DETAILED ACTION
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.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05/18/2026 has been entered.
Response to Arguments
Applicants' arguments filed 05/18/2026 have been fully considered but they are not persuasive. The Applicant purports that the prior art fails to disclose “determining a performance coefficient from the generated pattern.” In support of this position the Applicant argues “The Examiner mapped the claimed ‘performance coefficient’ to Wang's generic statistical measures including ‘standard deviation, correlation, correlation coefficient, median, mode’ at [0353]. These are generic statistical descriptors of wireless channel information, not a performance coefficient derived from a trained latent correlation probabilistic model applied to patterns of material property variations” and cites the instant application’s specification for support. The Examiner respectfully disagrees. The Applicant misinterprets the principle that claims are interpreted in the light of the specification. Although a “trained latent correlation probabilistic model” is found in examples or embodiments in the specification, the feature is not claimed explicitly. The claims as filled 05/18/2026 recite a “performance coefficient from the generated pattern” and do not further limit the performance coefficient as being provided by a “trained latent correlation probabilistic model.” Further, the claim language is not defined in the specification to require this unclaimed limitation. A reading of the specification provides no evidence to indicate that a “trained latent correlation probabilistic model” must be imported into the claims to give meaning to disputed terms. Constant v. Advanced Micro-Devices Inc., 7 USPQ2d 1064. The Applicant is reminded that It is the claims that define the claimed invention, and it is claims, not specifications that are anticipated or unpatentable. The broadest reasonable interpretation of the claimed term “performance coefficient” includes any value that indicates confidence in a “generated pattern.” Indicated in previously filled action, paragraph [0353] of Wang discloses a plurality of statistical measures. These statistical measures include calculating a correlation coefficient of an expression generated from time series channel information [0057]. Paragraphs [0057-0058] clarify that expression generated from time series channel information is a generated pattern. As the correlation coefficient indicates confidence in a generated pattern, the Examiner maintains the art rejection.
With respect to the above limitation the Applicant further argues that prior art reference Wang “does not account for the specific context in which the claimed performance coefficient operates” as Wang fails to disclose detecting variations in a dielectric constant. In response the Examiner reminds the Applicant that Wang is not relied upon alone to teach independent claim 1. Wang as modified by Dalfra disclose “generating a pattern based on the variation in the material property parameter including the dielectric constant.” The Examiner acquiesces that Wang does not explicitly disclose measuring a dielectric constant; however, Wang does disclose generating a pattern based on the variation in the material property parameter [0057-0058, Wang]. Dalfra discloses measuring and utilizing dielectric constant [0020, Dalfra]. The Examiner maintains that it would have been obvious one of ordinary skill in the art to modify Wang’s pattern generation with the teachings of Dalfra to include measuring and utilizing a dielectric constant.
The Applicant further argues that, “Dalfra uses the dielectric constant for material identification purposes, not for generating patterns from dielectric constant variations over time and deriving a performance coefficient therefrom.” In response the Examiner again points to the previously filled action. Dalfra is not relied upon to teach generating patterns or deriving a performance coefficient therefrom. Explained in greater detail above, Dalfra is explicitly relied upon to teach measuring and utilizing dielectric constant. The Applicant is reminded that it has been held that one cannot show non obviousness by attacking references individually where, as here, the rejections are based on combinations of references. In re Keller, 208 USPQ 871 (CCPA1981). As the Applicant has not established why the Wang as modified by Dalfra does not teach the aforementioned limitation, the Examiner maintains the art rejection.
The Applicant argues that “Proud does not disclose or suggest a latent correlation probabilistic model or any of the claimed anomaly detection methodology. The Applicant is again reminded that it has been held that one cannot show non obviousness by attacking references individually where, as here, the rejections are based on combinations of references. In re Keller, 208 USPQ 871 (CCPA1981). As the Applicant does not present arguments regarding the explicit subject matter incorporated by Proud or treat the combination as a whole, the Examiner maintains the art rejection.
