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 .
Response to Arguments
Applicant’s arguments with respect to claim(s) 1, 8, and 15 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 4, 7, 8, 11, 15, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over MITCHELL et al. (US 2013/0198031) in views of VIOLA et al. (US 2012/0265433), and HAYWARD (US 9,679,487).
Regarding claim 1, Mitchell discloses a computer-implemented method for generating a mobility profile and providing risk-based notifications to a user, comprising:
receiving, from a telematics source of a vehicle or a corresponding user device authorized by the user, mobility data including location and operational data associated with a vehicle of the user (Fig. 2, steps 202a, 202b, and 202c; p. [0012], [0015]; the system is configured to collect travel information (i.e., mobility data) associated with the user and device (e.g., vehicle, mobile phone) to create a set of historical travel patterns, and geographical locations of the user or vehicle based on signal received from a GPS satellite);
storing the mobility data in a computer-accessible repository so that the mobility data is accessible for subsequent analysis (p. [0011]);
processing, the mobility data to determine at least one user-specific mobility profile parameter correlated to a dynamically suggested travel route (p. [0013], lines 24-end; p. [0015], [0016], [0017]; the processing unit processes the data that includes current GPS position of the device and predicts the destination based on the stored travel patterns, and calculates an optimum route (i.e., suggested travel route) – Fig. 2),
wherein the processing includes selecting or generating the dynamically suggested travel route based on the user’s historical mobility data and current location data (Fig. 2, steps 202a, 202b, 202c, and 210; p. [0011]);
generating, based on the at least one user-specific mobility profile parameter, a notification or recommendation reflective of a risk level, user behavior, or preferred the dynamically suggested travel route (p. [0013], lines 24-end; p. [0015], [0016], [0017]; the processing unit processes the data that includes current GPS position of the device and predicts the destination based on the stored travel patterns, and calculates an optimum route (i.e., dynamically suggested travel route) – Fig. 2); and
transmitting the notification or recommendation, including the dynamically suggested travel route, to a user interface associated with the corresponding user device or the vehicle (p. [0016], lines 1-4; the one or more optimum routes (i.e., suggested travel route) may be displayed to the user on a dashboard or display screen (i.e., user interface)).
Mitchell does not particularly disclose the processing of mobility data by a trained data analytics or machine-learning model.
However, Viola teaches processing of mobility data by a trained data analytics or machine-learning model (p. [0035], last sentence; the suggestive mapping system 200 may use machine learning algorithms or other methods of training to learn locations of a user and provide a suggested map and/or route with or without an explicit address entered by a user or found in a communication or appointment). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Mitchell with the teachings of Viola, since such a modification would allow the system to process the data and provide a suggested route without an explicit user’s input.
But, the combination of Mitchell and Viola does not particularly disclose continuously updating the at least one user-specific mobility profile parameter based on real-time mobility data received from the telematics source during navigation along the dynamically suggested travel route; and
automatically adjusting the notification or recommendation based on the updated mobility profile parameter without user input.
However, Hayward teaches continuously updating the at least one user-specific mobility profile parameter based on real-time mobility data received from the telematics source during navigation along the dynamically suggested travel route (abstract, lines 1-5; col. 5, lines 25-30; col. 6, lines 7-24 and 37-56; col. 8, lines 44-63; telematics data may be collected in real-time by a mobile device within the vehicle or the vehicle itself, the telematic data may indicate vehicle direction, speed, motion, etc. as well as hazards in the surrounding environment (i.e., real-time mobility data), a remote computer may analyze the telematics data and/or other data collected in real-time and to determine traffic events in real-time or near real-time, based on the traffic event detected, the computing device may issue warnings, determine recommendations, and/or re-route vehicles, for instance the computing device may cause a display screen or other user interface of remote drivers to display a map with a current route of the vehicle, a virtual representation of the traffic event, and/or an alternate or recommended new route (i.e., updated user-specific mobility profile parameter) to an original destination that avoids the traffic event); and
automatically adjusting the notification or recommendation based on the updated mobility profile parameter without user input (col. 8, lines 44-63; the computing device may cause a display screen or other user interface of remote drivers to display a map with a current route of the vehicle, a virtual representation of the traffic event, and/or an alternate or recommended new route (i.e., updated user-specific mobility profile parameter/ notification) to an original destination that avoids the traffic event). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell and Viola with the teachings of Hayward, in order to generate alerts and/or recommendations based upon the analysis of collected telematics data and inform the users of real-time traffic conditions and/or recommended changes based on the traffic conditions.
