DETAILED ACTION
This Office action is in response to the communication filed on 10/16/2025.
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
2. Applicant’s amendments filed 10/16/2025 to the abstract of specification and claims are accepted and entered. In this amendment:
Claims 1, 11, 17, and 20 have been amended.
Claims 1-20 have been examined.
Response to Argument
3. Applicant’s arguments filed on 10/16/2025:
Regarding the objections to the claims, the arguments have been fully considered. In view of the amendments to the claims addressing the informalities raised in the previous office action, the objections to the claims have been withdrawn
The arguments of the 101 rejection are not persuasive for the reason below:
Applicant argues that the claim as a whole integrates the exception into a practical
application. For example, the claimed subject matter may integrate the judicial exception into a practical application by demonstrating that it improves the
relevant existing technology. As claim 1 recite limitations providing improvement to the relevant existing technology, claim 1 integrates the alleged judicial exception into a practical application, and therefore, recites patent-eligible subject matter. Claim 17, also recites patent-eligible subject matter for at least the same reasons as claim 1.
In response, the Examiner respectfully disagrees. The abstract idea recited in
claims 1 and 17 include “select a control factor for determining impacts and a level of the control factor by using a ratio between effective impacts and ineffective impacts and a standard deviation of impact detection values for same impacts, wherein the ratio and the standard deviation are calculated; determine that the vehicle impact was not detected using the control factor, and control the built-in cam in response to determining that the vehicle impact was not detected.” The additional elements of “improving an impact detecting performance of a built-in cam”, “a processor”, “data obtained from a sensor for vehicle impact detection”, “store image data” and “a storage configured to store data and algorithms driven by the processor” refer to a field of use, extra-solution activities (e.g., data gathering), and generic computer elements (i.e., processor, storage) used for mere computer implementation (e.g., storing). According, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to the abstract idea and thus, they do not provide improvement to the relevant existing technology.
Applicant’s arguments regarding the prior art have been fully considered but they
are moot in view of new ground of rejection as necessitated by the amendments.
Claim Rejections - 35 USC § 101
4. 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.
5. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
Under Step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance, the claims are directed to an apparatus and process (claims 1 and 17) which are statutory categories.
However, evaluating claims 1 and 17, under Step 2A, Prong One, the claims are directed to the judicial exception of an abstract idea using the groupings of mental processes and mathematical concepts including “select a control factor for determining impacts and a level of the control factor by using a ratio between effective impacts and ineffective impacts and a standard deviation of impact detection values for same impacts, wherein the ratio and the standard deviation are calculated by using data obtained from a sensor for vehicle impact detection”; and grouping of mental process including “determining that the vehicle impact was not detected using the control factor, and control the built-in cam to store image data in response to determining that the vehicle impact was not detected.”
Next, Step 2A, Prong Two evaluates whether additional elements of the claim “integrate the abstract idea into a practical application” in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. The additional limitations of “a storage to store data” (claim 1) and “acquiring data from a sensor” (claim 17) are data gathering and/or storing data, which are forms of insignificant extra-solution activities. In addition, data obtained from a generic sensor, and using a processor/storage which are generic computer components to acquire data and/or store data that is recited at a high level of generality, and adding a field of use (e.g., impact detecting performance of a built-in cam), do not integrate the judicial exception into a practical application. The claims do not recite additional elements that integrate the judicial exception into a practical application because the additional elements recited in the claims do not impose any meaningful limits on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
At Step 2B, consideration is given to additional elements that may make the abstract idea significantly more. Under Step 2B, there are no additional elements that make the claims significantly more than the abstract idea.
The additional limitations as recited above in step 2A - Prong Two, are considered insignificant extra-solution activities, mere computer implementation using generic computer elements and/or a field of use, which do not provide significantly more under Step 2B.
Dependent claims 2-16 and 18-20 do not integrate the claims into a practical application or amount to "significant more" because they merely add details to the algorithm which forms the abstract idea and/or include additional limitations that are insignificant extra-solution activities, mere computer implementation using generic computer elements and/or a field of use. Thus, the dependent claims are ineligible.
