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 .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 21-40 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Step 1:
Claims 21-34 are directed to a machine. Claims 35-39 are directed to a process. Claim 40 is directed to a manufacture. As such, claims 21-40 are drawn to one of the statutory categories of invention (Step 1: Yes).
Regarding Step 2A Prong 1:
Claims 21, 35, and 40 recite:
collecting data associated with a property;
while collecting the collected data, receiving annotation data from a user device, wherein the annotation data comprises information describing one or more features of the property;
in response to receiving the annotation data, generating a report comprising the annotation data and the collected data; and
transmitting the report to one or more communication devices.
Limitations (a) and (c) can practically be performed in the human mind with or without the use of a physical aid such as pen and paper; therefore, the limitation falls within the
mental processes grouping, and the claims recite an abstract idea. (Step 2A – Prong 1: Yes).
Regarding Step 2A Prong 2:
Limitation (b) recites receiving annotation data from a user device. This additional element represents mere data gathering that is necessary for use of the recited judicial exception and is recited at a high level of generality. Limitation (d) represents mere data outputting and is recited at a high level of generality. Limitations (b), and (d) in the claim are thus insignificant extra-solution activity. Thus, the claims as a whole do not integrate the exception into a practical application. (Step 2A –Prong 2: No).
Regarding Step 2B:
The claims do not include additional elements that are sufficient to amount to
significantly more than the judicial exception because the processor(s), memory, memory with program code, user device, and communication devices are at best the equivalent of merely adding the words "apply it" to the judicial exception. Mere instructions to apply an exception cannot provide an inventive concept. The claims lack affirmative recitation a specific, unconventional technical means. The additional elements, considered both individually and in combination, does not amount to significantly more than the judicial exception itself. A court is likely to view the steps as routine computer implementation. (Step 2B: No).
Regarding claims 22-24, 29-30, and 36-38, they are directed to further limit annotation data and / or collected data. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Regarding claims 25-27 and 39, the claims recite the additional elements, “handheld camera,” “aerial vehicle,” and “LiDAR” which are recited at a high level of generality. Therefore, the claims do not integrate the judicial exception into a practical application at Step 2A Prong 2. Further, the additional elements do not amount to significantly more than the judicial exception at Step 2B.
Regarding claim 28, The limitation “prompting the user” is nothing more than an insignificant extra solution activity and not integrated into a practical application under Step 2A Prong 2. Under Step 2B, the limitation “prompting the user” is nothing more than an insignificant extra solution activity and considering it both individually and in combination, does not amount to significantly more than the judicial exception itself.
Regarding claims 31-33, the limitations including “identifying,” “determining,” and “using annotation data …to determine” can reasonably be performed by the human mind or by a human using pen and paper, and is a mental process. Further, the claims do not recite any additional element.
Regarding claim 34, the claims recite the additional element, “an artificial intelligence system”, which is recited at a high level of generality. Therefore, the claims do not integrate the judicial exception into a practical application at Step 2A Prong 2. Further, the additional elements do not amount to significantly more than the judicial exception at Step 2B.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 21, 27, 29-30, and 33 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 4-5, and 18 of U.S. Patent No. US 12299812 B2 in view of Richman et al. (US 9609288 B1; hereinafter Richman).
claim
Current Application
19/191,680
claim
Patent
US 12299812 B2
21
A system, comprising: a processor;
1
A system, comprising: a processor;
and a memory coupled to the processor and comprising computer-readable program code that when executed by the processor causes the processor to perform operations comprising:
and a memory coupled to the processor and comprising computer-readable program code that when executed by the processor causes the processor to perform operations comprising:
collecting data associated with a property;
gathering, using LiDAR, LiDAR data associated with a property;
processing the LiDAR data using an artificial intelligence (AI) system to identify one or more locations of damage to the property based on the LiDAR data;
generating, with the AI system, a feature list comprising a list of the one or more locations of damage to the property;
while collecting the collected data, receiving annotation data from a user device, wherein the annotation data comprises information describing one or more features of the property;
receiving annotation data from a user device in response to the feature list, wherein the annotation data comprises information describing one or more features of the property and/or the LiDAR data;
in response to receiving the annotation data, generating a report comprising the annotation data and the collected data associated with the property;
and in response to receiving the annotation data, generating a report comprising the annotation data and the evidence-list of the one or more locations of damage to the property.
And transmitting the report to one or more communication devices.
Regarding claim 21, regarding the fourth limitation and the fifth limitation, collected data can comprise a feature list and / or an evidence-list. Further, “While collecting the collected data” can be interpreted as a broader recitation of U.S. Patent No. US 12299812 B2’s “in response to the feature list.” Further, collected data can comprise LiDAR data.
Claim 1 of U.S. Patent No. US 12299812 B2 does not explicitly disclose transmitting the report to one or more communication devices.
Richman teaches transmitting the report to one or more communication devices (“A report 116 can be an interactive document (e.g., a web page) that can be provided for presentation on the user device 110 (e.g., in a web browser), or to an outside user device,” (col 21, lines 7-23).
“The cloud system 120 is in communication with a generated reports 129 database, that can receive the report 116 and store the report 116 with information describing the report (e.g., information describing the property and rooftop, configuration information of the UAV 100, time information associated with the inspection, and so on),” (col 21, lines 24-41).
Transmitting the report includes providing the report to an outside user device and / or a cloud system receiving the report.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Richman to Patented claim 1. The motivation would have been to enable remote review by someone other than the person who collected the data and / or to enable record keeping / digital backup and later retrieval.
claim
Current Application
19/191,680
claim
Patent
US 12299812 B2
27
The system of claim 21, wherein the collected data comprises LiDAR data.
1
… gathering, using LiDAR, LiDAR data associated with a property;…
29
The system of claim 21, wherein the collected data is collected from outside the property.
