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 Status
Claims 1-23 are pending for examination in the Application No. 18/801,939 filed August 13th, 2024.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed as foreign Patent Application No. TW112130429, filed on August 14th, 2023.
Claim Objections
Claims 1, 3-4, 6, 10, 12, 14, 17 and 21 are objected to because of the following informalities failing to comply with 37 CFR 1.71(a) for "full, clear, concise, and exact terms" (see MPEP § 608.01(m)):
In claims 1 and 12, the examiner respectfully suggests amending the phrases “each of the plurality of traffic videos” and “each of the traffic videos” to recite “each [[of]]traffic video in the plurality of traffic videos” and “each [[of]]traffic video in the plurality of traffic videos”, respectively, to prevent confusion whether the term “each” recited in each of these phrases refers to each group of traffic videos (i.e., “plurality of traffic videos”) or to each singular traffic video in the “plurality of traffic videos”;
In claims 1, 4, 10-12, 15, 21, and 22, the examiner respectfully suggests amending any limitations comprising the phrase “so as to…” to no longer recited intended use/result language to clarify that the functional limitations following this phrase are functional requirements of the claim;
In claims 1, 3, 12, and 14, the examiner respectfully suggests amending the phrase “one of the traffic videos” to recite “one [[of]]traffic video in the plurality of traffic videos” to maintain consistency in terminology within the claim(s);
In claims 1, 3, 12, and 14, the examiner respectfully suggests amending the phrase “one of the traffic videos” to recite “one [[of]]traffic video in the plurality of traffic videos” to maintain consistency in terminology within the claim(s);
In claim 4, the examiner respectfully suggests amending the phrase “the potential factors” to recite “the plurality of potential factors” to prevent confusion with the alert previously recited in step h) of the claim;
In claims 6 and 17, the examiner respectfully suggests amending any limitations comprising the phrases “for outputting…”, “for capturing…”, and “for enabling” to no longer recited intended use/result language to clarify that the functional limitations following this phrase are functional requirements of the claim;
In step f) of claim 6 and lines 1-2 of claim 7, the examiner respectfully suggests amending the phrase “the potential factors of the traffic video” to recite “the potential factors [[of]]associated with the traffic video” to maintain consistency in terminology within the claim(s);
In step k) of claim 6, the examiner respectfully suggests amending the phrase “output the alert” to recite “output the another alert” to prevent confusion with the alert previously recited in step h) of the claim;
In the 2nd to last line of claim 17, the examiner respectfully suggests amending the phrase “output the alert” to recite “output the another alert” to prevent confusion with the alert generated in the case that it is determined a factor related to a vehicle presented in the traffic video is included in both the potential factors and the one of the aggregated factor groups previously recited in the claim; and
In claims 10 and 21, the phrase “one or more of: …; and…” is interpreted as disjunctive consisted with paragraphs [0044] and [0061] of Applicant’s instant Specification, and thus the examiner respectfully suggests amending the phrase “one or more of: …; and…” to recite “one or more of: …; [[and]]or…” to clarify this interpretation as not being conjunctive as currently recited in the claim (i.e., the plain and ordinary meaning of ‘one or more of X and y’ is ‘one or more of X and one or more of Y’—see Superguide Corp. v. Direct TV Enterprises, Inc., 358 F.3d 870, 69 USPQ2d 1865 (Fed. Cir. 2004)).
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier, as explained in MPEP § 2181, subsection I (note that the list of generic placeholders below is not exhaustive, and other generic placeholders may invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph):
A. The Claim Limitation Uses the Term "Means" or "Step" or a Generic Placeholder (A Term That Is Simply A Substitute for "Means")
With respect to the first prong of this analysis, a claim element that does not include the term "means" or "step" triggers a rebuttable presumption that 35 U.S.C. 112(f) does not apply. When the claim limitation does not use the term "means," examiners should determine whether the presumption that 35 U.S.C. 112(f) does not apply is overcome. The presumption may be overcome if the claim limitation uses a generic placeholder (a term that is simply a substitute for the term "means"). The following is a list of non-structural generic placeholders that may invoke 35 U.S.C. 112(f): "mechanism for," "module for," "device for," "unit for," "component for," "element for," "member for," "apparatus for," "machine for," or "system for." Welker Bearing Co., v. PHD, Inc., 550 F.3d 1090, 1096, 89 USPQ2d 1289, 1293-94 (Fed. Cir. 2008); Mass. Inst. of Tech. v. Abacus Software, 462 F.3d 1344, 1354, 80 USPQ2d 1225, 1228 (Fed. Cir. 2006); Personalized Media, 161 F.3d at 704, 48 USPQ2d at 1886–87; Mas-Hamilton Group v. LaGard, Inc., 156 F.3d 1206, 1214-1215, 48 USPQ2d 1010, 1017 (Fed. Cir. 1998). Note that there is no fixed list of generic placeholders that always result in 35 U.S.C. 112(f) interpretation, and likewise there is no fixed list of words that always avoid 35 U.S.C. 112(f) interpretation. Every case will turn on its own unique set of facts.
Such claim limitation(s) is/are:
"alert device for outputting an alert…" in claims 6 and 17 described in para. [0069], [0079], [0084], and [0089].
Regarding claim limitation A above, the originally filed disclosure provides insufficient structure, material, or acts for performing the claimed function and, thus, do not have support under 35 U.S.C. § 112 (a) and (b) (see analysis under “Claim Rejections - 35 USC § 112” below).
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the second paragraph of subsection IV of MPEP § 2181:
IV. DETERMINING WHETHER 35 U.S.C. 112(a) or PRE-AIA 35 U.S.C. 112, FIRST PARAGRAPH SUPPORT EXISTS
When a claim containing a computer-implemented 35 U.S.C. 112(f) claim limitation is found to be indefinite under 35 U.S.C. 112(b) for failure to disclose sufficient corresponding structure (e.g., the computer and the algorithm) in the specification that performs the entire claimed function, it will also lack written description under section 112(a). See MPEP § 2163.03, subsection VI. Examiners should further consider whether the disclosure contains sufficient information regarding the subject matter of the claims as to enable one skilled in the pertinent art to make and use the full scope of the claimed invention in compliance with the enablement requirement of section 112(a). See MPEP § 2161.01, subsection III, and MPEP § 2164.08.
Claims 6-9 and 17-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. Claims 6 and 17 invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, by reciting the claim limitation “alert device”, (see analysis in § 112 (f) “Claim Interpretations” above). These claims are found to be indefinite under 35 U.S.C. 112(b), based on failure of the specification to clearly link structure capable of performing the recited function (see analysis in § 112 (b) below). Claims that are found to be indefinite under 35 U.S.C. 112(b), based on failure of the specification to describe and/or clearly link structure capable of performing the recited function, also lacks adequate written description under 35 U.S.C. 112(a) (see subsection IV of MPEP § 2181). Therefore, these claims lack an adequate written description and are rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph. Claim(s) 7-9 and 18-20, which is/are similarly interpreted, do not resolve or clarify this/these issue(s) is/are similarly rejected under 35 U.S.C. 112(a) for the same reasons as above in view of their dependency to these claims.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
The following is a quotation of subsection II.A. of MPEP § 2181:
A. The Corresponding Structure Must Be Disclosed In the Specification Itself in a Way That One Skilled In the Art Will Understand What Structure Will Perform the Recited Function
The proper test for meeting the definiteness requirement is that the corresponding structure (or material or acts) of a means- (or step-) plus-function limitation must be disclosed in the specification itself in a way that one skilled in the art will understand what structure (or material or acts) will perform the recited function. See Atmel Corp. v. Information Storage Devices, Inc., 198 F.3d 1374, 1381, 53 USPQ2d 1225, 1230 (Fed. Cir. 1999).
