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 .
This application is a CON of 16/941,742 07/29/2020 ABN
16/941,742 has PRO 62/879,847 07/29/2019
Examiner notes 16/941,742 has gone through appeal process, where the appeal board affirmed Examiner’s rejection on similar claims. 16/941,742 was abandoned after the appeal decision.
Status of Claims
Claim 1 is canceled.
Claim 2-21 are currently pending and rejected.
Claim Rejection – 35 U.S.C. 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.
Claims 2-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The rationale for this finding is explained below. In the instant case, the claims are directed towards processing geocoded data of catastrophic risk models and generating risk exposure predictions. The concept is clearly related to managing transaction risks between people, thus the present claims fall within the Certain Method of Organizing Human Activity grouping. Moreover, without defining the scale and difficulty of the calculations, the present claims could be performed in the human mind. Therefore, the present claims also fall within the Mental Processes grouping. The claims do not include limitations that are “significantly more” than the abstract idea because the claims do not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Note that the limitations, in the instant claims, are done by the generically recited computer device. The limitations are merely instructions to implement the abstract idea on a computer and require no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry. Therefore, claims 2-22 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Step 1: The claims 2-21 are directed to a process, machine, manufacture, or composition matter.
In Alice Corp. Pty. Ltd. v. CLS Bank Intern., 134 S. Ct. 2347 (2014), the Supreme Court applied a two-step test for determining whether a claim recites patentable subject matter. First, we determine whether the claims at issue are directed to one or more patent-ineligible concepts, i.e., laws of nature, natural phenomenon, and abstract ideas. Id. at 2355 (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 132 S. Ct. 1289, 1296–96 (2012)). If so, we then consider whether the elements of each claim, both individually and as an ordered combination, transform the nature of the claim into a patent-eligible application to ensure that the patent in practice amounts to significantly more than a patent upon the ineligible concept itself.
Claims 2-13 are directed to a machine (i.e., system claims).
Claims 14-21 are directed to a process (i.e., method claims).
Step 2A: The claims are directed to an abstract idea.
Prong One
The present claims are directed towards processing geocoded data of catastrophic risk models and generating risk exposure predictions. The concept comprises the steps of:
storing a plurality of catastrophic event models
determining an analysis radius to apply to a set of locations
using the analysis radius to identify a geographic tile size for dividing a map into a plurality of tiles
assigning the set of locations to a set of tiles of the plurality of tiles
accessing catastrophic risk models
calculate a risk exposure accumulation value
calculate a combined risk exposure accumulation value of adjacent geographic areas
identifying grouping of geographically adjacent geographic areas exceeding a predetermined risk exposure accumulation value
identifying a respective buffered analysis zone
applying a respective plurality of intermediate points arranged at predetermined distance intervals
calculating an intermediate point exposure accumulation value for the respective intermediate point
identifying one or more intermediate points of interest based on the respective intermediate point exposure accumulation value exceeding a calculated risk exposure accumulation value
Even though the independent claims 2 and 14 are lengthy, they still follow the same pattern of the ineligible claims in Electric Power Group v. Alstom, because they are directed to a process of obtaining data (i.e. accessing information from database or Internet), analyzing the obtained data (i.e. performing calculations and determinations analogous to human mental processing), and providing result of the analysis (i.e. outputting result of analysis). Moreover, each of the catastrophic risk exposure analysis can be performed mentally. The steps of storing models and catastrophic event and outputting result of analysis can be done by writing down the information on paper. The computer elements (processing circuitry and computer readable memory) are merely extra-solution that automate human processing. As such, the present claims fall within the Certain Method of Organizing Human Activity grouping and Mental Processing grouping, according to 2019 Revised Patent Subject Matter Eligibility Guidance.
The novelty of the claimed invention lies entirely in the steps of data analysis, which is in the realm of abstract concept. No matter how novel the data analysis steps are, they are still describing an abstract concept. The claims do not contain features that are directed to improve computer function or other technology. Therefore, the claims recite an abstract idea.