4
The system of claim 1, wherein the LiDAR data is collected from outside the property.
30
The system of claim 21, wherein the collected data is collected from inside the property.
5
The system of claim 1, wherein the LiDAR data is collected from inside the property.
33
The system of claim 21, wherein the operations further comprise using the annotation data to automatically determine whether all or a portion of the property should be repaired or replaced.
18
The system of claim 1, wherein the operations further comprise using the annotation data to automatically determine whether all or a portion of the property should be repaired or replaced.
Further regarding claims 29-30, collected data can comprise LiDAR data.
Claim 35 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 19 of U.S. Patent No. US 12299812 B2 in view of Richman et al. (US 9609288 B1; hereinafter Richman).
claim
Current Application
19/191,680
claim
Patent
US 12299812 B2
35
A method comprising:
19
A method comprising:
performing operations as follows on a processor of a computing device:
performing operations as follows on a processor of a computing device:
collecting data associated with a property;
gathering, using LiDAR, LiDAR data associated with a property;
processing the LiDAR data using an artificial intelligence (AI) system to identify one or more locations of damage to the property based on the LiDAR data;
generating, with the AI system, a feature list comprising a list of the one or more locations of damage to the property;
while collecting the collected data, receiving annotation data from a user device, wherein the annotation data comprises information describing one or more features of the property;
receiving annotation data from a user device in response to the feature list, wherein the annotation data comprises information describing one or more features of the property and/or the LiDAR data;
in response to receiving the annotation data, generating a report comprising the annotation data and the collected data;
and in response to receiving the annotation data, generating a report comprising the annotation data and the evidence-list of the one or more locations of damage to the property.
And transmitting the report to one or more communication devices.
Regarding claim 35, regarding the fourth limitation and the fifth limitation, collected data can comprise a feature list and / or an evidence-list. Further, “While collecting the collected data” can be interpreted as a broader recitation of U.S. Patent No. US 12299812 B2’s “in response to the feature list.” Further, collected data can comprise LiDAR data.
Claim 19 of U.S. Patent No. US 12299812 B2 does not explicitly disclose transmitting the report to one or more communication devices.
Richman teaches transmitting the report to one or more communication devices (“A report 116 can be an interactive document (e.g., a web page) that can be provided for presentation on the user device 110 (e.g., in a web browser), or to an outside user device,” (col 21, lines 7-23).
“The cloud system 120 is in communication with a generated reports 129 database, that can receive the report 116 and store the report 116 with information describing the report (e.g., information describing the property and rooftop, configuration information of the UAV 100, time information associated with the inspection, and so on),” (col 21, lines 24-41).
Transmitting the report includes providing the report to an outside user device and / or a cloud system receiving the report.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Richman to Patented claim 19. The motivation would have been to enable remote review by someone other than the person who collected the data and / or to enable record keeping / digital backup and later retrieval.
Claims 40 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 20 of U.S. Patent No. US 12299812 B2 in view of Richman et al. (US 9609288 B1; hereinafter Richman).
claim
Current Application
19/191,680
claim
Patent
US 12299812 B2
40
A computer program product comprising:
20
A computer program product comprising:
a non-transitory computer readable storage medium having computer-readable program code embodied therewith, the computer-readable program code configured when executed by a processor to:
a non-transitory computer readable storage medium having computer-readable program code embodied therewith, the computer-readable program code configured when executed by a processor to:
collect data associated with a property;
gather, using LiDAR, LiDAR data associated with a property;
process the LiDAR data using an artificial intelligence (AI) system to identify one or more locations of damage to the property based on the LiDAR data;
generate, with the AI system, a feature list comprising a list of the one or more locations of damage to the property;
while collecting the collected data, receive annotation data from a user device, wherein the annotation data comprises information describing one or more features of the property;
receive annotation data from a user device in response to the feature list, wherein the annotation data comprises information describing one or more features of the property and/or the LiDAR data;
in response to receiving the annotation data, generate a report comprising the annotation data and the collected data;
and in response to receiving the annotation data, generate a report comprising the annotation data and the evidence-list of the one or more locations of damage to the property.
And transmit the report to one or more communication devices.
Regarding claim 40, regarding the fourth limitation and the fifth limitation, collected data can comprise a feature list and / or an evidence-list. Further, “While collecting the collected data” can be interpreted as a broader recitation of U.S. Patent No. US 12299812 B2’s “in response to the feature list.” Further, collected data can comprise LiDAR data.
Claim 20 of U.S. Patent No. US 12299812 B2 does not explicitly disclose transmitting the report to one or more communication devices.
Richman teaches transmitting the report to one or more communication devices (“A report 116 can be an interactive document (e.g., a web page) that can be provided for presentation on the user device 110 (e.g., in a web browser), or to an outside user device,” (col 21, lines 7-23).
“The cloud system 120 is in communication with a generated reports 129 database, that can receive the report 116 and store the report 116 with information describing the report (e.g., information describing the property and rooftop, configuration information of the UAV 100, time information associated with the inspection, and so on),” (col 21, lines 24-41).
Transmitting the report includes providing the report to an outside user device and / or a cloud system receiving the report.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Richman to Patented claim 20. The motivation would have been to enable remote review by someone other than the person who collected the data and / or to enable record keeping / digital backup and later retrieval.
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 21-32 and 35-40 are rejected under 35 U.S.C. 103 as being unpatentable over Richman et al. (US 9609288 B1; hereinafter Richman) in view of Howe et al. (US 20160055602 A1; hereinafter Howe).
