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 .
The following is a Final Office Action in response to communications received August 05, 2026. No Claim(s) have been canceled. Claims 1, 10 and 16 have been amended. No new claims have been added. Therefore, claims 1-20 are pending and addressed below.
Priority
Application No. 19169598 filed 04/03/2025 is a Continuation of 15154247 filed 05/13/2016
Assignee/Applicant Name: Allstate Insurance Company
Inventor(s): Chintakindi, Sunil
Response to Amendment/Arguments
Drawings
The amendments to the specification in response to the objection set forth in the previous Office Action for failing to comply with 37 CFR 1.84(p)(5). The examiner withdraws the objection to the drawings.
Claim Rejections - 35 USC § 101
Applicant's arguments filed 05/06/2026 have been fully considered but they are not persuasive.
In the remarks applicant argues that amended claim 1 recites generating a score for each road segments by “applying a weighted interaction term between the …road segment condition of the road segment and an identified driving behavior of the driver”, where the road…condition is “detected in real-time or near real-time using the one or more sensors”. The claimed limitations cannot reasonably be performed by the human mind. The claim requires physical sensors to detect changing road segment conditions in real time requiring computing a weighted interaction term that couples that sensor detected condition to a specific identified driving behavior of the driver for each parsed road segment of a route. The human mind is not equipped to detect precipitation, road wetness, traffic conditions through sensors nor compute per segment weighted interaction between such sensor detected conditions and measurable driver behavior across a parsed navigational route. The examiner respectfully disagrees with the premise of applicant’s argument. The claimed sensors are generic computer components and tools to perform the mental processes. The human mind through observation, analysis and decision is able to detect whether the roads are wet, flooded, slick, heavy/light traffic, narrow, whether the roads are rough, well maintained, etc. and able to determine whether the driver is speeding, adjusting the driving according to road conditions, etc. The sensors as claimed are recited at a high level of generality and merely automates functions that could reasonable be performed using mental concepts, therefore acting as a generic computer to perform the abstract idea. The human mind also is capable of determining which road conditions are higher risk, which driving behavior is safe, unsafe, dangerous and weight which situation is more important when scoring/grading/rating different road segments for a safe/unsafe travel. The rejection is maintained.
In the remarks applicant argues that under step 2A prong 2, the amended claims recite integration into a practical application by reciting specific sensor based technique for generating road hazard scores. The claimed elements include applying weighted interaction term between real time sensor detected road segment condition and identified driving behavior of the driver. Using the total score to generate route modification where score exceeds a threshold. The claimed limitations are not generic “apply it on a computer” as the limitations recite a particular arrangement of sensing per segment weighted interaction scoring and threshold triggered route modification improving operation of a navigation system. Applicant points to BASCOM and Finjan v Bluecoat which provides guidance of patent eligibility found in improving technology as an indication of patent eligibility. Applicant argues that the sensor detected conditions and driver behavior combined through weighted interaction term to produce road segment scores which are aggregated and compared to a threshold to trigger a route modification. Applicant’s argument is not persuasive. The claim limitations do not recite a specific sensor technique, rather the claim limitations recite using sensors for collecting data and what data the sensors collect. The claims explicitly recited “apply it” sensors for obtaining driver data and detecting road conditions.
receiving driver-specific data obtained using one or more sensors
road segment condition detected in real-time or near real-time using the one or more sensors
Furthermore, applicant’s argument that “applying weighted interaction term between real time sensor detected road segment condition and identified driving behavior of the driver” improves operation of a navigation system, does not explain how calculating scores using weighted variables impacts navigation technology. The weighting of variables used to generate driving scores used to change routes to a different navigation routes does not impact or improve upon any underlying technology. The calculated score using weighted variables is merely mathematical calculations based on selected information. The mathematical calculation of a score using weighted variables involved here has no substantial practical application except in connection with a computer. The generation of a modified route based on scores is an algorithm that has no impact upon the computer, its functionality or field its functionality or field is patent ineligible. Therefore, the generating of changed route is not sufficient to transform the claim into patent eligible subject matter. The claim limitations merely apply technology to collect data, analyzed data and output the result of the analysis. The rejection is maintained.
In the remarks applicant argues amended claims under step 2B, the claimed subject matter provide significantly more than the alleged abstract idea and therefore, are patent eligible. Applicant argues the ordered combination of the amended limitation “detecting…road segment condition in real-time…using …sensors, identifying …driving behavior of driver, applying weighted interaction term between sensor detected condition and identified behavior to generate per segment …score, aggregating…scores into a total hazard score and generating a route modification when total exceeds a threshold. Applicant argues that similar to BASCOM, the ordered combination of the claim limitations provides a particular non-generic arrangement of these features and therefore, an inventive concept. The analysis cannot be reduced to individual single features in isolation but rather as a combination. The claims do not recite a desired result where achievement is achieved by any known means, but rather specific weighted interaction scoring operations. Therefore, in light of Finjan the claims recite significantly more that the idea itself. Applicant’s argument is not persuasive. The ordered combination of the claimed steps recited using technology to obtain data, analyze data and output the result where the result is applied to modify a travel route. According to Electric Power Group, applying technology to collect data, analyze data and output the result is well understood and routine use of technology. Accordingly the ordered combination as a whole of the technical process claimed is well understood and routine. With respect to applicant’s “significantly more” argument, in referencing Alice reciting additional elements that include “apply it” (or an equivalent) with an abstract idea, are not enough to qualify as “significantly more”. The recited functions of the underlying additional elements (driving behavior system, sensors, control system) are recited at a high level or generality without technical details, amounting to no more than mere instructions to implement the abstract idea on a computer. The limitations require no more than a generic computer elements to perform generic computer functions that are well understood activities known to the industry. As a result, none of the underlying technology recited by the claims offers a meaningful limitation beyond generally linking the use of the method to a particular technological environment, that is, implementation via computers. .. . The claim limitations do not recite that any of the “devices” perform more than a high level generic function ... . None of the limitations recite technological implementation details for any of these steps, but instead recite only results desired to be achieved by any and all possible means. .. . Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The rejection is maintained.
Claim Rejections - 35 USC § 102
In the remarks applicant argues that the prior art Bogovich fails to teach “applying a weighted interaction term between the dynamic road segment condition of the road segment and an identified driving behavior of the driver”. In the remarks applicant argues that the prior art Bogovich fails to teach “applying a weighted interaction term between the dynamic road segment condition of the road segment and an identified driving behavior of the driver”. Applicant argues that the prior art reference Bogovich teaches static factors from hazard evaluation data, dynamic factors form hazard evaluation data as well as driver behavior factors. The claim interaction term is a cross product that couples a particular sensor detected road condition of a segment to a particular identified behavior of the specific driver who takes cures fast or includes snow combined with driver braking. Bogovich generalizes route risk and temporal weighting of historical incidents but fails to disclose road condition and driver behavior as interaction term. Applicant further argues that the prior art fails to teach road condition detected in real time by sensors and combining driver behavior to score each segment. The weighing as taught by Bogovich applies weighting to historical information over time and not as claimed. With respect to the argument that the prior art fails to teach “road condition detected in real time by sensors and combining driver behavior to score each segment”, the examiner respectfully disagrees. The prior art explicitly teaches “data may be collected at point and time when incident occurred (e.g. weather conditions, traffic conditions, vehicle speed)…traffic information may be retrieved in real-time from respective data sources…”-Col 8 lines 19-26; and teaches “travel route information may be periodically uploaded or uploaded in real-time (or near real-time) via a computer and/or router. The in-vehicle monitoring system may be configured to automatically upload travel route information (and other information) through a home wireless router to a computer. In some advanced monitoring systems, weather and traffic data (and other useful information) may be downloaded (in real-time or near real-time) to the vehicle. In some embodiments, it may be desirable to use mobile devices 112 (with the requisite capabilities) to transmit the information, provide GPS coordinates, and stream in data from other sources”, Col 11 lines 65-Col 12 lines 1-51. See also Col 13 lines 52-59. The examiner maintains that the prior art reference teaches the argued limitation. With respect to the argument, that the prior art fails to disclose road condition and driver behavior as interaction term and weighing as taught by Bogovich applies weighting to historical information over time and not as claimed, the examiner respectfully disagrees. The prior art teaches road and driver behavior interaction for example the speed of a driver on a curve –"Some examples of this other information include, but are not limited to, the vehicle's speed (e.g., a vehicle without a sport suspension attempting to take a dangerous curve at a high speed), vehicle's speed compared to the posted speed limit” -Col 9 lines 5-10; Col 5 lines 15-36 wherein the prior art teaches cause of loss include driving behavior including ran through red light, rear-ended while stopping, rear-ended changing lanes, sideswiped during normal driving, sideswiped changing lanes, Col 6 lines 47-53 wherein the prior art teaches risk information include age, alcohol blood level, distance from home, Col 9 lines 5-9, lines 64-Col 10 lines 1-8, wherein the prior art teaches driver route preference behavior or lower risk driver, Col 10 lines 40-46, lines 58-Col 11 lines 1-9 wherein the prior art teaches applying to risk attributes weights to different types of loss in order to indicate more accurately risk/cost; Col 11 lines 48-55, Col 12 lines 28-Col 13 lines 1-51 wherein the prior art teaches assigning risk value to road segments based on road conditions (snowfall)). With respect to applicant’s argument that the “weighing as taught by Bogovich applies weighting to historical information over time and not as claimed”, the examiner respectfully disagrees. Although Bogovich does teach applying weights to historical information, the prior art also teaches counting the number of each type or road risk that then may be multiplied by a risk rating factor for respective risk type (Col 9 lines 48-56). The prior art further teaches assigning risk values to road segments where relevant respective risk may include road conditions including light rain, snow, fog, ice and driver behavior including drugs, speed, ran through red light, speed of vehicle versus posted speed limit and other road conditions and driving behavior, which is applied to calculate risk value. The prior art does not explicitly teach applying weights to “identified” driving behavior, rather the prior art teaches applying weights to driving behavior as it relates to road condition. Therefore, the 102 rejection has been withdrawn and a new 103 rejection has been applied. Accordingly, Applicant’s argument is moot as the 102 rejection has been withdrawn and modified to a 103 rejection. See rejection below.
Claim Rejections - 35 USC § 103
Applicant's arguments filed 08/05/2026 have been fully considered but they are not persuasive.
In the remarks applicant argues that the prior art Bogovich fails to teach “applying a weighted interaction term between the dynamic road segment condition of the road segment and an identified driving behavior of the driver”. Applicant argues that the prior art reference Bogovich teaches static factors from hazard evaluation data, dynamic factors form hazard evaluation data as well as driver behavior factors. The claim interaction term is a cross product that couples a particular sensor detected road condition of a segment to a particular identified behavior of the specific driver who takes cures fast or includes snow combined with driver braking. Bogovich generalizes route risk and temporal weighting of historical incidents but fails to disclose road condition and driver behavior as interaction term. Applicant further argues that the prior art fails to teach road condition detected in real time by sensors and combining driver behavior to score each segment. The weighing as taught by Bogovich applies weighting to historical information over time and not as claimed. See response above and rejection below.
Claim Interpretation
The specification discloses:
[067] Road segment hazard score= exp(prior accident frequency on the road segment * W1 + road curvature * W 2 + road segment has lane merge * W 3 + road segment has merge from left* W4).
[068] W 1 though W 4 may be weighting factors applied to each variable.
[070] Road segment hazard score = exp(prior accident frequency on the road segment * W 1 +
road curvature * W 2 + road segment has lane merge * W 3 + road segment has merge from
left * W4 + road segment has construction * Ws + number of inches of snow on road
segment* W6+ road segment is wet* W1 + traffic factor* Ws).