Claims 6-9, 12, and 17-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claims 6-9 and 17-20, claims 6 and 17 recite the claim limitation “alert device”, which invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (see analysis in § 112(f) “Claim Interpretations” above). However, the written description fails to contain sufficient information regarding the subject matter of the claim(s) as to enable one skilled in the pertinent art to make and use the full scope of the claimed invention, the specification fails to set forth the corresponding structure, material, or acts in compliance with 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph, and the claim limitation(s) cannot "be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof” (see subsection II.A. of MPEP § 2181). As seen in the limitation(s) listed in § 112 (f) “Claim Interpretations” above, the disclosure merely describes the function(s) of this/these limitation(s). Claim(s) 7-9 and 18-20, which is/are similarly interpreted, do not resolve or clarify this/these issue(s) and, thus, is/are similarly rejected under 35 U.S.C. 112(b) for the same reasons as above.
Regarding claim(s) 12, the limitation “the first factoring data including information associated with one of a vehicle, a pedestrian, a traffic sign and combinations thereof” in lines 13-15 of the claim renders the claim indefinite because it is unclear whether the limitation requires one of each of a “vehicle”, “pedestrian”, “traffic sign”, and “combinations thereof” or only one of the listed elements. The plain and ordinary meaning of this claim limitation is interpreted as conjunctive (i.e., ‘one of a vehicle, at least one of a pedestrian, one of a traffic sign, and one of combinations thereof’). See Superguide Corp. v. Direct TV Enterprises, Inc., 358 F.3d 870, 69 USPQ2d 1865 (Fed. Cir. 2004). For examination purposes, the limitation will be read as disjunctive (i.e., “the first factoring data including information associated with one of a vehicle, a pedestrian, a traffic sign [[and]]or combinations thereof”. Furthermore, claims 13-22 inherit this insufficient antecedent basis in view of their dependency to the claim.
Regarding claim(s) 6, the phrase “in the case that a result of the determination of step g) is affirmative” in step h) of the claim renders the claim indefinite because it is unclear whether the phrase is referring to a result of the determination of “whether a factor related to the vehicle presented in the traffic video is included in both the potential factors and the one of the aggregated groups” or “that the operation is to be initiated” recited in step g) of the claim. The examiner notes that this claim recites similar subject matter to claim 17. Therefore, for examination purposes, the phrase “in the case that a result of the determination of step g) is affirmative” in this claim will be read as “in the case that[[ a result of]] the determination of step g) that a factor related to the vehicle presented in the traffic video is included in both the potential factors and the one of the aggregated groups is affirmative”. Furthermore, claims 7-9 inherit this insufficient antecedent basis in view of their dependency to the claim.
Regarding claim(s) 6, the phrase “the potential factors” in step g) of the claim renders the claim indefinite because it is unclear whether the phrase is referring to the “potential factors associated with the traffic video” recited in step f) of claim 6 or the “plurality of potential factors associated with a potential traffic accident” recited in claim 4. For examination purposes, this phrase will be read as “the potential factors associated with the traffic video”. Furthermore, claims 7-9 inherit this insufficient antecedent basis in view of their dependency to the claim.
Regarding claim(s) 8, the phrase “in the case that the result of the determination of step j) is negative” in step l) of the claim renders the claim indefinite because it is unclear whether the phrase is referring to the result of the determination of “whether the factor related to the vehicle is still included in both the potential factors and the one of the aggregated factor groups” or “that the monitoring operation is to be continued” recited in step j) of claim 6. The examiner notes that this claim recites similar subject matter to claim 19. Therefore, for examination purposes, the phrase “in the case that the result of the determination of step j) is affirmative” in this claim will be read as “in the case that[[ the result of the determination]]it is determined [[of]]in step j) [[is negative]]that the monitoring operation is not to be continued”. Furthermore, claim 9 inherits this insufficient antecedent basis in view of its dependency to the claim.
Regarding claim(s) 8, the phrase “in the case that the determination of step l) is negative” in step m) of the claim renders the claim indefinite because it is unclear whether the phrase is referring to the determination of “whether the accumulating number has reached a predetermined number” or “the result of the determination of step j)” recited in step l) of the claim. The examiner notes that this claim recites similar subject matter to claim 19. Therefore, for examination purposes, the phrase “in the case that the determination of step l) is negative” in this claim will be read as “in the case that[[ the determination]]it is determined [[of]]in step l) [[is negative]]that the accumulating number has not reached a predetermined number”. Furthermore, claim 9 inherits this insufficient antecedent basis in view of its dependency to the claim.
Regarding claim(s) 9, the phrase “in the case that the result of the determination of step j) is affirmative” in step k) of the claim renders the claim indefinite because it is unclear whether the phrase is referring to the result of the determination of “whether the factor related to the vehicle is still included in both the potential factors and the one of the aggregated groups” or “that the monitoring operation is to be continued” recited in step j) of claim 6. The examiner notes that this claim recites similar subject matter to claim 20. Therefore, for examination purposes, the phrase “in the case that the result of the determination of step j) is affirmative” in this claim will be read as “in the case that[[ the result of the determination]]it is determined [[of]]in step j) [[is affirmative]]that the monitoring operation is to be continued”.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-3, 10, 12-14, 21, and 23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion, organizing human activity and mathematical concepts and calculations). The claim(s) recite(s) a method, a system, an apparatus, a computer-readable medium, etc... configured to X. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved .The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (i.e., processor, memory).
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1, 12, and 23 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories? YES; claim(s) 1, 12, and 23 are directed to a method (i.e., a process), a device (i.e., an apparatus), and a non-transitory computer-readable storage medium (i.e., a product of manufacture), respectively.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? YES; The claims are directed toward a mental process (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
The method in claim 1 (and the device and non-transitory computer-readable storage medium in claim(s) 12 and 23, respectively) comprise a mental process that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea.
Regarding Claim(s) 1, 12, and 23: the method recites the steps (functions) of:
a) processing… each of the plurality of traffic videos so as to determine, for each of the traffic videos, whether a traffic accident is identified therein, and in the case that a traffic accident is identified in one of the traffic videos, categorizing the traffic accident into one of a plurality of pre-determined categories (mental process including observation and evaluation, and can be done mentally in the human mind);
b) collecting,… for each of the traffic videos in which the traffic accidents are identified, first factoring data associated with the traffic accident recorded in the traffic video within an accident-related time period associated with a time instance at which the traffic accident occurred, tagging the traffic video as a traffic accident video with the one of the pre-determined categories,… the first factoring data including information associated with one of a vehicle, a pedestrian, a traffic sign and combinations thereof (mental process including observation and evaluation, and can be done mentally in the human mind);
c) processing… each of the traffic accident videos… so as to collect, for each of the traffic accident videos, second factoring data that is different from the first factoring data and that is contained in the traffic accident video within the accident-related time period…, the second factoring data including information associated with at least geographical information and weather information (mental process including observation and evaluation, and can be done mentally in the human mind);
d) compiling… a factor group for each of the traffic accident videos based on the first factoring data and the second factoring data, and aggregating the factor groups to create aggregated factor groups (mental process including observation and evaluation, and can be done mentally in the human mind);
e) creating… a spreadsheet that contains the aggregated factor groups generated in step d) and that can be sorted using geographical locations (mental process including observation and evaluation, and can be done mentally in the human mind).
These limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? NO, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claim(s) 1, 12, and 23 does/do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. Claim(s) 1, 12, and 23 recite(s) the further limitations of:
the method being implemented using a computer device that includes a processor and a data storage, the data storage storing a plurality of traffic videos (insignificant pre/post-solution extra activity of generating data; where the data is the “plurality of traffic videos”) OR (generic computer(s) or component(s) configured to perform the method; where the generic computer(s) or component(s) are the “computer device”, “processor”, and “data storage”);
…by the processor… (generic computer(s) or component(s) configured to perform the method); and
…storing the traffic accident video and the associated first factoring data in the data storage (insignificant pre/post-solution extra activity of generating and/or gathering data; where the data is the “plurality of traffic videos” and the “associated first factoring data”) OR (generic computer(s) or component(s) configured to perform the method; where the generic computer(s) or component(s) is the “data storage”).