The Applicant additionally purports that the prior art fails to disclose a “closed-loop feedback mechanism.” Although this term is unclaimed, the Applicant argues that the limitations of claim 1 recited on page 13 of the remarks amount to the “closed-loop feedback mechanism.” The Examiner respectfully disagrees. A “closed-loop feedback mechanism” requires a step of adjustment or correction preformed in a cyclical manner. The limitations pointed to on page 13 of the remarks include steps of determining a threshold based on one or more stored patterns, comparing the performance coefficient to a threshold, and storing the generated pattern if the performance coefficient is less than the threshold. Although the generated pattern is stored at the end of the process, the claims do not explicitly require future thresholds be based on the new pattern. These limitations lack a forward step of adjustment and do not explicitly require the process to be performed in a cyclical manner. The Examiner does not find valid reason that the unclaimed “closed-loop feedback mechanism” must be imported into the claims. The Examiner points to the rejection below and maintains that each and very limitation as recited by independent claim 1 is disclosed by the prior art.
Applicant’s arguments with respect to prior art reference Zhang have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 6rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. The claimed subject matter of Claim 6 is identical to the following limitation of Claim 1, from which Claim 6 depends: “based on determining that the performance coefficient meets the threshold value, detecting the anomaly of the at least one object.“ Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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, 3-4, 6 10-11, 13-14, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Wang(US20200300972A1) in view of Dalfra(US20210263131A1), and further in view of Jin(US20210286874A1).
Regarding claim 1, Wang discloses
A method of managing objects by an electronic device, comprising: monitoring (“In one embodiment, the present teaching discloses a method, apparatus, device, system, and/or software (method/apparatus/device/system/software) of a wireless monitoring system”[0057]), using an ultra-wide band (UWB) sensor of the electronic device (“The wireless signal may comprise: transmitted/received signal, EM radiation, RF signal/transmission, […] UWB) “[0059]) , at least one object over a time period (“ A characteristics and/or a spatial-temporal information (STI, e.g. motion information) of the object and/or of the motion of the object may be monitored based on the TSCI.”[0057]); based on the monitoring of the at least one object, extracting a variation in a material property parameter of the at least one object (“The expression may comprise placement, placement of moveable parts, location, position, orientation, identifiable place, region, spatial coordinate, presentation, state, static expression, size,”[0058]) […];generating a pattern based on the variation in the material property parameter (“A first part of the task may comprise at least one of: preprocessing, processing, signal conditioning, […], motion estimation, motion change detection, motion pattern detection, motion pattern estimation, motion pattern recognition, vital sign detection,”[0134]); determining a performance coefficient from the generated pattern (“The method of the wireless monitoring system of clause 1 or clause 2: wherein at least one of: the first information (info) and the second info, comprising at least one of: […] standard deviation, correlation, correlation coefficient, median, mode”[0353]) […] detecting an anomaly of the at least one object (“The characteristics and/or STI (e.g. motion information) may comprise: location, location coordinate, change in location […], complex motion, and/or combination of multiple motions, event, signal statistics, signal dynamics, anomaly […] based on an analysis of the feature”[0125]), wherein the threshold value is determined based on at least one previous pattern of the at least one object(”A threshold to be applied to a test statistics […]. The threshold may be adjusted to achieve different sensitivity” [0159] & “The threshold adjustment may depend on […] the past history” [0160]) stored in the database (“A database (e.g. in local server, hub device, cloud server, storage network) may be used to store the TSCI” [0062]
Wang discloses the extracting, generating, and identifying steps of claim 1, but does not explicitly disclose nor limit wherein the material property parameter comprises a dielectric constant of the at least one object. Dalfra discloses the method wherein a material property parameter includes a dielectric constant of the at least one object(“the radar identifies a material type of a detected object through a dielectric constant and/or surface morphology of the detected object”[0020])
Dalfra teaches in the same field of endeavor of remote observation. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang with the teachings of Dalfra to incorporate the features of measuring the dielectric constant of a material through radar so as to gain the advantage of increasing available monitoring data [0080, Dalfra]. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Wang discloses wherein a threshold value is determined based on at least one previous pattern of the at least one object, but does not explicitly disclose nor limit wherein the method includes determining whether the performance coefficient meets a threshold value. Jin discloses wherein, based on determining that the performance coefficient meets a threshold value, detecting an anomaly of the at least one object (“ When it is determined that the aggregate score satisfies (e.g., equals or exceeds) the anomaly score threshold, the process proceeds to Block 1510 “ [0257] & “In Block 1510, the event has been deemed an anomaly” [0258]); and based on determining that the performance coefficient does not meet the threshold value, updating the generated pattern to a database (“When it is determined that the aggregate score does not satisfy (e.g., is less than) the anomaly score threshold, the process proceeds to Block 1512” [0257] & “the event has been deemed normal (i.e., not an anomaly). In one or more embodiments, the event may be used to update a scoring model. Specifically, the event may be added to the historic events data store 1230 and used to generate or update frequent patterns in the future.” [0259]).