[071] In this example algorithm, W1 though Ws represent weighting factors and variables such as
road segment has construction, number of inches of snow on road segment, road segment
is wet, and traffic factor may be dynamic factors used in combination with the static factors
described above.
[073] Road segment hazard score = exp(prior accident frequency on the road segment * W 1 +
road curvature * W 2 + road segment has lane merge * W 3 + road segment has merge from
left * W4 + road segment has construction * Ws + number of inches of snow on road
segment* W6+ road segment is wet* W1 + traffic factor* Ws + (road curvature* driver
takes curves fast* W9) + (number of inches of snow* driver brakes hard* W10)).
[074] In this example, W1 through W10 are weighting factors and variables such as "driver takes
curve fast" and "driver brakes hard" are example driving behaviors that may be used to
determine a road segment safety rating particular to a driver.
[075] The algorithms and variables shown above are for illustrative purposes, and various other
algorithms, various different weighting factors, additional or different variables, etc. may
be used without departing from the invention. The above-described algorithms are merely some examples of algorithms that may be used to determine a road segment hazard score
and should not be viewed as limiting the invention to only those example algorithms
provided.
In light of the specification, the examiner is interpreting the limitation “weighted interaction term between the dynamic road segment condition of the road segment and an identified driving behavior of the driver” to be weighted variables in calculating a score related to road condition variable and driving behavior variable that is weighted.
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.
Claims 1-20 are rejected under 35 U.S.C. § 101 because the instant application is directed to non-patentable subject matter. Specifically, the claims are directed toward at least one judicial exception without reciting additional elements that amount to significantly more than the judicial exception. The rationale for this determination is in accordance with the guidelines of USPTO, applies to all statutory categories, and is explained in detail below.
In reference to Claim(s) 1-9:
STEP 1. Per Step 1 of the two-step analysis, the claims are determined to include a system, as in independent Claim 1 and the dependent claims. Such systems fall under the statutory category of "machine." Therefore, the claims are directed to a statutory eligibility category.
STEP 2A Prong 1. The claimed invention is directed to an abstract idea without significantly more. System claim 1 recites system operations for use to 1) receive data, 2) analyzing driver specific data 3) parsing routes into road segments, 4) receiving geocoded data 5) generating road segment hazard score 6) applying weighted interaction term between road condition and driving behavior 7) generating total hazard score 8) generating route modification based on score threshold 9) receiving preliminary route 10) transmitting route modification. The claimed limitations which under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of systems applied (driving behavior system, hazard score system, control system).
The claimed sensors are generic computer components and tools to perform the mental processes. The human mind through observation, analysis and decision is able to detect whether the roads are wet, flooded, slick, heavy/light traffic, narrow, whether the roads are rough, well maintained, etc. and able to determine whether the driver is speeding, adjusting the driving according to road conditions, etc. The sensors as claimed are recited at a high level of generality and merely automates functions that could reasonable be performed using mental concepts, therefore acting as a generic computer to perform the abstract idea. The human mind also is capable of determining which road conditions are higher risk, which driving behavior is safe, unsafe, dangerous and weight which situation is more important when scoring/grading/rating different road segments for a safe/unsafe travel. Therefore, the limitations, encompass human thought processes of observation, analysis, evaluation and communication of result which, where the data interpretation is perceptible only in the human mind. See In re TLl Commc'ns LLC Patent Litig., 823 F.3d 607, 611 (Fed. Cir. 2016); FairWarning IP, LLC v. latric Sys., Inc., 839 F.3d 1089, 1093-94 (Fed. Cir. 2016)
The specification describes the inventive concept as searching, analyzing and applying a generating hazard score for predetermined routes from a current location to a specified destination, where based on hazard score thresholds modifying the predetermined routes a newer route with lesser hazards. (spec ¶ 0005). The specification further discloses a hazard based insurance system applied where the system determines route hazards for use in pricing insurance coverage (spec ¶ 0021). Accordingly, the claimed subject matter in light of the specification, when considered as a whole the claimed subject matter is directed toward risk mitigation and commercial activities, wherein the generated hazard score for analyzed road segments is applied to determine and transmit a route under a hazard threshold. Such concepts can be found in the abstract category of commercial interactions and marketing. These concepts are enumerated in Section I of the 2019 revised patent subject matter eligibility guidance published in the federal register (84 FR 50) on January 7, 2019) is directed toward abstract category of mental processes and methods of organizing human activity.
STEP 2A Prong 2: The identified judicial exception is not integrated into a practical application because the claims fail to provide indications of patent eligible subject matter that integrate the alleged abstract idea into a practical application. The additional elements recited in the claim beyond the abstract idea include a system comprising a driving behavior system, hazard score analysis system and control system.
The additional element “driving behavior system” is applied to perform the operations “receiving driver specific data”, the “hazard score analysis system” applied to perform the operation “receiving geocoded data”, and the “control system” applied to perform the operations “receiving …preliminary navigational route” and “transmitting…route modifications”. According to MPEP 2106.05(d) II (see also MPEP 2106.05(g)) the courts have recognized the following computer functions are claimed in a merely generic manner (e.g., at a high level of generality) where technology is merely applied to perform the abstract idea or as insignificant extra-solution activity.
Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014)
The claim limitations (“receiving driver specific data”, “receiving geocoded data”, “receiving …preliminary navigational route” and “transmitting…route modifications”) are recited at a high level of generality without details of technical implementation and thus are insignificant extra solution activity.
The additional element beyond the abstract idea “driving behavior system” is further applied to perform the operations “analyzing driver specific data”, the “hazard score analysis system” applied to perform the operation “parsing preliminary…route into …segments”, “applying weighted interaction term”, “generating a road segment hazard score…”, “generating a total hazard score” and “generating …route modifications” which individually are not directed toward any indications of patent eligibility according to MPEP 2106.05 (a)-(c), (e )-(h). This is because individually the focus of the operations is analysis of data acted upon for use in scoring hazards applied to determine an output of navigational routes to a destination as it relates to a hazard threshold.
When the claims are taken as an ordered combination or as a whole, the combination of limitations, the combination of limitations 1-2 and 3 are directed toward analyzing received data to identify user behavior and parse navigational routes into road segments which are processes not directed toward the systems themselves instead directed toward the analysis and manipulation of data for analysis related to human behavior. The combination of limitations 1-3 and 4-6 is directed toward receiving additional data and generating for each road segment hazard score based on the limitations 1-4 used to generate a total hazard score- as a combination is not directed toward the system itself or any other technology, but instead to generate score reflecting road hazards. The combination of limitations 1-6 and 7 is directed toward modifying routes in response to the score determined from limitations 1-6 when a hazard score is above a threshold. The combination of limitations 1-7 and 8-9 is directed toward receiving and outputting the results of limitations 1-7. Therefore, the combination 1-6 and 7-8 is not directed toward the system itself or any other technology, but instead to generate score reflecting road hazards that are applied to generate and modify navigational routes based on hazard analysis of the routes.
When considered as a whole or ordered combination the combination of limitations 1-8 is directed toward - which as a whole is directed toward analyzing and parsing driver and road segment route data to generate hazard score in order to determine a navigational route of the road segment applying the hazard score, wherein based on a hazard score threshold the route is modified and outputting the results. The recited limitations are high level lacking technical details directed toward expected outcomes for use in routing road segments according to hazard threshold to a destination. The weighting of variables used to generate driving scores used to change routes to a different navigation routes does not impact or improve upon any underlying technology. The calculated score using weighted variables is merely mathematical calculations based on selected information. The mathematical calculation of a score using weighted variables involved here has no substantial practical application except in connection with a computer. The generation of a modified route based on scores is an algorithm that has no impact upon the computer, its functionality or field its functionality or field is patent ineligible. Therefore, the generating of changed route is not sufficient to transform the claim into patent eligible subject matter. The claim limitations merely apply technology to collect data, analyzed data and output the result of the analysis.
The combinations of parts is not directed toward any of the indications of patent eligible subject matter under step 2A prong 2, but instead a analyzing and scoring human behavior and road hazard risk. MPEP guidance (see MPEP 2106.05 (a)-(c), (e )-(h). The claim limitations as a whole, as an ordered combination and the combination of steps not integrate the judicial exception into a practical application as the claim process fails to impose meaningful limits upon the abstract idea. . This is because the claimed subject matter fails to provide additional elements or combination or elements that go beyond applying technology as a tool to perform the identified abstract idea. The functions recited by the system in the claims recite the concept of a risk mitigation and the analysis of human behavior. The claim limitations and specification lacks technical disclosure on what the technical problem was and how the claimed limitations provide a technical solution to a technical problem rather than a solution to a problem found in the abstract idea. Taking the claim elements separately, or as a combination, the operation performed by the system at each step of the process is purely in terms of results desired and devoid of implementation of details. Technology is not integral to the process as the claimed subject matter is so high level that any generic programming could be applied and the functions could be performed by any known means. Furthermore, the claimed functions do not provide an operation that could be considered as sufficient to provide a technological implementation or application of/or improvement to this concept (i.e. integrated into a practical application).
The integration of elements do not improve upon technology or improve upon computer functionality or capability in how computers carry out one of their basic functions. The integration of elements do not provide a process that allows computers to perform functions that previously could not be performed. The integration of elements do not provide a process which applies a relationship to apply a new way of using an application. The limitations do not recite a specific use machine or the transformation of an article to a different state or thing. The limitations do not provide other meaningful limits beyond generally linking the use of the abstract idea to a particular technological environment. The resource claimed performing the steps is merely a “field of use” application of technology. The instant application, therefore, still appears only to implement the abstract idea to the particular technological environments apply what generic computer functionality in the related arts. The steps are still a combination made to perform a risk analysis for driving activity and does not provide any of the determined indications of patent eligibility set forth in the 2019 USPTO 101 guidance. The additional steps only add to those abstract ideas using generic functions, and the claims do not show improved ways of, for example, an particular technical function for performing the abstract idea that imposes meaningful limits upon the abstract idea. Moreover, Examiner was not able to identify any specific technological processes that goes beyond merely confining the abstract idea in a particular technological environment, which, when considered in the ordered combination with the other steps, could have transformed the nature of the abstract idea previously identified. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim provides no technical details regarding how the operations performed by the “resource”. Instead, similar to the claims at issue in Intellectual Ventures I LLC v. Capital One Financial Corp., 850 F.3d 1332 (Fed. Cir. 2017), “the claim language . . . provides only a result-oriented solution with insufficient detail for how a computer accomplishes it. Our law demands more.” Intellectual Ventures, 850 F.3d at 1342 (citing Elec. Power Grp. LLC v. Alstom, S.A., 830 F.3d 1350, 1356 (Fed. Cir. 2016)). The claim is directed to an abstract idea
STEP 2B; The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to concepts of the abstract idea into a practical application. The additional elements recited in the claim beyond the abstract idea include a system comprising a driving behavior system, hazard score analysis system and control system.
Taking the claim elements separately, the function performed by the computer at each step of the process is purely conventional. The claimed system(s) are recited as performing the functions “receiving…data”, “analyzing…data”, “parsing…data”, “applying weights”, “generating …hazard score”, “generating …route modifications” and “transmitting …modifications” – which individually, are some of the most basic functions of a computer systems.
The systems claimed are merely applied with the abstract idea and are not enough to qualify as “significantly more”, as the system is used as a tool with an abstract idea, amounting to no more than mere instructions to implement the abstract idea on a computer system, requiring no more than a generic system to perform generic computer functions that are well understood activities known to the industry. The system claims fail to offer a meaningful limitation beyond generally linking the use of the method to a particular technological environment, that is, implementation via computers.... The claim limitations do not recite that any of the “devices” perform more than a high level generic function .... None of the limitations recite technological implementation details for any of these steps, but instead recite only results desired to be achieved by any and all possible means.