These limitations are recited at a high level of generality (i.e. as a general action or change being taken based on the results of the acquiring step) and amounts to mere pre/post-solution actions, which is/are a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, 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.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? NO, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Claim(s) 1, 12, and 23 does/do not recite any additional elements that are not well-understood, routine or conventional. The use of a computer to process, collect, compile, store, etc., as claimed in Claim(s) 1, 12, and 23 is/are a routine, well-understood and conventional process(es) that is/are performed by computers.
Thus, since Claim(s) 1, 12, and 23 is/are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that Claim(s) 1, 12, and 23 is/are not eligible subject matter under 35 U.S.C 101.
Regarding claims 2-3, 10, 13-14, and 21: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s) recite either:
(1) a mental process including observation and evaluation, and can be done mentally in the human mind (i.e., claim(s) 5 (and similar claims 15 and 18), 9, and partial of 13 (and similar partial of claim 17) recite(s) the mental process(es) of: applying artificial intelligence, lateral scanning of received video, and performing lateral scanning, respectively);
(2) mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations (i.e., claim(s) 3 (and similar claim 14) and 10 (and similar claim 21) recite(s) the mathematical concept(s)/relationship(s)/formula(s) or equation(s)/calculation(s) of: categorizing the near traffic accident event into a fourth category in the case that a near traffic accident is identified in one of the traffic videos while not traffic accident is identified, tagging the traffic video with the fourth category as a near traffic accident video, and/or compiling a factor group for the near traffic accident video based on the first factoring data and the second factoring data; and processing each of the driver videos and determining driver data including identifying signs indicating that the driver is a state of mind-wandering, respectively);
(3) insignificant pre/post-solution extra activity of generating data (i.e., claim(s) 2 (and similar claim 13) and 3 (and similar claim 14), and 10 (and similar claim 21) recite(s) the activity/activities of generating/gathering: wherein the plurality of pre-determined categories includes a first category, in which at least one vehicle and at least one non-vehicle moving object are involved, a second category, in which at least two vehicles are involved, and a third category, in which a vehicle and a stationary object are involved; collecting first factoring data, storing the near traffic accident video and the associated first factoring data, and/or compiling a factor group for the near traffic accident video based on the first factoring data and the second factoring data; and obtaining and storing a plurality of driver videos, respectively); and/or
(4) generic computers or components configured to perform the method (i.e., claim(s) claim(s) 3 (and similar claim 14) and 11 recite(s) the generic computer(s) or component(s) of: data storage, driver monitoring system, and processor).
Claim Rejections - 35 USC § 103
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.
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 1-2, 12-13, and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Owada et al. (Owada; JP 2019004373 A) in view of Dong et al. (Dong; CN 109598929 A), and further in view of Chen et al. (Chen; CN 106448149 A).
Regarding claim 1, Owada discloses a method for automatically obtaining factors related to traffic accidents, the method being implemented using a computer device that includes a processor and a data storage (description, para(s). [0050], recite(s)
[0050] “…The event information input unit 24 may consist, for example, a wireless communication interface, a computer program that describes the operation of moving corresponding video information from temporary memory 22 to storage memory 26 based on event information input via this interface, and a CPU that executes this computer program.”
, where a “CPU” and a “storage memory” are at least a processor and a data storage, respectively), the data storage storing a plurality of traffic videos (description, para(s). [0010] and [0016], recite(s)
[0010] “The present invention was made to solve the above-mentioned problems, and its purpose is to provide a system that can provide video related to a region (area) more efficiently.”
[0016] “(6) The present invention also relates to a video information sharing device according to any one of (1) to (5), wherein the event information is information of a traffic accident event indicating that a traffic accident has occurred, and includes at least the time the traffic accident occurred and the location where the traffic accident occurred, and the event information input unit, if the input event information is traffic accident event information, retrieves video information taken within a predetermined period including the time the traffic accident occurred from the temporary memory and stores it in the storage memory.”
, where storing “video information” in the “storage memory” is storing a plurality of traffic videos into the data storage), the method comprising:
a) processing, by the processor, each of the plurality of traffic videos so as to determine, for each of the traffic videos, whether a traffic accident is identified therein, and in the case that a traffic accident is identified in one of the traffic videos, categorizing the traffic accident(description, para(s). [0016]—see citation in the preceding claim limitation above—, where determining that a “traffic event has occurred” is identifying a traffic accident in the traffic videos; and description, para(s). [0082], further recite(s) categorizing the traffic event as a “type of event”:
[0082] “…The external transmission unit 29 retrieves the relevant video information from the storage memory 26 based on the type of event, time, and location (geographic location) of the requested video information, and transmits it to the user. …”
);
b) collecting, by the processor for each of the traffic videos in which the traffic accidents are identified, first factoring data associated with the traffic accident recorded in the traffic video within an accident-related time period associated with a time instance at which the traffic accident occurred, tagging the traffic video as a traffic accident videostoring the traffic accident video and the associated first factoring data in the data storage (description, para(s). [0016]—see citation in the preceding claim limitation “…the data storage storing…” above—, where description, para(s). [0040], further recite(s):
[0040] “Traffic accident event information includes a message indicating that a traffic accident has occurred, as well as the time the accident was detected (the time the accident occurred).
Furthermore, this event information may also include the time when the user instructed the submission of the event information, as well as the location information of the traffic accident. This location information may be obtained using, for example, GPS. In addition, event information may include other information such as the time the traffic accident occurred or the time specified by the user, such as the type of vehicle, temperature, and weather.”
, where at least “event information may include other information such as the time the traffic incident occurred or the time specified by the user” is at least a first factoring data; and labeling the “video information” as a “traffic accident” is tagging the traffic video as a traffic accident video);
c) processing, by the processor, each of the traffic accident videos stored in the data storage so as to collect, for each of the traffic accident videos, second factoring data that is different from the first factoring data and that is contained in the traffic accident video within the accident-related time period (description, para(s). [0040]—see citation in the preceding claim limitation immediately above—, where the “location information” and/or “temperature, and weather” are at least second factoring data);
d) compiling, by the processor, a factor group for each of the traffic accident videos based on the first factoring data and the second factoring data (description, para(s). [0050], recite(s)
[0050] “…the event information input unit 24 may associate the event information that caused the saving with the video information to be saved and save it in the storage memory 26. In this case, event information may be included in the video information. The event information input unit 24 may consist, for example, a wireless communication interface, a computer program that describes the operation of moving corresponding video information from temporary memory 22 to storage memory 26 based on event information input via this interface, and a CPU that executes this computer program.”
, where “associat[ing] the event information that caused the saving with the video information to be saved” and saving the “event information” with the “video information” is compiling a factor group (i.e., “event information”) for each corresponding traffic video (i.e., corresponding “video information”)), and aggregating the factor groups to create aggregated factor groups (description, para(s). [0053], recite(s)
[0053] “…The processing of providing the information varies, but basically, it searches for and retrieves the corresponding video information from the storage memory 26 based on the time and location (geographic information) of the request. The external transmission unit 29 transmits the video information extracted in this manner to the user. The request may specify either time or location, or it may include other conditions. For example, the request may specify the type of event. For example, you can specify that the video footage must be of a traffic accident (traffic accident event) occurring between March 1st and March 10th. Other types of conditions may also be added.”
