DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. The amendment filed on 03/18/2026 has been received and fully considered.
3. Claims 1-14 are presented for examination.
Response to Arguments
4. Applicant's arguments filed 03/18/2026 have been fully considered but they are not persuasive; however, the rejection under 35 USC 101 has been withdrawn. Regarding applicant’s assertions that: “Claim 12 is directed to a simulation system. Claim 13 is directed to a conveyance system that includes the simulation system of claim 12. Withdrawal of the rejection is respectfully requested.”, the Examiner respectfully notes that the claim remain unclear as to whether it is directed to a different claimed subject matter a conveyor system or the system of claim 12. As previous noted, for examination purposes, the claim is interpreted as being directed to “the system according to claim 12, further comprises… and the Examiner respectfully requests that claim be amended to state “The system of claim 12 further comprising…”. As such the rejection has been maintained. As per Applicant’s assertions that: “… neither Sakakibara or Dubois, whether considered individually or in combination, disclose "calculate an index representing a change over time in the congestion level, search for a route for each of the plurality of moving bodies using a cost based on the congestion level calculated on the basis of the estimated reduction rate, perform a simulation of movement on the searched route, and instruct at least one of the plurality of moving bodies in the warehouse to move along the route”, the examiner respectfully notes that Sakakibara et al., used as the primary reference in the rejection, clearly provides for calculating the index represented the change in traffic conditions (see para [0120], in which traffic index is calculated using index calculation unit 24 further para [0131], every time the index calculation unit 24 causes each simulation vehicle SV to move on the road network, the index calculation unit 24 calculates a traffic evaluation index; and executes a route searching process to generate a scheduled route for each of the moving bodies/vehicles [0076], and at para [0107], the traffic flow simulator 21 causes a plurality of simulation vehicles SV to travel/move in a road network formed as a link network included in a predetermined area and outputs a traffic evaluation index such as a link trip time period and a congestion length (see further para [0108], in which the traffic flow simulator 21 executes simulation in accordance with the set condition (para [0109]). While Sakakibara et al. does not specifically state that an estimated reduction rate that is an index representing a change over time in congestion level of the route of each of the plurality of moving bodies and the said moving bodies is that of moving bodies in the warehouse, it is notes that Dubois, Jr. et al., used as the secondary reference in the rejection, at col.7 lines 8-55 provides for using a traffic congestion data generated based traffic index to include a traffic rating that indicate a relative degree of traffic congestion e.g. could estimate a traffic reduction rate, for example traffic events or the presence of things that can affect traffic. But fail to show that a cost is used and that the plurality of moving bodies are bodies moving in the warehouse; nonetheless, Wurman et al. teaches, now further rely upon, provides for using a cost analysis using the process to move selected bodies along a path in the warehouse (see para [0209-02010], it is assumed that path 16p and path 16q are the least costly paths 16 between mobile drive unit 20h and inventory holder 30p and 30q, respectively. As a result, resource scheduling module 92 selects one of inventory holder 30p and 30q based, at least in part, on the cost associated with path 16p and 16q. further in para [0035], As one example, inventory system 10 may represent a mail order warehouse facility, and inventory items may represent merchandise stored in the warehouse facility. [0040] Workspace 70 represents an area associated with inventory system 10 in which mobile drive units 20 can move and/or inventory holders 30 can be stored. For example, workspace 70 may represent all or part of the floor of a mail-order warehouse in which inventory system 10 operates.), and the combination of the cited references clearly renders obvious the limitation contrary to applicant’s assertions.
Claim Rejections - 35 USC § 103
6. 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.
6.0 Claim(s) 1-14 are rejected under 35 U.S.C. 103 as being unpatentable over Sakakibara et al. (USPG_PUB No. 2021/0233394), in view of Dubois, Jr. et al. (U.S. Patent No. 10,109,185), further in view of Wurman et al. (USPG_PUB No. 2017/0038770).