When the claims are taken as a whole, as an ordered combination, the combination of steps does not add “significantly more” by virtue of considering the steps as a whole, as an ordered combination. All of these computer functions are generic, routine, conventional computer activities that are performed only for their conventional uses. See Elec. Power Grp. v. Alstom S.A., 830 F.3d 1350, 1353 (Fed. Cir. 2016). Also see In re Katz Interactive Call Processing Patent Litigation, 639 F.3d 1303, 1316 (Fed. Cir. 2011) Absent a possible narrower construction of the terms “receiving…data”, “analyzing…data”, “parsing…data”, “applying weights”, “generating …hazard score”, “generating …route modifications” and “transmitting …modifications”... are functions can be achieved by any general purpose computer without special programming. The system functions are nominally claimed and do not provide any particular technological technology or as a combination a process directed toward the technology itself. Even though the claim is directed to a system, the claim is not "truly drawn to a specific" system, but rather is directed toward the operations to analyze driving data and road segment data in order to generate hazard scores used to generate or modify road segment that combined provide a route to a destination based on the hazard analysis. Simply reciting the use of a system to performed operations that could entirely be performed in the human mind will not change the analysis. This claim was determined not to meet the Alice/May 2A and 2B test. The "incidental use" of a computer did not allow the claim to meet the Alice 2A or 2B requirements. None of these activities are used in some unconventional manner nor do any produce some unexpected result. In short, each step does no more than require a generic computer to perform generic computer functions.
As to the data operated upon, "even if a process of collecting and analyzing information is 'limited to particular content' or a particular 'source,' that limitation does not make the collection and analysis other than abstract." SAP America, Inc. v. Invest Pic LLC, 898 F.3d 1161, 1168 (Fed. Cir. 2018). Considered as an ordered combination, the computer components of Applicant’s claimed functions add nothing that is not already present when the steps are considered separately. The sequence of data reception-analysis modification-transmission is equally generic and conventional. See Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 715 (Fed. Cir. 2014) (sequence of receiving, selecting, offering for exchange, display, allowing access, and receiving payment recited as an abstraction), Inventor Holdings, LLC v. Bed Bath & Beyond, Inc., 876 F.3d 1372, 1378 (Fed. Cir. 2017) (sequence of data retrieval, analysis, modification, generation, display, and transmission), Two-Way Media Ltd. v. Comcast Cable Communications, LLC, 874 F.3d 1329, 1339 (Fed. Cir. 2017) (sequence of processing, routing, controlling, and monitoring).
The ordered combination of the claimed steps recited using technology to obtain data, analyze data and output the result where the result is applied to modify a travel route. According to Electric Power Group, applying technology to collect data, analyze data and output the result is well understood and routine use of technology. Accordingly the ordered combination as a whole of the technical process claimed is well understood and routine. With respect to applicant’s “significantly more” argument, in referencing Alice reciting additional elements that include “apply it” (or an equivalent) with an abstract idea, are not enough to qualify as “significantly more”. The recited functions of the underlying additional elements (driving behavior system, sensors, control system) are recited at a high level or generality without technical details, amounting to no more than mere instructions to implement the abstract idea on a computer. The limitations require no more than a generic computer elements to perform generic computer functions that are well understood activities known to the industry. As a result, none of the underlying technology recited by the claims offers a meaningful limitation beyond generally linking the use of the method to a particular technological environment, that is, implementation via computers.... The claim limitations do not recite that any of the “devices” perform more than a high level generic function .... None of the limitations recite technological implementation details for any of these steps, but instead recite only results desired to be achieved by any and all possible means.... Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The ordering of the steps is therefore ordinary and conventional. The analysis concludes that the claims do not provide an inventive concept because the additional elements recited in the claims do not provide significantly more than the recited judicial exception.
According to 2106.05 well-understood and routine processes to perform the abstract idea is not sufficient to transform the claim into patent eligibility. As evidence the examiner provides:
With respect to “driving behavior system”, the specification describes:
[0038]The driving behavior module 214 may analyze sensor data received from one or more of
sensors 216a-216c and may identify one or more driving behaviors of a particular driver or
operator of the vehicle. For instance, the driving behavior module 214 may determine
whether the user generally drives at a speed over the speed limit, generally follows too
closely behind a vehicle in front of him, generally brakes hard, and the like. This
information may be transmitted to the hazard score analysis module 210 for use in
determining a hazard score for a particular road segment.
[0039] In some arrangements, raw sensor data (e.g., from one or more of sensors 216a-216c) may
be used in conjunction with other data (e.g., from data store 204, 206) to generate the road
segment hazard score. For instance, one or more sensors may be used to detect
precipitation. That information may be provided to the hazard score analysis module 210
in real-time, or near real-time, and may be combined with other data (e.g., accident data,
traffic volume data, etc.) for the road segment, and/or user driving behavior data, to
generate or determine the road segment hazard score for the road segment. In some
examples, based on this real-time or near real-time data, any hazards identified (e.g.,
hazards appearing along the route being travelled) may be transmitted to the user, via an
audible warning or alert displayed on a computing device, such as an on-board vehicle
computing device, mobile device of the user, etc. The hazards may be unique to the driver
based on driving characteristic data collected for the user, as well as current external or
environmental conditions.
[0065]… Additionally, or alternatively, hazard evaluation information may
be received from driving behavior module 214. As discussed above, driving behavior
module may analyze sensor data received from one or more of sensors 216a-216c and may
identify one or more driving behaviors of a particular driver or operator of the vehicle. For
instance, the driving behavior module 214 may determine whether the user generally drives
at a speed over the speed limit, generally follows too closely behind a vehicle in front of
him, generally brakes hard, and the like. This information may be received at step 404 for
use in determining a hazard score for a particular road segment.
With respect to the limitation “hazard score analysis system” and “control system”, the specification describes:
[0022] Input/Output (I/O) 109 may include a microphone, keypad, touch screen, and/or stylus through which a user of the real-time hazard-based insurance computing device 101 may provide input, and may also include one or more of a speaker for providing audio output and a video display device for providing textual, audiovisual and/or graphical output. Software may be stored within memory 115 and/or storage to provide instructions to processor 103 for enabling real-time hazard-based insurance computing device 101 to perform various actions. For example, memory 115 may store software used by the real-time hazard-based insurance device 101, such as an operating system 117, application programs 119, and an associated internal database 121. The various hardware memory units in memory 115 may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. Certain devices and systems within hazard unit based insurance systems may have minimum hardware requirements in order to support sufficient storage capacity, processing capacity, analysis capacity, network communication, etc. For instance, in some embodiments, one or more nonvolatile hardware memory units having a minimum size (e.g., at least 1 gigabyte (GB), 2 GB, 5 GB, etc.), and/or one or more volatile hardware memory units having a minimum size (e.g., 256 megabytes (MB), 512 MB, 1 GB, etc.) may be used in a real-time hazard-based insurance computing device 101 (e.g., a personal mobile device 151, vehicle-based device 161, insurance system server 141, etc.), in order to receive a preliminary navigational route, parse the preliminary navigational route into a plurality of road segments, receive, from at least one sensor arranged on a vehicle, driving data associated with a driver of the vehicle or the preliminary navigational route, calculate, for each road segment of the plurality of road segments and based in part on the driving data, a road segment hazard score, calculate a total route hazard score based on the road segment hazard score calculated for each road segment of the plurality of road segments, transmit the total route hazard score to a first computing device and a second computing device, receive, from the first computing device, a first bid to insure the preliminary navigational route for a first premium amount, receive, from the second computing device, a second bid to insure the preliminary navigational route for a second premium amount, and select one of the first bid and the second bid, etc., using the various devices of the hazard unit based insurance systems. Memory 115 also may include one or more physical persistent memory devices and/or one or more non-persistent memory devices. Memory 115 may include, but is not limited to, random access memory (RAM) 105, read only memory (ROM) 107, electronically erasable programmable read only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by processor 103.
[0031] The real-time hazard-based insurance system 200 may include one or more modules that may include hardware and/or software configured to perform various functions within the real-time hazard-based insurance system 200. The one or more modules may be separate, physical devices or, in other examples, one or more modules may be part of the same physical device.
[0032] The real-time hazard-based insurance system 200 may include a control module 202. Control module 202 may be configured to receive a preliminary navigational route that a driver plans on traveling or on which a driver is currently traveling. For example, the preliminary navigational route may be received from the user via a computing device, such as one or more of computing devices 212a-212f. For instance, the preliminary navigational route may be received via an application (e.g., online or mobile application) executing on a smartphone 212a, personal digital assistant (PDA) 212b, tablet 212c, cell phone 212d, or other computing device 212e. In some examples, the preliminary navigational route may be input by a user on vehicle display 212f and transmitted to control module 202. Control module 202 may transmit the preliminary navigational route to a hazard score analysis module 210. The hazard score analysis module 210 may parse the preliminary navigational route into one or more road segments. The hazard score analysis module 210 may receive data from one or more data stores, such as data stores 204 and 206, and may determine a hazard score for each of the one or more road segments based on the received data. In some examples, a road segment may be some or all of a particular road. The road segments may have varying lengths or distances, may be formed of various materials, may include various types of roads (e.g., highway, country road, etc.), and the like.
[0034] Accordingly, some information may be received by the hazard score analysis module 210 from internal data store 204. The internal data store 204 may include information associated with accidents associated with the road segment, accidents associated with that type of road or one or more features of the road segment (e.g., number of bends, merging, etc.), severity of accidents associated with the road segment (e.g., based on insurance claim data), number of accidents associated with the road segment, time of day of accident, date of accident, and the like. Accident information received from internal data store 204 may be collected from historical accident or claim information of the insurance provider entity 201. The internal data store 204 may also include information associated with conditions of the road segment (e.g., pot holes, type of road, etc.). In some arrangements, this information may be received from a telematics device associated with one or more vehicles, and associated sensors detecting such information. The received telematics data may be stored and used to determine, for example, a road segment hazard score.
[0036] The hazard score analysis module 210 may detect a location of a vehicle (e.g., via global positioning system (GPS) data collected from the vehicle) and may identify a road segment associated with the location of the vehicle. This identification of the road segment may be performed by comparing the location coordinates from the vehicle to location coordinates of roads obtained, for example, from a mapping company or from analysis of many vehicles' location coordinates over time. The hazard score analysis module 210 may then receive data from various data stores, such as data store 204 and/or data store 206, and may generate a road segment hazard score for the identified road segment.
[0037] The road segment hazard score may be generated by the hazard score analysis module 210 based on data associated with the road segment, as discussed above, as well as data associated with a driver of the vehicle. For instance, driver-specific data may be received by the azard score analysis module 210 and may be used in conjunction with the various types of data discussed above, to determine a road segment hazard score for a particular road segment. For instance, the real-time hazard-based insurance system 200 may include a plurality of sensors 216a-216c. The sensors 216a-216c may be any of various types of sensors, as will be discussed more fully herein. The sensors 216a-216c may be used to obtain data associated with driving behaviors of the user, such as hard braking, speeding, swerving, rapid acceleration, and the like. In another example, one or more sensors may be used to detect environmental conditions such as precipitation, humidity, cloud cover, or the like. In still another example, one or more sensors may be used to determine road conditions or to obtain information from outside sources (e.g., external databases, or the like) regarding traffic conditions, types of road (e.g., two-lane road, four-lane road), speed limit of the road, or the like. The data from one or more sensors 216a-216c, which may include data from combinations of different types of sensors, may be transmitted to driving behavior module 214 for analysis.
[067] Road segment hazard score= exp(prior accident frequency on the road segment * W1 + road curvature * W 2 + road segment has lane merge * W 3 + road segment has merge from left* W4).
[068] W 1 though W 4 may be weighting factors applied to each variable.