, where retrieving “video information” and its corresponding “event information” “based on the time and location (geographic information) of the request” and/or “[o]ther types of conditions” is at least aggregating the first and second factoring data (i.e., the “event information” corresponding to the retrieved “video information”) into aggregated factor groups (i.e., factor groups matching the retrieval condition)); and
e) creating, by the processor, a(data) that contains the aggregated factor groups generated in step d) and that can be sorted using geographical locations (description, para(s). [0050]—see preceding citation in the claim limitation immediately above—, where the retrieved “video information” comprising of associated “event information” is at least data that contains the aggregated factor groups (i.e., “video information” with associated “event information” matching the retrieval condition)).
Where Owada does not specifically disclose
in the case that a traffic accident is identified in one of the traffic videos, categorizing the traffic accident into one of a plurality of pre-determined categories;
…tagging the traffic video as a traffic accident video with the one of the pre-determined categories…; and
e) creating… a(data structure) that contains the aggregated factor groups;
Dong teaches in the same field of endeavor of obtaining factors related to traffic accidents to create aggregated factor groups
…in the case that a traffic accident is identified…, categorizing the traffic accident into one of a plurality of pre-determined categories (description, para(s). [0014-0015] and [0080], recite(s)
[0014] “S1. Extract traffic accident data, road attribute data, and traffic flow status data from traffic management departments, and obtain information on the surrounding environment of roads from relevant management departments; traffic accident data includes traffic accident categories;”
[0015] “S2. By using shared fields, traffic accident data, road attribute data, traffic flow operation status data, and environmental information are matched and linked together into a database. Shared fields include: road segment identification code;”
[0080] “Based on the objects involved in traffic accidents, they are classified into the following categories: traffic accidents between vehicles, traffic accidents between vehicles and pedestrians, traffic accidents between motor vehicles and non-motor vehicles, accidents involving the vehicles themselves, and accidents involving vehicles and fixed objects.”
, where the “traffic accident categories” of “traffic accidents between vehicles, traffic accidents between vehicles and pedestrians, traffic accidents between motor vehicles and non-motor vehicles, accidents involving the vehicles themselves, and accidents involving vehicles and fixed objects” are at least a plurality of pre-determined categories);
…tagging the traffic video as a traffic accident… with the one of the pre-determined categories… (description, para(s). [0080]—see citation in the preceding claim limitation immediately above—, where classifying the traffic videos as one of a plurality of pre-determined categories is tagging a traffic accident with one of the pre-determined categories); and
e) creating… a(data structure) that contains the aggregated factor groups (description, para(s). [0015]—see citation above—, where the “database” is a data structure that contains aggregated factor groups (i.e., “traffic accident data” comprising of “shared fields”)).
Since Owada discloses categorizing the traffic accident as a type of traffic event (e.g., para(s). [0082]—see citation in step a) of claim 1), it would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Owada to incorporate categorizing the traffic accident into one of a plurality of pre-determined categories in the case that a traffic accident is identified in one of the traffic videos and tagging the traffic video as a traffic accident video to improve the aggregation of factor groups by further include accident types as an event type as taught by Dong above.
Where Owada in view of Dong does not specifically disclose
e) creating… a spreadsheet… that can be sorted using geographical locations;
Chen teaches in the same field of endeavor of sorting traffic accident data
e) creating… a spreadsheet… that can be sorted using geographical locations (description, para(s). [0080], [0119], and [0121], recite(s)
[0080] “…It involves basic processing techniques in Excel such as filtering, comparison, and pivot tables, as well as statistical data analysis methods in SPSS such as χ²NER34 test, cluster analysis, Spearman's rank correlation test, curve estimation, and decision tree model;”
[0119] “S4. Environmental variable characteristic analysis: Using the K-center clustering method, based on the proportion of accident types occurring on road segments, the clustering results of urban road segments are obtained; using statistical methods, the distribution of accident occurrence time, weather, and vehicle color in the accident occurrence rate is obtained”
[0121] “For the accident location cluster analysis in step S4, after statistically analyzing the accident types occurring in high-incidence areas using EXCEL, locations with ≥20 accidents were selected; based on the proportion of accident types occurring at these locations, cluster analysis was performed, and the results are shown in Table 7.”
, where the “accident location cluster analysis” using “EXCEL” is sorting (e.g., “filtering”) a spreadsheet (e.g., “EXCEL”) using at least geographical locations (e.g., “accident location”)).
Since Dong teaches creating a data structure that contains aggregated factor groups (description, para(s). [0015]—see citation in the teachings of Dong above), it would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Owada in view of Dong to incorporate creating a spreadsheet that contains the aggregated factor groups generated in step d) that can be sorted using geographical locations to improve the aggregation of factor groups as taught by Chen above.
Regarding claim 2, Owada, modified by Dong and Chen, discloses the method as claimed in Claim 1, wherein Dong further teaches the plurality of pre-determined categories includes a first category, in which at least one vehicle and at least one non-vehicle moving object are involved, a second category, in which at least two vehicles are involved, and a third category, in which a vehicle and a stationary object are involved (description, para(s). [0080]—see the teaching of claim limitation “…in the case that a traffic accident is identified…, categorizing…” by Dong above).
Regarding claim 12, the claim is the computer device of claim 1 further comprising:
the first factoring data including information associated with one of a vehicle, a pedestrian, a traffic sign and combinations thereof; and
the second factoring data including information associated with at least geographical information and weather information. Owada discloses said computer device of claim 1 further comprising:
the first factoring data including information associated with one of a vehicle, a pedestrian, a traffic sign and combinations thereof (description, para(s). [0040]—see similar limitation in step b) of claim 1 above—, where at least “event information may include other information such as… type of vehicle” is at least a first factoring data associated with at least a vehicle); and
the second factoring data including information associated with at least geographical information and weather information (description, para(s). [0040]—see citation in step c) of claim 1 above—, where the “location information” and “temperature, and weather” are at least geographical and weather information). Therefore, claim 12 recites similar limitations to claim 1 and is rejected for similar rationale and reasoning (see the analysis for claim 1 above).
Regarding claim 13, the claim recites similar limitations to claim 2 and is rejected for similar rationale and reasoning (see the analysis for claim 2 above).
Regarding claim 23, the claim recites similar limitations to claim 1 but in the form of a non-transitory computer-readable storage medium. Owada discloses said non-transitory computer-readable storage medium (description, para(s). [0101], recite(s)
[0101] “…. Furthermore, since the storage memory 26 is used for long-term storage, a hard disk or flash memory is preferable. However, the temporary memory 22 and the storage memory 26 may use the same memory. The same memory can be divided into two parts, with one part designated as temporary memory 22 and the other as storage memory 26.”
, where the “storage memory” is at least a non-transitory computer-readable storage medium). Therefore, claim 23 recites similar limitations to claim 1 and is rejected for similar rationale and reasoning (see the analysis for claim 1 above).
Claims 3-5 and 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Owada, as modified by Dong and Chen as applied to claims 2 and 13 and/or 1 and 12 above, and further in view of Bai et al. (Bai; US 2017/0268896 A1).
Regarding claim 3, Owada, modified by Dong and Chen, discloses the method as claimed in Claim 2, wherein Bai teaches in the same field of endeavor of obtaining factors related to traffic accidents:
step a) further includes: in the case that a near traffic accident event is identified in one of the traffic videos while no traffic accident is identified, categorize the near traffic accident event into a fourth category (para(s). [0044] and [0104], recite(s)
[0044] “…FCW server 302 may interact with FCW database 306 to access collision event data and/or information, such as …images, videos…”
[0104] “In step 906 , to classify new event data, the comparison calculator 420 can search and analyze historical event data in collision event database 422 to determine if prior and/or historical road hazards and/or potential collision events occurred within a predetermined proximity to the vehicle 104 location. Comparison calculator 420 can compare current or new event data collected from vehicle 104 or other vehicles to prior and/or historical event data by any of the comparison or statistical methods described above. If new event data is a comparative or statistical match to one or more prior event data patterns, comparison calculator 420 may then classify new event data 906 according to one or more prior event data patterns. The method may further include step 908 , where computer system 404 may store the new and/or current event data into the collision event database 422 with the matched or correlated prior and/or historical event data.”