6.1 In considering claims 1, 7, 14, Sakakibara et al. teaches a simulation device, comprising:
a processor; a storage unit, coupled to the processor, that stores an estimated reduction rate that is an index representing a change over time in congestion level of the route of each of the plurality of moving bodies and a memory, connected to the processor, the memory storing instructions that when executed by the processor (fig.2, [0019] [0084] The storage unit 12 includes a storage medium such as a hard disk and a semiconductor memory. The computer program 18 includes an application program that causes the control unit 11 to function as a device such as a traffic flow simulator 21 or a signal control device 22. [0106] The control unit 11 of the center apparatus 5 can function as the traffic flow simulator 21, by executing the computer program 18 read out from the storage unit 12.), configures the processor to:
perform a simulation of movement of a plurality of moving bodies physically present in a warehouse each moving along respective routes in the warehouse (see fig.2, 5, para [0015], he traffic flow simulator includes: a route selection unit configured to select a route for each of a plurality of the simulation vehicles in accordance with a predetermined route selection model; [0107] The traffic flow simulator 21 is a device that causes a plurality of simulation vehicles SV to tentatively travel in a road network formed as a link network included in a predetermined area (e.g., one prefecture, city, state, or the like) in a digital map,); calculate a congestion level of the route of each of the plurality of moving bodies based on a result of the simulation (see fig.2, 5 “congestion length outputted by the traffic flow simulator 21”, para [0120] At this time, the traffic flow simulator 21 generates a traffic flow on a road network composed of time series data of the vehicle position of each predetermined control cycle (e.g., 0.1 to 1.0 seconds), and on the basis of the generated traffic flow, calculates a traffic evaluation index such as a trip time period, a congestion length, or a queue length of each road section (link).); calculate an index representing a change over time in the congestion level (see para [0120] At this time, the traffic flow simulator 21 generates a traffic flow on a road network composed of time series data of the vehicle position of each predetermined control cycle (e.g., 0.1 to 1.0 seconds), and on the basis of the generated traffic flow, calculates a traffic evaluation index such as a trip time period, a congestion length, or a queue length of each road section (link). [0131] Every time the index calculation unit 24 causes each simulation vehicle SV to move on the road network, the index calculation unit 24 calculates a traffic evaluation index such as a link trip time period at each time point. The index calculation unit 24 outputs, to the route selection unit 23, the calculated traffic evaluation index such as the link trip time period.); search for a route for each of the plurality of moving bodies based on the congestion level calculated on the basis of the estimated reduction rate (para [0076] The scheduled travel information in the real travel information is generated by the navigation device of the on-vehicle device 2. Specifically, the navigation device executes a route searching process while using, as input information, the departure point and the destination point inputted by an occupant, and generates a scheduled route of the vehicle 1.), perform a simulation of movement on the searched route (see para [0107] The traffic flow simulator 21 is a device that causes a plurality of simulation vehicles SV to tentatively travel in a road network formed as a link network included in a predetermined area (e.g., one prefecture, city, state, or the like) in a digital map, and outputs a traffic evaluation index such as a link trip time period and a congestion length. [0108] The traffic flow simulator 21 reads out data necessary for simulation, from the databases 15 to 17, and executes traffic flow simulation related to passage of vehicles. [0109] In the present embodiment, when a predetermined setting input of an area, a time frame, a restricted section, a congestion section, and the like for which simulation is to be performed, is performed through an input operation to the input unit 13 by the user, the traffic flow simulator 21 executes simulation in accordance with the set condition.), and instruct at least one of the plurality of moving bodies (The traffic flow simulator 21 is a device that causes a plurality of simulation vehicles SV to travel/move along the road network formed as a link network included in a predetermined area). Sakakibara et al., however, does not specifically state that an estimated reduction rate that is an index representing a change over time in congestion level of the route of each of the plurality of moving bodies and the said moving bodies is that of moving bodies in the warehouse.