Claim Rejections - 35 USC § 103
8. The following is a quotation under AIA of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action.
A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
9. Claims 1-3 and 17-18 are rejected under 35 U.S.C. 103 as being obvious over US 2021/0284091 of Balasubramanian et al. hereinafter “Balasubramanian” (of record) in view of US patent 10853882 of Leise et al. hereinafter “Leise” (of record).
As per Claims 1 and 17, Balasubramanian teaches an apparatus and a method for improving an impact detecting performance of a built-in cam comprising:
a processor configured to select a control factor for determining impacts and a level of the control factor by using a ratio between effective impacts and ineffective impacts (collision crash discrimination metrics detect the crash, see abstract, [0110], Fig 5 shows a severity metric 300 includes a number of severity levels considered “control factor”, block 310 severity min considered ineffective impact and severity max considered effective impact, the severity levels (i.e., levels 0-3) is considered ratios, especially when measuring the impact, see [0079]-[0088]) and a standard deviation of impact detection values for same impacts (detect occurrence of various magnitudes dictated by speed considered “detection impact values for same impacts”, variety of factor/ occurrence of crash considered standard deviation, see [0101]- [0102]),
wherein the ratio (level impact) and the standard deviation are calculated by using data obtained from a sensor for vehicle impact detection (Fig 8A shows measuring relative velocity and displacement resulting from the impact [0098], Fig 8B shows calculating level impact and relative velocity of object [0108], [0111]-[0119], the active safety sensors provide data, see [0050], [0053]);
determining that the vehicle impact was not detected using the control factor (severity minimum level 0 considered was not detected using control factor, see [0080], [0085]), and
a storage configured to store data and algorithms driven by the processor (Fig 6: airbag control unit “ACU” detects vehicle impact [0045], [0043]. It is noted ACU includes a microprocessor and a storage component, i.e., EEPROM).
Balasubramanian does not explicitly teach controlling the build-in-cam to store image data in response to determining that the vehicle impact was not detected.
Leise teaches controlling the build-in-cam to store image data in response to determining that the vehicle impact was not detected (storing fault allocation data, col 6 lines 2-31, the set of video image is combined of the impact characteristics of vehicle crash, i.e., at fault or not fault, see col 1 lines 43-67, i.e., a compilation that displays a sequence of events leading up to, during and immediately after vehicle crash meaning images captured at fault and at “no fault” drivers, “no fault” considered vehicle impact was not detected, col 22 lines 12-24, col 20 lines 46-51, col 19 lines 36-40).
It would have been obvious to one ordinary skill in the art before the effective filing date of claimed invention to modify the teaching of Balasubramanian to control the built-in-cam to store image data in response to determining that the vehicle impact was not detected as taught by Leise in order to allow for a complete representation of the scene of a vehicle crash from multiple captured images and increase the accuracy in determining faults (Leise, col 2 lines14-18).
As per Claims 2 and 18, Balasubramanian in view of Leise teaches the apparatus and method for improving an impact detecting performance of a built-in cam of claims 1 and 17, Balasubramanian teaches wherein the processor is further configured to select the control factor and the level of the control factor by using a the-larger-the-better characteristic indicating a better characteristic as the ratio between the effective impacts and the ineffective impacts is larger and a the-smaller-the-better characteristic indicating a better characteristic as the standard deviation of the impact detection values for the same impacts is smaller (relative speed considered characteristic of motion, Fig 7B shows, i.e., high/low speed. It is noted a higher speed considered a severity level impact when vehicle crash occurs. Variety of factor/ occurrence of crash consider standard deviation, see [0101]- [0102]).
As per Claim 3, Balasubramanian in view of Leise teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 1, Balasubramanian teaches wherein the processor is further configured to process the data to calculate processing data for each combination of a plurality of control factors (see [0079]-[0088], i.e., Fig 5: a combination of relative velocity 310).
10. Claim 4 is rejected under 35 U.S.C. 103 as being obvious over Balasubramanian in view of Leise and US 2019/0126874 of Panigrahi et al “Panigrahi” (of record).