, where classifying “event data” as “potential collision events” is categorizing a near traffic accident into a fourth category);
step b) further includes collecting first factoring data associated with the near traffic accident event recorded in the traffic video within an event-related time period associated with a time instance at which the near traffic accident event occurred, tagging the traffic video with the fourth category as a near traffic accident video, and storing the near traffic accident video and the associated first factoring data in the data storage (para(s). [0104]—see preceding citation immediately above—, where para(s). [0056] and [0087] further recite(s):
[0056] “As further indicated above, the vehicle 104 may also include the vehicle event sensor system 434 for collecting event data. Event data can include detecting the location, orientation, heading, etc., of entities external to the vehicle 104 , such as other vehicles, bicycles, and motorcycles, pedestrians, obstacles in the roadway, traffic signals, signs, wildlife, trees, or any entity that can provide information to collision warning system 400 . …”
[0087] “The comparison calculator 420 can analyze new event data to determine a statistical match with existing, or prior, road hazard event data. In an embodiment, the comparison calculator 420 may determine a statistical match using probabilities calculated from the data. Comparison calculator 420 may further calculate statistical matches based on dates and times, road hazard characteristics, environmental conditions, traffic conditions, locations, entity headings, or any other condition or data analysis relevant for the embodiments.”
, where determining “entities” associated with the near traffic accident event is at least a first factoring data; and “stor[ing]… current event data into the collision event database” when it is determined that the near traffic accident event is classified as a “potential collision event” is storing at least the near traffic accident video and the associated first factoring data into a data storage);
step c) further includes collecting the second factoring data that is different from the first factoring data and that is contained in the near traffic accident video within the event-related time period (para(s). [0058], recite(s)
[0058] “Data for a potential collision event can be classified as location based, time based, scenario based, hazard or risk based, or another classification or a combination of classifications. Event data from various sources within and external to vehicle 104 can be saved in a data logger in a vehicle collision event database 422 .”
[0144] “Exemplary embodiments are intended to include or otherwise cover identification and warning for any type of event or scenario that could be a hazard to a moving vehicle 104 either on a road or off-road. Weather patterns and forces of nature can be identified and saved as potential collision events, such as flooding roads or areas, snowy or icy roads or areas, storm-hit or windy roads or areas, including road hazards, such as fallen rocks or trees caused by forces of nature.”
, where “location” and/or “weather” are at least second factoring data); and
step d) further includes compiling a factor group for the near traffic accident video based on the first factoring data and the second factoring data (para(s). [0104]—see citation in current claim above—, where “stor[ing]… current event data into the collision database” is compiling a factor group (e.g., a database entry) based on at least the first and second factoring data (i.e., the “event data” comprises first and second factoring data)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Owada, modified by Dong and Chen, to incorporate categorizing a near traffic accident event identified in one of the traffic videos while no traffic accident is identified into a fourth category and performing steps b)-d) recited in claim 1 for near traffic accident video to improve categorizing traffic accident videos by incorporating factors related to near traffic accident events as taught by Bai above.
Regarding claim 4, Owada, modified by Dong and Chen, discloses the method as claimed in Claim 1, Bai teaches in the same field of endeavor of obtaining factors related to traffic accidents the method as claimed in claim 1 further comprising:
in response to receipt of a new traffic video, processing, by the processor, the new traffic video so as to obtain a plurality of potential factors associated with a potential traffic accident (para(s). [0062] and [0084-0085], recite(s)
[0062] “The event detection component 418 can include processes and instructions 410 for detecting event characteristics or information from data and information collected by the CWS 400 . The event detection component can include an image recognition component that can match image and video collected from the CWS 400 with prior images and video that have been identified as related to a potential collision event.”
[0084] “…CWS 400 activation enables collection of new event data while vehicle 104 approaches and passes through intersection 102 ”
[0085] “Computer system 404 can process the new event data, compare the new event data from one vehicle to historical event data that the same vehicle or other vehicles collected at the same or proximate location, and generate a prediction as to whether the vehicle should be provided with information relating to a potential collision or provided an alert of a potential collision scenario. The operations of the CWS 400 are described in conjunction with embodiments of the disclosure below.”
, where comparing ”video collected from the CWS” is processing new traffic video to perform the intended use/result of obtaining a plurality of potential factors associated with a potential traffic accident (e.g., “new event data”));
comparing, by the processor, the potential factors and the content of the spreadsheet to calculate a similarity value (para(s). [0097], recite(s)
[0097] “ Further, if the comparison calculator 420 determines, in step 814 to determine if new event data matches a prior event data pattern, that new event data matches and/or correlates to a prior and/or historical event data pattern, then the method optionally proceeds in step 820 to determine if new event data meets a condition and/or characteristic of the prior and/or historical event data. In step 820 , the new event data should meet a threshold condition and/or characteristic of event data to qualify as a potential collision risk and/or road hazard. A condition and/or data characteristic can include, but is not limited to, a temporal component including a relevant time frame, a direction of movement and/or heading of an entity, and heading of the vehicle 104 approaching the entity, etc.”
, where determining if the “new event data matches and/or correlates to a prior and/or historical event data pattern” by at least “meet[ing] a threshold condition and/or characteristic” is at least calculating a similarity value by comparing potential factors and content of a spreadsheet (e.g., the “database” comprising “prior and/or historical event data pattern”)); and
when it is determined by the processor, using the similarity value, that a surrounding of a location presented in the new traffic video is prone to traffic accidents, generating an alert for the new traffic video (para(s). [0097]—see citation in the preceding limitation above—, where para(s). [0099] further recite(s):
[0099] “If, in step 820 to determine if new event data meets a condition, the comparison calculator 420 determines the new event data meets a condition and/or characteristic of prior and/or historical event data, then the method may include step 824 to warn vehicle 104 of a predicted potential collision event and/or road hazard. …”
, where “warn[ing]” is generating an alert).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Owada, modified by Dong and Chen, to incorporate process a new traffic video, calculate a similarity value by comparing potential factors associated with a potential traffic accident and the content of the spreadsheet, and generating an alert when it is determined using the similarity value that a surrounding of a location presented in the new traffic video is prone to accidents to warn about a predicted potential collision event and/or road hazard as taught by Bai above.
Regarding claim 5, Owada, modified by Dong, Chen, and Bai, discloses the method as claimed in Claim 4, Bai further teaches the method as claimed in claim 4 further comprising:
when a vehicle approaches the surrounding of the location presented in the new traffic video and being prone to traffic accidents (para(s). [0084], recite(s)
[0084] “CWS 400 can collect collision event data at or near intersection 102 from multiple sources in vehicle 104 , for example V2X signals from other vehicles and users, vehicle event sensor system 434 , navigation system 508 , and user input on input device 424 . CWS 400 activation enables collection of new event data while vehicle 104 approaches and passes through intersection 102 .”
), transmitting a notification to a carputer installed in the vehicle via a network (para(s). [0112], recite(s)
[0112] “Computer system 404 can detect V2P, V2V, and V2M signals received through vehicle 104 V2V transceiver 106 . Computer system 404 can analyze and translate V2X signals as to source, location, and telemetry, and collision event map component 416 can map the signals onto informing alert image 1100 .”
, where the “computer system” of a “vehicle” is a carputer).
Regarding claim 14, the claim recites similar limitations to claim 3 and is rejected for similar rationale and reasoning (see the analysis for claim 3 above).
