DETAILED ACTION
Status
1. The present application is being examined under the pre-AIA first to invent provisions. Claims 10-32, 49-52, 54-56, and 71-78 are currently pending in this application.
Priority
2. The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
3. The disclosure of the prior-filed application, Application No. PCT/US19200044 has pro application(s) 62/757,166, 62/713,897, 62/714,078, is a CIP of 16/143286, is a con of 15/973,406, with earliest filing date of 5/07/2018, 16/143,286 is a con of PCT/US2018/045036, 15/973406, has a pro application 62/583,487 with the earliest filing date of 11/08/2017, PCT/US1845036 has a pro app 62/583,487, 62/562,487, 62/540,557, 62/540,513, with the earliest filing date of 08/02/2017, 15/973406 has a pro app 62/583,487, 62/562,487, 62/540,557, CIP of PCT/2017/031721 with earliest filing date of 05/09/2017, 16/143286 CIP of PCT/US2017/031721 with the earliest filing date of 05/09/2017, and PCT/US17/31721 has provisional applications 62/427,141, 62412,843, 62/350,672, 62/333,589 with the earliest filing date of 05/09/2016 which fail to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application. The cited application failed to provide adequate support for a digital twin representing the industrial environment. Therefore, the examiner considers 02/28/2019 as the effective filing date for examination.
Information Disclosure Statement
4. The information disclosure statement (IDS) submitted on 5/19/2026 was received. The submission is in compliance with the provisions of 37 CFR 1.97 and 37 CFR 1.98. Accordingly, the information disclosure statement has being considered by the examiner.
Drawings
5. The drawings submitted on 11/25/2024 are in compliance with 37 CFR § 1.81 and 37 CFR § 1.83 and have been accepted by the examiner.
Continued Examination Under 37 CFR 1.114
6. A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after allowance or after an Office action under Ex Parte Quayle, 25 USPQ 74, 453 O.G. 213 (Comm'r Pat. 1935). Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant's submission filed on 5/19/2026 has been entered.
Claim Rejections - 35 USC § 102
7. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
8. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
9. Claims 10-32 and 49-56 are rejected under 35 U.S.C. 102(b) as being anticipated by Hershey et al. US 2017/0286572.
With regards to claim 10, Hershey et al. US 2017/0286572 teaches a method comprising:
receiving imported data from one or more data sources, the imported data corresponding to an industrial environment; (s110; figure 1B)
generating an environment digital twin representing the industrial environment based on the imported data; (paragraph 0053)
identifying one or more industrial entities within the industrial environment; generating a set of discrete digital twins representing the one or more industrial entities twin within the environment: embedding the set of discrete digital twins within the environment digital twin; (paragraph 0058)
establishing a connection with a sensor system of the industrial environment; (Paragraph 0056)
receiving real-time sensor data from one or more sensors of the sensor system via the connection; (Paragraph 0037) and
updating at least one of the environment digital twin and the set of discrete digital twins based on the real-time sensor data. (Paragraph 0037)
determining an environmental control instruction based, at least in part, on at least one of the updated environmental digital twin or at least one of the updated set of discrete digital twins; (paragraph 0055-0056) and
controlling at least one device in the industrial environment based, at least in part, on the environmental control instruction. (paragraph 0055-0056)
With regards to claim 11, Hershey et al. US 2017/0286572 teaches the connection with the sensor system is established via one of a webhook and an application programming interface (API). (Paragraph 0076)
With regards to claim 12, Hershey et al. US 2017/0286572 teaches the environmental digital twin and the set of discrete digital twins are visual digital twins that are configured to be rendered in a visual manner. (paragraph 0149)
With regards to claim 13, Hershey et al. US 2017/0286572 teaches outputting the visual digital twins to a client application that displays the visual digital twins via a virtual reality headset. (VR/AR 302; paragraph 0164, 0166) (206; Paragraph 0051)
With regards to claim 14, Hershey et al. US 2017/0286572 teaches outputting the visual digital twins to a client application that displays the visual digital twins via a display device of a user device. (paragraph 0149)
With regards to claim 15, Hershey et al. US 2017/0286572 teaches outputting the visual digital twins to a client application that displays the visual digital twins via an augmented reality-enabled device. (VR/AR; paragraph 0164, 0166)
With regards to claim 16, Hershey et al. US 2017/0286572 teaches receiving user input relating to one or more steps performed in an industrial process relating to the industrial environment; and generating a process digital twin that defines the steps of the industrial process with respect to the industrial environment and one or more of the set of industrial entities. (user interface; paragraph 0149)
With regards to claim 17, Hershey et al. US 2017/0286572 teaches instantiating a graph database having a set of nodes connected by edges, wherein a first node of the set of nodes contains data defining the environment digital twin and one or more entity nodes respectively contain respective data defining a respective discrete digital twin of the set of discrete digital twins. (paragraph 0084& 0123)
With regards to claim 18, Hershey et al. US 2017/0286572 teaches each edge represents a relationship between two respective digital twins. (Paragraph 0084& 0123)
With regards to claim 19, Hershey et al. US 2017/0286572 teaches embedding a discrete digital twin includes connecting an entity node corresponding to a respective discrete digital twin to the first node with an edge representing a respective relationship between a respective industrial entity represented by the respective discrete digital twin and the industrial environment. (Paragraph 0100)
With regards to claim 20, Hershey et al. US 2017/0286572 teaches each edge represents a spatial relationship between two respective digital twins, and an operational relationship between two respective digital twins. (Paragraph 0081)
With regards to claim 21, Hershey et al. US 2017/0286572 teaches each edge stores metadata corresponding to the relationship between the two respective digital twins. (Paragraph 0053)
With regards to claim 22, Hershey et al. US 2017/0286572 teaches each entity node of the one or more entity nodes includes one or more properties of a respective properties of the respective industrial entity represented by the entity node. (Paragraph 0045)
