DETAILED ACTION
This action is in reply to the amendments and arguments filed October 23rd, 2025. Claims 1, 3-9, and 12-23 are currently pending.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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.
Claims 1, 3-9, 12-18, and 20-23 are rejected under 35 U.S.C. 103 as being unpatentable over previously cited of record Di Pietro et al. (US Pub. No. 20190353500 A1), herein after Di Pietro, further in view of previously cited of record McClernon et al. (US Pub. No. 20140365111 A1), herein after McClernon, further in view of previously cited of record Liu; Yue (US Pub. No. 20220063664 A1), herein after Liu, and further in view of Mishra et al. (US Pub. No. 20230133248 A1), herein after Mishra.
Regarding claim 1, Di Pietro teaches [a] method comprising: receiving vehicle operational data from a plurality of vehicles comprising a fleet of vehicles operating in an area of interest, wherein the vehicle operational data for each of the vehicles indicates a motion and a corresponding location of the vehicle (Di Pietro: Para. 0015, teaching receiving data regarding the motions of a vehicle and its location; and Para. 0028, teaching that the invention can be for a fleet of vehicles); processing the received vehicle operational data to identify events of interest, wherein each of the identified events of interest has an event type and has associated therewith a geographic area in which the event of interest occurred (Di Pietro: Para. 0013, teaching a device for processing sensor data received from a vehicle for the purpose of identifying and categorizing events; and Para. 0015, teaching that the event is categorized and/or identified based on travel data collected from multiple vehicles including data on the location associated with the event); wherein the processing further comprises creating for each of the identified events of interest a record identifying for the event of interest the event type, the geographic area in which the event of interest occurred, an identification of the vehicle in connection with which the event of interest occurred, and a time stamp indicative of a time at which the event of interest occurred (Di Pietro: Para. 0012, teaching that the travel data of an event includes the classification identifying the type of event, the location of the event, and a timestamp; Para. 0042, teaching that the travel data includes sensitive data that could identify the vehicles involved with the event; and Para. 0045, teaching that the sensitive data can be shared with the appropriate authorities).
Di Pietro is silent to identifying clusters of the events of interest, wherein each of the clusters comprises multiple occurrences of ones of the events of interest having the same type and having associated therewith the same geographic area; and for at least one of the identified clusters, executing a responsive action to mitigate operating conditions associated with the event type of the events of interest of the at least one of the identified clusters, the method further comprising analyzing the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle.
In a similar field, McClernon teaches identifying clusters of the events of interest, wherein each of the clusters comprises multiple occurrences of ones of the events of interest having the same type and having associated therewith the same geographic area (McClernon: Para. 0096, teaching clustering hotspots of events in an area of the same type) for the benefit of improved warning of events in an area.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the display of events in an area from Di Pietro to cluster similar events together, as taught by McClernon, for the benefit of improved warning of events in an area.
They are silent to silent to for at least one of the identified clusters, executing a responsive action to mitigate operating conditions associated with the event type of the events of interest of the at least one of the identified clusters, the method further comprising analyzing the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle.
In a similar field, Liu teaches for at least one of the identified clusters, executing a responsive action to mitigate operating conditions associated with the event type of the events of interest of the at least one of the identified clusters (Liu: Para. 0029, teaching restricting the speed and acceleration of vehicles in an area of interest based on collision avoidance predictions) for the benefit of allowing the vehicle to proceed in a potentially hazardous area while mitigating the risk of danger.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the applicant’s claimed invention to modify the event detection and warning from Di Pietro in view of McClernon to restrict the motion of the vehicle in areas near events, as taught by Liu, for the benefit of allowing the vehicle to proceed in a potentially hazardous area while mitigating the risk of danger.
They are silent to silent to the method further comprising analyzing the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle.
In a similar field, Mishra teaches the method further comprising analyzing the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle (Mishra: Para. 0043, teaching that the identified vehicle involved with the event can be assessed for damages and degraded health; and Para. 0064, teaching that the degraded health of a vehicle can be used to assess the depreciated sales price of the vehicle after the event) for the benefit of maintaining a fleet of operational vehicles.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the applicant’s claimed invention to modify the event monitoring and prediction system from Di Pietro in view of McClernon in further view of Mishra to analyze the health of vehicles caught up in the event and the deprecation in monetary value of the vehicle after the event, as taught by Mishra, for the benefit of maintaining a fleet of operational vehicles.
