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 Arguments
Applicant’s arguments, see Remarks, filed 10/16/2025, with respect to the rejection(s) of the claim(s) under 35 U.S.C. 102 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Bucsa et al. U.S. PGPub 2015/0331666.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 2, 4-8, 10-12 and 14-25 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bucsa et al. U.S. PGPub 2015/0331666 (hereinafter “Bucsa”).
Regarding claims 1, 11 and 15, Bucsa discloses a method of performing an operation (e.g. activate/deactivate premises devices, lights, LEDs) based on sensor signal data associated with a target event (e.g. audible speech) and obtained from at least one sensor by a device (e.g. Voice Interactive Personal Assistant (VIPA)) comprising a processor, said method comprising: generating, by said processor, a feature profile (e.g. speech phrase) from said sensor signal data (e.g. ¶14 and 76); matching, by said processor, said generated feature profile to a set of predetermined feature profiles (e.g. set of local commands) available to said processor (e.g. ¶5, 13, 36-39, 79, 83 and 93); discloses determining, by said processor, whether said operation (i.e. modifying configuration and/or parameters) can be performed locally (i.e. via local processing) on said device or remotely (i.e. via remote processing), based on an evaluation of said sensor signal data (e.g. ¶5, 13, 36-39, 79, 83 and 93); performing said operation, by said device, controlled by said processor, upon detection of the target event, based on local processing (via local processing) of said sensor signal data, if said generated feature profile matches at least one of said set of predetermined feature profiles (e.g. ¶5, 13, 36-39, 79, 83 and 93), and performing said operation, upon detection of the target event, by said device, controlled by said processor, based on remote processing (via remote processing) of said sensor signal data, if said generated feature profile does not match at least one of said set of predetermined feature profiles (e.g. ¶5, 13, 36-39, 79, 83 and 93), wherein said sensor signal data comprises at least one of motion data, ambient sound data, image data, video data, temperature data, humidity data, pressure data, luminance data, chemical composition or substance data, olfactive data and tactile data (e.g. ¶14 and 76), and wherein performing said operation, by said device, comprises controlling lighting (e.g. ¶8, 28, 30, 35-37, 44-45, 62 and 82).
Regarding claim 2, Bucsa discloses the method according to claim 1, wherein said generating comprises generating said feature profile by using a predefined data analysis algorithm including one of a transformation algorithm and a feature extraction algorithm (e.g. algorithm of the analyzer) (e.g. ¶42 and 78).
Regarding claim 4, Bucsa discloses the method according to claim 1, wherein said matching comprises comparing said generated feature profile to a set of predetermined feature profiles available to said processor (e.g. ¶5, 13, 36-39, 79, 83 and 93).
Regarding claims 5 and 22, Bucsa discloses the method according to claim 1, wherein said matching comprises determining whether a generated feature profile repeats in a predetermined time period (e.g. ¶64).
Regarding claim 6, Bucsa discloses the method according to claim 1, wherein said performing said operation, by said device, using said sensor signal data comprises applying an operation algorithm to said sensor signal data wherein said operation algorithm comprises a data analysis algorithm for generating said feature profile (e.g. ¶5, 13, 36-39, 79, 83 and 93).
Regarding claim 7, Bucsa discloses the method according to claim 1, wherein said device further comprises a transceiver, and said method comprises, prior to performing said operation based on said remote processing of sensor signal data: transmitting, by said transceiver, said sensor signal data to said remote computing device (e.g. ¶5, 13, 36-39, 79, 83 and 93), and receiving, by said transceiver, from said remote computing device, said processed sensor signal data obtained by applying at least one processing algorithm at said transmitted sensor signal data by said remote computing device (e.g. ¶5, 13, 36-39, 79, 83 and 93).
Regarding claim 8, Bucsa discloses the method according to claim 7, wherein transmitting said sensor signal data by said transceiver comprises transmitting a representation of said sensor signal data to said remote computing device (e.g. ¶5, 13, 36-39, 79, 83 and 93).
Regarding claims 10 and 12, Bucsa discloses the method according to claim 1, wherein said device comprises a lighting fixture comprising at least one lighting module (e.g. software generating lighting commands), and wherein performing said operation, by said device, comprises controlling lighting by said at least one lighting module (e.g. ¶8, 28, 30, 35-37, 44-45, 62 and 82; Fig. 1-3C).
Regarding claim 11, Bucsa discloses a device for performing an operation based on sensor signal data associated with a target event obtained from at least one sensor, said device comprising a processor and a transceiver, wherein said processor and transceiver are arranged for performing said operation, controlled by said processor, in accordance with the method of any of claim 1 (e.g. ¶5, 13, 36-39, 79, 83 and 93).
Regarding claim 14, Bucsa discloses a system, comprising a device according to claim 11 and a remote backend computing device (e.g. ¶5, 13, 36-39, 79, 83 and 93; Fig. 1), wherein said remote backend computing device is arranged for: receiving sensor signal data from said device (e.g. ¶5, 13, 36-39, 79, 83 and 93); processing received sensor signal data by applying at least one processing algorithm (e.g. ¶5, 13, 36-39, 79, 83 and 93), and transmitting said processed sensor signal data to said device (e.g. ¶5, 13, 36-39, 79, 83 and 93).
Regarding claim 15, Bucsa discloses a computer program product comprising program code stored on a non-transitory computer readable medium, said program code arranged for performing said method according to claim 1, when said program code is executed by at least one processor (e.g. Fig. 2).
Regarding claims 16 and 21, Bucsa discloses the method of claim 1, further comprising distinguishing between a background event and the target event based on said sensor signal data (e.g. ¶50).
Regarding claims 17 and 18, Bucsa discloses the method of claim 10, wherein the lighting module comprises an LED lighting module (e.g. ¶44-45).
Regarding claim 19, Bucsa discloses the device of claim 11, wherein said device further comprises the at least one sensor (e.g. ¶5, 13, 36-39, 79, 83 and 93).
Regarding claim 20, Bucsa discloses the device of claim 11, wherein the at least one sensor comprises a motion detector (e.g. motion of user mouth when speaking) and wherein said sensor signal data comprises motion data (e.g. ¶14, 30 and 76).
Regarding claims 23-25, Bucsa discloses the method of claim 1, wherein said processor comprises a feature profile matching module configured to perform an adversary evaluation, wherein said adversary evaluation is configured to determine whether the operation can be performed on said device based on an evaluation of said sensor signal data by said processor (e.g. ¶5, 13, 36-39, 79, 83 and 93).
Allowable Subject Matter
Claim 3 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: Regarding claim 3, the prior art of record does not disclose a method wherein said transformation algorithm is a Fast Fourier Transform, FFT, algorithm, and said generated feature profile is a spectrum feature profile comprising a set of frequency components having an amplitude exceeding a predetermined threshold value, wherein said set of predetermined feature profiles comprises predetermined spectrum feature profiles defined by a number and frequency of frequency components exceeding said threshold. The allowability, at least in part, resides in these facts.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHARLES R KASENGE whose telephone number is (571)272-3743. The examiner can normally be reached Monday - Friday 7:30am to 4pm EST.
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CK
January 23, 2026
/CHARLES R KASENGE/Primary Examiner, Art Unit 2116
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