Prong Two
The independent claims 2 and 14 recite a non-transitory computer-readable storage and a processing circuitry coupled with a memory as additional elements. The additional elements are claimed to perform basic computer functions, such as storing data, accessing data, performing calculations, automating analytic steps that are analogous to mental processing, and outputting result.
a non-transitory database storage region storing a plurality of catastrophic event models, wherein each catastrophic event model comprises geo-coded information relevant to a respective catastrophic event of at least one type of catastrophic event (note: “receiving, processing, and storing data” is a basic computer function in MPEP 2106.5(d); specifying what data is being stored, in this case catastrophic event models, does not improve computer function)
determining an analysis radius to apply to a set of locations, identifying a geographic tile size for dividing a map, and assigning the set of locations to a set of tiles (note: these are analytical steps that can be performed by human)
access, from the non-transitory database storage region responsive to the catastrophic event identification information, at least one catastrophic event model of the plurality of catastrophic event models (note: this step merely requires accessing data from database; “receiving, processing, and storing data” is a basic computer function in MPEP 2106.5(d))
calculate a risk exposure accumulation value; calculate a combined risk exposure accumulation value of adjacent geographic areas; identifying grouping of geographically adjacent geographic areas exceeding a predetermined risk exposure accumulation value (note: the computer elements here are still just performing repetitive calculations, which is a basic computer function in MPEP 2106.5(d))
identifying a respective buffered analysis zone; applying a respective plurality of intermediate points arranged at predetermined distance intervals; calculating an intermediate point exposure accumulation value for the respective intermediate point; identifying one or more intermediate points of interest based on the respective intermediate point exposure accumulation value exceeding a calculated risk exposure accumulation value (note: the computer elements here are still just performing repetitive calculations, which is a basic computer function in MPEP 2106.5(d))
Dependent claims 2-13 and 15-21 do not recite any additional element other than the non-transitory computer-readable storage and the processing circuitry. The recitation of the computer elements amounts to mere instruction to implement an abstract concept on computers. The present claims do not solve a problem specifically arising in the realm of computer networks. Rather, the present claims implement an abstract concept using existing computer technology in a networked computer environment. The present claims do not recite limitation that improve the functioning of computer, effect a physical transformation, or apply the abstract concept in some other meaningful way beyond generally linking the use of the abstract concept to a particular technological environment. As such, the present claims fail to integrate into a practical application.
Examiner also points out that the present claims are unlike the eligible claims in McRO. The court found McRo’s claims eligible because McRO’s claimed rules enabled the automation of specific animation tasks that previously could not be automated. In other words, McRO solves a technical problem of prior automation systems. More importantly, McRO described the claimed invention as improving computer animation through the use of specific rules, rather than human artists, to set morph weights and transition parameters between phonemes. As explained in the specification, human artists did not use the claimed rules, and instead relied on subjective determinations to set morph weights and manipulate the animated face to match pronounced phonemes. The present claims do not recite specific rules that are not used by human to enable a computer operation that was not possible prior to the invention. Instead, the present claims merely use existing computers to automate calculations based on preset models/formulas. Receiving data over network and performing repetitive calculations are well-understood, routine, and conventional computer functions, according to MPEP 2106.5(d). Computer implementation is merely an extra-solution, and the claimed steps are not intended to resolve a computer problem. As such, the present claims are closer to the ineligible claims in Electric Power Group v. Alstom, which describe a process of obtaining data, analyzing data, and providing result of the analysis.
Examiner further points out that the present claims are unlike the claims in CardioNet LLC v. InfoBIonic and Enfish, because the present claims merely perform calculations on stored data using models/formulas without reciting a particular improvement in the computer’s capability of processing data stored in a catastrophic risk model. The Enfish court relied on the distinction made in Alice between, on one hand, computer-functionality improvements and, on the other, uses of existing computers as tools in aid of processes focuses on "abstract ideas". In Enfish, the claims at issue focused not on asserted advances in uses to which existing computer capabilities could be put, but on a specific improvement - a particular database technique - in how computers could carry out one of their basic functions of storage and retrieval of data. But the present claims do not recite any specific improvement similar to Enfish.
Step 2B: The claims do not recite additional elements that amount to significantly more than the abstract idea.
As discussed earlier, the present claims only recite a non-transitory computer-readable storage and a processing circuitry coupled with a memory as additional elements. The additional elements are claimed to perform basic computer functions, such as storing data, receiving request over network, accessing data, performing calculations, automating analytic steps that are analogous to mental processing, and outputting result. According to MPEP 2106.05(d), “performing repetitive calculations”, “receiving, processing, and storing data”, “electronically scanning or extracting data from a physical document”, “electronic recordkeeping”, and “receiving or transmitting data over a network, e.g., using the Internet to gather data” are considered well-understood, routine, and conventional functions of computer. The present claims do not improve the functioning of computer technology. Simply implementing the abstract idea on a generic computer or using a computer as a tool to perform an abstract idea cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. Therefore, the present claims are ineligible for patent.