Regarding claim 3, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 1, and McClernon goes on to further teach [t]he method of claim 1, further comprising: generating a heat map of the identified clusters of the events of interest; overlaying the heat map on a map of the area of interest (McClernon: Para. 0072, teaching displaying of events in an area; and Para. 0074, teaching that multiple events may be grouped into a heatmap).
Regarding claim 4, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 1, and Di Pietro goes on to further teach [t]he method of claim 1, wherein at least one of the identifying and the executing is performed by a machine learning module (Di Pietro: Para. 0062, teaching that the event recognition may be performed using machine learning techniques).
Regarding claim 5, Di Pietro, McClernon, Liu, and Mishra, and Liu goes on to further teach [t]he method of claim 1, wherein the responsive action comprises imposing restrictions on vehicle operations in a geofenced area of the area of interest (Liu: Para. 0029, teaching restricting the speed and acceleration of vehicles in an area of interest based on collision avoidance predictions).
Regarding claim 6, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 5, and Di Pietro goes on to further teach [t]he method of claim 5, wherein the restrictions comprise at least one of limiting a maximum speed of the vehicle, limiting a maximum acceleration of the vehicle, and providing a notification to an operator of at least one of the vehicles (Liu: Para. 0029, teaching restricting the speed and acceleration of vehicles in an area of interest based on collision avoidance predictions).
Regarding claim 7, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 1, and Di Pietro goes on to further teach [t]he method of claim 1, wherein the responsive action comprises notifying an operator of at least one of the vehicles of the operating conditions (Di Pietro: Para. 0096, teaching displaying to an operator a visualization of the event on a display).
Regarding claim 8, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 7, and Di Pietro goes on to further teach [t]he method of claim 7, wherein the notifying comprises providing at least one of: an audio alert via a speaker installed on the at least one of the vehicles; a text alert via a display installed on the at least one of the vehicles; and a graphic alert via the display installed on the at least one of the vehicles (Di Pietro: Para. 0023, teaching that the travel data includes text descriptions, audio data, and images; and Para. 0095 and 0096, teaching that the traveling data is displayed to the operator alongside the notification of the event).
Regarding claim 9, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 1, and Di Pietro goes on to further teach [t]he method of claim 1, wherein the vehicle operational data comprises data generated by inertial measurement units (IMUs) installed on the vehicles (Di Pietro: Para. 0032, teaching the use of inertial measurement units (IMUs) for gathering travel data).
Regarding claim 12, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 10, and McClernon goes on to further teach [t]he method of claim 10, further comprising: analyzing the records to detect that a hot spot is emerging in connection with the geographic area (McClernon: Para. 0096, teaching clustering hotspots of events in an area of the same type); and Di Pietro goes on to further teach notifying a fleet manager of the detected emerging hot spot (Di Pietro: Para. 0028, teaching that the invention is applicable to a fleet of vehicles; and Para. 0095, teaching that the vehicles are notified of events in an area as they occur).
Regarding claim 13, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 1, and Di Pietro goes on to further teach [t]he method of claim 1, further comprising providing a substantially real-time notification to a fleet manager in connection with one of the events of interest (Di Pietro: Para. 0027, teaching that information of events are supplied in real-time).