As per Claim 4, Balasubramanian in view of Leise teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 3, Balasubramanian teaches wherein the processor is further configured to obtain an average of hitting values for each hitting point and hitting angle (moving average considered “calculates the average value of a set of data points over a specific a period”, the average values considered “average of hitting values”, data points considered “hitting points” [0099]. As it is known a collision at specific hitting point does have a hitting angle), a standard deviation of hitting values for each hitting point and hitting angle by applying each level of the control factors (Fig 5 shows object relative velocity 310 “standard deviation” for each severity level, object longitudinal distance considered “impact location or hitting point” [0079]-[0089]). Balasubramanian does not explicitly teach number of hitting points. Panigrahi teaches number of hitting points (detect impact locations considered “hitting points” [0036], [0063], [0067]). It would have been obvious to one ordinary skill in the art before the effective filing date of claimed invention to modify the teachings of Balasubramanian and Leise to include a number of impact locations as taught by Panigrahi that would facilitate to improve the accuracy of collision severity determination.
11. Claims 5-10 are rejected under 35 U.S.C. 103 as being obvious over Balasubramanian in view of Leise, Panigrahi and US patent 6186539 of Foo et al., “Foo” (of record).
As per Claim 5, Balasubramanian in view of Leise and Panigrahi teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 4, Balasubramanian in view of Leise and Panigrahi does not teach wherein the processor is further configured to calculate an average value of the effective impacts and an average value of the ineffective impacts based on the processing data for each level combination of the control factors, to calculate a ratio between the average value of the effective impacts and the average value of the ineffective impacts. Foo teaches calculating an average value of the effective impacts and an average value of the ineffective impacts based on the processing data for each level combination of the control factors, to calculate a ratio between the average value of the effective impacts and the average value of the ineffective impacts (Figs 9-10 show low threshold belted meaning “impact occurring at low speed” considered “ineffective impact” and high threshold unbelted meaning “impact occurring at high speed” considered “effective impact”. Fig 12D shows determining moving average 602-604, 608-610 considered “average ineffective impact value” and moving average 628 yes considered “average effective impact value”, see col 26 line 65 to col 27 lines 45). It would have been obvious to one ordinary skill in the art before the effective filing date of claimed invention to modify the teachings of Balasubramanian, Leise, and Panigrahi to determine average values of high impact and low impact as taught by Foo that would facilitate to improve the accuracy of collision severity determination.
As per Claim 6, Balasubramanian in view of Leise, Panigrahi and Foo teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 5, Balasubramanian teaches wherein the processor is further configured to use the average of the hitting value for each hitting point and hitting angle and for each level combination of the control factors (Fig 6 shows 330, 340, 344 considered “control factors”), to calculate the ratio between the average value of the effective impacts and the average value of the ineffective impacts (moving average 342, 346 are determined [0099], Fig 7A shows high impact magnitude [0103]-[0104] and Fig 7B shows low impact magnitude events [0105]). Balasubramanian does not explicitly teach number of hitting points. Panigrahi teaches number of hitting points (detect impact locations considered “hitting points” [0036], [0063], [0067] as stated in claim 4). It would have been obvious to one ordinary skill in the art before the effective filing date of claimed invention to modify the teachings of Balasubramanian and Leise to include a number of impact locations as taught by Panigrahi that would facilitate to improve the accuracy of collision severity determination.
As per Claim 7, Balasubramanian in view of Leise, Panigrahi, and Foo teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 5, Balasubramanian teaches wherein the processor is further configured to select a level of the calculated control factors for which a largest value among ratios of the average value of the effective impacts and the average value of the ineffective impacts is calculated for each level combination of the control factors (as stated in claim 1, level impact considered ratios, select a threshold implemented in crash discrimination metrics in response to detecting the object, see Abstract, [0019]. Threshold metrics considered low and high level impacts, and object detection can be a control factor).