Regarding claim 21, Richman teaches a system, comprising: a processor; and a memory coupled to the processor and comprising computer-readable program code that when executed by the processor causes the processor to perform operations (“Each of the processes, methods, and algorithms described in the preceding sections may be embodied in, and fully or partially automated by, code modules executed by one or more computer systems or computer processors comprising computer hardware. The code modules (or “engines”) may be stored on any type of non-transitory computer-readable medium or computer storage device, such as hard drives, solid state memory, optical disc, and/or the like,” (col 36, lines 38-56).
“The UAV primary processing system 900 can be a system of one or more processors 935, graphics processors 936, I/O subsystem 934, logic circuits, analog circuits, associated volatile and/or non-volatile memory, associated input/output data ports, power ports, etc., and/or one or more software processing executing one or more processors or computers,” (col 33, lines 61-67; col 34, lines 1-16; Fig 9).
Computer-readable program code includes code modules and / or software.) comprising:
collecting data associated with a property (“FIG. 1A illustrates an example of an Unmanned Aerial Vehicle (UAV) 10 performing a first automated flight plan to perform rooftop damage inspection of a property 20,” (col 5, lines 33-39).
“In the example of FIG. 1A, the UAV 10 is shown conducting an automated flight plan over the rooftop 30 while activating sensors included with the UAV 10. The UAV 10 can activate the sensors periodically (e.g., after traveling a threshold distance, such as ½ meter, 1 meter, 2 meters, or after a threshold time period, such as ½ second, 1 second), or can capture sensor information continuously (e.g., a camera can record video, such as 60 frames per second video). Upon the UAV's 10 completion of traversing the rooftop 30, the UAV can provide the obtained sensor information (e.g., images) to the operator for review (e.g., on a laptop, tablet, wearable computer, and so on) through a wired, or wireless connection (e.g., BLUETOOTH, 4G, LTE, Wi-Fi, and so on).,” (col 6, lines 12-31). Collecting data includes capturing sensor information. ); while collecting the collected data, receiving annotation data from a user device, wherein the annotation data comprises information describing one or more features of the property (“…the inspection can be performed in multiple steps, an initial operation during which a UAV can travel over the property and obtain sensor information (e.g., images), and a subsequent operation during which the UAV can receive (e.g., from an operator using a user device such as a ground control system) indications of specific locations of damage or likely damage on the rooftop, and can descend over each location to obtain detailed sensor information of the location. Interacting with a user interface of the user device, an operator can identify locations of damage or likely damage after the user device receives the sensor information from the initial flight operation, and the identified locations can be provided to the UAV to effect the subsequent operation,” (col 5, lines 4-18).
“…the UAV 100 can ascend to the safe altitude (e.g., identified in the flight information 114), travel over the rooftop according to the flight pattern, and activate sensors included in the UAV 100 to obtain real-world information describing the rooftop. After obtaining the real-world information, the UAV 100 can provide sensor information 106 to the user device 110. The user device 110 can combine the received sensor information 106 (e.g., stitch together images of the rooftop, generate a 3D model of the property, and so on), and the operator can indicate, on the user device 110, areas of the rooftop that are damaged. The UAV 100 can receive information identifying the areas from the user device 110, and can perform detailed inspections of the damaged areas (e.g., as described in FIG. 1B). The sensor information 106 associated with the detailed inspection can be provided to the user device 110,” (col 20, lines 42-62).
“In the example, the operator 12 has indicated that a location 32 on the rooftop 30 (e.g., a location in an image presented on his/her user device that illustrates the rooftop 30) is damaged. Optionally, the selected damage type may have a selected area of inspection…,” (col 13, 19-40).
“The operator can include textual information describing each damaged area (e.g., the operator can indicate that a particular damaged area is damaged from hail) and visual information for each damaged area (e.g., the operator can circle portions of an image illustrating the damaged area to identify particular types of damage, and can assign each type of damage a particular color),” (col 29, lines 56-67; col 30, lines 1-8).
Annotation data includes operator indications of specific locations of damage and / or operator indicated damage type and / or textual information and / or circled image portions. Receiving annotation data while collecting the collected data includes receiving the operator indicated areas of the rooftop that are damaged (annotation data) during ongoing / multi-step collection (col 20, lines 42-62; col 5, lines 4-18).);
“After receiving sensor information 106 associated with the detailed inspection of damaged areas, the user device 110 can generate one or more interactive reports 116 describing the damage. A report 116 can be an interactive document (e.g., a web page) that can be provided for presentation on the user device 110 (e.g., in a web browser), or to an outside user device. The report 116 can include a graphical representation of the property (e.g., a dimensioned, graphical map of the rooftop) with damaged areas identified (e.g., highlighted). The operator can indicate types of damage identified, and the report 116 can describe the types of damage, an area of each damaged area, and can provide a reviewing user of the report 116 with access to the raw sensor information 106 for each damaged area,” (col 21, lines 7-23).); and
transmitting the report to one or more communication devices (“A report 116 can be an interactive document (e.g., a web page) that can be provided for presentation on the user device 110 (e.g., in a web browser), or to an outside user device,” (col 21, lines 7-23).
“The cloud system 120 is in communication with a generated reports 129 database, that can receive the report 116 and store the report 116 with information describing the report (e.g., information describing the property and rooftop, configuration information of the UAV 100, time information associated with the inspection, and so on),” (col 21, lines 24-41).
Transmitting the report includes providing the report to an outside user device and / or a cloud system receiving the report. ).
Richman is not relied upon teaching that the report is generated in response to receiving the annotation data. Richman is not relied upon teaching that the generated report comprises the (antecedent) annotation data.
