim 5. Boteju, via Boteju/Noguera-Arnaldos further teaches:
The behavior analysis system according to claim 5, wherein the artificial intelligence module determines whether the at least one motion and/or at least one sound in the first monitoring message and/or the second monitoring message is associated with a target object in response to the determination that the first monitoring message and/or the second monitoring message comprising the at least one motion and/or the at least one sound; (Boteju, fig.1, “Compare the tracked resting activity levels and walking activity levels with the average levels, according to dog’s breed and age”)
and the artificial intelligence module detects the first behavior event from the first monitoring message and detects the second behavior event from the second monitoring message in response to the determination that the at least one motion and/or at least one sound in the first monitoring message and/or the second monitoring message being associated with the target object. (Boteju, fig.1, video component; sensor; “If there’s a change/Signs of unusual behavior” corresponds to detecting whether the video of the first monitoring message and motion of the second monitoring message are associated with the target object (unusual behavior))
Regarding Claim 8, Boteju/Noguera-Arnaldos respectively teaches and incorporates the claimed limitations and rejections of Claim 6. Boteju, via Boteju/Noguera-Arnaldos, further teaches:
The behavior analysis system according to claim 6, wherein the artificial intelligence module determines whether the at least one motion and/or at least one sound in the first monitoring message and/or the second monitoring message is associated with a target object in response to the determination that the first monitoring message and/or the second monitoring message comprising the at least one motion and/or the at least one sound; (Boteju, fig.1, “Compare the tracked resting activity levels and walking activity levels with the average levels, according to dog’s breed and age”)
and the artificial intelligence module detects the first behavior event from the first monitoring message and detects the second behavior event from the second monitoring message in response to the determination that the at least one motion and/or at least one sound in the first monitoring message and/or the second monitoring message being associated with the target object. (Boteju, fig.1, video component; sensor; “If there’s a change/Signs of unusual behavior” corresponds to detecting whether the video of the first monitoring message and motion of the second monitoring message are associated with the target object (unusual behavior))
Regarding Claim 9, Boteju/Noguera-Arnaldos respectively teaches and incorporates the claimed limitations and rejections of Claim 1. Boteju, via Boteju/Noguera-Arnaldos further teaches:
The behavior analysis system according to claim 1, the computing unit further comprising: a knowledge module, in communication with the language module, configured to provide reference information; (Boteju [p.3 left ¶1] Thus, through the comparison of results obtained from all the sections above, the system predicts if there is a change of usual behaviour of the dog generating daily reports of dog behaviour.
[p.4 left middle] The calculated meanTotalRestingTime was the dog's current resting time and the standard resting time based on its breed and age was already stored in the database by the dog breed recognition section. Those two values were accessed using API method calls which were implemented using the Django rest API framework.) (Note: the values accessed using the API method calls corresponds to the knowledge module; the standard resting time corresponds to the reference information; identifying the change of usual behavior (event aggregation report) is based on the standard resting time (reference information); thus, the event aggregation report is also based on the reference information.)
Noguera-Arnaldos, via Boteju/Noguera-Arnaldos, further teaches:
wherein the language module generates the behavior summary based on the event aggregation report and the reference information. (Noguera-Arnaldos [p.7 ¶2] Besides the above-mentioned process, the im4Things bot is also able to notify the users about the home appliance’s state changes. Therefore, once a home appliance’s alert is triggered, the im4Things bot sends to the im4Things Cloud service a natural language expression concerning the situation. Then, the im4Things Cloud service notifies the users subscribed to the home appliance. Finally, it is worth mentioning that im4Things system allows users to control home appliances from the local network and remote locations.) (Note: the natural language expression corresponds to the behavior summary in the form of natural language)
Independent Claim 11 recites A behavioral analysis method performing precisely the methods of Claim 1. Thus, Claim 8 is rejected for reasons set forth in Claim 1.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Boteju/ Noguera-Arnaldos further in view of Barkio, “Barkio Academy: How to Monitor Dogs from Multiple Dog Stations” (hereinafter Barkio).
Regarding Claim 10, Boteju/Noguera-Arnaldos respectively teaches and incorporates the claimed limitations and rejections of Claim 9. Boteju/Noguera-Arnaldos does not teach, but Barkio further teaches:
The behavior analysis system according to claim 9, wherein the language module is further configured to generate a behavior suggestion based on the event aggregation report, the reference information, and the behavior summary; and the user equipment displays the behavior summary and the behavior suggestion. (Barkio [1:07]
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) (Note: the app determining whether the dog is noisy corresponds to a behavior suggestion; the app UI corresponds to the user equipment)
Barkio and Boteju/Noguera-Arnaldos are analogous to the present invention because both are from the same field of endeavor of video behavior monitoring methods. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to implement the behavior suggestion method from Barkio into Boteju/Noguera-Arnaldos’s method of monitoring the pet behavior. The motivation would be to “With Barkio, you can monitor up to 4 dog stations from one Person station.”.
Conclusion
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/J.H./Examiner, Art Unit 2122
/KAKALI CHAKI/Supervisory Patent Examiner, Art Unit 2122
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