Regarding claim 4, the combination of Mitchell, Viola, and Hayward disclose the computer-implemented method of claim 1, Mitchell discloses wherein generating the notification or recommendation further comprises providing a suggested travel route to the user based on at least one historical travel pattern derived from the mobility data and real-time route availability data (abstract; [0011], [0012], [0016], [0017]; historical travel and route information is stored in the system such that a destination can be predicted using the current location, time, and stored travel data, an optimum route (i.e., suggested travel route) of travel is computed).
Regarding claim 7, the combination of Mitchell, Viola, and Hayward disclose the computer-implemented method of claim 1, wherein storing the mobility data comprises storing the mobility data in an electronic database associated with a remote computing device (p. [0019], [0021]; mapping device may store location, calendar, historical and contextual data (i.e., mobility data) in user data store…the user data store may reside within the remote server). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Mitchell with the teachings of Viola, since such a modification would free up storage resources at the user device.
Regarding claim 8, Mitchell discloses a computing system for generating a mobility profile and providing risk-based notifications to a user, comprising:
one or more processors (p. [0012]); and
one or more memories having stored thereon computer-executable instructions that, when executed (p. [0012]), cause the computing system to:
receive, from a telematics source of a vehicle or a corresponding user device authorized by the user, mobility data including location and operational data associated with a vehicle of the user (Fig. 2, steps 202a, 202b, and 202c; p. [0012], [0015]; the system is configured to collect travel information (i.e., mobility data) associated with the user and device (e.g., vehicle, mobile phone) to create a set of historical travel patterns, and geographical locations of the user or vehicle based on signal received from a GPS satellite);
store the mobility data in a computer-accessible repository so that the mobility data is accessible for subsequent analysis (p. [0011]);
process, the mobility data to determine at least one user-specific mobility profile parameter correlated to a dynamically suggested travel route (p. [0013], lines 24-end; p. [0015], [0016], [0017]; the processing unit processes the data that includes current GPS position of the device and predicts the destination based on the stored travel patterns, and calculates an optimum route (i.e., suggested travel route) – Fig. 2),
wherein the processing includes selecting or generating the dynamically suggested travel route based on the user’s historical mobility data and current location data (p. [0013], lines 24-end; p. [0015], [0016], [0017]; the processing unit processes the data that includes current GPS position of the device and predicts the destination based on the stored travel patterns, and calculates an optimum route (i.e., dynamically suggested travel route) – Fig. 2);
generate, based on the at least one user-specific mobility profile parameter, a notification or recommendation reflective of a risk level, user behavior, or the dynamically suggested travel route (p. [0013], lines 24-end; p. [0015], [0016], [0017]; the processing unit processes the data that includes current GPS position of the device and predicts the destination based on the stored travel patterns, and calculates an optimum route (i.e., dynamically suggested travel route) – Fig. 2); and
transmit the notification or recommendation, including the dynamically suggested travel route, to a user interface associated with the corresponding user device or the vehicle (p. [0016], lines 1-4; the one or more optimum routes (i.e., suggested travel route) may be displayed to the user on a dashboard or display screen (i.e., user interface)).
Mitchell does not particularly disclose the processing of mobility data by a trained data analytics or machine-learning model.
However, Viola teaches processing of mobility data by a trained data analytics or machine-learning model (p. [0035], last sentence; the suggestive mapping system 200 may use machine learning algorithms or other methods of training to learn locations of a user and provide a suggested map and/or route with or without an explicit address entered by a user or found in a communication or appointment). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Mitchell with the teachings of Viola, since such a modification would allow the system to process the data and provide a suggested route without an explicit user’s input.