Jin teaches in the same field of endeavor of anomaly detection. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang as modified by Dalfra with the teachings of Jin to incorporate the features of comparing a performance coefficient and a threshold value so as to gain the advantage of improving detection [0303, Jin]. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 3, Wang as modified by Dalfra and Jin discloses all the limitations of claim 1. Wang discloses the method wherein, the extracting of the variation, comprises: identifying the at least one object (“ A characteristics and/or a spatial-temporal information (STI, e.g. motion information) of the object and/or of the motion of the object may be monitored based on the TSCI.”[0057]) based on a reflected UWB signal received at the UWB sensor from the at least one object (“The wireless monitoring system comprises: a transmitter, a receiver, and a processor. The transmitter is configured for transmitting, using N1 transmit antennas” [0035]); generating noise free data of the reflected UWB signal and a binary image of the noise free data by pre-processing the reflected UWB signal (“process the raw signal by removing/suppressing influence of the dominant periodic signal (e.g. filter the raw signal, or estimate the dominant periodic signal and subtract it from the raw signal)”[0273]); and determining the variation in least one of the material property parameter from the noise free data and the binary image (“s5b: compute characteristics of the next dominant periodic signal based on the processed raw signal. The characteristics may be computed based on frequency transform, trigonometric transform, fast Fourier transform (FFT), wavelet transform, ACF, etc.”[0294]).
Regarding claim 4, Wang as modified by Dalfra and Jin discloses all the limitations of claim 3. Wang discloses the method wherein the generating of the noise free data of the reflected UWB signal and the binary image of the noise free data, comprises: generating the noise free data of the reflected UWB signal by removing a direct current (DC) noise and a carrier signal in the reflected UWB signal (“process the raw signal by removing/suppressing influence of the dominant periodic signal (e.g. filter the raw signal, or estimate the dominant periodic signal and subtract it from the raw signal)”[0273]); filtering the noise free data by removing a low frequency time component from the noise free data (“An operation, pre-processing, processing and/or postprocessing may be applied to data […] feature extraction, decomposition, projection, orthogonal projection, non-orthogonal projection, over-complete projection, eigen-decomposition, singular value decomposition (SVD)”[0144]); performing a background subtraction on the filtered noise free data using wavelets data (“ An operation, pre-processing, processing and/or postprocessing may be applied to data […] discrete time FT (DTFT), discrete FT (DFT), fast FT (FFT),wavelet transform,”[0144]); and generating the binary image of the noise free data using an output obtained from the performing of the background subtraction on the filtered noise free data (“process the raw signal by removing/suppressing influence of the dominant periodic signal (e.g. filter the raw signal, or estimate the dominant periodic signal and subtract it from the raw signal).”[0273]).
Regarding claim 6, Wang as modified by Dalfra and Jin discloses all the limitations of claim 1. Wang discloses the method wherein […], detecting the anomaly of the at least one object (“The characteristics and/or STI (e.g. motion information) may comprise: location, location coordinate, change in location […], complex motion, and/or combination of multiple motions, event, signal statistics, signal dynamics, anomaly […] based on an analysis of the feature”[0125]).
Wang discloses wherein a threshold value is determined based on at least one previous pattern of the at least one object, but does not explicitly disclose nor limit wherein the method includes determining whether the performance coefficient meets a threshold value. Jin discloses, determining that the performance coefficient meets the threshold value object (“ When it is determined that the aggregate score satisfies (e.g., equals or exceeds) the anomaly score threshold, the process proceeds to Block 1510 “ [0257] & “In Block 1510, the event has been deemed an anomaly” [0258]).