Howe teaches while collecting the collected data, receiving annotation data from a user device (“After the user takes a photo or video, the program prompts the user to name a negative condition (step 66). The program stores several conditions for every trade category. For instance, for the trade category of a stucco, the condition can be bp tear, crack, incomplete, spall, stain, weep screed, or missing. For the trade category of is cabinet, the condition can alignment, attachment, stain, ceiling separation, finish worn, trim separation, or wall separation. For the trade category of a deck, the condition can be cracked membrane, ponding, or reverse slope,” (page 3, para [0055]-[0056]; Fig 2).
“Once the condition has been specified, the program may ask for additional detail of the condition (step 70). For instance, for cracks, the program may ask for the number of occurrences or the lengths of each crack. For snails, the program may ask for the number of units by linear feet or square feet. For ceiling separation or worn finish, the program may ask for the total linear feet. The inspection program works with an image association program, which associates a project name, an inspection location, sublocation, a category or defect description, and any notes or details to the stored images. The inspection program also works with a report generator so that reports, such as those in FIGS. 36-41 can be generated,” (page 3, para [0056]; Figs 36-39).
“Once a user has taken a photo or video and entered all of the data from the various fields 84a-g, the user clicks next to save the data. It also returns the user to the screen 81 (FIG. 5), with the Project and Address fields automatically populated…” (pages 4-5, para [0068]; Fig 5).
“Referring back to FIG. 5, another drop down menu is the category drop down menu 84c. The category drop down menu 84e is related with the detail field 84f,” (page 4, para [0063]-[0066]; Figs 17-29).
“When the user clicks notes 84g from screen 81 (FIG. 5), the Notes view 168 appears (FIG. 30). The user can either type notes using the touch keyboard 169 or can choose to click the microphone icon 170 and speak into the phone, which will then translate the sound into text,” (para [0067; Fig 30]).
“As examples, the inspection devices are smartphones or tablet computers,” (page 2, para [0052]).
Annotation data includes a user identified condition and / or notes. From at least Fig 2, it is clear from the looping nature of the flowchart that annotation is interleaved with data capture and annotation data is received while collecting the collected data. A user device includes smartphones and / or tablet computers.)
Howe teaches the report is generated in response to receiving the annotation data (“‘Send Project pictures’ 182 will start the upload process of the photos, videos, and data to a webserver,” (page 5, para [0069]).
“After files are uploaded to the webserver, a report generator program takes all relevant data for a particular project (including multiple users and dates, if applicable), and generates uniquely formatted reports shown in FIGS. 16-41. The reports can instantly be generated and shared to desired recipients… Another report called “Inspection Condition Report by Address 216” (FIG. 38) is also sorted by Address 218. It also displays a small photo 220 with data 222 from all categories, but it only includes shots that have Conditions 224 associated with it (i.e. Category and Details were selected). Another report is the report titled “Inspection Condition Report by Trade—Project Wide 226 (FIG. 39),” which is similar to the previous report, however, it is sorted by Category 228 and Detail 230. Yet another report called “inspection Report by Address 232 (FIG. 40)” has a large photo 234 for every shot, regardless of whether a Category and Detail has been selected, and includes all data associated with the particular shot,” (page 5, para [0072]; Figs 36-41).
From at least Figure 38, it is clear that the report is generated in response to the annotation data being received ).
Howe teaches the generated report comprises the (antecedent) annotation data ((page 3, para [0055]-[0056]; Fig 2). (page 5, para [0069]). (page 5, para [0072]; Figs 36-41). From at least Figures 36-38, it is clear that the report comprises the antecedent annotation data.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Howe to Richman. The motivation would have been to “[eliminate] the overhead associated with an employee having to spend time analyzing and figuring out occurrences, sorting through photos… [and] provides clients with immediate and detailed inspection results,” (Howe; page 5, para [0073]) and / or to improve the efficiency of inspection and / or the accuracy / quality of annotations.
Regarding claims 35 and 40, they are rejected using the same citations and rationales described in the rejection of claim 21.
Further regarding claim 40, it additionally recites a computer program product comprising: a non-transitory computer readable storage medium having computer-readable program code embodied therewith, the computer-readable program code configured when executed by a processor to:
Richman teaches a computer program product comprising: a non-transitory computer readable storage medium having computer-readable program code embodied therewith, the computer-readable program code configured when executed by a processor to: (“Each of the processes, methods, and algorithms described in the preceding sections may be embodied in, and fully or partially automated by, code modules executed by one or more computer systems or computer processors comprising computer hardware. The code modules (or “engines”) may be stored on any type of non-transitory computer-readable medium or computer storage device, such as hard drives, solid state memory, optical disc, and/or the like,” (col 36, lines 38-56).
A computer program product includes code modules stored on a non-transitory computer-readable medium or computer storage device. Code modules comprise computer-readable program code.)
Regarding claim 22, Richman in view of Howe teaches the system of claim 21, wherein the annotation data is received upon the collecting of the data (Howe; “After the user takes a photo or video, the program prompts the user to name a negative condition (step 66). The program stores several conditions for every trade category. For instance, for the trade category of a stucco, the condition can be bp tear, crack, incomplete, spall, stain, weep screed, or missing. For the trade category of is cabinet, the condition can alignment, attachment, stain, ceiling separation, finish worn, trim separation, or wall separation. For the trade category of a deck, the condition can be cracked membrane, ponding, or reverse slope,” (page 3, para [0055]-[0056]; Fig 2).
“Once a user has taken a photo or video and entered all of the data from the various fields 84a-g, the user clicks next to save the data. It also returns the user to the screen 81 (FIG. 5), with the Project and Address fields automatically populated…” (Howe; pages 4-5, para [0068]; Fig 5).
“Referring back to FIG. 5, another drop down menu is the category drop down menu 84c. The category drop down menu 84e is related with the detail field 84f,” (Howe; page 4, para [0063]-[0066]; Figs 17-29).