[070] Road segment hazard score = exp(prior accident frequency on the road segment * W 1 +
road curvature * W 2 + road segment has lane merge * W 3 + road segment has merge from
left * W4 + road segment has construction * Ws + number of inches of snow on road
segment* W6+ road segment is wet* W1 + traffic factor* Ws).
[071] In this example algorithm, W1 though Ws represent weighting factors and variables such as
road segment has construction, number of inches of snow on road segment, road segment
is wet, and traffic factor may be dynamic factors used in combination with the static factors
described above.
[073] Road segment hazard score = exp(prior accident frequency on the road segment * W 1 +
road curvature * W 2 + road segment has lane merge * W 3 + road segment has merge from
left * W4 + road segment has construction * Ws + number of inches of snow on road
segment* W6+ road segment is wet* W1 + traffic factor* Ws + (road curvature* driver
takes curves fast* W9) + (number of inches of snow* driver brakes hard* W10)).
[074] In this example, W1 through W10 are weighting factors and variables such as "driver takes
curve fast" and "driver brakes hard" are example driving behaviors that may be used to
determine a road segment safety rating particular to a driver.
[075] The algorithms and variables shown above are for illustrative purposes, and various other
algorithms, various different weighting factors, additional or different variables, etc. may
be used without departing from the invention. The above-described algorithms are merely some examples of algorithms that may be used to determine a road segment hazard score
and should not be viewed as limiting the invention to only those example algorithms
provided.
US Pub No. 2014/0344008 A1 by Gammage et al teaches "The average score 812 for the device technology attribute 814 is the average value of the sum of the scores 816a- f"; US Pub. No. 20100023442 A1 by O'Hara et al discloses "calculating the average and/or cumulative total of the score or factor over a fixed time interval"; US Pub No. 2009/0144095 A1 by Gurinder et al
The instant application, therefore, still appears to only implement the abstract ideas to the particular technological environments using what is generic components and functions in the related arts. The claim is not patent eligible.
The remaining dependent claims—which impose additional limitations—also fail to claim patent-eligible subject matter because the limitations cannot be considered statutory. In reference to claims 2-9 these dependent claim have also been reviewed with the same analysis as independent claim 1. Dependent claim 2 is directed toward real time route modification- a business process using technology. Dependent claim(s) 3 and 4 are directed toward data content-non-functional descriptive subject matter. Dependent claim 5 is directed toward driving behavior data for use in generating hazard scores weighted – mathematical concepts. Dependent claim 6 is directed toward generating routes which lower scores- risk mitigation. Dependent claim 7 is directed toward applying user interfaces to indicate route modifications-insignificant extra solution activity. Dependent claim 8 is directed toward summing/averaging hazard score for each route segment- mathematical concepts. Dependent claim 9 is directed toward receiving data- insignificant extra solution activity
The dependent claim(s) have been examined individually and in combination with the preceding claims, however they do not cure the deficiencies of claim 1. Where all claims are directed to the same abstract idea, “addressing each claim of the asserted patents [is] unnecessary.” Content Extraction & Transmission LLC v. Wells Fargo Bank, Nat 7 Ass ’n, 776 F.3d 1343, 1348 (Fed. Cir. 2014). If applicant believes the dependent claims 2-9 are directed towards patent eligible subject matter, they are invited to point out the specific limitations in the claim that are directed towards patent eligible subject matter.
In reference to Claim(s) 10-15:
STEP 1. Per Step 1 of the two-step analysis, the claims are determined to include a non-transitory computer readable medium, as in independent Claim 10 and the dependent claims. Such mediums fall under the statutory category of "manufacture." Therefore, the claims are directed to a statutory eligibility category.
STEP 2A Prong 1. The claimed invention is directed to an abstract idea without significantly more. Medium claim 10 recites executed instruction of a processor to 1) receive data, 2) analyze driver specific data 3) parse routes into road segments, 4) receive geocoded data 5) apply weights 6) generate road segment hazard score 7) generate total hazard score 8) generate route modification based on score threshold 9) transmit route modification. The claimed limitations which under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of systems applied (driving behavior system, hazard score system, control system).
The claimed physical structures (readable medium) are generic computer components and tools to perform the mental processes. The computer components are recited at a high level of generality and merely automates functions that could reasonable be performed using mental concepts, therefore acting as a generic computer components to perform the abstract idea.
. The steps recite steps that can easily be performed in the human mind as mental processes because the operations “receive driver specific data”, “receive geocoded data” which mimics mental processes of observation. The operations “analyze driver specific data”, “parse …route into…segments”, “apply weights”, “generate…score”, “apply weight”, “generate a total…score” and “generate …route modifications”, mimics mental processes of analysis and evaluation. The limitation “transmit …modification” is merely communication of results. Therefore, the limitations, encompass human thought processes of observation, analysis, evaluation and communication of result which, where the data interpretation is perceptible only in the human mind. See In re TLl Commc'ns LLC Patent Litig., 823 F.3d 607, 611 (Fed. Cir. 2016); FairWarning IP, LLC v. latric Sys., Inc., 839 F.3d 1089, 1093-94 (Fed. Cir. 2016)
The specification describes the inventive concept as searching, analyzing and applying a generating hazard score for predetermined routes from a current location to a specified destination, where based on hazard score thresholds modifying the predetermined routes a newer route with lesser hazards. (spec ¶ 0005). The specification further discloses a hazard based insurance system applied where the system determines route hazards for use in pricing insurance coverage (spec ¶ 0021). Accordingly, the claimed subject matter in light of the specification, when considered as a whole the claimed subject matter is directed toward risk mitigation and commercial activities, wherein the generated hazard score for analyzed road segments is applied to determine and transmit a route under a hazard threshold. Such concepts can be found in the abstract category of commercial interactions and marketing. These concepts are enumerated in Section I of the 2019 revised patent subject matter eligibility guidance published in the federal register (84 FR 50) on January 7, 2019) is directed toward abstract category of mental processes and methods of organizing human activity.
STEP 2A Prong 2: The identified judicial exception is not integrated into a practical application because the claims fail to provide indications of patent eligible subject matter that integrate the alleged abstract idea into a practical application. The additional elements recited in the claim beyond the abstract idea include non-transitory computer readable media storing instructions executed by one or more processors.
The additional element “one or more processors” executing instructions is applied to perform the operations “receive driver specific data”, “receive geocoded data”, and “transmit…route modifications”. According to MPEP 2106.05(d) II (see also MPEP 2106.05(g)) the courts have recognized the following computer functions are claimed in a merely generic manner (e.g., at a high level of generality) where technology is merely applied to perform the abstract idea or as insignificant extra-solution activity.
Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014)
The claim limitations (“receiving driver specific data”, “receiving geocoded data”, and “transmitting…route modifications”) are recited at a high level of generality without details of technical implementation and thus are insignificant extra solution activity.
The additional element beyond the abstract idea “one or more processors” is further applied to perform the operations “analyze driver specific data”, “parse preliminary…route into …segments”, “apply weights”, “generate a road segment hazard score…”, “generate a total hazard score” and “generate …route modifications” which individually are not directed toward any indications of patent eligibility according to MPEP 2106.05 (a)-(c), (e )-(h). This is because individually the focus of the operations is analysis of data acted upon for use in scoring hazards applied to determine an output of navigational routes to a destination as it relates to a hazard threshold.
When the claims are taken as an ordered combination or as a whole, the combination of limitations, the combination of limitations 1-2 and 3 are directed toward analyzing received data to identify user behavior and parse navigational routes into road segments which are processes not directed toward the systems themselves instead directed toward the analysis and manipulation of data for analysis related to human behavior. The combination of limitations 1-3 and 4-6 is directed toward receiving additional data, applying weights and generating for each road segment hazard score based on the limitations 1-4 used to generate a total hazard score- as a combination is not directed toward the system itself or any other technology, but instead to generate score reflecting road hazards. The combination of limitations 1-6 and 7 is directed toward modifying routes in response to the score determined from limitations 1-6 when a hazard score is above a threshold. The combination of limitations 1-7 and 8 is directed toward outputting the results of limitations 1-7. Therefore, the combination 1-6 and 7-8 is not directed toward the readable medium itself or any other technology, but instead to generate score reflecting road hazards that are applied to generate and modify navigational routes based on hazard analysis of the routes.
When considered as a whole or ordered combination the combination of limitations 1-8 is directed toward - which as a whole is directed toward analyzing and parsing driver and road segment route data to generate hazard score in order to determine a navigational route of the road segment applying the hazard score, wherein based on a hazard score threshold the route is modified and outputting the results. The weighting of variables used to generate driving scores used to change routes to a different navigation routes does not impact or improve upon any underlying technology. The calculated score using weighted variables is merely mathematical calculations based on selected information. The mathematical calculation of a score using weighted variables involved here has no substantial practical application except in connection with a computer. The generation of a modified route based on scores is an algorithm that has no impact upon the computer, its functionality or field its functionality or field is patent ineligible. Therefore, the generating of changed route is not sufficient to transform the claim into patent eligible subject matter. The claim limitations merely apply technology to collect data, analyzed data and output the result of the analysis. The recited limitations are high level lacking technical details directed toward expected outcomes for use in routing road segments according to hazard threshold to a destination.
The combinations of parts is not directed toward any of the indications of patent eligible subject matter under step 2A prong 2, but instead a analyzing and scoring human behavior and road hazard risk. MPEP guidance (see MPEP 2106.05 (a)-(c), (e )-(h). The claim limitations as a whole, as an ordered combination and the combination of steps not integrate the judicial exception into a practical application as the claim process fails to impose meaningful limits upon the abstract idea. . This is because the claimed subject matter fails to provide additional elements or combination or elements that go beyond applying technology as a tool to perform the identified abstract idea. The functions recited by the medium executed instructions in the claims recite the concept of a risk mitigation and the analysis of human behavior. The claim limitations and specification lack technical disclosure on what the technical problem was and how the claimed limitations provide a technical solution to a technical problem rather than a solution to a problem found in the abstract idea. Taking the claim elements separately, or as a combination, the operation performed by the media instructions at each step of the process is purely in terms of results desired and devoid of implementation of details. Technology is not integral to the process as the claimed subject matter is so high level that any generic programming could be applied and the functions could be performed by any known means. Furthermore, the claimed functions do not provide an operation that could be considered as sufficient to provide a technological implementation or application of/or improvement to this concept (i.e. integrated into a practical application).
The integration of elements do not improve upon technology or improve upon computer functionality or capability in how computers carry out one of their basic functions. The integration of elements do not provide a process that allows computers to perform functions that previously could not be performed. The integration of elements do not provide a process which applies a relationship to apply a new way of using an application. The limitations do not recite a specific use machine or the transformation of an article to a different state or thing. The limitations do not provide other meaningful limits beyond generally linking the use of the abstract idea to a particular technological environment. The resource claimed performing the steps is merely a “field of use” application of technology. The instant application, therefore, still appears only to implement the abstract idea to the particular technological environments apply what generic computer functionality in the related arts. The steps are still a combination made to perform a risk analysis for driving activity and does not provide any of the determined indications of patent eligibility set forth in the 2019 USPTO 101 guidance. The additional steps only add to those abstract ideas using generic functions, and the claims do not show improved ways of, for example, an particular technical function for performing the abstract idea that imposes meaningful limits upon the abstract idea. Moreover, Examiner was not able to identify any specific technological processes that goes beyond merely confining the abstract idea in a particular technological environment, which, when considered in the ordered combination with the other steps, could have transformed the nature of the abstract idea previously identified. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim provides no technical details regarding how the operations performed by the “resource”. Instead, similar to the claims at issue in Intellectual Ventures I LLC v. Capital One Financial Corp., 850 F.3d 1332 (Fed. Cir. 2017), “the claim language . . . provides only a result-oriented solution with insufficient detail for how a computer accomplishes it. Our law demands more.” Intellectual Ventures, 850 F.3d at 1342 (citing Elec. Power Grp. LLC v. Alstom, S.A., 830 F.3d 1350, 1356 (Fed. Cir. 2016)). The claim is directed to an abstract idea
STEP 2B; The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to concepts of the abstract idea into a practical application. The additional elements recited in the claim beyond the abstract idea include non-transitory computer-readable media having instructions stored thereon that, when executed by one or more processors.