Jin teaches in the same field of endeavor of anomaly detection. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang as modified by Dalfra with the teachings of Jin to incorporate the features of comparing a performance coefficient and a threshold value so as to gain the advantage of improving detection [0303, Jin]. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 10, Wang as modified by Dalfra and Jin discloses all the limitations of claim 1. Wang discloses the method wherein, the monitoring of the at least one object, comprises: transmitting, using the UWB sensor (“The wireless monitoring system comprises: a transmitter, a receiver, and a processor. The transmitter is configured for transmitting, using N1 transmit antennas” [0035]), a reference UWB signal towards the at least one object; and receiving (“The wireless signal may comprise: transmitted/received signal, EM radiation, RF signal/transmission, […] reference signal”[0059]), using the UWB sensor, a reflected UWB signal corresponding to the transmitted reference UWB signal from the at least one object (“ The receiver is configured for: receiving, using N2 receive antennas”[0035]).
Regarding claim 11, Wang discloses
An electronic device for managing objects, the electronic device comprising: an ultra-wide band (UWB) sensor (“The wireless signal may comprise: transmitted/received signal, EM radiation, RF signal/transmission, […] UWB) “[0059]); a memory storing one or more instructions (“a memory communicatively coupled with the processor and a set of instructions stored in the memory.”[0057]); and a processor communicatively coupled to the UWB sensor and the memory (“A time series of channel information (CI) of a wireless multipath channel (channel) may be obtained (e.g. dynamically) using a processor”[0059), wherein the one or more instructions, when executed by the processor, cause the electronic device to: monitor (“In one embodiment, the present teaching discloses a method, apparatus, device, system, and/or software (method/apparatus/device/system/software) of a wireless monitoring system”[0057]), using the UWB sensor (“The wireless signal may comprise: transmitted/received signal, EM radiation, RF signal/transmission, […] UWB) “[0059]), at least one object over a time period (“ A characteristics and/or a spatial-temporal information (STI, e.g. motion information) of the object and/or of the motion of the object may be monitored based on the TSCI.”[0057]); based on the monitoring of the at least one object , extract a variation in a material property parameter of the at least one object (“The expression may comprise placement, placement of moveable parts, location, position, orientation, identifiable place, region, spatial coordinate, presentation, state, static expression, size,”[0058]) […];generate a pattern based on the variation in the material property parameter (“A first part of the task may comprise at least one of: preprocessing, processing, signal conditioning, […], motion estimation, motion change detection, motion pattern detection, motion pattern estimation, motion pattern recognition, vital sign detection,”[0134]) […]; determine a performance coefficient from the generated pattern (“A first part of the task may comprise at least one of: preprocessing, processing, signal conditioning, […], motion estimation, motion change detection, motion pattern detection, motion pattern estimation, motion pattern recognition, vital sign detection,”[0134]) […] detecting an anomaly of the at least one object (“The characteristics and/or STI (e.g. motion information) may comprise: location, location coordinate, change in location […], complex motion, and/or combination of multiple motions, event, signal statistics, signal dynamics, anomaly […] based on an analysis of the feature”[0125]) wherein the threshold value is determined based on at least one previous pattern of the at least one object (”A threshold to be applied to a test statistics […]. The threshold may be adjusted to achieve different sensitivity” [0159] & “The threshold adjustment may depend on […] the past history” [0160]).
Wang discloses the extracting, generating, and identifying steps of claim 1, but does not explicitly disclose nor limit wherein the material property parameter comprises a dielectric constant of the at least one object. Dalfra discloses the device wherein a material property parameter includes a dielectric constant of the at least one object(“the radar identifies a material type of a detected object
through a dielectric constant and/or surface morphology of the detected object”[0020]) ]) stored in the database (“A database (e.g. in local server, hub device, cloud server, storage network) may be used to store the TSCI” [0062]
Dalfra teaches in the same field of endeavor of remote observation. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang with the teachings of Dalfra to incorporate the features of measuring the dielectric constant of a material through radar so as to gain the advantage of increasing available monitoring data [0080, Dalfra]. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Wang discloses wherein a threshold value is determined based on at least one previous pattern of the at least one object, but does not explicitly disclose nor limit wherein the method includes determining whether the performance coefficient meets a threshold value. Jin discloses wherein, based on determining that the performance coefficient meets a threshold value, detect an anomaly of the at least one object (“ When it is determined that the aggregate score satisfies (e.g., equals or exceeds) the anomaly score threshold, the process proceeds to Block 1510 “ [0257] & “In Block 1510, the event has been deemed an anomaly” [0258]); and based on determining that the performance coefficient does not meet the threshold value, update the generated pattern to a database (“When it is determined that the aggregate score does not satisfy (e.g., is less than) the anomaly score threshold, the process proceeds to Block 1512” [0257] & “the event has been deemed normal (i.e., not an anomaly). In one or more embodiments, the event may be used to update a scoring model. Specifically, the event may be added to the historic events data store 1230 and used to generate or update frequent patterns in the future.” [0259]).