As per Claim 8, Balasubramanian in view of Leise, Panigrahi and Foo teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 5, Balasubramanian teaches wherein the processor is further configured to calculate a standard deviation of impact detection values for the same impacts based on the processing data for each level combination of the control factors (Fig 5 shows object relative velocity 300 considered “standard deviation” is calculated based on severity level 310 “control factors”. It is noted a high severity level is considered to have a high impact and inversely, lower severity levels have a lower impact).
As per Claim 9, Balasubramanian in view of Leise, Panigrahi and Foo teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 8, Balasubramanian teaches wherein the processor is further configured to use the standard deviation for each level combination of the control factors, to calculate the standard deviation of the impact detection values for the same impacts (as stated in claim 8). Balasubramanian does not teach the number of hitting points for each hitting point and hitting angle. Panigrahi teaches the number of hitting points for each hitting point and hitting angle (detect impact locations considered “hitting points” [0036], [0063], [0067]. As it is known a collision at specific hitting point does have a hitting angle). It would have been obvious to one ordinary skill in the art before the effective filing date of claimed invention to modify the teachings of Balasubramanian, Leise, Panigrahi, and Foo including number of impact locations and impact angle that would facilitate to improve the accuracy of collision severity determination).
As per Claim 10, Balasubramanian in view of Leise, Panigrahi and Foo teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 8, Balasubramanian teaches wherein the processor is further configured to select a control factor for which a smallest value among standard deviations of the impact detection values for the same impacts for each level combination of the control factors is calculated and a level of the calculated control factor (Fig 5 shows object relative velocity 300 considered “standard deviation” and the severity min “low impact” is selected first for each level “control factor” and outputted as the preset severity flag 192 considered same severity levels or impacts [0079]-[0088]).
12. Claims 13-14 are rejected under 35 U.S.C. 103 as being obvious over Balasubramanian in view of Leise, Panigrahi and Sakai, US 2008/0004855 (of record).
As per Claim 13, Balasubramanian in view of Leise and Panigrahi teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 4, Balasubramanian teaches wherein the processor is further configured to: generate for each level of control factors (“severity levels” as shown in Fig 5). Balasubramanian does not teach generating an orthogonal table for each level of the control factors, and generate an orthogonal table comprising numbers of cases as many as a number of levels multiplied by a number of control factors. Sakai teaches generating an orthogonal table for each level of the control factors, and generate an orthogonal table comprising numbers of cases as many as a number of levels multiplied by a number of control factors (Fig 8 shows orthogonal table showing control factors and level values [0059]). It would have been obvious to one ordinary skill in the art before the effective filing date of claimed invention to modify the teachings of Balasubramanian, Leise, and Panigrahi having an orthogonal table and displaying control factor and level values as taught by Sakai that would facilitate showing a convenience quality engineering analysis when involving a large number (Sakai [0006]).
As per Claim 14, Balasubramanian in view of Leise, Panigrahi and Sakai teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 13, Balasubramanian teaches wherein the processor is further configured to calculate the ratio between the effective impacts and the ineffective impacts for each of the numbers of cases and the standard deviation of the impact detection values for the same impacts (Fig 5: block 310 severity min considered ineffective impact and severity max considered effective impact, see [0079]-[0088] the severity levels (i.e., levels 0-3) can consider ratios when measuring the impact).
13. Claim 15 is rejected under 35 U.S.C. 103 as being obvious over Balasubramanian in view of Leise and further JP 3055361B2 of Miyamori (of record).
As per Claim 15, Balasubramanian in view of Leise teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 1, Balasubramanian teaches wherein the control factor comprises a noise filter (Fig 6 shows low-pass/high-pass filter 332, 334, [0097]-[0098]. It is noted low-pass/high-pass filter is a noise filter). Balasubramanian does not explicitly teach integration of an impact amount, an impact amount sampling period, and a previous impact amount reference period. Miyamori teaches integration of an impact amount (considered interval integration value of impact amount, page 10 paras 1-2), an impact amount sampling period (last two paras of page 7), and a previous impact amount reference period (the relatively slow collision considered a previous impact amount, page 5, [0002], a relatively long period of time considered reference period, page 6, para 2 of [0007]). It would have been obvious to one ordinary skill in the art before the effective filing date of claimed invention to modify the teachings of Balasubramanian and Leise having filter as a noise filter, impact amount and reference period as taught by Miyamori that would facilitate to improve the collision determination accuracy (Miyamori, page 5 last para and page 6, para 1).