Taking the claim elements separately, the function performed by the computer at each step of the process is purely conventional. The claimed system(s) are recited as performing the functions “receiving…data”, “analyzing…data”, “parsing…data”, “applying weights”, “generating …hazard score”, “generating …route modifications” and “transmitting …modifications” – which individually, are some of the most basic functions of a computer systems.
The one or more processors executing instructions claimed are merely applied with the abstract idea and are not enough to qualify as “significantly more”, as the system is used as a tool with an abstract idea, amounting to no more than mere instructions to implement the abstract idea on a computer system, requiring no more than a generic system to perform generic computer functions that are well understood activities known to the industry. The manufacture claims fail to offer a meaningful limitation beyond generally linking the use of the method to a particular technological environment, that is, implementation via computers.... The claim limitations do not recite that any of the “devices” perform more than a high level generic function .... None of the limitations recite technological implementation details for any of these steps, but instead recite only results desired to be achieved by any and all possible means.
When the claims are taken as a whole, as an ordered combination, the combination of steps does not add “significantly more” by virtue of considering the steps as a whole, as an ordered combination. All of these computer functions are generic, routine, conventional computer activities that are performed only for their conventional uses. See Elec. Power Grp. V. Alstom S.A., 830 F.3d 1350, 1353 (Fed. Cir. 2016). Also see In re Katz Interactive Call Processing Patent Litigation, 639 F.3d 1303, 1316 (Fed. Cir. 2011). Absent a possible narrower construction of the terms “receiving…data”, “analyzing…data”, “parsing…data”, “generating …hazard score”, “generating …route modifications” and “transmitting …modifications”... are functions can be achieved by any general purpose computer without special programming. The system functions are nominally claimed and do not provide any particular technological technology or as a combination a process directed toward the technology itself. Even though the claim is directed to a system, the claim is not “truly drawn to a specific” system, but rather is directed toward the operations to analyze driving data and road segment data in order to generate hazard scores used to generate or modify road segment that combined provide a route to a destination based on the hazard analysis. Simply reciting the use of a system to performed operations that could entirely be performed in the human mind will not change the analysis. This claim was determined not to meet the Alice/May 2A and 2B test. The “incidental use” of a computer did not allow the claim to meet the Alice 2A or 2B requirements. None of these activities are used in some unconventional manner nor do any produce some unexpected result. In short, each step does no more than require a generic computer to perform generic computer functions.
As to the data operated upon, “even if a process of collecting and analyzing information is ‘limited to particular content’ or a particular ‘source,’ that limitation does not make the collection and analysis other than abstract.” SAP America, Inc. v. Invest Pic LLC, 898 F.3d 1161, 1168 (Fed. Cir. 2018). Considered as an ordered combination, the computer components of Applicant’s claimed functions add nothing that is not already present when the steps are considered separately. The sequence of data reception-analysis modification-transmission is equally generic and conventional. See Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 715 (Fed. Cir. 2014) (sequence of receiving, selecting, offering for exchange, display, allowing access, and receiving payment recited as an abstraction), Inventor Holdings, LLC v. Bed Bath & Beyond, Inc., 876 F.3d 1372, 1378 (Fed. Cir. 2017) (sequence of data retrieval, analysis, modification, generation, display, and transmission), Two-Way Media Ltd. V. Comcast Cable Communications, LLC, 874 F.3d 1329, 1339 (Fed. Cir. 2017) (sequence of processing, routing, controlling, and monitoring). The ordering of the steps is therefore ordinary and conventional. The analysis concludes that the claims do not provide an inventive concept because the additional elements recited in the claims do not provide significantly more than the recited judicial exception.
According to 2106.05 well-understood and routine processes to perform the abstract idea is not sufficient to transform the claim into patent eligibility. As evidence the examiner provides:
With respect to “computer readable media”, the specification describes:
[0019] As will be appreciated by one of skill in the art upon reading the following disclosure, various aspects described herein may be embodied as a method, a computer system, or a computer program product. Accordingly, those aspects may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, such aspects may take the form of a computer program product stored by one or more computer-readable storage media having computer-readable program code, or instructions, embodied in or on the storage media. Any suitable computer-readable storage media may be utilized, including hard disks, CD-ROMs, optical storage devices, magnetic storage devices, and/or any combination thereof. In addition, various signals representing data or events as described herein may be transferred between a source and a destination in the form of electromagnetic waves traveling through signal-conducting media such as metal wires, optical fibers, and/or wireless transmission media (e.g., air and/or space).
[0030]… The various hardware memory units in memory 115 may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. Certain devices and systems within hazard unit based insurance systems may have minimum hardware requirements in order to support sufficient storage capacity, processing capacity, analysis capacity, network communication, etc. For instance, in some embodiments, one or more nonvolatile hardware memory units having a minimum size (e.g., at least 1 gigabyte (GB), 2 GB, 5 GB, etc.), and/or one or more volatile hardware memory units having a minimum size (e.g., 256 megabytes (MB), 512 MB, 1 GB, etc.) may be used in a real-time hazard-based insurance computing device 101 (e.g., a personal mobile device 151, vehicle-based device 161, insurance system server 141, etc.), in order to receive a preliminary navigational route, parse the preliminary navigational route into a plurality of road segments, receive, from at least one sensor arranged on a vehicle, driving data associated with a driver of the vehicle or the preliminary navigational route, calculate, for each road segment of the plurality of road segments and based in part on the driving data, a road segment hazard score, calculate a total route hazard score based on the road segment hazard score calculated for each road segment of the plurality of road segments, transmit the total route hazard score to a first computing device and a second computing device, receive, from the first computing device, a first bid to insure the preliminary navigational route for a first premium amount, receive, from the second computing device, a second bid to insure the preliminary navigational route for a second premium amount, and select one of the first bid and the second bid, etc., using the various devices of the hazard unit based insurance systems. Memory 115 also may include one or more physical persistent memory devices and/or one or more non-persistent memory devices. Memory 115 may include, but is not limited to, random access memory (RAM) 105, read only memory (ROM) 107, electronically erasable programmable read only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by processor 103.
[0032] The real-time hazard-based insurance system 200 may include a control module 202. Control module 202 may be configured to receive a preliminary navigational route that a driver plans on traveling or on which a driver is currently traveling. For example, the preliminary navigational route may be received from the user via a computing device, such as one or more of computing devices 212a-212f. For instance, the preliminary navigational route may be received via an application (e.g., online or mobile application) executing on a smartphone 212a, personal digital assistant (PDA) 212b, tablet 212c, cell phone 212d, or other computing device 212e. In some examples, the preliminary navigational route may be input by a user on vehicle display 212f and transmitted to control module 202. Control module 202 may transmit the preliminary navigational route to a hazard score analysis module 210. The hazard score analysis module 210 may parse the preliminary navigational route into one or more road segments. The hazard score analysis module 210 may receive data from one or more data stores, such as data stores 204 and 206, and may determine a hazard score for each of the one or more road segments based on the received data. In some examples, a road segment may be some or all of a particular road. The road segments may have varying lengths or distances, may be formed of various materials, may include various types of roads (e.g., highway, country road, etc.), and the like.
[0034] Accordingly, some information may be received by the hazard score analysis module 210 from internal data store 204. The internal data store 204 may include information associated with accidents associated with the road segment, accidents associated with that type of road or one or more features of the road segment (e.g., number of bends, merging, etc.), severity of accidents associated with the road segment (e.g., based on insurance claim data), number of accidents associated with the road segment, time of day of accident, date of accident, and the like. Accident information received from internal data store 204 may be collected from historical accident or claim information of the insurance provider entity 201. The internal data store 204 may also include information associated with conditions of the road segment (e.g., pot holes, type of road, etc.). In some arrangements, this information may be received from a telematics device associated with one or more vehicles, and associated sensors detecting such information. The received telematics data may be stored and used to determine, for example, a road segment hazard score.
[0036] The hazard score analysis module 210 may detect a location of a vehicle (e.g., via global positioning system (GPS) data collected from the vehicle) and may identify a road segment associated with the location of the vehicle. This identification of the road segment may be performed by comparing the location coordinates from the vehicle to location coordinates of roads obtained, for example, from a mapping company or from analysis of many vehicles’ location coordinates over time. The hazard score analysis module 210 may then receive data from various data stores, such as data store 204 and/or data store 206, and may generate a road segment hazard score for the identified road segment.
[0037] The road segment hazard score may be generated by the hazard score analysis module 210 based on data associated with the road segment, as discussed above, as well as data associated with a driver of the vehicle. For instance, driver-specific data may be received by the hazard score analysis module 210 and may be used in conjunction with the various types of data discussed above, to determine a road segment hazard score for a particular road segment. For instance, the real-time hazard-based insurance system 200 may include a plurality of sensors 216a-216c. The sensors 216a-216c may be any of various types of sensors, as will be discussed more fully herein. The sensors 216a-216c may be used to obtain data associated with driving behaviors of the user, such as hard braking, speeding, swerving, rapid acceleration, and the like. In another example, one or more sensors may be used to detect environmental conditions such as precipitation, humidity, cloud cover, or the like. In still another example, one or more sensors may be used to determine road conditions or to obtain information from outside sources (e.g., external databases, or the like) regarding traffic conditions, types of road (e.g., two-lane road, four-lane road), speed limit of the road, or the like. The data from one or more sensors 216a-216c, which may include data from combinations of different types of sensors, may be transmitted to driving behavior module 214 for analysis.
[0038]The driving behavior module 214 may analyze sensor data received from one or more of
sensors 216a-216c and may identify one or more driving behaviors of a particular driver or
operator of the vehicle. For instance, the driving behavior module 214 may determine
whether the user generally drives at a speed over the speed limit, generally follows too
closely behind a vehicle in front of him, generally brakes hard, and the like. This
information may be transmitted to the hazard score analysis module 210 for use in
determining a hazard score for a particular road segment.
[0039] In some arrangements, raw sensor data (e.g., from one or more of sensors 216a-216c) may
be used in conjunction with other data (e.g., from data store 204, 206) to generate the road
segment hazard score. For instance, one or more sensors may be used to detect
precipitation. That information may be provided to the hazard score analysis module 210
in real-time, or near real-time, and may be combined with other data (e.g., accident data,
traffic volume data, etc.) for the road segment, and/or user driving behavior data, to
generate or determine the road segment hazard score for the road segment. In some
examples, based on this real-time or near real-time data, any hazards identified (e.g.,
hazards appearing along the route being travelled) may be transmitted to the user, via an
audible warning or alert displayed on a computing device, such as an on-board vehicle
computing device, mobile device of the user, etc. The hazards may be unique to the driver
based on driving characteristic data collected for the user, as well as current external or
environmental conditions.
[0065]… Additionally, or alternatively, hazard evaluation information may
be received from driving behavior module 214. As discussed above, driving behavior
module may analyze sensor data received from one or more of sensors 216a-216c and may
identify one or more driving behaviors of a particular driver or operator of the vehicle. For
instance, the driving behavior module 214 may determine whether the user generally drives
at a speed over the speed limit, generally follows too closely behind a vehicle in front of
him, generally brakes hard, and the like. This information may be received at step 404 for
use in determining a hazard score for a particular road segment.