But, the combination of Mitchell and Viola does not particularly disclose to further process the mobility data by continuously updating the at least one user-specific mobility profile parameter based on real-time mobility data received from the telematics source during navigation along the dynamically suggested travel route; and
automatically adjusting the notification or recommendation based on the updated mobility profile parameter without user input.
However, Hayward teaches continuously updating the at least one user-specific mobility profile parameter based on real-time mobility data received from the telematics source during navigation along the dynamically suggested travel route (abstract, lines 1-5; col. 5, lines 25-30; col. 6, lines 7-24 and 37-56; col. 8, lines 44-63; telematics data may be collected in real-time by a mobile device within the vehicle or the vehicle itself, the telematic data may indicate vehicle direction, speed, motion, etc. as well as hazards in the surrounding environment (i.e., real-time mobility data), a remote computer may analyze the telematics data and/or other data collected in real-time and to determine traffic events in real-time or near real-time, based on the traffic event detected, the computing device may issue warnings, determine recommendations, and/or re-route vehicles, for instance the computing device may cause a display screen or other user interface of remote drivers to display a map with a current route of the vehicle, a virtual representation of the traffic event, and/or an alternate or recommended new route (i.e., updated user-specific mobility profile parameter) to an original destination that avoids the traffic event); and
automatically adjusting the notification or recommendation based on the updated mobility profile parameter without user input (col. 8, lines 44-63; the computing device may cause a display screen or other user interface of remote drivers to display a map with a current route of the vehicle, a virtual representation of the traffic event, and/or an alternate or recommended new route (i.e., updated user-specific mobility profile parameter/ notification) to an original destination that avoids the traffic event). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell and Viola with the teachings of Hayward, in order to generate alerts and/or recommendations based upon the analysis of collected telematics data and inform the users of real-time traffic conditions and/or recommended changes based on the traffic conditions.
Regarding claim 11, the combination of Mitchell, Viola, and Hayward disclose the computing system of claim 8, Mitchell discloses wherein the one or more memories having stored thereon computer-executable instructions that when executed, cause the computing system to: provide a suggested travel route to the user based on at least one historical travel pattern derived from the mobility data and real-time route availability data (abstract; [0011], [0012], [0016], [0017]; historical travel and route information is stored in the system such that a destination can be predicted using the current location, time, and stored travel data…an optimum route (i.e., suggested travel route) of travel is computed).
Regarding claim 15, Mitchell discloses a non-transitory computer-readable medium having stored thereon computer-computer executable instructions that, when executed, cause a computer to:
receive, from a telematics source of a vehicle or a corresponding user device authorized by a user, mobility data including location and operational data associated with a vehicle of a user ();
store the mobility data in a computer-accessible repository so that the mobility data is accessible for subsequent analysis (p. [0011]);
process, the mobility data to determine at least one user-specific mobility profile parameter correlated to a dynamically suggested travel route (Fig. 2, steps 202a, 202b, and 202c; p. [0012], [0015]; the system is configured to collect travel information (i.e., mobility data) associated with the user and device (e.g., vehicle, mobile phone) to create a set of historical travel patterns, and geographical locations of the user or vehicle based on signal received from a GPS satellite),
wherein the processing includes selecting or generating the dynamically suggested travel route based on the user’s historical mobility data and current location data (p. [0013], lines 24-end; p. [0015], [0016], [0017]; the processing unit processes the data that includes current GPS position of the device and predicts the destination based on the stored travel patterns, and calculates an optimum route (i.e., dynamically suggested travel route) – Fig. 2);
generate, based on the at least one user-specific mobility profile parameter, a notification or recommendation reflective of a risk level, user behavior, or preferred the dynamically suggested travel route (p. [0013], lines 24-end; p. [0015], [0016], [0017]; the processing unit processes the data that includes current GPS position of the device and predicts the destination based on the stored travel patterns, and calculates an optimum route (i.e., dynamically suggested travel route) – Fig. 2); and
transmit the notification or recommendation, including the dynamically suggested travel route, to a user interface associated with the corresponding user device or the vehicle (p. [0016], lines 1-4; the one or more optimum routes (i.e., suggested travel route) may be displayed to the user on a dashboard or display screen (i.e., user interface)).