“When the user clicks notes 84g from screen 81 (FIG. 5), the Notes view 168 appears (FIG. 30). The user can either type notes using the touch keyboard 169 or can choose to click the microphone icon 170 and speak into the phone, which will then translate the sound into text,” (Howe; para [0067; Fig 30]).
Annotation data includes a user identified condition and / or notes. From at least Fig 2, it is clear from the looping nature of the flowchart that annotation is interleaved with data capture and the annotation data is received upon the collecting of the data.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Howe to Richman. The motivation would have been to “[eliminate] the overhead associated with an employee having to spend time analyzing and figuring out occurrences, sorting through photos… [and] provides clients with immediate and detailed inspection results,” (Howe; page 5, para [0073]) and / or to improve the efficiency of inspection and / or the accuracy / quality of annotations.
Regarding claim 36, it is rejected using the same citations and rationales described in the rejection of claim 22.
Regarding claim 23, Richman in view of Howe teaches the system of claim 21, wherein the collected data comprises one or more photographs (Richman; “At this waypoint, the UAV will take one or more photos of the property, or building. One of these “central” photos may be used as described below to aid in the identification of potentially damaged areas of the rooftop, or be used to assist with visual odometry,” (col 7, lines 63-67; col 8, lines 1-10).
“Also, the UAV may also transmit information to the user device indicating that a photograph has been taken, and the coordinates of the photograph… Also, the UAV may be optionally configured to transmit in real-time the images to the user device,” (Richman; col 14, lines 44-57).).
Regarding claim 37, it is rejected using the same citations and rationales described in the rejection of claim 23.
Regarding claim 24, Richman in view of Howe teaches the system of claim 21, wherein the collected data comprises video (Richman; “The UAV 10 can activate the sensors periodically (e.g., after traveling a threshold distance, such as ½ meter, 1 meter, 2 meters, or after a threshold time period, such as ½ second, 1 second), or can capture sensor information continuously (e.g., a camera can record video, such as 60 frames per second video),” (col 6, lines 12-31).).
Regarding claim 38, it is rejected using the same citations and rationales described in the rejection of claim 24.
Regarding claim 25, Richman in view of Howe teaches the system of claim 21, wherein the collected data is collected using a handheld camera (Richman; “Optionally, the operator can take an image of the property (e.g., the operator can hold a camera and take a picture), and using height information of the property (e.g., obtained from a property database), the user device can determine an estimated height of obstructions (e.g., trees) within the property boundary,” (col 25, lines 32-45).
Howe; “As examples, the inspection devices are smartphones or tablet computers. Each inspection device 20 and 22 may be operated as stand-alone devices having its own camera, computer, processor, input/output devices, and memory,” (page 2, para [0052]).
“Referring now to FIG. 2, a flowchart shows the steps of an inspection program that are executed by the processors of the inspection devices 20 or 22, or the server 26,” (Howe; page 3, para [0053]).
“The user may click on the camera icon from screen 81, which will bring up the camera (FIG. 7),” (Howe; page 3, para [0058]).
A handheld camera includes a camera held by the operator and / or a smartphone / tablet computer.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Howe to Richman. The motivation would have been to enable indoor and / or close-range data collection.
Regarding claim 39, it is rejected using the same citations and rationales described in the rejection of claim 25.
Regarding claim 26, Richman in view of Howe teaches the system of claim 21, wherein the collected data is collected using an aerial vehicle (Richman; “This specification describes systems and methods to perform inspections of properties for damage (e.g., weather damage, structural damage, and so on) using an Unmanned Aerial Vehicle (UAV). While the specification describes determining damage of rooftops as an example, the system and methods can be utilized to determine damage to any portion of a property (e.g., home, building, apartment, multi-unit home, factory, bridge, power plant, and so on),” (col 2, lines 25-43).
“In the example of FIG. 1A, the UAV 10 is shown conducting an automated flight plan over the rooftop 30 while activating sensors included with the UAV 10…” (Richman; col 6, lines 12-31).).
Regarding claim 27, Richman in view of Howe teaches the system of claim 21, wherein the collected data comprises LiDAR data (Richman; “For example, the UAV can utilize a planar scanner (e.g., a scanner that measures distance at greater than a single location), in conjunction with information describing the UAVs position and attitude, to generate a fuller 3D point cloud. Similar, the UAV can utilize a full Lidar scanner (e.g., a Veloydne Puck) while performing the rooftop 12 inspection,” (col 10, lines 52-65).
“The UAV may have various devices connected to it for data collection. For example, photographic camera 949, video cameras, infra-red camera, multispectral camera, and Lidar, radio transceiver, sonar, TCAS (traffic collision avoidance system),” (Richman; col 34 lines 66-67; col 35, lines 1-6).).
Regarding claim 28, Richman in view of Howe teaches the system of claim 21, wherein the operations further comprise prompting a user to input the annotation data (Howe; “After the user takes a photo or video, the program prompts the user to name a negative condition (step 66)…(page 3, para [0055]-[0056]; Fig 2).
“Occasionally, more specific data is desired. In that case, a sub-view will appear requiring the user to input additional information. There are different sub-view designs based upon what type of information is necessary. For instance, if a use selects the cabinet category, and then selects the cabinet drawer/door broken detail, a sub-view 138 appeal's (FIG. 19) prompting the user to input the number of occurrences the cabinet drawer or door is broken, or how many cabinet drawers are broken…” (Howe; page 4, para [0064]; Figs 19-21).).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Howe to Richman. The motivation would have been to “[eliminate] the overhead associated with an employee having to spend time analyzing and figuring out occurrences, sorting through photos… [and] provides clients with immediate and detailed inspection results,” (Howe; page 5, para [0073]) and / or to improve the efficiency of inspection and / or the accuracy / quality of annotations.