[067] Road segment hazard score= exp(prior accident frequency on the road segment * W1 + road curvature * W 2 + road segment has lane merge * W 3 + road segment has merge from left* W4).
[068] W 1 though W 4 may be weighting factors applied to each variable.
[070] Road segment hazard score = exp(prior accident frequency on the road segment * W 1 +
road curvature * W 2 + road segment has lane merge * W 3 + road segment has merge from
left * W4 + road segment has construction * Ws + number of inches of snow on road
segment* W6+ road segment is wet* W1 + traffic factor* Ws).
[071] In this example algorithm, W1 though Ws represent weighting factors and variables such as
road segment has construction, number of inches of snow on road segment, road segment
is wet, and traffic factor may be dynamic factors used in combination with the static factors
described above.
[073] Road segment hazard score = exp(prior accident frequency on the road segment * W 1 +
road curvature * W 2 + road segment has lane merge * W 3 + road segment has merge from
left * W4 + road segment has construction * Ws + number of inches of snow on road
segment* W6+ road segment is wet* W1 + traffic factor* Ws + (road curvature* driver
takes curves fast* W9) + (number of inches of snow* driver brakes hard* W10)).
[074] In this example, W1 through W10 are weighting factors and variables such as "driver takes
curve fast" and "driver brakes hard" are example driving behaviors that may be used to
determine a road segment safety rating particular to a driver.
[075] The algorithms and variables shown above are for illustrative purposes, and various other
algorithms, various different weighting factors, additional or different variables, etc. may
be used without departing from the invention. The above-described algorithms are merely some examples of algorithms that may be used to determine a road segment hazard score
and should not be viewed as limiting the invention to only those example algorithms
provided.
US Pub No. 2014/0344008 A1 by Gammage et al teaches “The average score 812 for the device technology attribute 814 is the average value of the sum of the scores 816a- f”; US Pub. No. 20100023442 A1 by O’Hara et al discloses “calculating the average and/or cumulative total of the score or factor over a fixed time interval”; US Pub No. 2009/0144095 A1 by Gurinder et al
The Instant application, therefore, still appears to only implement the abstract ideas to the particular technological environments using what is generic components and functions in the related arts. The claim is not patent eligible.
The remaining dependent claims—which impose additional limitations—also fail to claim patent-eligible subject matter because the limitations cannot be considered statutory. In reference to claims 11-15 these dependent claim have also been reviewed with the same analysis as independent claim 10. Dependent claim 11 is directed toward real time route modification- a business process using technology. Dependent claim(s) 12 and 13 are directed toward data content-non-functional descriptive subject matter. Dependent claim 14 is directed toward generating routes which lower scores- risk mitigation. Dependent claim 15 is directed toward applying user interfaces to indicate route modifications-insignificant extra solution activity.
The dependent claim(s) have been examined individually and in combination with the preceding claims, however they do not cure the deficiencies of claim 10. Where all claims are directed to the same abstract idea, “addressing each claim of the asserted patents [is] unnecessary.” Content Extraction & Transmission LLC v. Wells Fargo Bank, Nat 7 Ass ’n, 776 F.3d 1343, 1348 (Fed. Cir. 2014). If applicant believes the dependent claims 11-15 are directed towards patent eligible subject matter, they are invited to point out the specific limitations in the claim that are directed towards patent eligible subject matter.
In reference to Claim(s) 16-20:
STEP 1. Per Step 1 of the two-step analysis, the claims are determined to include a method, as in independent Claim 16 and the dependent claims. Such methods fall under the statutory category of “process.” Therefore, the claims are directed to a statutory eligibility category.
STEP 2A Prong 1. The claimed invention is directed to an abstract idea without significantly more. Method claim 16 recites method steps 1) receive data, 2) analyze driver specific data 3) parse routes into road segments, 4) receive geocoded data 5) generate road segment hazard score 6) apply weights, 7) generate total hazard score 8) generate route modification based on score threshold 9) transmit route modification. The claimed limitations which under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of systems applied (driving behavior system, hazard score system, control system).
The claimed physical structures (readable medium) are generic computer components and tools to perform the mental processes. The computer components are recited at a high level of generality and merely automates functions that could reasonable be performed using mental concepts, therefore acting as a generic computer components to perform the abstract idea.
. The steps recite steps that can easily be performed in the human mind as mental processes because the operations “receive driver specific data”, “receive geocoded data” which mimics mental processes of observation. The operations “analyze driver specific data”, “parse …route into…segments”, “apply weights”, “generate…score”, “generate a total…score” and “generate …route modifications”, mimics mental processes of analysis and evaluation. The limitation “transmit …modification” is merely communication of results. Therefore, the limitations, encompass human thought processes of observation, analysis, evaluation and communication of result which, where the data interpretation is perceptible only in the human mind. See In re TLl Commc’ns LLC Patent Litig., 823 F.3d 607, 611 (Fed. Cir. 2016); FairWarning IP, LLC v. latric Sys., Inc., 839 F.3d 1089, 1093-94 (Fed. Cir. 2016)
The specification describes the inventive concept as searching, analyzing and applying a generating hazard score for predetermined routes from a current location to a specified destination, where based on hazard score thresholds modifying the predetermined routes a newer route with lesser hazards. (spec ¶ 0005). The specification further discloses a hazard based insurance system applied where the system determines route hazards for use in pricing insurance coverage (spec ¶ 0021). Accordingly, the claimed subject matter in light of the specification, when considered as a whole the claimed subject matter is directed toward risk mitigation and commercial activities, wherein the generated hazard score for analyzed road segments is applied to determine and transmit a route under a hazard threshold. Such concepts can be found in the abstract category of commercial interactions and marketing. These concepts are enumerated in Section I of the 2019 revised patent subject matter eligibility guidance published in the federal register (84 FR 50) on January 7, 2019) is directed toward abstract category of mental processes and methods of organizing human activity.
STEP 2A Prong 2: The identified judicial exception is not integrated into a practical application because the claims fail to provide indications of patent eligible subject matter that integrate the alleged abstract idea into a practical application. The claim limitations fail to recite additional elements beyond the abstract idea.
The method steps “receive driver specific data”, “receive geocoded data”, and “transmit…route modifications” are not tied to any technology and lack technical implementation. According to MPEP 2106.05(d) II (see also MPEP 2106.05(g)) the courts have recognized the following computer functions are claimed in a merely generic manner (e.g., at a high level of generality) where technology is merely applied to perform the abstract idea or as insignificant extra-solution activity.
Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014)
The claim limitations (“receiving driver specific data”, “receiving geocoded data”, and “transmitting…route modifications”) are recited at a high level of generality without details of technical implementation and thus are insignificant extra solution activity.
The recited steps “analyze driver specific data”, “parse preliminary…route into …segments”, “apply weights”, “generate a road segment hazard score…”, “generate a total hazard score” and “generate …route modifications” which individually are not directed toward any indications of patent eligibility according to MPEP 2106.05 (a)-(c), (e )-(h). This is because individually the focus of the steps to analysis of data acted upon for use in scoring hazards applied to determine an output of navigational routes to a destination as it relates to a hazard threshold.
When the claims are taken as an ordered combination or as a whole, the combination of limitations, the combination of limitations 1-2 and 3 are directed toward analyzing received data to identify user behavior and parse navigational routes into road segments which are processes not directed toward the systems themselves instead directed toward the analysis and manipulation of data for analysis related to human behavior. The combination of limitations 1-3 and 4-6 is directed toward receiving additional data and generating for each road segment hazard score based on the limitations 1-4 used to generate a total hazard score- as a combination is not directed toward the system itself or any other technology, but instead to generate score reflecting road hazards. The combination of limitations 1-6 and 7 is directed toward modifying routes in response to the score determined from limitations 1-6 when a hazard score is above a threshold. The combination of limitations 1-7 and 8 is directed toward outputting the results of limitations 1-7. Therefore, the combination 1-6 and 7-8 is not directed toward the readable medium itself or any other technology, but instead to generate score reflecting road hazards that are applied to generate and modify navigational routes based on hazard analysis of the routes.
When considered as a whole or ordered combination the combination of limitations 1-8 is directed toward – which as a whole is directed toward analyzing and parsing driver and road segment route data to generate hazard score in order to determine a navigational route of the road segment applying the hazard score, wherein based on a hazard score threshold the route is modified and outputting the results. The weighting of variables used to generate driving scores used to change routes to a different navigation routes does not impact or improve upon any underlying technology. The calculated score using weighted variables is merely mathematical calculations based on selected information. The mathematical calculation of a score using weighted variables involved here has no substantial practical application except in connection with a computer. The generation of a modified route based on scores is an algorithm that has no impact upon the computer, its functionality or field its functionality or field is patent ineligible. Therefore, the generating of changed route is not sufficient to transform the claim into patent eligible subject matter. The claim limitations merely apply technology to collect data, analyzed data and output the result of the analysis. The recited limitations are high level lacking technical details directed toward expected outcomes for use in routing road segments according to hazard threshold to a destination.
The combinations of parts is not directed toward any of the indications of patent eligible subject matter under step 2A prong 2, but instead a analyzing and scoring human behavior and road hazard risk. MPEP guidance (see MPEP 2106.05 (a)-(c), (e )-(h). The claim limitations as a whole, as an ordered combination and the combination of steps not integrate the judicial exception into a practical application as the claim process fails to impose meaningful limits upon the abstract idea. . This is because the claimed subject matter fails to provide additional elements or combination or elements instead recite a method to perform the identified abstract idea. The claim limitations and specification lacks technical disclosure on what the technical problem was and how the claimed limitations provide a technical solution to a technical problem rather than a solution to a problem found in the abstract idea. Taking the claim elements separately, or as a combination, the method at each step of the process is purely in terms of results desired and devoid of implementation of details. Technology is not integral to the process as the claimed subject matter. Furthermore, the claimed functions do not provide an operation that could be considered as sufficient to provide a technological implementation or application of/or improvement to this concept (i.e. integrated into a practical application).
The integration of elements do not improve upon technology or improve upon computer functionality or capability in how computers carry out one of their basic functions. The integration of elements do not provide a process that allows computers to perform functions that previously could not be performed. The integration of elements do not provide a process which applies a relationship to apply a new way of using an application. The limitations do not recite a specific use machine or the transformation of an article to a different state or thing. The limitations do not provide other meaningful limits beyond generally linking the use of the abstract idea to a particular technological environment. The steps are still a combination made to perform data analysis, generate routes based on generated hazard scores and does not provide any of the determined indications of patent eligibility set forth in the 2019 USPTO 101 guidance. The claims do not show improved ways of, for example, an particular technical function for performing the abstract idea that imposes meaningful limits upon the abstract idea. Moreover, Examiner was not able to identify any specific technological processes that goes beyond merely confining the abstract idea in a particular technological environment, which, when considered in the ordered combination with the other steps, could have transformed the nature of the abstract idea previously identified. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim provides no technical details regarding how the operations performed by the “resource”. Instead, similar to the claims at issue in Intellectual Ventures I LLC v. Capital One Financial Corp., 850 F.3d 1332 (Fed. Cir. 2017), “the claim language . . . provides only a result-oriented solution with insufficient detail for how a computer accomplishes it. Our law demands more.” Intellectual Ventures, 850 F.3d at 1342 (citing Elec. Power Grp. LLC v. Alstom, S.A., 830 F.3d 1350, 1356 (Fed. Cir. 2016)). The claim is directed to an abstract idea
STEP 2B; The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to concepts of the abstract idea into a practical application. The claim limitations do not recite any technology or technical techniques. Therefore, the limitations fail under step 2B.
The instant application, therefore, still appears to only implement the abstract ideas to the particular technological environments using what is generic components and functions in the related arts. The claim is not patent eligible.