Mitchell does not particularly disclose the processing of mobility data by a trained data analytics or machine-learning model.
However, Viola teaches processing of mobility data by a trained data analytics or machine-learning model (p. [0035], last sentence; the suggestive mapping system 200 may use machine learning algorithms or other methods of training to learn locations of a user and provide a suggested map and/or route with or without an explicit address entered by a user or found in a communication or appointment). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Mitchell with the teachings of Viola, since such a modification would allow the system to process the data and provide a suggested route without an explicit user’s input.
But, the combination of Mitchell and Viola does not particularly disclose to further process the mobility data by continuously updating the at least one user-specific mobility profile parameter based on real-time mobility data received from the telematics source during navigation along the dynamically suggested travel route; and
automatically adjusting the notification or recommendation based on the updated mobility profile parameter without user input.
However, Hayward teaches continuously updating the at least one user-specific mobility profile parameter based on real-time mobility data received from the telematics source during navigation along the dynamically suggested travel route (abstract, lines 1-5; col. 5, lines 25-30; col. 6, lines 7-24 and 37-56; col. 8, lines 44-63; telematics data may be collected in real-time by a mobile device within the vehicle or the vehicle itself, the telematic data may indicate vehicle direction, speed, motion, etc. as well as hazards in the surrounding environment (i.e., real-time mobility data), a remote computer may analyze the telematics data and/or other data collected in real-time and to determine traffic events in real-time or near real-time, based on the traffic event detected, the computing device may issue warnings, determine recommendations, and/or re-route vehicles, for instance the computing device may cause a display screen or other user interface of remote drivers to display a map with a current route of the vehicle, a virtual representation of the traffic event, and/or an alternate or recommended new route (i.e., updated user-specific mobility profile parameter) to an original destination that avoids the traffic event); and
automatically adjusting the notification or recommendation based on the updated mobility profile parameter without user input (col. 8, lines 44-63; the computing device may cause a display screen or other user interface of remote drivers to display a map with a current route of the vehicle, a virtual representation of the traffic event, and/or an alternate or recommended new route (i.e., updated user-specific mobility profile parameter/ notification) to an original destination that avoids the traffic event). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell and Viola with the teachings of Hayward, in order to generate alerts and/or recommendations based upon the analysis of collected telematics data and inform the users of real-time traffic conditions and/or recommended changes based on the traffic conditions.
Regarding claim 20, the combination of Mitchell, Viola, and Hayward disclose the non-transitory computer-readable medium of claim 15, having stored thereon computer-executable instructions that, when executed, cause a computer to: store the mobility data in an electronic database associated with a remote computing device (p. [0019], [0021]; mapping device may store location, calendar, historical and contextual data (i.e., mobility data) in user data store…the user data store may reside within the remote server). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify Mitchell with the teachings of Viola, since such a modification would free up storage resources at the user device.
Claims 2, 9, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over MITCHELL et al. in views of VIOLA et al., HAYWARD, and SENCI et al. (US 2019/0139048).
Regarding claim 2, the combination of Mitchell, Viola, and Hayward disclose the computer-implemented method of claim 1, but does not particularly disclose further comprising: receiving, from at least one third-party data source, consumer-history data indicative of transaction or purchasing activity of the user; and refine or update the at least one user-specific mobility profile parameter using the consumer-history data.
However, Senci teaches receiving, from at least one third-party data source, consumer-history data indicative of transaction or purchasing activity of the user; and refine or update the at least one user-specific mobility profile parameter using the consumer-history data (p. [0005], [0029], [0080]; the computing device may update a risk score (i.e., parameter) based on a plurality of transactions (i.e., purchasing activity)). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell, Viola, and Hayward with the teachings of Senci, in order to detect fraud and prevent unauthorized transactions.