Regarding claim 14, Di Pietro teaches [a] system comprising: a plurality of vehicles comprising a fleet of vehicles operating in an area of interest, each of the vehicles having installed thereon an inertial measurement device for generating motion data for the vehicle and having associated therewith a global positioning system (GPS) for generating location data for the vehicle; and a fleet management system for receiving the motion data and the location data for the vehicles, the fleet management system further configured to (Di Pietro: Para. 0028, teaching that the invention is applicable to a fleet of vehicles; Para. 0032, teaching the use of inertial measurement units (IMUs) for gathering travel data; and Para. 0025, teaching the use of GPS for positioning vehicles as part of the travel data); process the received motion data and location data to identify events of interest in connection with the vehicles, wherein each of the identified events of interest has an event type and has associated therewith a geographic location in which the event of interest occurred (Di Pietro: Para. 0013, teaching a device for processing sensor data received from a vehicle for the purpose of identifying and categorizing events; and Para. 0015, teaching that the event is categorized and/or identified based on travel data collected from multiple vehicles including data on the location associated with the event); for each of the identified clusters, determine a responsive action to mitigate operating conditions associated with the event type of the events of interest of the at least one of the identified clusters (Di Pietro: Para. 0012, teaching that the travel data of an event includes the classification identifying the type of event, the location of the event, and a timestamp; Para. 0042, teaching that the travel data includes sensitive data that could identify the vehicles involved with the event; and Para. 0045, teaching that the sensitive data can be shared with the appropriate authorities).
Di Pietro is silent to identify clusters of the events of interest, wherein each of the clusters comprises multiple occurrences of ones of the events of interest having the same type and having associated therewith the same geographic location; and for each of the identified clusters, determine a responsive action to mitigate operating conditions associated with the event type of the events of interest of the at least one of the identified clusters, the fleet management system further configured to analyze the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle.
In a similar field, McClernon teaches identify clusters of the events of interest, wherein each of the clusters comprises multiple occurrences of ones of the events of interest having the same type and having associated therewith the same geographic location (McClernon: Para. 0096, teaching clustering hotspots of events in an area of the same type) for the benefit of improved warning of events in an area.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the display of events in an area from Di Pietro to cluster similar events together, as taught by McClernon, for the benefit of improved warning of events in an area.
Di Pietro in view of McClernon are silent to for each of the identified clusters, determine a responsive action to mitigate operating conditions associated with the event type of the events of interest of the at least one of the identified clusters, the fleet management system further configured to analyze the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle.
In a similar field, Liu teaches for each of the identified clusters, determine a responsive action to mitigate operating conditions associated with the event type of the events of interest of the at least one of the identified clusters (Liu: Para. 0029, teaching restricting the speed and acceleration of vehicles in an area of interest based on collision avoidance predictions) for the benefit of allowing the vehicle to proceed in a potentially hazardous area while mitigating the risk of danger.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the applicant’s claimed invention to modify the event detection and warning from Di Pietro in view of McClernon to restrict the motion of the vehicle in areas near events, as taught by Liu, for the benefit of allowing the vehicle to proceed in a potentially hazardous area while mitigating the risk of danger.
They are silent to silent to the fleet management system further configured to analyze the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle.
In a similar field, Mishra teaches the fleet management system further configured to analyze the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle (Mishra: Para. 0043, teaching that the identified vehicle involved with the event can be assessed for damages and degraded health; and Para. 0064, teaching that the degraded health of a vehicle can be used to assess the depreciated sales price of the vehicle after the event) for the benefit of maintaining a fleet of operational vehicles.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the applicant’s claimed invention to modify the event monitoring and prediction system from Di Pietro in view of McClernon in further view of Mishra to analyze the health of vehicles caught up in the event and the deprecation in monetary value of the vehicle after the event, as taught by Mishra, for the benefit of maintaining a fleet of operational vehicles.
Regarding claim 15, Di Pietro, McClernon, and Liu remain as applied as in claim 14, and McClernon goes on to further teach [t]he system of claim 14, wherein the fleet management system is further configured to: generate a heat map of the identified clusters of the events of interest; and overlay the heat map on a map of the area of interest (McClernon: Para. 0072, teaching displaying of events in an area; and Para. 0074, teaching that multiple events may be grouped into a heatmap).
Regarding claim 16, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 14, and Liu goes on to further teach [t]he system of claim 14, wherein the responsive action comprises establishing a geofence in the geographic area of the identified cluster and imposing restrictions on vehicle operations within the geofence (Liu: Para. 0029, teaching restricting the speed and acceleration of vehicles in an area of interest based on collision avoidance predictions).
Regarding claim 17, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 14, and Di Pietro goes on to further teach [t]he system of claim 14, wherein the responsive action comprises providing a notification to an operator of at least one of the vehicles of the operating conditions, wherein the notification comprises at least one of an audio alert, a text alert, and a graphic alert (Di Pietro: Para. 0023, teaching that the travel data includes text descriptions, audio data, and images; and Para. 0095 and 0096, teaching that the traveling data is displayed to the operator alongside the notification of the event).