Dubois, Jr. et al. teaches a storage unit (302) that stores therein an estimated reduction rate that is an index representing a change over time in congestion level of the route of each of the plurality of moving bodies (see col.7 lines 8-55, provides for using a traffic congestion data generated based traffic index to include a traffic rating that indicate a relative degree of traffic congestion e.g. could estimate a traffic reduction rate, for example traffic events or the presence of things that can affect traffic (see col.7 lines 8-55, traffic congestion data generated based on the traffic congestion data index 320. For example, traffic image index 312 can include several entries 314-318 which each relate traffic image with a location and contains entries 322-326 that each relate traffic congestion data with locations and can include, for example, a traffic congestion rating that indicates a relative degree of traffic congestion, traffic events or the presence of things that can affect traffic.).
Sakakibara et al. and Dubois, Jr. et al. are analogous art because they are from the same field of endeavor and that the model analyzes by Dubois, Jr. et al. is similar to that of Sakakibara et al. Therefore, it would have been obvious to a person of skilled in the art at the time of filing of filing of the applicant’s invention to combine the method of Dubois, Jr. et al. with that of Sakakibara et al. because Dubois, Jr. et al. provides for maintaining the indexes by the traffic server to allow identification of traffic images in response to queries for traffic images for a given location in a more accurate (col.9 lines 3-12).
But fail to show that a cost is used and that the plurality of moving bodies are bodies moving in the warehouse; nonetheless, Wurman et al. teaches, now further rely upon, provides for using a cost analysis using the process to move selected bodies along a path in the warehouse (see para [0209-02010], it is assumed that path 16p and path 16q are the least costly paths 16 between mobile drive unit 20h and inventory holder 30p and 30q, respectively. As a result, resource scheduling module 92 selects one of inventory holder 30p and 30q based, at least in part, on the cost associated with path 16p and 16q. further in para [0035], As one example, inventory system 10 may represent a mail order warehouse facility, and inventory items may represent merchandise stored in the warehouse facility. [0040] Workspace 70 represents an area associated with inventory system 10 in which mobile drive units 20 can move and/or inventory holders 30 can be stored. For example, workspace 70 may represent all or part of the floor of a mail-order warehouse in which inventory system 10 operates.).
Sakakibara et al., Dubois, Jr. et al., and Wurman et al. are analogous art because they are from the same field of endeavor and that the model analyzes by Wurman et al. is similar to that of Sakakibara et al. and Dubois, Jr. et al. Therefore, it would have been obvious to a person of skilled in the art at the time of filing of filing of the applicant’s invention to combine the method of Wurman et al. with that of Sakakibara et al. and Dubois, Jr. et al. because Wurman et al. teaches the improvement of effectiveness without reducing the overall efficiency of inventory system 10 (para [0051], and improve the operational efficiency of inventory system 10 by transmitting new paths 16 to mobile drive units 20 that are optimized based on the attributes of inventory holders 30 or inventory stations 50 associated with the relevant mobile drive units 20 or the tasks they are completing (para [0107]).
6.2 As per claims 2 and 8, the combined teachings of Sakakibara et al., Dubois, Jr. et al., and Wurman et al. teach the step to calculate an estimated reduction rate based on the index representing a change over time in congestion level (see Sakakibara et al. para [0126] The route selection unit 23 executes route selection for each simulation vehicle SV by using a traffic evaluation index (e.g., link trip time period) sequentially inputted from the index calculation unit 24. At each control cycle, the route selection unit 23 outputs, to the index calculation unit 24, the selected route for each simulation vehicle SV.), and store the calculated estimated reduction rate in the storage unit (see Dubois, Jr. et al. col.7 lines 8-55, The data stores 308, 310 can be used to store traffic images, and traffic congestion data that are generated based on the traffic images, as well as traffic congestion data index 320. The indexes 312, 320 are data structures that relate location and time to traffic images or generated traffic congestion data; Sakakibara et al. para [0175] Then, the route selection unit 23 outputs the route M1 to the index calculation unit 24 and records the route M1 into the storage unit 12 (step ST10).). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of filing of the applicant’s invention to combine the method of Wurman et al. with that of Sakakibara et al. and Dubois, Jr. et al. because Wurman et al. teaches the improvement of effectiveness without reducing the overall efficiency of inventory system 10 (para [0051], and improve the operational efficiency of inventory system 10 by transmitting new paths 16 to mobile drive units 20 that are optimized based on the attributes of inventory holders 30 or inventory stations 50 associated with the relevant mobile drive units 20 or the tasks they are completing (para [0107]).