14. Claim 16 is rejected under 35 U.S.C. 103 as being obvious over Balasubramanian in view of Leise and further US patent 6703804 of Courdier et al. “Courdier” (of record).
As per Claim 16, Balasubramanian in view of Leise teaches the apparatus for improving an impact detecting performance of a built-in cam of claim 1, Balasubramanian does not teach wherein the processor is further configured whether an engine is started, or a wiper is operated to select the control factor and a level of the control factor. Courdier teaches a wiper is operated to select the control factor and a level of the control factor (col 3 lines 14-15, Claim 22. It is noted a control device of a motor vehicle wiper motor is considered a control factor. In addition, a rotor position in a motor control system considered a control factor level. It would have been obvious to one ordinary skill in the art before the effective filing date of claimed invention to modify the teachings of Balasubramanian and Leise having a wiper operating as taught by Courdier that would facilitate a rotor position in a motor control system.
15. Claim 19 is rejected under 35 U.S.C. 103 as being obvious over Balasubramanian in view of Leise and Foo.
As per Claim 19, Balasubramanian in view of Leise teaches the improving method of claim 17, wherein the selecting of the control factor for determining the impacts and the level of the control factor comprises:
processing the data to calculate processing data for each combination of a plurality of control factors (see [0079]-[0088], i.e., Fig 5: a combination of relative velocity 310); and
selecting a control factor and a level of the control factor for which a largest value among ratios of the average value of the effective impacts and the average value of the ineffective impacts is calculated for each level combination of the control factors (as stated in claim 17, level impact considered ratios, select a threshold implemented in crash discrimination metrics in response to detecting the object, see Abstract, [0019]. Threshold metrics considered low and high level impacts, and object detection can be a control factor).
Balasubramanian in view of Leise does not teach calculating an average value of the effective impacts and an average value of the ineffective impacts based on processing data for each level combination of the control factors, to calculate a ratio between the average value of the effective impacts and the average value of the ineffective impacts. Foo teaches calculating an average value of the effective impacts and an average value of the ineffective impacts based on the processing data for each level combination of the control factors, to calculate a ratio between the average value of the effective impacts and the average value of the ineffective impacts (Figs 9-10 show low threshold belted meaning “impact occurring at low speed” considered “ineffective impact” and high threshold unbelted meaning “impact occurring at high speed” considered “effective impact”. Fig 12D shows determining moving average 602-604, 608-610 considered “average ineffective impact value” and moving average 628 yes considered “average effective impact value”, see col 26 line 65 to col 27 lines 45). It would have been obvious to one ordinary skill in the art before the effective filing date of claimed invention to modify the teachings of Balasubramanian and Leise, to determine average values of high impact and low impact as taught by Foo that would facilitate to improve the accuracy of collision severity determination.
Examiner’s Note
16. Claims 11-12 and 20 are considered novel and non-obvious subject matter with respect to the prior art, but as currently present are rejected under 35 U.S.C. § 101 and 112 as set forth in this Office action.
The following is an examiner's statement of claims distinguished over the prior art:
The prior art of record in individual or in combination does not teach or suggest
“calculating an average change amount of n output values for each control factor depending on a combination of a number of the control factors and a number of levels,
and determining that a control factor with an average change amount for each of the control factors that is greater than or equal to a predetermined reference value has a large effect on impact detection, and selecting a control factor with the average change amount that is equal to or greater than the predetermined reference value” as recited in claim 11 and 20.
Conclusion
17. Applicant's amendment necessitated the new ground 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 extension fee 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.
18. Any inquiry concerning this communication or earlier communications from the
examiner should be directed to LYNDA DINH whose telephone number is (571) 270-
7150. The examiner can normally be reached on M-F: 10 AM -6 PM ET.
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/LYNDA DINH/Examiner, Art Unit 2857
/LINA CORDERO/Primary Examiner, Art Unit 2857
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