Regarding claim 15, the claim recites similar limitations to claim 4 and is rejected for similar rationale and reasoning (see the analysis for claim 4 above).
Regarding claim 16, the claim recites similar limitations to claim 5 and is rejected for similar rationale and reasoning (see the analysis for claim 5 above).
Claims 6-7 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Owada, as modified by Dong and Chen as applied to claims 1 and 12 above, and further in view of Yu et al. (Yu; CN 116343493 A), and further more in view of Feng et al. (Feng; CN 111862681 A).
Regarding claim 6, Owada, modified by Dong and Chen, discloses the method as claimed in Claim 1, wherein Yu teaches in the same field of endeavor of obtaining factors related to traffic accidents the computer device being in communication with a monitoring system, the monitoring system being in communication with a plurality of road monitoring assemblies, each of the road monitoring assemblies being mounted in a specific geographical location (description, para(s). [n0031] and [n0067], recite(s)
[n0031] “The first passage time of each non-motorized vehicle and any first monitoring image are transmitted to the monitoring terminal at the next target intersection. After the monitoring terminal at the next target intersection identifies the second passage time of each non-motorized vehicle based on the second monitoring image of the next target intersection …”
[n0067] “Referring to Figure 1, this application provides a non-motorized vehicle violation identification system. This system may include, but is not limited to, a monitoring terminal and a server. The monitoring terminal may, but is not limited to, a radio frequency (RF) integrated machine, which includes a camera, an RF unit, and a main control unit. In specific implementation, the camera is responsible for capturing monitoring images of the target intersection and performing image recognition on the images to obtain vehicle identification information (such as license plate number) and speed of each non-motorized vehicle in the monitoring image. Simultaneously, the aforementioned identified data is transmitted to the main control unit for subsequent violation identification processing. …”
, where the “vehicle violation identification system” is a monitoring system being in communication with a plurality of road monitoring assemblies (e.g., “monitoring terminal[s]”, each comprising of a “camera” capturing “monitoring images of [a] target intersection”)) and including an alert device for outputting an alert (description, para(s). [n0089], recite(s)
[n0089] “…Upon receiving the violation capture image of that target vehicle, the traffic violation monitoring platform can determine the owner's terminal based on the owner information in the image, generate a violation notification, and send the violation notification to the owner's terminal. Optionally, the violation notification can be, but is not limited to, via SMS. Thus, through the aforementioned design, this embodiment notifies the vehicle owner of the speeding violation process via SMS. By sending real-time warnings and reminders, the safety awareness of the vehicle owner during riding can be enhanced, thereby further reducing speeding violations.”
, where the “traffic violation platform” is at least an alert device outputting an alert (e.g., “warnings” and/or “notification[s]”)) and a monitoring camera for capturing a traffic video (description, para(s). [n0067]—see citation in current claim above—, where the “camera” part of each “monitoring terminal” is a monitoring camera), the method further comprising:
f) in response to receipt of a traffic video from one of the road monitoring assemblies, processing the traffic video to obtain potential factors associated with the traffic video, and determining whether to initiate a monitoring operation based on the potential factors of the traffic video and one of the aggregated factor groups included in the spreadsheet (description, para(s). [n0086] and [n0104], recite(s)
[n0086] “…Based on the actual vehicle information of the first target vehicle, image processing is performed on any first monitoring image to obtain a violation capture image of the first target vehicle. The violation capture image of any first target vehicle records both the violation information and the actual vehicle information. In specific applications, examples include, but are not limited to, recording the actual vehicle information in the first monitoring image. Simultaneously, the location information of the target intersection (pre-stored in the monitoring terminal) is obtained, and the aforementioned speed of the target vehicle and the location information of the target intersection are also recorded in the first monitoring image. Thus, the first monitoring image contains both the actual vehicle information of the speeding non-motorized vehicle (i.e., license plate number, owner information, etc.) and violation information, such as the name of the capture intersection, the capture time, and the type of violation. By superimposing this information onto the first monitoring image, a violation capture image of the speeding non-motorized vehicle can be obtained.”
[n0104] “…Image recognition is performed on several first monitoring images to obtain the first passage time of each non-motorized vehicle at the target intersection. In this embodiment, the image recognition of the first monitoring images can refer to the aforementioned step S1. At the same time, the non-motorized vehicles in the images are first identified, and then the non-motorized vehicles are matched with the image capture time to obtain the first passage time of each non-motorized vehicle at the target intersection. Then, the first passage time of each non-motorized vehicle can be sent to the monitoring terminal at the next target intersection to realize the identification of speed violations of each non-motorized vehicle between the target intersection and the next target intersection. Of course, the first monitoring images and the identified vehicle identification information will also be sent to the monitoring terminal at the next target intersection.”
, where performing “image recognition” and/or identifying “speed violations” in the traffic video is obtaining potential factors associated with the traffic video, and determines whether to initiate a monitoring operation (e.g., “monitoring”) based on the potential factors (e.g., “speed violations”) and one of the aggregated factor groups included in the spreadsheet (e.g., “location information of the target intersection (pre-stored…)”));
g) in the case that the monitoring operation is to be initiated, determining whether a factor related to a vehicle presented in the traffic video is included in both the potential factors and the one of the aggregated factor groups (description, para(s). [n0086]—see preceding limitation immediately above—, where obtaining a “violation capture image” comprising a “violation” and “location information” is determining a factor (e.g., a “speed”) related to a vehicle presented in the traffic video is included in both the potential factors (e.g., “violation”) and one of the aggregated factor groups (e.g., “location information”) in the case that the monitoring operation is to be initiated);
h) in the case that a result of the determination of step g) is affirmative, generating an alert associated with the vehicle, and transmitting the alert to the monitoring system for enabling the monitoring system to control a next one of the road monitoring assemblies to output the alert(description, para(s). [n0089]—see citation in the current claim above—, where the “notification” and/or “warnings” is generating an alert associated with the vehicle; and description, para(s). [n0105], further recite(s):
[n0105] “The first passage time of each non-motorized vehicle and any first monitoring image are transmitted to the monitoring terminal at the next target intersection. After the monitoring terminal at the next target intersection identifies the second passage time of each non-motorized vehicle based on the second monitoring image of the next target intersection, it determines the interval speed of each non-motorized vehicle according to the first and second passage times. Then, it merges any first monitoring image, any second monitoring image, and actual vehicle information of the second target vehicle to obtain the interval violation capture image of the second target vehicle. The interval violation capture image of the second target vehicle is then sent to the server. The interval speed of any non-motorized vehicle is the speed at which the non-motorized vehicle travels between the target intersection and the next target intersection, and the second target vehicle is a non-motorized vehicle whose interval speed is greater than the speed limit.”