The remaining dependent claims—which impose additional limitations—also fail to claim patent-eligible subject matter because the limitations cannot be considered statutory. In reference to claims 17-20 these dependent claim have also been reviewed with the same analysis as independent claim 16 Dependent claim(s) 17 and 18 are directed toward data content-non-functional descriptive subject matter. Dependent claim 19 is directed toward generating routes which lower scores- risk mitigation. Dependent claim 20 is directed toward applying user interfaces to indicate route modifications-insignificant extra solution activity.
The dependent claim(s) have been examined individually and in combination with the preceding claims, however they do not cure the deficiencies of claim 16. Where all claims are directed to the same abstract idea, “addressing each claim of the asserted patents [is] unnecessary.” Content Extraction & Transmission LLC v. Wells Fargo Bank, Nat 7 Ass ’n, 776 F.3d 1343, 1348 (Fed. Cir. 2014). If applicant believes the dependent claims 17-20 are directed towards patent eligible subject matter, they are invited to point out the specific limitations in the claim that are directed towards patent eligible subject matter.
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.
Claim(s) 1-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Patent No. 8,606,512 B1 by Bogovich et al (Bogovich), and further in view of US Patent No. 9,727,920 B1 by Healy et al. (Healy).
In reference to claim 1:
Bogovich teaches:
(Currently Amended) A real-time hazard-based navigational system ((Bogovich) in at least Col 1 lines 39-49) comprising:
a … system receiving driver-specific data obtained using one or more sensors ((Bogovich) in at least FIG. 2-3; Col 1 lines 40-49, Col 2 lines 60-66, Col 4 lines 8-10, Col 9 lines 64-Col 10 lines 1 -30, Col 12 lines 8-16, Col 13 lines 60-Col 14 lines 1 -32, lines 45-46 wherein the prior art teaches system may include telematic device, Col 15 lines 40-45 wherein the prior art teaches telematics data includes distance travelled) and analyzing the driver-specific data to identify one or more driving behaviors of a driver of a vehicle ((Bogovich) in at least Col 2 lines 11-33, Col 8 lines 58-Col 9 lines 1-9 wherein the prior art teaches receiving time of day driver driving, vehicle speed, Col 11 lines 25-48 wherein the prior art teaches receiving environment information of driving location, time of day) ;
a … system parsing a preliminary navigational route into one or more road segments ((Bogovich) in at least Abstract, Col 3 lines 16-25, Col 9 lines 45-64, Col 10 lines 13-38 wherein the prior art teaches route category ratings),
receiving geocoded data associated with the one or more road segments ((Bogovich) in at least Abstract; Col 1 lines 33-Col 2 lines 1- 10 wherein the prior art teaches receiving regional information and retrieve risk value road segments of that region: Co! 3 lines 46-Col 4 lines 1-25, Co! 5 lines 3-10 wherein the prior art teaches using geographical route information to calculate route risk; Col 7 lines 23-Co! 8 lines 1-18, Co! 8 lines 58-67 wherein the prior art teaches information of road segment through wilderness area for rate of accidents; Col 10 lines 12-38, Col i 2 lines 5-27, Co! 13 lines 25-40 wherein the prior art teaches route information includes posted speed limits included in geographic information), the geocoded data including a dynamic road segment condition detected in real-time or near real-time using the one or more sensors ((Bogovich) in at least Col 8 lines 19-26, Col 11 lines 65-Col 12 lines 1-51),
generating a road segment hazard score for each of the one or more road segments by analyzing the geocoded data and the one or more driving behaviors ((Bogovich) in at !east Col 1 lines 33-Col 2 lines 1-10 wherein the prior art teaches receiving regional information and retrieve risk value tor road segments of that region; Col 2 lines 61 -66, Col 4 lines 26-46, Col 5 lines 3-10 wherein the prior art teaches using geographical route information to calculate route risk; Col 8 lines 58-67 wherein the prior art teaches information of road segment wilderness area for rate of accidents; Col 9 lines 21 -29 wherein the prior art teaches personal computing device calculate route risk value, Col 11 lines 55-64 wherein the prior art teaches the driving behavior device (mobile) record and store route data and uploaded and the route information used to query data source for route rating data and calculating total risk value, Col 13 lines 25-40 wherein the prior art teaches route information includes posted speed limits included in geographic information), wherein generating the road segment hazard score comprises applying a weighted interaction term between the dynamic road segment condition of the road segment and an identified driving behavior of the driver, a total hazard score using the road segment hazard score for each of the one or more road segments ((Bogovich) in at least in at least ((Bogovich) in at least in at least Abstract; Col 1 lines 34-38, Col 2 lines 11-23 wherein the prior art teaches risk values assigned according to driver risk tolerance designating driver preference; Col 5 lines 15-36 wherein the prior art teaches cause of loss include driving behavior including ran through red light, rear-ended while stopping, rear-ended changing lanes, sideswiped during normal driving, sideswiped changing lanes, Col 6 lines 47-53 wherein the prior art teaches risk information include age, alcohol blood level, distance from home, Col 9 lines 5-9, lines 64-Col 10 lines 1-8, wherein the prior art teaches driver route preference behavior or lower risk driver, Col 10 lines 40-46, lines 58-Col 11 lines 1-9 wherein the prior art teaches applying to risk attributes weights to different types of loss in order to indicate more accurately risk/cost; Col 11 lines 48-55, Col 12 lines 28-Col 13 lines 1-51 wherein the prior art teaches assigning risk value to road segments based on road conditions (snowfall)), and
generating one or more route modifications when the total hazard score exceeds a threshold ((Bogovich) in at least Col 2 lines 11-23, col 3 lines 17-25, Col 9 lines 57-63 wherein the prior art teaches assigning risk range (threshold) category to route based on risk scores, col 10 lines 13-30, Col 12 lines 28-31); and
a … system receiving the preliminary navigational route ((Bogovich) in at least FIG. 1, Col 1 lines 39-Col 2 lines 1-10, Col 3 lines 47-57, Col 8 lines 38-57, Col 9 lines 22- 4)and
transmitting the one or more route modifications to one or more computing devices to cause the one or more computing devices to indicate the one or more route modifications. ((Bogovich) in at least Col 2 lines 11-33, Col 3 lines 15-25, Col 10 lines 13-30, Col 12 lines 28-51 wherein the prior art teaches presenting initial route, shortest route, quickest route, route by risk value, and alternative routes with different risk categories).
Bogovich suggest and makes obvious the limitation “weighted interaction term between the dynamic road segment condition of the road segment and an identified driving behavior of the driver”, the prior art reference does teaches the system providing associated risk value when provided with location information and other information for road segment (Col 1 lines 45-49) the applying varying weights to different types of loss costs where loss may indicate risk and the importance of these certain portions of loss may be weighted more heavily in loss cost calculations (abstract; Col 10 lines 58-67). The prior art teaches using vehicle information, geographic information and other information either alone or in combination in calculating risk value (Col 7 lines 19-22). The prior art teaches counting the number of each type or road risk that then may be multiplied by a risk rating factor for respective risk type (Col 9 lines 48-56). The prior art further teaches assigning risk values to road segments where relevant respective risk may include road conditions including light rain, snow, fog, ice and driver behavior including drugs, speed, ran through red light, speed of vehicle versus posted speed limit and other road conditions and driving behavior, which is applied to calculate risk value. According to KSR, when the prior art teaches some teaching, suggestion or motivation in the prior art that would have led one of ordinary skill in the art to modify the prior art reference to arrive at the claimed invention. This because the prior art provides design incentives and other market forces that would have prompted one of ordinary skill in the art to arrive at the claimed invention with a reasonable expectation of success. Accordingly, one of ordinary skill in the art, in view of the identified design incentives or other market forces, could have implemented the claimed variation of the prior art, and the claimed variation would have been predictable to one of ordinary skill in the art.
Bogovich does not explicitly teach:
driving behavior system
hazard score analysis system
control system
Healy teaches:
a driving behavior system receiving driver-specific data obtained…((Healy) in at least Col 15 lines 62-Col 16 lines 1-39)
a hazard score analysis system parsing a preliminary navigational route ((Healy) in at least col 16 lines 21-39, lines 48-62, Col 8 lines 17-51, col 10 lines 54-col 11 lines 1-21, Col 13 lines 1-55)
a control system receiving the preliminary navigational route…((Healy) in at least Col 2 lines 47-67, Col 6 lines 21-62, Col 8 lines 52-67, Col 12 lines 22-36, Col 14 lines 3-15)
Both Bogovich and Healy are directed toward collecting driving behavior data, road condition data and other data related to insurance risk assessment for road segments applying a plurality of computer modules/system for use in the analysis of insurance risk. Healy teaches the motivation of applying a plurality of specific modules for use in analyzing specific categories of risk assessment including driver behavior, vehicle behavior, road segment and route assessments and an overall system in order to identify and analyze different risk categories for route risk factors for insurance processes. It would have been obvious to one having ordinary skill at the time of effective filing the invention to expand the details of the of the plurality of modules for the analysis, generating scores and routes of Bogovich to include the specific modules as taught by Healy since Healy teaches the motivation of applying a plurality of specific modules for use in analyzing specific categories of risk assessment including driver behavior, vehicle behavior, road segment and route assessments and an overall system in order to identify and analyze different risk categories for route risk factors for insurance processes.
In reference to Claim 2:
The combination of Bogovich and Healy discloses the limitations of independent claim 1. Bogovich further discloses the limitations of dependent claim 2
The real-time hazard-based navigational system of claim 1 (see rejection of claim 1 above),
wherein the one or more route modifications are generated using real-time data.((Bogovich) in at least col 8 lines 30-37 wherein the prior art teaches data applied for assigning risk retrieved/collected in real time, col 12 lines 2-27 wherein the prior art teaches updating road segment data, and route information updated in real time)
In reference to Claim 3:
The combination of Bogovich and Healy discloses the limitations of dependent claim 2. Bogovich further discloses the limitations of dependent claim 3.
The real-time hazard-based navigational system of claim 2 (see rejection of claim 2 above),
wherein the real-time data includes at least one of weather data, traffic data, road conditions, traffic volume, accident severity, or environmental conditions. ((Bogovich) in at least col 8 lines 19-37 wherein the prior art teaches collected data includes weather conditions, traffic conditions, traffic volume)
In reference to Claim 4:
The combination of Bogovich and Healy discloses the limitations of independent claim 1. Bogovich further discloses the limitations of dependent claim 4.
The real-time hazard-based navigational system of claim 1 (see rejection of claim 1 above),
wherein the driver-specific data includes at least one of speed relative to speed limits, driving distance from other vehicles, hard braking, or swerving. ((Bogovich) in at least Col 7 lines 30-39 wherein the prior art teaches determining milage of road segments, Col 9 lines 5-10, Col 12 lines 52-60, Col 13 lines 1-50,
In reference to Claim 5:
The combination of Bogovich and Healy discloses the limitations of independent claim 1. Bogovich further discloses the limitations of dependent claim 5.
The real-time hazard-based navigational system of claim 1 (see rejection of claim 1 above),
wherein the one or more driving behaviors used to generate the road segment hazard score are weighted. ((Bogovich} in at least Col 5 lines 50-62, Col 11 lines 1-9 wherein the prior art teaches average calculations change over time as the weights applied to incidents, based on longer risk events; Col 11 lines 49-55, Col 13 lines 25-51).
In reference to Claim 6:
The combination of Bogovich and Healy discloses the limitations of independent claim 1. Bogovich further discloses the limitations of dependent claim 6.