Regarding claim 9, the combination of Mitchell, Viola, and Hayward disclose the computer system of claim 8, but does not particularly disclose the one or more memories having stored thereon computer-executable instructions that when executed, cause the computing system to: receive, from at least one third-party data source, consumer-history data indicative of transaction or purchasing activity of the user; and refine or update the at least one user-specific mobility profile parameter using the consumer-history data.
However, Senci teaches receiving, from at least one third-party data source, consumer-history data indicative of transaction or purchasing activity of the user; and refine or update the at least one user-specific mobility profile parameter using the consumer-history data (p. [0005], [0029], [0080]; the computing device may update a risk score (i.e., parameter) based on a plurality of transactions (i.e., purchasing activity)). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell, Viola, and Hayward with the teachings of Senci, in order to detect fraud and prevent unauthorized transactions.
Regarding claim 16, the combination of Mitchell, Viola, and Hayward disclose the non-transitory computer-readable medium of claim 15, when executed, cause a computer to: receive, from at least one third-party data source, consumer-history data indicative of transaction or purchasing activity of the user; and refine or update the at least one user-specific mobility profile parameter using the consumer-history data.
However, Senci teaches receiving, from at least one third-party data source, consumer-history data indicative of transaction or purchasing activity of the user; and refine or update the at least one user-specific mobility profile parameter using the consumer-history data (p. [0005], [0029], [0080]; the computing device may update a risk score (i.e., parameter) based on a plurality of transactions (i.e., purchasing activity)). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell, Viola, and Hayward with the teachings of Senci, in order to detect fraud and prevent unauthorized transactions.
Claims 3, 10, 17, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over MITCHELL et al. in views of VIOLA et al., HAYWARD, and ONG (WO 2016/028228).
Regarding claim 3, the combination of Mitchell, Viola, and Hayward disclose the computer-implemented method of claim 1, but does not particularly disclose wherein the at least one user- specific mobility profile parameter comprises a risk score that is automatically recalculated when updated telematics data or consumer-history data is received, and wherein a notification is triggered when the risk score crosses a defined threshold.
However, Ong teaches wherein the at least one user- specific mobility profile parameter comprises a risk score that is automatically recalculated when updated telematics data or consumer-history data is received (page 3, lines 10-25; page 4, lines 4-end; page 5, lines 32-end; the method comprises determining a driving risk profile comprising a risk score, the method comprises while driving the vehicle, receiving status data representing current values (i.e., updated telematics data) that includes operating parameters of the motor vehicle, processing the status date to automatically detect a driving context, and determining an updated risk score; note that the driving context is detected based on data from a computing device associated with the vehicle, the computing device may comprise an on-board device (i.e., telematics device)), and wherein a notification is triggered when the risk score crosses a defined threshold (page 4, lines 29-end; an alert (i.e., notification) may be signaled to the driver when the updated risk score is higher than a predetermined threshold). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell, Viola, and Hayward with the teachings of Ong, since such a modification would allow determining an updated risk score that is generated in real-time, keep the user informed on changes of initial risk score in order for the user to take precautions to reduce the risks.
Regarding claim 10, the combination of Mitchell, Viola, and Hayward disclose the computing system of claim 8, but does not particularly disclose the one or more memories having stored thereon computer-executable instructions that when executed, cause the computing system to: automatically recalculate a risk score when updated telematics data or consumer-history data is received, and trigger a notification when the risk score crosses a defined threshold.