, where “transmitting to the monitoring terminal at the next target intersection” the “first monitoring image” is transmitting the alert to perform the intended use/result of controlling a next one of the road monitoring assemblies (e.g., “monitoring terminal at the next target intersection”) to output the alert the monitoring system);
i) in response to receipt of another traffic video from the next one of the road monitoring assemblies, processing the another traffic video to obtain potential factors associated with the another traffic video, and determining whether to continue the monitoring operation based on the potential factors of the another traffic video and one of the aggregated factor groups included in the spreadsheet (description, para(s). [n0105]—see preceding citation immediately above—, where processing the “second monitoring image’ to determine the “vehicle information” and/or “speed” is processing the another traffic video to obtain potential factors associated with the another traffic video; where identifying the “speed violations” of the vehicle is determining to continue monitoring based on the potential factor (e.g., “violation”) of the another traffic video and one of the aggregated factor groups included in the spreadsheet (e.g., the “location information” and/or “vehicle information”));
j) in the case that the monitoring operation is to be continued, determining whether the factor related to the vehicle is still included in both the potential factors and the one of the aggregated factor groups (description, para(s). [n0105]—see citation in the current claim above—, where determining that the vehicle in the another traffic video matches the vehicle in the traffic video and comprises a speeding “violation” is determining the factor related to the vehicle (e.g., “speed”) is still included in both the potential factors (e.g., “violation”) and the one of the aggregated factor groups (e.g., “location information” and/or “vehicle information”)); and
k) in the case that a result of the determination of step j) is affirmative, generating another alert associated with the vehicle, and transmitting the another alert to the monitoring system for enabling the monitoring system to control another next one of the road monitoring assemblies to output the alert(description, para(s). [n0105]—see citation in the current claim above—, where determining an “interval violation capture image” is generating another alert associated with the vehicle and “send[ing]” the “interval violation capture image” is transmitting the another alert to the monitoring system; wherein the process can be repeated for another “target intersection” (i.e., the process of step i) above)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Owada, modified by Dong and Chen, to incorporate a monitoring system being in communication with a plurality of road monitoring assemblies including a monitoring camera for capturing a traffic video and an alert device for outputting an alert based on potential factors of a traffic video and one of the aggregated factor groups included in the spreadsheet to categorize traffic accident data comprising of traffic violations in consecutive traffic videos as taught by Yu above.
Where Owada, modified by Dong, Chen, and Yu, does not specifically disclose
…, the alert including at least a moving direction of the vehicle; and
…, the another alert including at least a moving direction of the vehicle;
Feng teaches in the same field of endeavor of tracking vehicles between individual traffic videos
…, the alert including at least a moving direction of the vehicle; and
…, the another alert including at least a moving direction of the vehicle (description, para(s). [0010] and [0063], recite(s)
[0010] “Furthermore, the vehicle tracking module includes vehicle tracking and detection sensors. Multiple vehicle tracking and detection sensors are set up on the side of the road to form a continuous detection area. After a vehicle enters the detection area, the vehicle tracking and detection sensors collect the vehicle's real-time speed information, direction of movement information, latitude and longitude information, acceleration information, direction angle information, lane information, and trajectory information, and generate a unique ID digital identification information for the vehicle. The vehicle tracking and detection sensors will send the collected data to the roadside service platform until the vehicle completely leaves the coverage area of the vehicle tracking and detection sensors.”
[0063] “It can respond promptly to changes in road conditions and traffic conditions, as well as to abnormal traffic accidents and obstacles that endanger driving safety. It can quickly generate corresponding early warning information, alarm information, traffic plans and other auxiliary information, which can prevent drivers from having incomplete information and taking untimely measures, thus avoiding major traffic accidents and secondary accidents.”
, where “send[ing] the collected data” from “Multiple vehicle tracking and detection sensors… set up on the side of the road” to generate “early warning” and/or “alarm” information is generating an alert including at least a moving direction (e.g., “direction of movement information”) of the vehicle);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Owada, modified by Dong, Chen, and Yu, to incorporate into the alert and another alert at least a moving direction of the vehicle to track the vehicle across the plurality of road monitoring assemblies capturing a continuous area as taught by Feng above.
Regarding claim 7, Owada, modified by Dong, Chen, Yu, and Feng, discloses the method as claimed in Claim 6, wherein step f) includes comparing the potential factors of the traffic video and the one of the aggregated factor groups to calculate a similarity value, and initiating the monitoring operation when the similarity value is within a predetermined range (description, para(s). [n0086] and [n0104]—see citations in step f) of claim 6 above—, where the vehicle in the traffic video is “matched” to a “capture time” at a “target intersection” location is calculating a similarity value by comparing the potential factors of the traffic video (e.g., a “capture time” and/or “target intersection” location) and initiating the monitoring operation when the similarity value is within a predetermined range (e.g., “match[ing]”)).
Regarding claim 17, the claim recites similar limitations to claim 6 and is rejected for similar rationale and reasoning (see the analysis for claim 6 above).
Regarding claim 18, the claim recites similar limitations to claim 7 and is rejected for similar rationale and reasoning (see the analysis for claim 7 above).
Claims 10-11 and 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Owada, as modified by Dong and Chen as applied to claims 1 and 12 above, and further in view of Lekova et al. (Lekova; US 2018/0126901 A1), and further more in view of Tang et al. (Tang; US 2019/0035279 A1).
Regarding claim 10, Owada, modified by Dong and Chen, discloses the method as claimed in Claim 1, wherein Lekova teaches in the same field of endeavor of obtaining factors related to traffic accidents the data storage storing a plurality of driver videos, each of the driver videos being obtained by a driver monitoring system installed in a vehicle and including a face image of a driver of the vehicle (para(s). [0028] and [0062], recite(s):
[0028] “In a first variation, the sensor measurements include an image or video (e.g., set of images) of the cabin interior, which can be sampled by the inward-facing camera directed toward the driver's side head volume or otherwise sampled (example shown in FIG. 2). For example, Block S110 can include sampling sensor measurements at an onboard system of the vehicle, wherein the sensor measurements include an image of the driver (e.g., S110a, S110′). The camera's field of view preferably includes all or a portion of the driver's head, and can optionally include all or a portion of the passenger-side volume (e.g., the passenger's body or head), all or a portion of the rear seats, all or a portion of the rear window, the driver's side window(s), the passenger side window(s), or include any other suitable portion of the vehicle interior. The image(s) can be used to optically identify and/or track the driver's head position, head movement, eye position (e.g., gaze direction), eye movement, parameters thereof (e.g., duration, angle, etc.), or determine any other suitable distraction factor value. …”
[0062] “In a second example, the driver distraction module can determine that the driver of the vehicle is characterized by the distracted state based on checking the result against a face detection module output (e.g., contemporaneously generated, asynchronously generated, etc.). …”
, where the “video (e.g., set of images) of the cabin interior” obtained by a “inward-facing camera” is a driver monitoring system installed in a vehicle obtaining driver videos), wherein:
step c) further includes, by the processor, processing each of the driver videos stored in the data storage so as to determine, for each of the driver videos, driver data that is associated with a state of the driver(para(s). [0139], recite(s)
[0018] “In a fifth application, the detected distraction event or score thereof can be stored in association with an identifier for the driver (e.g., in a driver profile). This driver profile can be used to determine driver-specific notifications, alerts, routes, or any other suitable information. In one variation, the method 100 can include identifying contexts associated with a higher frequency of distraction for a given driver (e.g., based on historic distraction patterns) and automatically determine a route that minimizes the probability of distraction (e.g., minimizes the number of encountered distraction-associated contexts) for the driver (e.g., identified using the method disclosed in U.S. application Ser. No. 15/642,094 filed 5 Jul. 2017, incorporated herein in its entirety; or any other suitable method). In a second variation, the method 100 can include preemptively notifying the driver when nearing locations historically associated with a distraction event for the driver. In a third variation, the method 100 can include providing coaching to a driver based on a historical distraction event data associated with the driver (e.g., providing feedback to the driver based on past behavior to prevent future distracted behavior, at such times as similar behavior patterns are determined via the method or at other suitable times). However, the driver profile can be otherwise suitably used. Furthermore, the detected distraction event or score thereof can be otherwise suitably used. In this and related applications, the score (e.g., distraction score) is preferably determined by a scoring module, but can be otherwise suitably determined. …”
, where determining a driver video as a “detected distraction event” is processing the driver videos stored to perform the intended use/result of determining driver data (e.g., “behavior”) associated with a state of the driver),
wherein determining the driver data includes identifying signs indicating that the driver is in a state of mind-wandering, the signs indicating that the driver is in the state of mind-wandering includes one or more of: excess saccade of the eyeballs related to the movement of the vehicle; an average distance of eyeball saccade detected within a specific driving distance being larger than a predetermined distance; and an average staring time of eyeball at a direction that is not parallel to the moving direction of the vehicle within a specific driving distance being larger than a predetermined time (para(s). [0022], [0041], and [0043], recite(s)
[0022] “First, variants of the method can enable potential collisions to be avoided, by alerting (e.g., notifying) a driver that he or she is distracted or is likely to become distracted based on driver behavior. For example, the method can include generating an audio alert when the gaze of the driver has drifted (e.g., beyond a threshold angular departure from the direction of travel of the vehicle for greater than a threshold amount of time), which can refocus the driver's attention on the road.”