Regarding claim 29, Richman in view of Howe teaches the system of claim 21, wherein the collected data is collected from outside the property (Richman; “Ideally, the waypoint is set at an altitude high enough, for example 45-60 meters above the ground so that the entire building or structure will be in the field of view of the camera. At this waypoint, the UAV will take one or more photos of the property, or building. One of these “central” photos may be used as described below to aid in the identification of potentially damaged areas of the rooftop, or be used to assist with visual odometry,” (col 7, lines 63-67; col 8, lines 1-10).
“The UAV ascends to safe altitude and performs inspection of the rooftop indicated in the job information (block 804). The UAV ascends to a safe altitude (e.g., indicated by an operator adjacent to the UAV) and performs a flight pattern over the rooftop. As the UAV travels, it obtains sensor information of the rooftop,” (Richman; col 32, lines 30-41).
“As described above, the UAV can utilize a wide-angle lens to obtain images of the sides of the property (e.g., a side of a home), and using the obtained imagery, a 3D model can be generated,” (Richman; col 27, lines 43-53).).
Regarding claim 30, Richman in view of Howe teaches the system of claim 21, wherein the collected data is collected from inside the property (Howe; “For instance, if the user is taking photo of a kitchen, a sublocation might be cabinet. A user chooses from the list of sublocations 122 by finger scrolling or by jumping directly to the first letter of the word by clicking on one of the letters 124 on the right hand side. If none of the existing sublocations are desired, a user may enter a new sublocation on box 126. As long as project, address, and location data has been entered, the user may click “next” to record a new image,” (page 4, para [0062]; Fig 38; Fig 32).
“The steps of the method include: providing a floor plan of a property to be inspected; dividing the floor plan into a plurality of inspection locations; storing the floor plan and the inspection locations in the memory; providing a description of a defect within an inspection location; capturing an image from the inspection locution using the camera storing the image into the memory; and associating the image with the inspection location and the description of its detect,” (Howe; page 1, para [0005]).
“To illustrate, the program may store the following inspection locations: bath 1, bath 2, bedroom 1, bedroom 2, bedroom 3, dining room, entry, family room, front yard, garage, hall, kitchen, laundry, master bath, master bedroom, nook, powder room, roof, stairs, deck, and driveway,” (Howe; page 3, para [0053]).
Inside the property includes the kitchen, baths, bedrooms, etc.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Howe to Richman. The motivation would have been to enable the collection of more complete data for the property and / or enable capturing a relationship between internal and external damage and / or improve the accuracy, completeness, detail, and / or value of an inspection.
Regarding claim 31, Richman in view of Howe teaches the system of claim 21, wherein the operations further comprise identifying a probable cause of damage for the property based on collected data and the annotation data (Richman; “The UAV 10, the user device of the operator, or the cloud system, can optionally automatically classify (e.g., using visual classifiers, computer vision algorithms) damage seen in the real-world information. As will be described, the rooftop damage can be characterized (e.g., one or more labels can be assigned to the damage), such as hail damage, no damage, wind damage, poor imagery, and so on,” (col 17, lines 28-50).
“For instance, the job determination engine 122 can receive information identifying that hail damage is expected, or is to be looked for, and can determine that a UAV which includes particular sensors, and specific visual classifiers to identify hail damage, is needed (e.g., a heat and/or thermal imaging sensors, specific visual classifiers that can discriminate hail damage from other types of damage, wind damage, rain damage, and so on),” (Richman; col 19, lines 19-32).
“The UAV can execute the visual classifier on received sensor information (e.g., images), and determine whether damage is evident. For instance, the visual classifier can determine whether the features described above are included in the obtained sensor information… The UAV can also utilize information describing a material the rooftop is made of (e.g., wood, tile, clay) for use in identifying damage (e.g., some of the features indicative of hail damage are specific to particular materials),” (Richman; col 32, lines 42-62).
Howe; “The program stores several sublocations which can be a structure, an appliance, or an accessory that is within the inspection location. For instance, a sublocation can be a countertop, chimney chase, confined rake, closet, cabinet, ceiling, an access, an area drain, doors, drywall, wood fences, flatwork, framing, landscape, masonry, mechanical, paint, pluming, roofing-tile, siding, slab/foundation, tub/shower, or a bridge,” (page 3, para [0053]).
“Once the sublocation is named, the user may provide a trade category (step 58). The program stores several trade categories, which classify the sublocation. For instance, a trade category can be several classifications of countertops, such as countertops cultured marble, countertops granite, countertops laminate, countertops synthetic. Other trade categories include metal fences or wood fences,” (Howe; page 3, para [0054]).
Identifying a probable cause of damage for the property includes discriminating hail damage from other types of damage. Richman teaches identifying a probable cause of damage is based on the material the rooftop is made of. Howe teaches the material is annotation data. After combination, Howe’s material / annotation data becomes the material input to Richman’s classifier.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Howe to Richman. The motivation would have been to increase the accuracy of at least hail damage identification and / or provide ground truth labels to improve machine learning / classification models and / or to improve the efficiency and / or consistency of inspection.
Regarding claim 32, Richman in view of Howe teaches the system of claim 21, wherein the operations further comprise determining an event occurred based on collected data and the annotation data (Richman; “The UAV can execute the visual classifier on received sensor information (e.g., images), and determine whether damage is evident. For instance, the visual classifier can determine whether the features described above are included in the obtained sensor information. The visual classifier can further utilize obtained sensor information of the rooftop at prior points in time (e.g., points in time when the rooftop did not have damage) to compare currently obtained sensor information to the prior sensor information (e.g., as described in FIG. 7),” (col 32, lines 42-62).