Regarding claim 18, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 14, and Di Pietro goes on to further teach [t]he system of claim 14, wherein the vehicles comprise electric vehicles (Di Pietro: Para. 0029, teaching that the vehicles managed includes electric vehicles).
Regarding claim 20, Di Pietro teaches [o]ne or more non-transitory computer-readable storage media comprising instructions for execution which, when executed by a processor, are operable to perform operations comprising (Di Pietro: Para. 0028, teaching that the invention is applicable to a fleet of vehicles; Para. 0032, teaching the use of inertial measurement units (IMUs) for gathering travel data; Para. 0025, teaching the use of GPS for positioning vehicles as part of the travel data; and Para. 0051, teaching a non-transitory computer readable medium programmed to perform the processes of the invention); processing vehicle data generated by inertial measurement units (IMUs) and global positioning system (GPS) units installed on vehicles comprising a fleet of vehicles operating in an area of interest to identify occurrences of events, wherein each of the identified occurrences has associated therewith an event type and a geographic location (Di Pietro: Para. 0013, teaching a device for processing sensor data received from a vehicle for the purpose of identifying and categorizing events; and Para. 0015, teaching that the event is categorized and/or identified based on travel data collected from multiple vehicles including data on the location associated with the event); wherein the processing further comprises creating for each of the identified events of interest a record identifying for the event of interest the event type, the geographic area in which the event of interest occurred, an identification of the vehicle in connection with which the event of interest occurred, and a time stamp indicative of a time at which the event of interest occurred (Di Pietro: Para. 0012, teaching that the travel data of an event includes the classification identifying the type of event, the location of the event, and a timestamp; Para. 0042, teaching that the travel data includes sensitive data that could identify the vehicles involved with the event; and Para. 0045, teaching that the sensitive data can be shared with the appropriate authorities).
Di Pietro is silent to identifying clusters of the event occurrences, wherein each of the clusters comprises event occurrences having the same event type and geographic location; and for each of the clusters, implementing a responsive action to mitigate operating conditions associated with the event type of the clusters, the operations further comprising analyzing the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle.
In a similar field, McClernon teaches identifying clusters of the event occurrences, wherein each of the clusters comprises event occurrences having the same event type and geographic location (McClernon: Para. 0096, teaching clustering hotspots of events in an area of the same type) for the benefit of improved warning of events in an area.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the display of events in an area from Di Pietro to cluster similar events together, as taught by McClernon, for the benefit of improved warning of events in an area.
Di Pietro in view of McClernon are silent to for each of the clusters, implementing a responsive action to mitigate operating conditions associated with the event type of the clusters, the operations further comprising analyzing the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle.
In a similar field, Liu teaches for each of the clusters, implementing a responsive action to mitigate operating conditions associated with the event type of the clusters (Liu: Para. 0029, teaching restricting the speed and acceleration of vehicles in an area of interest based on collision avoidance predictions) for the benefit of allowing the vehicle to proceed in a potentially hazardous area while mitigating the risk of danger.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the applicant’s claimed invention to modify the event detection and warning from Di Pietro in view of McClernon to restrict the motion of the vehicle in areas near events, as taught by Liu, for the benefit of allowing the vehicle to proceed in a potentially hazardous area while mitigating the risk of danger.
They are silent to silent to the operations further comprising analyzing the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle.
In a similar field, Mishra teaches the operations further comprising analyzing the records to determine for each of the vehicles at least one of a depreciated value of the vehicle and a remaining useful life of the vehicle (Mishra: Para. 0043, teaching that the identified vehicle involved with the event can be assessed for damages and degraded health; and Para. 0064, teaching that the degraded health of a vehicle can be used to assess the depreciated sales price of the vehicle after the event) for the benefit of maintaining a fleet of operational vehicles.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the applicant’s claimed invention to modify the event monitoring and prediction system from Di Pietro in view of McClernon in further view of Mishra to analyze the health of vehicles caught up in the event and the deprecation in monetary value of the vehicle after the event, as taught by Mishra, for the benefit of maintaining a fleet of operational vehicles.