[0041] “In a first variation, determining the distraction factor value can include determining the parameters of the driver's gaze, such as gaze direction, gaze duration, gaze angle (e.g., relative to a reference point), rate of change of gaze direction, or any other suitable gaze parameter. This can include identifying the driver's corneal reflectance, pupil, retinal patterns, or other eye parameter in the sampled images or video frames (e.g., the image segment associated with the driver's volume), and determining the driver's gaze direction using gaze estimation, head pose determination, or any other suitable technique. The gaze direction can optionally be classified as one of a set of predetermined directions (e.g., forward, right side, left side, rearward, etc.) or otherwise characterized. Additionally or alternatively, the number, frequency, duration, or other parameter of the gazes can be determined for each head pose, time duration, or from any other set of images.”
[0043] “…The reference image (or reference head pose) can be a prerecorded image with the driver in the vehicle (e.g., where the driver is instructed to gaze forward during image recordation), a prerecorded image of the driver (e.g., driver's license standard image) superimposed within the driver head volume, an image composited from multiple images recorded over one or more driving sessions (e.g., the average head pose), or be any other suitable reference image …”
, where identifying if a “driver’s gaze” is “beyond a threshold angular departure from the direction of travel of the vehicle for greater than a threshold amount of time” is identifying signs that the driver is in a state of mind-wandering (e.g., “distraction”) including at least an average staring time of eyeball at a direction that is not parallel to the moving direction of the vehicle within a specific driving distance being larger than a predetermined time).
Where Owada, modified by Dong, Chen, and Lekova, does not specifically disclose
…, and incorporating the driver data in the second factoring data;
Tang teaches in the same field of endeavor of obtaining factors related to traffic accidents
…, and incorporating the driver data in the second factoring data (para(s). [0068] and [0071], recite(s)
[0068] “The past accident information includes dates, places, weather, road conditions, accident situations, vehicle information, and driver's information regarding traffic accidents occurred in the past.”
[0071] “The driver's information includes, for example, an age, a gender, a height, a weight, a visual acuity, a pulse rate, a heart rate, a blood pressure, a respiration rate, the number of times of blinks and yawning, personality, a medical history, a medication history, a driver's license type, a driving history, a traffic accident history, a traffic violation history, and a criminal record.”
, where including “driver’s information” into “past accident information” is incorporating driver data in the second factoring data).
Since Owada disclosed that the second factoring data includes information about a traffic accident event (see the rejection of step d) of claim 1 above), it would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Owada, modified by Dong, Chen, and Lekova, to incorporate driver data in the second factoring data because traffic accidents also include human factors as taught by Tang (para(s). [0002-0004], recite(s)
[0002] “In recent years, traffic accidents have become one of the most fatal accidents in daily life. Hereinafter, a car that is driven by a driver is referred to as a vehicle, and the other car traveling around the vehicle is referred to as the other vehicle. In addition, a driver of the other vehicle is referred to as the other person. In addition, the traffic accidents include accidents such as a car-to-car accident, a car-to-bicycle (including bike) accident, and a car-to-pedestrian accident.”
[0003] “Factors of the traffic accidents are classified into human factors and environmental factors.”
[0004] “The human factor includes a lack of skill and experience of the driver, careless drive by the driver, aggressive driving by the driver, and the like.”
).
Regarding claim 11, Owada, modified by Dong, Chen, Lekova, and Tang, discloses the method as claimed in Claim 10, wherein Tang further teaches the method as claimed in Claim 10 further comprising:
in response to receipt of a new traffic video and a new driver video associated with the new traffic video, processing, by the processor, the new traffic video and the new driver video so as to obtain a plurality of potential factors associated with a potential traffic accident (para(s). [0077], recite(s)
[0077] “In the accident predicting processing, the data analyzing unit 23 predicts occurrence of a traffic accident by analyzing the real-time vehicle information and driver's information of the vehicle supplied from the sensor unit 26 and vehicle information and driver's information of the other vehicle supplied from the communication unit 27 . Specifically, a warning level is determined on the basis of the result of comparison between one or more key factors of the traffic accident and a threshold value α corresponding thereto. …”
, where analyzing the “real-time vehicle information and driver’s information” is processing at least new traffic (e.g., “vehicle”) video and driver (e.g., “driver’s”) video to perform the intended use/result of obtaining a plurality of potential factors (e.g., “information”) associated with a potential traffic accident);
comparing, by the processor, the potential factors and the content of the spreadsheet to calculate a similarity value (para(s). [0077]—see preceding citation immediately above—, where para(s). [0083] and [0085] further recite(s):
[0083] “In the database 24 , the analysis result of the data analyzing unit 23 , that is, the key factor of the traffic accident for each area, the threshold value of the key factor, and the recommended drive mode are accumulated and updated each time.”
[0085] “The real-time data collection control unit 25 designates the type of the data to be sensed relative to the sensor unit 26 and sets the sensing mode on the basis of the key factors of the dangerous area notified from the database 24 via the data analyzing unit 23 . Then, the real-time data collection control unit 25 makes the sensor unit 26 acquire real-time vehicle information (for example, traveling speed, load, tire pressure, and operation conditions of lights, wipers, and defrosters) and driver's information (pupil opening degree, pulse rate, heart rate, blood pressure, respiration rate, the number of times of blinks and yawning, and the like). In addition, the real-time data collection control unit 25 controls the communication unit 27 to acquire vehicle information and driver's information of the other vehicle.”
, where the “comparison between one or more key factors of the traffic accident” from the “database” is comparing the potential factors (e.g., “real-time vehicle information… and driver’s information”) and the content of the spreadsheet (e.g., “key factors” in the “database”)); and
when it is determined by the processor, using the similarity value, that a surrounding of a location presented in the new traffic video is prone to traffic accidents, generating an alert for the new traffic video (para(s). [0077]—see citation in the current claim above—, where para(s). [0154] further recite(s):
[0154] “In step S 13 , the database 24 notifies the key factors of the car traffic accident, the threshold value, and the recommended drive mode corresponding to the dangerous area of the data analyzing unit 23 . The data analyzing unit 23 notifies the notified key factors of the real-time data collection control unit 25 and notifies the recommended drive mode of the system control unit 28 .”
, where “notif[ying]” about potential “traffic accident” factors (e.g., “key factors of the car traffic accident”) is generating an alert for the new traffic video when it is determined that a surrounding of a location presented in the new traffic video is prone to traffic accidents (e.g., “dangerous”) using the similarity value).
Regarding claim 21, the claim recites similar limitations to claim 10 and is rejected for similar rationale and reasoning (see the analysis for claim 10 above).
Regarding claim 22, the claim recites similar limitations to claim 11 and is rejected for similar rationale and reasoning (see the analysis for claim 11 above).
Allowable Subject Matter
Claims 8-9 and 19-20 would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims and, if rewritten or amended to overcome the objection(s) and rejection(s) under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, and 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JULIA Z YAO whose telephone number is (571)272-2870. The examiner can normally be reached Monday - Friday (8:30AM - 5PM).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Emily Terrell can be reached at (571)270-3717. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/J.Z.Y./Examiner, Art Unit 2666
/MING Y HON/Primary Examiner, Art Unit 2666
Prosecution Insights