6.3 Regarding claims 3 and 9, the combined teachings of Sakakibara et al., Dubois, Jr. et al., and Wurman et al. teach a display connected to the processor, wherein the processor is configured to display a distribution of at least one of a congestion level calculated based on a result of the simulation and a congestion level calculated based on the estimated reduction rate in a space subjected to the simulation (see Dubois, Jr. et al. fig.3-4; further see Sakakibara et al. fig2, 5, para [0107] The traffic flow simulator 21 is a device that causes a plurality of simulation vehicles SV to tentatively travel in a road network formed as a link network included in a predetermined area (e.g., one prefecture, city, state, or the like) in a digital map, and outputs a traffic evaluation index such as a link trip time period and a congestion length. [0118] Output data (traffic evaluation index) of the traffic flow simulator 21 includes at least one of a link trip time period, a congestion length, a queue length, and the number of vehicles having passed a link.). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of filing of the applicant’s invention to combine the method of Wurman et al. with that of Sakakibara et al. and Dubois, Jr. et al. because Wurman et al. teaches the improvement of effectiveness without reducing the overall efficiency of inventory system 10 (para [0051], and improve the operational efficiency of inventory system 10 by transmitting new paths 16 to mobile drive units 20 that are optimized based on the attributes of inventory holders 30 or inventory stations 50 associated with the relevant mobile drive units 20 or the tasks they are completing (para [0107]).
6.4 As per claims 4 and 10, the combined teachings of Sakakibara et al., Dubois, Jr. et al., and Wurman et al. teach that wherein the congestion level of the route is defined based on at least one of a time required for one of the moving bodies to move down the route and the number of moving bodies that travel on the route per unit time (see Sakakibara et al. fig 5, para [0118] Output data (traffic evaluation index) of the traffic flow simulator 21 includes at least one of a link trip time period, a congestion length, a queue length, and the number of vehicles having passed a link. [0119] The traffic flow simulator 21 generates a plurality of simulation vehicles SV from a plurality of departure points, and causes each simulation vehicle SV to disappear at a time point when the simulation vehicle SV has reached a destination point. [0120] At this time, the traffic flow simulator 21 generates a traffic flow on a road network composed of time series data of the vehicle position of each predetermined control cycle (e.g., 0.1 to 1.0 seconds), and on the basis of the generated traffic flow, calculates a traffic evaluation index such as a trip time period, a congestion length, or a queue length of each road section (link). Further Dubois, Jr. et al. fig.3, col.7 lines 17-27, The traffic congestion data index 320 contains entries 322-326 that each relate traffic congestion data with locations (“LOC”) corresponding to the traffic images used to generate the traffic congestion data (“CD”), and a time. Each entry in the traffic image index 312 can contain a location, and a pointer to one or more traffic images or user accounts that have traffic images taken at or near the location recently. The time for each entry is used to prune the indexes of stale entries to ensure that the traffic information (e.g. traffic images or traffic congestion data) is timely and relevant). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of filing of the applicant’s invention to combine the method of Wurman et al. with that of Sakakibara et al. and Dubois, Jr. et al. because Wurman et al. teaches the improvement of effectiveness without reducing the overall efficiency of inventory system 10 (para [0051], and improve the operational efficiency of inventory system 10 by transmitting new paths 16 to mobile drive units 20 that are optimized based on the attributes of inventory holders 30 or inventory stations 50 associated with the relevant mobile drive units 20 or the tasks they are completing (para [0107]).