The real-time hazard-based navigational system of claim 1 (see rejection of claim 1 above),
wherein the one or more route modifications includes generating a navigational route that has a lower total hazard score than the total hazard score of the preliminary navigational route. ((Bogovich) in at least Col 2 lines 11-17 wherein the prior art teaches computing, identifying and presenting alternative route with lower risk; col 10 lines 13-30),
In reference to Claim 7:
The combination of Bogovich and Healy discloses the limitations of independent claim 1. Bogovich further discloses the limitations of dependent claim 7.
The real-time hazard-based navigational system of claim 1 (see rejection of claim 1 above),
wherein the one or more computing devices indicate the one or more route modifications using a user interface. ((Bogovich) in at least Col 2 lines 11-23, col 3 lines 17-25, Col 9 lines 57-63, col 10 lines 13-30, Col 12 lines 28-31)
In reference to Claim 8:
The combination of Bogovich and Healy discloses the limitations of independent claim 1. Bogovich further discloses the limitations of dependent claim 8.
The real-time hazard-based navigational system of claim 1 (see rejection of claim 1 above),
wherein the total hazard score is determined by summing or averaging the road segment hazard score for each route segment. ((Bogovich) in at least in at !east Col 10 lines 40-46, Col 11 lines 48-55, Col 12 lines 28-Col 13 lines 1-51)
In reference to Claim 9:
The combination of Bogovich and Healy discloses the limitations of independent claim 1. Bogovich further discloses the limitations of dependent claim 9.
The real-time hazard-based navigational system of claim 1 (see rejection of claim 1 above),
wherein the control system is further configured to receive, from the one or more computing devices, a threshold total route hazard score for determining the one or more route modifications. ((Bogovich) in at least Col 2 lines 56-67 wherein the prior art teaches pricing tiers; Col 10 lines 39-45, Col 11 lines 49-55, Col 13 tines 25-87),
Claim(s) 10-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Patent No. 8,606,512 B1 by Bogovich et al (Bogovich).
In reference to claim 10:
Bogovich teaches:
(Currently Amended) A non-transitory computer-readable media having instructions stored thereon that, when executed by one or more processors ((Bogovich) in at least col 9 lines 10-17), cause the one or more processors to:
receive driver-specific data obtained using one or more sensors ((Bogovich) in at least FIG. 2-3; Col 1 lines 40-49, Col 2 lines 60-66, Col 4 lines 8-10, Col 9 lines 64-Col 10 lines 1 -30, Col 12 lines 8-16, Col 13 lines 60-Col 14 lines 1 -32, lines 45-46 wherein the prior art teaches system may include telematic device),
analyze the driver-specific data to identify one or more driving behaviors of a driver of a vehicle ((Bogovich) in at least Col 2 lines 11-33, Col 8 lines 58-Col 9 lines 1-9 wherein the prior art teaches receiving time of day driver driving, vehicle speed, Col 11 lines 25-48 wherein the prior art teaches receiving environment information of driving location, time of day);
parse a preliminary navigational route into one or more road segments ((Bogovich) in at least Abstract, Col 3 lines 16-25, Co! 9 lines 45-64, Col 10 lines 13-38 wherein the prior art teaches route category ratings);
receive geocoded data associated with the one or more road segments ((Bogovich) in at least Abstract; Col 1 lines 33-Col 2 lines 1- 10 wherein the prior art teaches receiving regional information and retrieve risk value road segments of that region: Col 3 lines 46-Col 4 lines 1-25, Col 5 lines 3-10 wherein the prior art teaches using geographical route information to calculate route risk; Col 7 lines 23-Col 8 lines 1-18, Col 8 lines 58-67 wherein the prior art teaches information of road segment through wilderness area for rate of accidents; Co! 10 lines 12-38, Col 12 lines 5-27, Col 13 lines 25-40 wherein the prior art teaches route information includes posted speed limits included in geographic information);
generate a road segment hazard score for each of the one or more road segments by analyzing the geocoded data and the one or more driving behaviors ((Bogovich) in at !east Col 1 lines 33-Col 2 lines 1-10 wherein the prior art teaches receiving regional information and retrieve risk value tor road segments of that region; Col 2 lines 61 -66, Col 4 lines 26-46, Co! 5 lines 3-10 wherein the prior art teaches using geographical route information to calculate mute risk; Col 8 lines 58-67 wherein the prior art teac!1es information of road segment wilderness area for rate of accidents; Col 9 lines 21 -29 wherein the prior art teaches personal computing device calculate route risk value, Col 11 lines 55-64 wherein the prior art teaches the driving behavior device (mobile) record and store route data and uploaded and the route information used to query data source for route rating data and calculating total risk value, Col 13 lines 25-40 wherein the prior art teaches route information includes posted speed limits included in geographic information), wherein the geocoded data includes a dynamic road segment condition detected in real-time or near real-time using the one or more sensors ((Bogovich) in at least Col 8 lines 19-26, Col 11 lines 65-Col 12 lines 1-51), and wherein generating the road segment hazard score comprises applying a weighted interaction term between the dynamic road segment condition of the road segment and an identified driving behavior of the driver ((Bogovich) in at least in at least Abstract; Col 1 lines 34-38, Col 2 lines 11-23 wherein the prior art teaches risk values assigned according to driver risk tolerance designating driver preference; Col 5 lines 15-36 wherein the prior art teaches cause of loss include driving behavior including ran through red light, rear-ended while stopping, rear-ended changing lanes, sideswiped during normal driving, sideswiped changing lanes, Col 6 lines 47-53 wherein the prior art teaches risk information include age, alcohol blood level, distance from home, Col 9 lines 5-9, lines 64-Col 10 lines 1-8, wherein the prior art teaches driver route preference behavior or lower risk driver, Col 10 lines 40-Col 11 lines 1-9 wherein the prior art teaches applying to risk attributes weights to different types of loss in order to indicate more accurately risk/cost; Col 11 lines 48-55, Col 12 lines 28-Col 13 lines 1-51 wherein the prior art teaches assigning risk value to road segments based on road conditions (snowfall));
generate a total hazard score using the road segment hazard score for each of the one or more road segments ((Bogovich) in at least in at least Col 10 lines 40-46, Col 11 lines 48-55, Col 12 lines 28-Col 13 lines 1-51);
generate one or more route modifications when the total hazard score exceeds a threshold ((Bogovich) in at least Col 2 lines 11-23, col 3 lines 17-25, Col 9 lines 57-63 wherein the prior art teaches assigning risk range (threshold) category to route based on risk scores, col 10 lines 13-30, Col 12 lines 28-31); and
transmit the one or more route modifications to one or more computing devices to cause the one or more computing devices to indicate the one or more route modifications. ((Bogovich) in at least Col 2 lines 11-33, Col 3 lines 15-25, Col 10 lines 13-30, Col 12 lines 28-51 wherein the prior art teaches presenting initial route, shortest route, quickest route, route by risk value, and alternative routes with different risk categories)
Bogovich suggest and makes obvious the limitation “weighted interaction term between the dynamic road segment condition of the road segment and an identified driving behavior of the driver”, the prior art reference does teaches the system providing associated risk vale when provided with location information and other information for road segment (Col 1 lines 45-49) the applying varying weights to different types of loss costs where loss may indicate risk and the importance of these certain portions of loss may be weighted more heavily in loss cost calculations (abstract; Col 10 lines 58-67). The prior art teaches using vehicle information, geographic information and other information either alone or in combination in calculating risk value (Col 7 lines 19-22). The prior art teaches counting the number of each type or road risk that then may be multiplied by a risk rating factor for respective risk type (Col 9 lines 48-56). The prior art further teaches assigning risk values to road segments where relevant respective risk may include road conditions including light rain, snow, fog, ice and driver behavior including drugs, speed, ran through red light, speed of vehicle versus posted speed limit and other road conditions and driving behavior, which is applied to calculate risk value. According to KSR, when the prior art teaches some teaching, suggestion or motivation in the prior art that would have led one of ordinary skill in the art to modify the prior art reference to arrive at the claimed invention. This because the prior art provide design incentives and other market forces that would have prompted one of ordinary skill in the art to arrive at the claimed invention with a reasonable expectation of success. Accordingly, one of ordinary skill in the art, in view of the identified design incentives or other market forces, could have implemented the claimed variation of the prior art, and the claimed variation would have been predictable to one of ordinary skill in the art.
In reference to claim 11:
Bogovich teaches:
The non-transitory computer-readable media of claim 10 (see rejection of claim 10 above),
wherein the one or more route modifications are generated using real-time data. ((Bogovich) in at least col 8 lines 30-37 wherein the prior art teaches data applied for assigning risk retrieved/collected in real time, col 12 lines 2-27 wherein the prior art teaches updating road segment data, and route information updated in real time)
In reference to claim 12:
Bogovich teaches:
The non-transitory computer-readable media of claim 11 (see rejection of claim 11 above),
wherein the real-time data includes at least one of weather data, traffic data, road conditions, traffic volume, severity of accidents, or environmental conditions. ((Bogovich) in at least col 8 lines 19-37 wherein the prior art teaches collected data includes weather conditions, traffic conditions, traffic volume)
In reference to claim 13
Bogovich teaches:
The non-transitory computer-readable media of claim 10 (see rejection of claim 10 above),
wherein the driver-specific data includes at least one of speed relative to speed limits, driving distance from other vehicles, hard braking, and swerving. ((Bogovich) in at least Col 14 lines 3-15 wherein the prior art teaches data includes maximum speed traveled, average speed travelled, braking, acceleration, Col 15 lines 40-45 wherein the prior art teaches telematics data includes distance travelled),
In reference to claim 14:
Bogovich teaches:
The non-transitory computer-readable media of claim 10 (see rejection of claim 10 above),
wherein the one or more route modifications includes generating a navigational route that has a lower total hazard score than the total hazard score of the preliminary navigational route. ((Bogovich) in at least Col 2 lines 11-17 wherein the prior art teaches computing, identifying and presenting alternative route with lower risk; col 10 lines 13-30),
In reference to claim 15:
Bogovich teaches:
The non-transitory computer-readable media of claim 10 (see rejection of claim 10 above),
wherein the one or more computing devices indicate the one or more route modifications using a user interface. ((Bogovich) in at least Col 2 lines 11-17 wherein the prior art teaches computing, identifying and presenting alternative route with lower risk; col 10 lines 13-30),
In reference to claim 16:
Bogovich teaches:
The steps of method claim 16 correspond to the executed instructions of medium claim 10. Therefore, claim 16 has been analyzed and rejected as previously discussed with respect to claim 10.
In reference to claim 17:
Bogovich teaches:
The steps of method claim 17 correspond to the executed instructions of medium claim 12. Therefore, claim 17 has been analyzed and rejected as previously discussed with respect to claim 12.
In reference to claim 18:
Bogovich teaches:
The steps of method claim 18 correspond to the executed instructions of medium claim 13. Therefore, claim 18 has been analyzed and rejected as previously discussed with respect to claim 13
In reference to claim 19:
Bogovich teaches:
The steps of method claim 19 correspond to the executed instructions of medium claim 14. Therefore, claim 19 has been analyzed and rejected as previously discussed with respect to claim 14
In reference to claim 20:
Bogovich teaches:
The steps of method claim 15 correspond to the executed instructions of medium claim 20. Therefore, claim 20 has been analyzed and rejected as previously discussed with respect to claim 15
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US Pub No. 2017/0221149 A1 by Hsu-Hoffman et al-para 0018-0019, para 0021, para 0023-0025; AU 2017/100444 A4 by Ratnasingam; US Patent No. 8,996,234 B1 by Tamari et al, CA 2805439 A1 by Bowne et al; CA 2609806 A1 by Phelan et al.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARY M GREGG whose telephone number is (571)270-5050. The examiner can normally be reached M-F 9am-5pm.
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/MARY M GREGG/Examiner, Art Unit 3695
/CHRISTINE M Tran/Supervisory Patent Examiner, Art Unit 3695