However, Ong teaches the one or more memories having stored thereon computer-executable instructions that when executed, cause the computing system to: automatically recalculate a risk score when updated telematics data or consumer-history data is received (page 3, lines 10-25; page 4, lines 4-end; page 5, lines 32-end; the method comprises determining a driving risk profile comprising a risk score, the method comprises while driving the vehicle, receiving status data representing current values (i.e., updated telematics data) that includes operating parameters of the motor vehicle, processing the status date to automatically detect a driving context, and determining an updated risk score; note that the driving context is detected based on data from a computing device associated with the vehicle, the computing device may comprise an on-board device (i.e., telematics device)), and trigger a notification when the risk score crosses a defined threshold (page 4, lines 29-end; an alert (i.e., notification) may be signaled to the driver when the updated risk score is higher than a predetermined threshold). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell, Viola, and Hayward with the teachings of Ong, since such a modification would allow determining an updated risk score that is generated in real-time, keep the user informed on changes of initial risk score in order for the user to take precautions to reduce the risks.
Regarding claim 17, the combination of Mitchell, Viola, and Hayward disclose the computer-readable medium of claim 15, but does not particularly disclose having stored thereon computer- executable instructions that, when executed, cause a computer to:
automatically recalculate a risk score when updated telematics data or consumer-history data is received, and
trigger a notification when the risk score crosses a defined threshold.
However, Ong teaches computer- executable instructions that, when executed, cause a computer to: automatically recalculate a risk score when updated telematics data or consumer-history data is received (page 3, lines 10-25; page 4, lines 4-end; page 5, lines 32-end; the method comprises determining a driving risk profile comprising a risk score, the method comprises while driving the vehicle, receiving status data representing current values (i.e., updated telematics data) that includes operating parameters of the motor vehicle, processing the status date to automatically detect a driving context, and determining an updated risk score; note that the driving context is detected based on data from a computing device associated with the vehicle, the computing device may comprise an on-board device (i.e., telematics device)), and trigger a notification when the risk score crosses a defined threshold (page 4, lines 29-end; an alert (i.e., notification) may be signaled to the driver when the updated risk score is higher than a predetermined threshold). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell, Viola, and Hayward with the teachings of Ong, since such a modification would allow determining an updated risk score that is generated in real-time, keep the user informed on changes of initial risk score in order for the user to take precautions to reduce the risks.
Regarding claim 18, the combination of Mitchell, Viola, Hayward, and Ong disclose the computer-readable medium of claim 17, Mitchell discloses having stored thereon computer- executable instructions that, when executed, cause a computer to: provide a suggested travel route to the user based on at least one historical travel pattern derived from the mobility data and real-time route availability data (abstract; [0011], [0012], [0016], [0017]; historical travel and route information is stored in the system such that a destination can be predicted using the current location, time, and stored travel data…an optimum route (i.e., suggested travel route) of travel is computed).
Claims 5 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over MITCHELL et al. in views of VIOLA et al., HAYWARD, and McGAVRAN et al. (US 2016/0358468).
Regarding claim 5, the combination of Mitchell and Viola disclose the computer-implemented method of claim 4, but does not particularly disclose wherein transmitting the suggested travel route further comprises automatically alerting the user to a potential delay or obstruction and adjusting the suggested route dynamically based on data obtained through a network-accessible traffic information service.
However, McGavran teaches wherein transmitting the suggested travel route further comprises automatically alerting the user to a potential delay or obstruction and adjusting the suggested route dynamically based on data obtained through a network-accessible traffic information service (Fig. 7, steps 705, 710, 715, 720, and 725; p. [0066]-[0068]; when the process determines that there is a road closure (i.e., obstruction) along the current route, the process presents a new route (i.e., adjust route) and presents a road-closure notification).Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell, Viola, Hayward, and Mitchell with the teachings of McGavran, in order to provide the user with traffic related notifications during navigation and provide an alternative route to avoid obstructions along the route.
Regarding claim 12, the combination of Mitchell, Viola, and Hayward disclose the computing system of claim 11, but does not particularly disclose the one or more memories having stored thereon computer-executable instructions that when executed, cause the computing system to: automatically alert the user to a potential delay or obstruction and adjusting the suggested route dynamically based on data obtained through a network-accessible traffic information service.