Prior Arts Cited But Not Applied
Roy Chowdhury et al. (Patent No.: US 11,847,603) is cited, because the reference teaches partitioning a map into polygons and determining size of the polygons and analysis radius for risk prediction (see col 3 line 17-39) and claim 19. However, Roy Chowdhury was filed on 07/19/2021, later than 07/29/2019 - the effective filing date of the present application. As such, Roy Chowdhury is not a prior art.
Fiete et al. (Pub. No.: US 2019/0378216) teaches using catastrophic models to predict risk exposures catastrophic events (see paragraph 0006, 0023, 0031, 0037-0038, 0041, and 0043). However, Fiete does not teach eliminating geographic areas having lower amounts of risk exposure accumulation from catastrophic risk model analysis, or performing accelerated catastrophic risk model analysis on one or more geographic regions corresponding to high exposure grouping.
Mildenhall et al. (Pub. No.: US 2017/0185909) teaches determining exposure including detecting, based on received data from external entities, an occurrence of a catastrophic event (see paragraph 0005). Mildenhall teaches using spatial footprint of events and a map to determine insured locations with the largest amount of exposure (see paragraph 0021), where the map is divided into a grid of a plurality of cells for analysis (see paragraph 0022-0023). The prior art also teaches calculating the summations of risk exposure in the grid cell (see paragraph 0061-0062, 0068) and identifying the highest exposure values (see paragraph 0023 and 0062). However, Mildenhall does not teach storing a plurality of catastrophic risk models, eliminating geographic areas having lower amounts of risk exposure accumulation from catastrophic risk model analysis, or identifying a respective buffered analysis zone spanning form a central point of a respective center file of the respective high exposure grouping and extending to at least the analysis radius, or applying a respectively plurality of intermediate points arranged at predetermined distance intervals throughout the respective buffered analysis zone.
Baumgartner et al. (Pub. No.: US 2017/0161859) teaches determining geolocation risk using catastrophe models (see paragraph 0040). However, Baumgartner does not teach eliminating geographic areas having lower amounts of risk exposure accumulation from catastrophic risk model analysis, or identifying a respective buffered analysis zone spanning form a central point of a respective center file of the respective high exposure grouping and extending to at least the analysis radius, or applying a respectively plurality of intermediate points arranged at predetermined distance intervals throughout the respective buffered analysis zone.
Chen et al. (Patent No.: US 7,707,050) is the best prior art. Chen teaches defining areas of analysis and grid width, and individually analyzing each geographical areas within the region of interest, and using accumulation analysis to determine one or more of the areas have high exposure concentrations (see col 2 line 13-28). Chen also teaches defining a threshold amount, so that only those areas having accumulation risk exposures over the threshold level will be identified (see col 3 line 46-57). In other words, Chen teaches eliminating geographic areas having lower amounts of risk exposure accumulation from catastrophic risk model analysis. However, Chen does not teach performing accelerated catastrophic risk model analysis comprising “a) identifying a respective buffered analysis zone spanning from a central point of a respective center tile of the respective high exposure grouping and extending to at least the analysis radius, b) applying, to the respective buffered analysis zone, a respective plurality of intermediate points arranged at predetermined distance intervals throughout the respective buffered analysis zone, each intermediate point of the respective plurality of intermediate points comprising a corresponding geographic location, c) for each respective intermediate point of the respective plurality of intermediate points, using the geocoded data of the at least one catastrophic risk model, calculating a respective intermediate point exposure accumulation value of a plurality of intermediate point exposure accumulation values, wherein the respective intermediate point exposure accumulation value represents exposure from all locations of the set of locations falling within an analysis radius of the respective intermediate point, and d) identifying, among the respective plurality of intermediate points, at least one high exposure intermediate point comprising a respective intermediate point risk exposure accumulation value exceeding the predetermined risk exposure accumulation value”, as recited in independent claim 2 and claim 14. Other prior arts do not fulfill the deficiency of Chen. Therefore, no prior art rejection is cited in this Office Action.
However, the novelty of the claimed invention lies entirely in the steps of data analysis, which is in the realm of abstract concept. No matter how novel the data analysis steps are, they are still describing an abstract concept. The claims do not contain features that are directed to improve computer function or other technology. Therefore, the claims recite an abstract idea and are not patent eligible under 35 U.S.C. 101.
Conclusion
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/HAO FU/Primary Examiner, Art Unit 3695
FEB-2026