Jin teaches in the same field of endeavor of anomaly detection. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang as modified by Dalfra with the teachings of Jin to incorporate the features of comparing a performance coefficient and a threshold value so as to gain the advantage of improving detection [0303, Jin]. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 13, Wang as modified by Dalfra and Jin discloses all the limitations of claim 11. Wang discloses wherein, the one or more instructions, when executed by the processor, cause the electronic device further to: identify the at least one object (“ A characteristics and/or a spatial-temporal information (STI, e.g. motion information) of the object and/or of the motion of the object may be monitored based on the TSCI.”[0057]) based on a reflected UWB signal received at the UWB sensor from the at least one object (“The wireless monitoring system comprises: a transmitter, a receiver, and a processor. The transmitter is configured for transmitting, using N1 transmit antennas” [0035]); generate noise free data of the reflected UWB signal and a binary image of the noise free data by pre-processing the reflected UWB signal (“process the raw signal by removing/suppressing influence of the dominant periodic signal (e.g. filter the raw signal, or estimate the dominant periodic signal and subtract it from the raw signal)”[0273]); and determine the variation in least one of the material property parameter from the noise free data and the binary image (“s5b: compute characteristics of the next dominant periodic signal based on the processed raw signal. The characteristics may be computed based on frequency transform,
Regarding claim 14, Wang as modified by Dalfra and Jin discloses all the limitations of claim 13. Wang discloses wherein, the one or more instructions, when executed by the processor, cause the electronic device further to: generate the noise free data of the reflected UWB signal by removing a direct current (DC) noise and a carrier signal in the reflected UWB signal (“process the raw signal by removing/suppressing influence of the dominant periodic signal (e.g. filter the raw signal, or estimate the dominant periodic signal and subtract it from the raw signal)”[0273]); filter the noise free data by removing a low frequency time component from the noise free data (“ An operation, pre-processing, processing and/or postprocessing may be applied to data […] feature extraction, decomposition, projection, orthogonal projection, non-orthogonal projection, over-complete projection, eigen-decomposition, singular value decomposition
(SVD)”[0144]); perform a background subtraction on the filtered noise free data using wavelets (“ An operation, pre-processing, processing and/or postprocessing may be applied to data […] discrete time FT (DTFT), discrete FT (DFT), fast FT (FFT), wavelet transform,”[0144]); and generate the binary image of the noise free data using an output obtained from the background subtraction performed on the filtered noise free data (“process the raw signal by removing/suppressing influence of the dominant periodic signal (e.g. filter the raw signal, or estimate the dominant periodic signal and subtract it from the raw signal).”[0273]).
Regarding claim 18, Wang as modified by Dalfra and Jin discloses all the limitations of claim 11. Wang discloses wherein, the one or more instructions, when executed by the processor, cause the electronic device further to: transmit, using the UWB sensor (“The wireless monitoring system comprises: a transmitter, a receiver, and a processor. The transmitter is configured for transmitting, using N1 transmit antennas” [0035]), a reference UWB signal towards the at least one object; and receive(“The wireless signal may comprise: transmitted/received signal, EM radiation, RF signal/transmission, […] reference signal”[0059]), using the UWB sensor, a reflected UWB signal corresponding to the transmitted reference UWB signal from the at least one object (“The receiver is configured for: receiving, using N2 receive antennas”[0035]).