“The UAV 10, the user device of the operator, or the cloud system, can optionally automatically classify (e.g., using visual classifiers, computer vision algorithms) damage seen in the real-world information. As will be described, the rooftop damage can be characterized (e.g., one or more labels can be assigned to the damage), such as hail damage, no damage, wind damage, poor imagery, and so on,” (Richman; col 17, lines 28-50).
“…The UAV can also utilize information describing a material the rooftop is made of (e.g., wood, tile, clay) for use in identifying damage (e.g., some of the features indicative of hail damage are specific to particular materials),” (Richman; col 32, lines 42-62).
Howe; “The program stores several sublocations which can be a structure, an appliance, or an accessory that is within the inspection location. For instance, a sublocation can be a countertop, chimney chase, confined rake, closet, cabinet, ceiling, an access, an area drain, doors, drywall, wood fences, flatwork, framing, landscape, masonry, mechanical, paint, pluming, roofing-tile, siding, slab/foundation, tub/shower, or a bridge,” (page 3, para [0053]).
“Once the sublocation is named, the user may provide a trade category (step 58). The program stores several trade categories, which classify the sublocation. For instance, a trade category can be several classifications of countertops, such as countertops cultured marble, countertops granite, countertops laminate, countertops synthetic. Other trade categories include metal fences or wood fences,” (Howe; page 3, para [0054]).
Determining an event occurred includes determining whether damage is evident and / or determining a hail event / damage occurred. Richman teaches identifying a damage event is based on the material the rooftop is made of. Howe teaches the material is annotation data. After combination, Howe’s material / annotation data becomes the material input to Richman’s classifier.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Howe to Richman. The motivation would have been to increase the accuracy of at least hail damage identification and / or provide ground truth labels to improve machine learning / classification models and / or to improve the efficiency and / or consistency of inspection.
Claim 33 is rejected under 35 U.S.C. 103 as being unpatentable over Richman in view of Howe in further view of Splittstoesser (US 20180336418 A1; hereinafter Splittstoesser).
Regarding claim 33, Richman in view of Howe is not relied upon teaching but Splittstoesser teaches the system of claim 21, wherein the operations further comprise using the annotation data to automatically determine whether all or a portion of the property should be repaired or replaced (“Damage data 218 may include one or more damage parameters 220 that may provide information regarding roof 115 and/or the environment of roof 115. Damage parameters 220 may be retrieved from one or more data sources. For example, a set of damage parameters 220 may be retrieved from weather data 212. DA computing device 102 may retrieve a set of damage parameters 220 from building profile 216 of building 114. In another example, DA computing device 102 may transmit a prompt to user computing device 106 for display to policyholder 116. Policyholder 116 may provide user input 222 including a set of damage parameters 220 in response to the prompt. User input 222 may include, but is not limited to, text data, image data, video data, and/or audio data,” (pages 6-7, para [0053]).
“More specifically, in the exemplary embodiment, DA computing device 102 may compare damage parameters 220 with corresponding model parameters 208. DA computing device 102 may be configured to compare damage parameters 220 and model parameters 208 using any suitable comparison technique. In one example, DA computing device 102 may calculate a difference between each damage parameter 220 and the corresponding model parameter 208. In another example, DA computing device 102 may calculate a normalized difference for each damage parameter. In the exemplary embodiment, DA computing device 102 may generate a parameter score 226 for each damage parameter comparison,” (page 7, para [0055]-[0056]).
“DA computing device 102 may retrieve 508 damage data associated with building 114 for one or more data sources, such as, and without limitation, insurance computing device 104, user computing device 106, building database 110, sensor system 112, and/or weather database 214 (shown in FIG. 2). The damage data may include a plurality of damage parameters associated with building 114. DA computing device 102 may compare 510 the damage data to the damage model. In some embodiments, DA computing device 102 may compare the damage parameters of the damage data to the model parameters of the damage model. In at least some embodiments, DA computing device 102 may generate a confidence score for building 114 based upon the comparison 510. DA computing device 102 may determine 512 a damage status of a roof of building 114 based at least partially upon the comparison 510,” (page 9, para [0074]).
“…the damage status may be “no damage”, “repairs recommended”, and/or “totaled” (i.e., the cost to repair the damage is greater than the cost to replace the damage component of the building),” (page 2, para [0022]).
“…the confidence score may be compared to the damage thresholds to determine a damage status for the building. The score ranges defined by the damage thresholds may be associated with different damage statuses. The DA computing device may determine which score range includes the confidence score and assign a corresponding damage status to the building. In one example, the damage thresholds for roof damage may define a first score range associated with a damage status of ‘limited roof damage’, a second score range associated with a damage status of ‘repairs recommended’, and a third score range associated with a damage status of ‘totaled roof’,” (page 4, para [0032]).
After combination, the annotation data includes Splittstoesser’s damage parameters and / or user input. Automatically determining whether all or a portion of the property should be repaired or replaced includes Splittstoesser’s computing device determining a damage status. The damage status is determined using damage parameters / user input (annotation data). A determination that all or a portion of the property should be repaired includes damage status of “repairs recommended.” A determination that all or a portion of the property should be replaced includes damage status of “totaled.” A portion of the property can include a roof.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Splittstoesser to Richman in view of Howe. The motivation would have been to enable “(i) limiting the amount of field inspections for building damage; … (iii) reducing processing time for insurance claims for building damage; [and / or] (iv) increased quantitative analysis of roof damage,” (Splittstoesser; page 5, para [0038]) and / or to enable more accurate repair and / or replacement determinations.
Claim 34 is rejected under 35 U.S.C. 103 as being unpatentable over Richman in view of Howe in further view of Spader et al. (US 10521865 B1; hereinafter Spader) in further view of Splittstoesser.