6.5 With regards to claims 5 and 11, the combined teachings of Sakakibara et al., Dubois, Jr. et al., and Wurman et al. teach that wherein the processor is configured to simulate movement of the plurality of moving bodies from a starting point to an end point that are randomly specified in a space subjected to the simulation (see Sakakibara et al. fig. 5, 8, para [0103] In the traffic volume table shown in FIG. 4, traffic volumes when the origins/destinations are cells A1, A5, A6, A10, and A12 in the OD table are specified. [0104] Specifically, as the traffic volume in a predetermined time period, there are 40 vehicles having an origin of cell A1 and having a destination of cell A5. In addition, as the traffic volume, there are 150 vehicles having an origin of cell A10 and having a destination of cell A5. [0161] The route selection unit 23 of the traffic flow simulator 21 executes the process of the flow chart shown in FIG. 9 for each simulation vehicle SV present in the road network. However, when dummy vehicles DV have been generated due to the above-described traffic flow correction process (FIG. 6), the dummy vehicles DV are also subjected to the route selection process, and are considered as simulation vehicles SV of which the routes and selection characteristics are unknown.). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of filing of the applicant’s invention to combine the method of Wurman et al. with that of Sakakibara et al. and Dubois, Jr. et al. because Wurman et al. teaches the improvement of effectiveness without reducing the overall efficiency of inventory system 10 (para [0051], and improve the operational efficiency of inventory system 10 by transmitting new paths 16 to mobile drive units 20 that are optimized based on the attributes of inventory holders 30 or inventory stations 50 associated with the relevant mobile drive units 20 or the tasks they are completing (para [0107]).
6.6 As per claims 6 and 12, the combined teachings of Sakakibara et al., Dubois, Jr. et al., and Wurman et al. teach vehicles which may be a “normal driving vehicle” that requires operation by an occupant, or an “automated driving vehicle” having a level of 4 or higher that does not require operation by an occupant (see Sakakibara et al. para [0060])), each conveys a rack that stores an item (Wurman et al. title, abstract, the method further includes docking the mobile drive unit with the inventory holder and moving the mobile drive unit and the inventory holder to a second point within the workspace. The second point is associated with conveyance equipment. The method further includes moving the inventory holder to a third point within the workspace using the conveyance equipment; para [0005], [0035] Inventory items represent any objects suitable for storage, retrieval, and/or processing in an automated inventory system 10. For the purposes of this description, “inventory items” may represent any one or more objects of a particular type that are stored in inventory system 10. Thus, a particular inventory holder 30 is currently “storing” a particular inventory item if the inventory holder 30 currently holds one or more units of that type, [0039], Inventory stations 50 may be controlled, entirely or in part, by human operators or may be fully automated. Moreover, the human or automated operators of inventory stations 50 may be capable of performing certain tasks to inventory items, such as packing or counting inventory items, as part of the operation of inventory system 10.). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of filing of the applicant’s invention to combine the method of Wurman et al. with that of Sakakibara et al. and Dubois, Jr. et al. because Wurman et al. teaches the improvement of effectiveness without reducing the overall efficiency of inventory system 10 (para [0051], and improve the operational efficiency of inventory system 10 by transmitting new paths 16 to mobile drive units 20 that are optimized based on the attributes of inventory holders 30 or inventory stations 50 associated with the relevant mobile drive units 20 or the tasks they are completing (para [0107]).