Regarding claim 21, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 20, and McClernon goes on to further teach [t]he one or more non-transitory computer-readable storage media of claim 20, wherein the operations further comprise: generating a heat map of the identified clusters of the events of interest; and overlaying the heat map on a map of the area of interest (McClernon: Para. 0072, teaching displaying of events in an area; and Para. 0074, teaching that multiple events may be grouped into a heatmap).
Regarding claim 22, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 20, and Liu goes on to further teach [t]he one or more non-transitory computer-readable storage media of claim 20, wherein the responsive action comprises limiting a maximum speed of the vehicle in a geofenced area (Liu: Para. 0029, teaching restricting the speed and acceleration of vehicles in an area of interest based on collision avoidance predictions).
Regarding claim 23, Di Pietro, McClernon, Liu, and Mishra remain as applied as in claim 20, and Di Pietro goes on to further teach [t]he one or more non-transitory computer-readable storage media of claim 20, wherein the responsive action comprises providing an audio, text, or graphic alert to an operator of at least one of the vehicles of the operating conditions (Di Pietro: Para. 0023, teaching that the travel data includes text descriptions, audio data, and images; and Para. 0095 and 0096, teaching that the traveling data is displayed to the operator alongside the notification of the event).
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Di Pietro in view of McClernon in further view of Liu in further view of Mishra as applied to claim 14 above, and further in view of Walsh; Vincent (US Pub. No. 20200133268 A1), herein after Walsh.
Regarding claim 19, Di Pietro, McClernon, and Liu remain as applied as in claim 14, however they are silent to [t]he system of claim 14, wherein the vehicles comprise lightweight utility vehicles operating on a closed campus.
In a similar field, Walsh teaches [t]he system of claim 14, wherein the vehicles comprise lightweight utility vehicles operating on a closed campus (Walsh: Para. 0032, teaching the control of a fleet of vehicles in a geographic region; Para. 0037, teaching control of a fleet of golf carts; and Para. 0075, teaching the control of vehicles and their routes based on events in an area) for the benefit of maintaining a fleet of various vehicles.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the applicant’s claimed invention to modify the fleet management based on events from Di Pietro in view of McClernon in further view of Liu in further view of Mishra to manage lightweight utility vehicles such as golf carts in a geofenced area, as taught by Walsh, for the benefit of maintaining a fleet of various vehicles.
Response to Arguments
Applicant's arguments filed October 23rd, 2025 have been fully considered but they are not persuasive.
Applicant’s amendments, see Remarks, filed October 23rd, 2025, with respect to the 101 and 112(b) rejections have been fully considered and render the 101 and 112(b) rejections of record moot. Therefore, the 101 and 112(b) rejections of record have been withdrawn.
Applicant’s arguments, see pages 11-12, filed October 23rd, 2025, with respect to the rejection(s) of claim(s) 1, 3-9, 12-18, and 20-23 under 103 in view of Di Pietro in view of McClernon and in further view of Liu and Taylor in light of the amendments have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Di Pietro in view of McClernon in further view of Liu in further view of Mishra.
Applicant contends (see page 11 lines 11-18, filed October 23rd, 2025) that Di Pietro is deficient in teaching the limitation of creating for each of the identified events of interest a record identifying for the event of interest… an identification of the vehicle in connection with which the event of interest occurred as recited in the independent claims as the prior art of Di Pietro teaches that the vehicles being identified as connected with the event are not the same vehicles that are transmitting the vehicle operational data. The examiner respectfully disagrees. The examiner notes that the BRI of the at issue limitation is merely that the identification is of a vehicle associated with the event, the claims do not require that the vehicle is in connection with the event be the one that reports information, thus it is reasonable to interpret that a separate vehicle gathers identification information of a vehicle connected to the event and then transmits it for processing.
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 Aaron K McCullers whose telephone number is (571)272-3523. The examiner can normally be reached Monday - Friday, Roughly 9 AM - 6 PM ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Angela Ortiz can be reached at (571) 272-1206. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/A.K.M./Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663