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 .
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 – 4, 9 – 15, and 19 – 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Huseynov (US 2015/0204725 A1; cited in the IDS filed on 12/02/2025).
With respect to independent claim 1, Huseynov teaches in Fig. 2 a system comprising:
at least one flame detector 2 configured to detect one or more radiations within a field of view (FOV) see paragraph [0024] and convert into one or more analog to digital converted (ADC) signals via ADC 4;
and at least one processor 6 operationally coupled to the at least one flame detector, the at least one processor is configured to:
receive the one or more ADC signals from the at least one flame detector as shown in Fig. 1;
determine a plurality of characteristics in paragraph [0029] from the one or more ADC signals,
wherein the plurality of characteristics comprises at least one of statistical features, frequency-based features “Joint Time-Frequency Analysis” as disclosed in paragraph [0036], or time-based features “Joint Time-Frequency Analysis” as disclosed in paragraph [0036]; and,
determine as disclosed in paragraph [0036] whether the one or more ADC signals are indicative of a fire, a friendly flame, or a reflection of a friendly flame based at least on the plurality of characteristics using a trained machine learning (ML) model.
With respect to dependent claim 2, Huseynov teaches in paragraphs [0047 – 0048] wherein the at least one processor is configured to train the ML model based at least on the plurality of characteristics extracted from the one or more ADC signals over a period of time.
With respect to dependent claim 3, Huseynov teaches in paragraph [0047-0048] training ANN and in paragraph [0034] teaches determining real flame event, and therefore, Huseynov should have the limitation of “wherein the at least one processor is configured to deploy the trained ML model for determining the fire, the friendly flame, or the reflection of the friendly flame.”
With respect to dependent claim 4, Huseynov teaches wherein the at least one flame detector comprises at least one of infrared (IR) sensors in paragraph [0016], photodiodes, or a combination of the IR sensors and the photodiodes.
With respect to dependent claim 9, Huseynov teaches in paragraphs [0047 – 0048] wherein the trained ML model comprises aggregated simulation of a plurality of models that are trained by the at least one processor over a period of time.
With respect to dependent claim 10, Huseynov teaches in Fig. 1 (Alarm relay 23) wherein the at least one processor is configured to: generate a signal in response to a determination that the one or more ADC signals are indicative of a fire; and transmit the signal to a communication device for alerting a user.
With respect to independent claim 11, as discussed above in the rejection justification to claim 1, Huseynov teaches a method comprising: receiving, via at least one processor, one or more analog to digital converter (ADC) signals from at least one flame detector; determining, via the at least one processor, a plurality of characteristics from the one or more ADC signals, wherein the plurality of characteristics comprises at least one of statistical features, frequency-based features, or time-based features; and, determining, via the at least one processor, whether the one or more ADC signals are indicative of a fire, a friendly flame, or a reflection of a friendly flame, based at least on the plurality of characteristics using a trained machine learning (ML) model.
With respect to dependent claim 12, Huseynov teaches in Fig. 1 wherein the at least one flame detector is configured to detect one or more radiations within a field of view (FOV) and convert into the one or more analog to digital converter (ADC) signals via ADC 4.
With respect to dependent claim 13, Huseynov teaches in paragraph [0047 – 0048] wherein the trained ML model is determined based at least on the plurality of characteristics extracted from the one or more ADC signals over a period of time.
With respect to dependent claim 14, as discussed above Huseynov teaches deploying, via the at least one processor, the trained ML model for determining the fire, the friendly flame, or the reflection of the friendly flame.
With respect to dependent claim 15, Huseynov teaches wherein the at least one flame detector comprises at least one of infrared (IR) sensors in paragraph [0016], photodiodes, or a combination of the IR sensors and the photodiodes.
With respect to dependent claim 19, Huseynov teaches in paragraph [0047 – 0048] wherein the trained ML model comprises aggregated simulation of a plurality of models that are trained by the at least one processor over a period of time.
With respect to dependent claim 20, Huseynov teaches in Fig. 1; see Alarm Relay23 generating, via the at least one processor, a signal in response to a determination that the one or more ADC signals are indicative of a fire; and, transmitting, via the at least one processor, the signal to a communication device for alerting a user.
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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.
Claim(s) 5 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Huseynov, and further in view of Kern (US 4,665,390; cited in the same IDS).
The teaching of Huseynov has been discussed above.
With respect to dependent claims 5 and 16, Huseynov is silent with wherein the statistical features comprises at least one of a skewness, kurtosis, or skewness and kurtosis ratio.
Kern, a pertinent art, teaches in column 3, line 43 – column 4, line 15 kurtosis statistics. In view of this, it would be obvious at the time of the claimed invention was filed to modify the teaching of Huseynov in order to analyze desired radiation collected with optical detector. This is in consistency with the Supreme Court Decision of the KSR. V. International Co.: applying a known technique to a known device (method or product) ready for improvement to yield predictable results.
Claim(s) 6 – 8 and 17 – 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Huseynov, and further in view of Castleman (US 2002/0011570 A1; cited in the same IDS).
The teaching of Huseynov has been discussed above.
With respect to dependent claim 6, Huseynov is silent with wherein the at least one processor is configured to detect fluctuations or modulation of the plurality of characteristics determined from the one or more ADC signals to determine whether the one or more ADC signals are indicative of the fire, the friendly flame, or the reflection of the friendly flame.
Castleman, a pertinent art, teaches in paragraph [0134] the limitation of claim 6. In view of this, it would be obvious at the time of the claimed invention was filed to modify the teaching of Huseynov in order to better determine whether a fire is occurring. This is in consistency with the Supreme Court Decision of the KSR. V. International Co.: applying a known technique to a known device (method or product) ready for improvement to yield predictable results.
With respect to dependent claims 7 – 8 and 17 – 18, Castleman teaches in paragraphs [0136 – 0137] wherein the at least one processor is configured to extract the plurality of characteristics within a low frequency range and a high frequency range of the fire, the friendly flame, and the reflection of the friendly flame and wherein the low frequency range defines a range between 2-9 Hz and 11-15Hz and the high frequency range defines frequencies higher than 15Hz.
Conclusion
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KIHO KIM, Ph.D.
Primary Examiner
Art Unit 2884
/Kiho Kim/Primary Examiner, Art Unit 2884