Claims 2, 8-9, 12, and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Wang(US20200300972A1) as modified by Dalfra(US20210263131A1) and Jin(US20210286874A1), as applied to claims 1 and 11 above, and further in view of Proud(US20140247148A1)
Regarding claim 2 Wang as modified by Dalfra and Jin discloses all the limitations of claim 1. Wang discloses wherein, the material property parameter and a motion parameter of the at least one object (“A first part of the task may comprise at least one of: preprocessing, processing, signal conditioning, […], motion estimation, motion change detection, motion pattern detection, motion pattern estimation, motion pattern recognition, vital sign detection,”[0134]).
Wang as modified by Dalfra and further modified by Jin does not explicitly disclose nor limit wherein the method includes generating at least one recommendation based on the functional state of the at least one object. Proud discloses the method comprising, determining, using an artificial intelligence (Al) engine, a functional state of the at least one object (“ An Artificial Intelligence (AI) or Machine Learning-grade algorithms is used to identify the user's activities, behaviors, behaviors and perform analysis”[0093]) […] generating at least one recommendation based on the recommendation state of the at least one object (“Observation or recommendations can be presented based on historical information and live information.” [00135]); and providing the at least one recommendation to a user of the at least one object (“In one embodiment, a breakdown of recounting data that has been collecting is presented for analysis of that data.”[0135]).
Proud teaches in the same field of endeavor of remote observation. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang as modified by Dalfra and further modified by Jin with the teachings of Proud to incorporate the features of generating and presenting a recommendation to a user so as to gain the advantage of improving end user monitoring capabilities [00135, Proud] Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 8, Wang as modified by Dalfra and Jin discloses all the limitations of claim 1. Wang discloses wherein, functional state of the at least one object based on the material property parameter and a motion parameter of the at least one object (“The expression may comprise placement, placement of moveable parts, location, position, orientation, identifiable place, region, spatial coordinate, presentation, state, static expression, size,”[0058])
Wang as modified by Dalfra and Fin does not explicitly disclose nor limit wherein the method includes, using an artificial intelligence (Al) engine. Proud discloses the method wherein, classifying, using an artificial intelligence (Al) engine (“ An Artificial Intelligence (AI) or Machine Learning-grade algorithms is used to identify the user's activities, behaviors, behaviors and perform analysis”[0093]) […]; and storing, in the database, the generated pattern and the functional state of the at least one object corresponding to the generated pattern (“In one embodiment, a breakdown of recounting data that has been collecting is presented for analysis of that data.”[0135]).
Proud teaches in the same field of endeavor of remote observation. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang as modified by Dalfra and further modified by Jin with the teachings of Proud to incorporate the features of generating and presenting a recommendation to a user so as to gain the advantage of improving end user monitoring capabilities [00135, Proud] Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using
Regarding claim 9, Wang as modified by Dalfra and Jin and further modified by Proud discloses all the limitations of claim 2. Wang discloses wherein, the motion parameter comprises a polynomial phase signal (PPS) parameter of the at least one object (“estimating the influence of the first repetitive motion based on at least one of: […], polynomial interpolation piecewise polynomial interpolation,
polynomial fitting, polynomial fitting with adaptive order, polynomial fitting“[0309]).
Regarding claim 12, Wang as modified by Dalfra and Jin discloses all the limitations of claim 11. Wang discloses wherein, a functional state of the at least one object based on the material property parameter and the motion parameter (“A first part of the task may comprise at least one of: preprocessing, processing, signal conditioning, […], motion estimation, motion change detection, motion pattern detection, motion pattern estimation, motion pattern recognition, vital sign detection,”[0134])
Wang as modified by Dalfra and Jin does not explicitly disclose nor limit wherein the device includes generating at least one recommendation based on the functional state of the at least one object. Proud discloses the device wherein, determine, using an artificial intelligence (Al) a functional state (“ An Artificial Intelligence (AI) or Machine Learning-grade algorithms is used to identify the user's activities, behaviors, behaviors and perform analysis”[0093]) […] engine generate at least one recommendation based on the functional state of the at least one object (“Observation or recommendations can be presented based on historical information and live information.” [00135]); and provide the at least one recommendation to a user of the at least one object(“In one embodiment, a breakdown of recounting data that has been collecting is presented for analysis of that data.”[0135]).