However, McGavran teaches computer-executable instructions that when executed, cause the computing system to: automatically alert the user to a potential delay or obstruction and adjusting the suggested route dynamically based on data obtained through a network-accessible traffic information service (Fig. 7, steps 705, 710, 715, 720, and 725; p. [0066]-[0068]; when the process determines that there is a road closure (i.e., obstruction) along the current route, the process presents a new route (i.e., adjust route) and presents a road-closure notification).Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell, Viola, and Hayward with the teachings of McGavran, in order to provide the user with traffic related notifications during navigation and provide an alternative route to avoid obstructions along the route.
Claims 6, 13, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over MITCHELL et al. in views of VIOLA et al., HAYWARD, and BARFIELD JR et al. (US 2016/0035150).
Regarding claim 6, the combination of Mitchell, Viola, and Hayward disclose the computer-implemented method of claim 1, but does not particularly disclose wherein analyzing the mobility data to determine the at least one user-specific mobility profile parameter includes performing a predictive maintenance operation by evaluating telemetry data from one or more operational sensors of the vehicle to predict potential mechanical faults and by notifying the user when a fault likelinood exceeds a threshold.
However, Barfield teaches wherein analyzing the mobility data to determine the at least one user-specific mobility profile parameter includes performing a predictive maintenance operation by evaluating telemetry data from one or more operational sensors of the vehicle to predict potential mechanical faults and by notifying the user when a fault likelihood exceeds a threshold (abstract; p. [0015], [0025]; vehicle data (i.e., telematics data) may be analyzed to predict potential component failures, diagnostic trouble codes, or other mechanical failures…reports or alerts may be delivered to an owner). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell, Viola, and Hayward with the teachings of Barfield, in order to prospectively notify the owner of vehicles of potential issues relating to the operation of the vehicle, allowing owners to take mitigating actions.
Regarding claim 13, the combination of Mitchell, Viola, and Hayward disclose the computing system of claim 8, but does not particularly disclose the one or more memories having stored thereon computer-executable instructions that when executed, cause the computing system to: evaluate telemetry data from one or more operational sensors of the vehicle to predict potential mechanical faults and by notifying the user when a fault likelihood exceeds a threshold.
However, Barfield teaches computer-executable instructions that when executed, cause the computing system to: evaluate telemetry data from one or more operational sensors of the vehicle to predict potential mechanical faults and by notifying the user when a fault likelihood exceeds a threshold (abstract; p. [0015], [0025]; vehicle data (i.e., telematics data) may be analyzed to predict potential component failures, diagnostic trouble codes, or other mechanical failures…reports or alerts may be delivered to an owner). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell, Viola, and Hayward with the teachings of Barfield, in order to prospectively notify the owner of vehicles of potential issues relating to the operation of the vehicle, allowing owners to take mitigating actions.
Regarding claim 19, the combination of Mitchell, Viola, and Hayward disclose the computer-readable medium of claim 15, but does not particularly disclose having stored thereon computer- executable instructions that, when executed, cause a computer to: evaluate telemetry data from one or more operational sensors of the vehicle to predict potential mechanical faults and by notifying the user when a fault likelihood exceeds a threshold.
However, Barfield teaches thereon computer- executable instructions that, when executed, cause a computer to: evaluate telemetry data from one or more operational sensors of the vehicle to predict potential mechanical faults and by notifying the user when a fault likelihood exceeds a threshold (abstract; p. [0015], [0025]; vehicle data (i.e., telematics data) may be analyzed to predict potential component failures, diagnostic trouble codes, or other mechanical failures…reports or alerts may be delivered to an owner). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention, to modify the combination of Mitchell, Viola, and Hayward with the teachings of Barfield, in order to prospectively notify the owner of vehicles of potential issues relating to the operation of the vehicle, allowing owners to take mitigating actions.
Conclusion
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 MARISOL FIGUEROA whose telephone number is (571)272-7840. The examiner can normally be reached Mon-Thurs 8:00am-4:30pm.
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/MARISOL FIGUEROA/
Primary Examiner
Art Unit 2643