6.7 Regarding claim 13, the combined teachings of Sakakibara et al., Dubois, Jr. et al., and Wurman et al. teach the conveyance system (see Wurman et al. fig.15-16, FIG. 15, [0094], inventory system 10 that includes certain types of conveyance equipment), comprising: the simulation system according to claim 12 (see Sakakibara et al. fig.2, 5; Wurman et al. title, abstract, para [0005], [0035-36]); the order management device that manages order information including a shipping address of the item and a quantity to be shipped (see Wurman et al. [0005], [0035], [0039], “management module 15”, [0036], for example, individual units of a particular inventory item may be received and stored in inventory holders 30 until a threshold number of units of that inventory item have been received. Mobile drive unit 20 may be tasked with retrieving an inventory holder 30 in this state. A pallet may then be packed with inventory items removed from that inventory holder 30 and shipped to another facility, such as a mail-order warehouse. Para [0149] in particular embodiments, resource scheduling module 92 may select a destination for mobile drive unit 20c that is close to frequently-requested inventory holders 30. For example, in a mail-order warehouse, resource scheduling module 92 may select a destination “shipping address” for mobile drive unit 20c near inventory holders 30 that store top-selling inventory items 40. …, in such embodiments, resource scheduling module 92 may consider the frequency with which particular inventory holders 30 are used in responding to inventory requests and select a location for mobile drive unit 20c that is near a frequently-requested inventory holder 30); and an operation management device that manages an operation of the automated guided vehicles by finding routes (see Wurman et al. para [0058], route planning module 94 receives route requests from mobile drive units 20. In response to receiving a route request, route planning module 94 generates a path to one or more destinations identified in the route request) based on a congestion level calculated using the estimated reduction rate obtained by the simulation system (see Dubois, Jr. et al., see col.7 lines 8-55, The data stores 308, 310 can be used to store traffic images, and traffic congestion data that are generated based on the traffic images, as well as a traffic image index 312, and a traffic congestion data index 320. The traffic congestion data can include, for example, a traffic congestion rating that indicates a relative degree of traffic congestion. Further Wurman et al. para [0107], management module 15 may be configured to manage congestion by transmitting new paths 16 to mobile drive units 20 that are located in or near congested areas or that are traveling on paths that will traverse or pass near congested areas; management module 15 may be configured to improve the operational efficiency of inventory system 10 by transmitting new paths 16 to mobile drive units 20 that are optimized based on the attributes of inventory holders 30 or inventory stations 50 associated with the relevant mobile drive units 20 or the tasks they are completing.), in order to convey a rack that stores the item in accordance with the order information (see Wurman et al. para [0035]-[0036], During operation, mobile drive units 20 may retrieve inventory holders 30 containing one or more inventory items requested in an order to be packed for delivery to a customer or inventory holders 30 carrying pallets containing aggregated collections of inventory items for shipment.). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of filing of the applicant’s invention to combine the method of Wurman et al. with that of Sakakibara et al. and Dubois, Jr. et al. because Wurman et al. teaches the improvement of effectiveness without reducing the overall efficiency of inventory system 10 (para [0051], and improve the operational efficiency of inventory system 10 by transmitting new paths 16 to mobile drive units 20 that are optimized based on the attributes of inventory holders 30 or inventory stations 50 associated with the relevant mobile drive units 20 or the tasks they are completing (para [0107]).
Claim Rejections - 35 USC § 112
7. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
7.1 Claim 13 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. the claims provide for a conveyance having the system according to claim 12; it is unclear whether the claim meant to state “the simulation system according to claim 12”, … For examination purposes, it is assumed by the examiner the claim meant to state “the simulation system according to claim 12” further comprising: The examiner respectfully requests further clarification and/or amendment to the claim, in response to the office correspondence.
Conclusion
8. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
8.1 YOSHIMOTO et al. (USPG_PUB No. 20190127146 A1) teaches a rack management system, including a processor and a storage unit.
9. Claims 1-14 are rejected and THIS ACTION IS MADE FINAL. 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.
10. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDRE PIERRE-LOUIS whose telephone number is (571)272-8636. The examiner can normally be reached M-F 9:00 AM-5:00 PM.
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, EMERSON C PUENTE can be reached at 571-272-3652. 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.
/ANDRE PIERRE LOUIS/Primary Patent Examiner, Art Unit 2187 May 30, 2026
Prosecution Insights