Proud teaches in the same field of endeavor of remote observation. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang as modified by Dalfra and Jin with the teachings of Proud to incorporate the features of generating and presenting a recommendation to a user so as to gain the advantage of improving end user monitoring capabilities[00135, Proud]. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 16, Wang as modified by Dalfra and Jin discloses all the limitations of claim 11. Wang discloses wherein, the one or more instructions, when executed by the processor, cause the electronic device further to: […] a functional state of the at least one object based on the material property parameter and a motion parameter of the at least one object (“The expression may comprise placement, placement of moveable parts, location, position, orientation, identifiable place, region, spatial coordinate, presentation, state, static expression, size,”[0058]);
Wang as modified by Dalfra and Jin does not explicitly disclose nor limit wherein the device includes, using an artificial intelligence (Al) engine. Proud discloses the device wherein, classify, using an artificial intelligence (Al) engine (“ An Artificial Intelligence (AI) or Machine Learning-grade algorithms is used to identify the user's activities, behaviors, behaviors and perform analysis”[0093]) , […] and store, in the database, the generated pattern and the functional state of the at least one object corresponding to the generated pattern to the database (“to process a request, a request may be entered into a database, a machine learning model may be located from model registry 3724 if not already in a cache, a validation step may ensure appropriate machine learning model is loaded into a cache”[0572]) (“In one embodiment, a breakdown of recounting data that has been collecting is presented for analysis of that data.”[0135]).
Proud teaches in the same field of endeavor of remote observation. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang as modified by Dalfra and Jin with the teachings of Proud to incorporate the features of generating and presenting a recommendation to a user so as to gain the advantage of improving end user monitoring capabilities[00135, Proud]. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 17, Wang as modified by Dalfra and Jin and further modified by Proud discloses all the limitations of claim 12. Wang discloses wherein, the motion parameter comprises a polynomial phase signal (PPS) parameter of the at least one object (“estimating the influence of the first repetitive motion based on at least one of: […], polynomial interpolation piecewise polynomial interpolation, polynomial fitting, polynomial fitting with adaptive order, polynomial fitting “[0309]).
Claims 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Wang(US20200300972A1) in view of Dalfra(US20210263131A1) and further in view of Jin(US20210286874A1) and Proud(US20140247148A1)
Regarding claim 19, Wang discloses
A method of managing objects by an electronic device, the method comprising: Monitoring (“In one embodiment, the present teaching discloses a method, apparatus, device, system, and/or software (method/apparatus/device/system/software) of a wireless monitoring system”[0057]), over a time period using a ultra-wide band (UWB) sensor (“The wireless signal may comprise: transmitted/received signal, EM radiation, RF signal/transmission, […] UWB) “[0059]), a variation in a material property associated with at least one object (“The expression may comprise placement, placement of moveable parts, location, position, orientation, identifiable place, region, spatial coordinate, presentation, state, static expression, size,”[0058]); […] parameter of the at least one object indicative of an extent of the variation of the material property and the movement associated with the at least one object (“estimating the influence of the first repetitive motion based on at least one of: […], polynomial interpolation piecewise polynomial interpolation, polynomial fitting, polynomial fitting with adaptive order, polynomial fitting “[0309]); determining a pattern […] (“A first part of the task may comprise at least one of: preprocessing, processing, signal conditioning, […], motion estimation, motion change detection, motion pattern detection, motion pattern estimation, motion pattern recognition, vital sign detection,”[0134]), determining a performance coefficient from the determined pattern (“The method of the wireless monitoring system of clause 1 or clause 2: wherein at least one of: the first information (info) and the second info, comprising at least one of: […] standard deviation, correlation, correlation coefficient, median, mode”[0353]), detecting an anomaly of the at least one object (“The characteristics and/or STI (e.g. motion information) may comprise: location, location coordinate, change in location […], complex motion, and/or combination of multiple motions, event, signal statistics, signal dynamics, anomaly […] based on an analysis of the feature”[0125]) […] wherein the threshold value is determined based on at least one previous pattern of the at least one object (”A threshold to be applied to a test statistics […]. The threshold may be adjusted to achieve different sensitivity” [0159] & “The threshold adjustment may depend on […] the past history” [0160]) stored in the database (“A database (e.g. in local server, hub device, cloud server, storage network) may be used to store the TSCI” [0062]