Regarding claim 34, Richman in view of Howe is not relied upon teaching but Spader teaches the system of claim 21, wherein the operations further comprise using an artificial intelligence system to automatically determine whether all or a portion of the property should be repaired or replaced based on stored data (“...claim evaluation software platform 212 may use images, values, past claims, indices, keywords, and/or any other stored information to determine a material of an feature, a status of a feature, a determined action to be taken (e.g., cleaning vs. repair), and/or an estimate for that determined action. In some embodiments, claim evaluation software platform 212 may further employ machine learning functionality to make any of the above determinations,” (col 18, lines 1-18).
“The user may then instruct the claim evaluation software platform to analyze the data in the project and/or sub-project and generate a claim evaluation. The claim evaluation software platform may be configured to analyze the data to determine a location, nature, and/or extent of the damage. For example, the claim evaluation software platform may determine that a set of cabinets and a cooktop in a kitchen have been damaged in a fire. The claim evaluation software platform may determine that an entire cabinet base must be replaced, that two cabinet doors must be replaced, and that the cooktop must be cleaned,” (col 7, lines 45-59).
“The claim evaluation software may be configured to determine an amount of loss (e.g., a claim disbursement amount) and/or the nature and amount of work (e.g., repair, replacement, abatement, cleaning, etc.) needed to address the claim,” (col 7, lines 65-67; col 8, lines 1-16).
“The data file may include any other data input by the user and/or extracted by the structural analysis software platform, including any claim, structure, and/or room identifiers, comments, features, objects, building materials, and/or any other data,” (col 6, lines 45-53).
An artificial intelligence system includes claim evaluation software platform 212 employing machine learning functionality. ).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Spader to Richman in view of Howe. The motivation would have been to enable “more accurate risk determination, and/or replacement or repair cost estimation or determination; [and / or] (v) improved speed in generating, processing, and/or issuing claims and/or claim disbursements after an insurance claim event,” (Spader; col 8, lines 48-61) and / or to reduce the time / labor of manually preparing claim assessments / inspection reports and / or to improve the accuracy / consistency of claim assessments / inspection reports.
Richman in view of Howe in further view of Spader is not relied upon teaching but Splittstoesser teaches automatically determine whether all or a portion of the property should be repaired or replaced based on the annotation data (“Damage data 218 may include one or more damage parameters 220 that may provide information regarding roof 115 and/or the environment of roof 115. Damage parameters 220 may be retrieved from one or more data sources. For example, a set of damage parameters 220 may be retrieved from weather data 212. DA computing device 102 may retrieve a set of damage parameters 220 from building profile 216 of building 114. In another example, DA computing device 102 may transmit a prompt to user computing device 106 for display to policyholder 116. Policyholder 116 may provide user input 222 including a set of damage parameters 220 in response to the prompt. User input 222 may include, but is not limited to, text data, image data, video data, and/or audio data,” (pages 6-7, para [0053]).
“More specifically, in the exemplary embodiment, DA computing device 102 may compare damage parameters 220 with corresponding model parameters 208. DA computing device 102 may be configured to compare damage parameters 220 and model parameters 208 using any suitable comparison technique. In one example, DA computing device 102 may calculate a difference between each damage parameter 220 and the corresponding model parameter 208. In another example, DA computing device 102 may calculate a normalized difference for each damage parameter. In the exemplary embodiment, DA computing device 102 may generate a parameter score 226 for each damage parameter comparison,” (page 7, para [0055]-[0056]).
“DA computing device 102 may retrieve 508 damage data associated with building 114 for one or more data sources, such as, and without limitation, insurance computing device 104, user computing device 106, building database 110, sensor system 112, and/or weather database 214 (shown in FIG. 2). The damage data may include a plurality of damage parameters associated with building 114. DA computing device 102 may compare 510 the damage data to the damage model. In some embodiments, DA computing device 102 may compare the damage parameters of the damage data to the model parameters of the damage model. In at least some embodiments, DA computing device 102 may generate a confidence score for building 114 based upon the comparison 510. DA computing device 102 may determine 512 a damage status of a roof of building 114 based at least partially upon the comparison 510,” (page 9, para [0074]).
“…the damage status may be “no damage”, “repairs recommended”, and/or “totaled” (i.e., the cost to repair the damage is greater than the cost to replace the damage component of the building),” (page 2, para [0022]).
“…the confidence score may be compared to the damage thresholds to determine a damage status for the building. The score ranges defined by the damage thresholds may be associated with different damage statuses. The DA computing device may determine which score range includes the confidence score and assign a corresponding damage status to the building. In one example, the damage thresholds for roof damage may define a first score range associated with a damage status of ‘limited roof damage’, a second score range associated with a damage status of ‘repairs recommended’, and a third score range associated with a damage status of ‘totaled roof’,” (page 4, para [0032]).
After combination, the annotation data includes Splittstoesser’s damage parameters and / or user input. Automatically determining whether all or a portion of the property should be repaired or replaced includes Splittstoesser’s computing device determining a damage status. The damage status is determined based on damage parameters / user input (annotation data). A determination that all or a portion of the property should be repaired includes damage status of “repairs recommended.” A determination that all or a portion of the property should be replaced includes damage status of “totaled.” A portion of the property can include a roof.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Splittstoesser to Richman in view of Howe in further view of Spader. The motivation would have been to enable “(i) limiting the amount of field inspections for building damage; … (iii) reducing processing time for insurance claims for building damage; [and / or] (iv) increased quantitative analysis of roof damage,” (Splittstoesser; page 5, para [0038]) and / or to enable more accurate repair and / or replacement determinations.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ERICA G THERKORN whose telephone number is (571)272-2939. The examiner can normally be reached Monday - Friday 9:00am - 5:00pm.
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/ERICA G THERKORN/Examiner, Art Unit 2618
/DEVONA E FAULK/Supervisory Patent Examiner, Art Unit 2618