Wang does not explicitly disclose nor limit wherein the method includes, extracting a dielectric constant. Dalfra discloses the method comprising extracting a dielectric constant (“the radar identifies a material type of a detected object through a dielectric constant and/or surface morphology of the detected object”[0020])
Dalfra teaches in the same field of endeavor of remote observation. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang with the teachings of Dalfra to incorporate the features of measuring the dielectric constant of a material through radar so as to gain the advantage of increasing available monitoring data [0080, Dalfra]. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Wang discloses wherein a threshold value is determined based on at least one previous pattern of the at least one object, but does not explicitly disclose nor limit wherein the method includes determining whether the performance coefficient meets a threshold value. Jin discloses wherein, based on determining that the performance coefficient meets a threshold value, detecting an anomaly of the at least one object (“ When it is determined that the aggregate score satisfies (e.g., equals or exceeds) the anomaly score threshold, the process proceeds to Block 1510 “ [0257] & “In Block 1510, the event has been deemed an anomaly” [0258]); and based on determining that the performance coefficient does not meet the threshold value, updating the generated pattern to a database (“When it is determined that the aggregate score does not satisfy (e.g., is less than) the anomaly score threshold, the process proceeds to Block 1512” [0257] & “the event has been deemed normal (i.e., not an anomaly). In one or more embodiments, the event may be used to update a scoring model. Specifically, the event may be added to the historic events data store 1230 and used to generate or update frequent patterns in the future.” [0259])
Jin teaches in the same field of endeavor of anomaly detection. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang as modified by Dalfra with the teachings of Jin to incorporate the features of comparing a performance coefficient and a threshold value so as to gain the advantage of improving detection [0303, Jin]. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Wang as modified by Dalfra and Jin does not explicitly disclose nor limit wherein the method includes providing to a user, at least one performance recommendation. Proud discloses the method comprising providing to a user, at least one performance recommendation of the at least one object corresponding to the determined pattern (“In one embodiment, a breakdown of recounting data that has been collecting is presented for analysis of that data. Observation or recommendations can be presented based on historical information and live information.”[0135]).
Proud teaches in the same field of endeavor of remote observation. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang as modified by Dalfra and Jin with the teachings of Proud to incorporate the features of presenting a recommendation to a user so as to gain the advantage of improving end user monitoring capabilities[00135, Proud]. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Regarding claim 20, Wang as modified by Dalfra and Jin and further modified by Proud discloses all the limitations of claim 19. Wang as modified by Dalfra do not explicitly disclose the use of an AI engine or providing a performance recommendation based on a functional state. Proud discloses, determining, using an artificial intelligence (Al) engine, a functional state of the at least one object based on the material property and a movement associated with the at least one object (“ An Artificial Intelligence (AI) or Machine Learning-grade algorithms is used to identify the user's activities, behaviors, behaviors and perform analysis”[0093]) […]wherein the providing of the at least one performance recommendation comprises: […] generating the at least one performance recommendation based on the functional state of the at least one object (“In one embodiment, a breakdown of recounting data that has been collecting is presented for analysis of that data. Observation or recommendations can be presented based on historical information and live information.”[0135]).
Proud teaches in the same field of endeavor of remote observation. It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Wang as modified by Dalfra and Jin with the teachings of Proud to incorporate the features of generating and presenting a recommendation to a user based on the functional state of the at least one object so as to gain the advantage of improving end user monitoring capabilities [00135, Proud]. Also, since it has been held that if a technique has been used to improve one device, and a person of ordinary skill in the art would recognize that it would improve similar devices in the same way, using the technique is obvious unless its actual application is beyond his or her skill (MPEP 2143).
Documents Considered but not Relied Upon
The prior art made of record and not relied upon is considered pertinent to the applicant’s Disclosure.
Bly(US20150031964A1)is considered analogous art to the instant application as it discloses in [0120] “ If the detected artifact signal is less than the artifact threshold, then the processor validates and stores the physiological signal to a memory 300.”
Conclusion
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/C.P.R./Examiner, Art Unit 3646
/JACK W KEITH/Supervisory Patent Examiner, Art Unit 3646
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