With regards to claim 23, Hershey et al. US 2017/0286572 teaches each entity node of the one or more entity nodes includes one or more behaviors of a respective properties of the respective industrial entity represented by the entity node. (Paragraph 0056)
With regards to claim 24, Hershey et al. US 2017/0286572 teaches the environment node includes one or more properties of the environment. (Paragraph 0046)
With regards to claim 25, Hershey et al. US 2017/0286572 teaches the environment node includes one or more behaviors of the environment. (Paragraph 0045)
With regards to claim 26, Hershey et al. US 2017/0286572 teaches executing a simulation based on the environment digital twin and the one or more discrete digital twins. (Paragraph 0056)
With regards to claim 27, Hershey et al. US 2017/0286572 teaches the simulation simulates one of an operation of a machine in the industrial environment that produces an output based on a set of inputs and movement of workers in the industrial environment. (Paragraph 0056)
With regards to claim 28, Hershey et al. US 2017/0286572 teaches the imported data includes a three- dimensional scan of the environment. (multidimensional; Paragraph 0090)
With regards to claim 29, Hershey et al. US 2017/0286572 teaches the imported data includes a LIDAR scan of industrial the environment.(optical scanner; Paragraph 0072)
With regards to claim 30, Hershey et al. US 2017/0286572 teaches generating the digital twin of the industrial environment includes one of generating a set of surfaces of the industrial environment and configuring a set of dimensions of the industrial environment. (Paragraph )
With regards to claim 31, Hershey et al. US 2017/0286572 teaches generating the set of discrete digital twins includes importing a predefined digital twin of an industrial entity from a manufacturer of the industrial entity, wherein the predefined digital twin includes properties and behaviors of the industrial entity. (Paragraph 0164, 0166)
With regards to claim 32, Hershey et al. US 2017/0286572 teaches generating the set of discrete digital twins includes classifying an industrial entity within the imported data of the industrial environment and generating a discrete digital twin corresponding to the classified industrial entity. (Paragraph 0164, 0166)
With regards to claim 49, Hershey et al. US 2017/0286572 teaches a method for updating one or more vibration fault level states of one or more digital twins comprising:
receiving a request from a client application to update one or more vibration fault level states of one or more digital twins; (s110; figure 1B)
retrieving the one or more digital twins required to fulfill the request: retrieving one or more dynamic models required to fulfill the request, wherein the one or more dynamic models include a dynamic model that predicts when a vibration fault level occurs based on an input dataset; (figure 2A) (paragraph 0147)
selecting data sources from a set of available data sources based on the one or more inputs of the one or more dynamic models; (Paragraph 0076)
obtaining data from selected data sources; (Paragraph 0076)
determining one or more outputs using the retrieved data as one or more inputs to the one or more dynamic models; (Figure 2A) and
updating at least one of the one or more vibration fault level states of the one or more digital twins based on the output of the one or more dynamic models. (Paragraph 0059)
determining an environmental control instruction based, at least in part, on at least one of the updated environmental digital twin or at least one of the updated vibration fault level state; (paragraph 0055-0056) and
controlling at least one device in the industrial environment based, at least in part, on the environmental control instruction. (paragraph 0055-0056)
With regards to claim 50, Hershey et al. US 2017/0286572 teaches the request is received from a client application that corresponds to an industrial environment and/or one or more industrial entities within the industrial environment. (Paragraph 0044)
With regards to claim 51, Hershey et al. US 2017/0286572 teaches the request is received from a client application that supports an Industrial Internet of Things sensor system. (Paragraph 0039)
With regards to claim 52, Hershey et al. US 2017/0286572 teaches the digital twins are digital twins of at least one of industrial entities and industrial environments. (Paragraph 0056)
With regards to claim 53, Hershey et al. US 2017/0286572 teaches the dynamic models take data selected from the set of vibration, temperature, pressure, humidity, wind, rainfall, tide, storm surge, cloud cover, snowfall, visibility, radiation, audio, video, image, water level, quantum, flow rate, signal power, signal frequency, motion, displacement, velocity, acceleration, lighting level, financial, cost, stock market, news, social media, revenue, worker, maintenance, productivity, asset performance, worker performance, worker response time, analyte concentration, biological compound concentration, metal concentration, and organic compound concentration data. (figure 2A)
With regards to claim 54, Hershey et al. US 2017/0286572 teaches the data source is selected from the set of an Internet of Things connected device, a machine vision system, an analog vibration sensor, a digital vibration sensor, a fixed digital vibration sensor, a tri-axial vibration sensor, a single axis vibration sensor, an optical vibration sensor, and a cross- point switch.(vibration data; paragraph 0148)
With regards to claim 55, Hershey et al. US 2017/0286572 teaches retrieving the one or more dynamic models includes identifying the one or more dynamic models based on the one or more properties indicated in the request and a respective type of the one or more digital twins. (figure 2A)
With regards to claim 56, Hershey et al. US 2017/0286572 teaches the one or more dynamic models are identified using a lookup table.(database; paragraph 0146)
With regards to claim 71, Hershey et al. US 2017/0286572 teaches the controlling the at least one device includes recommending a corrective action to a user. (paragraph 0060)
With regards to claim 72, Hershey et al. US 2017/0286572 teaches the controlling the at least one device includes, upon receiving approval of the corrective action from the user, initiating the corrective action by the at least one device. (paragraph 0061)
With regards to claim 73, Hershey et al. US 2017/0286572 teaches the updating includes updating at least one of a status of a device in the industrial environment, a location of a device in the industrial environment, a temperature of a device in the industrial environment, or a trajectory of a device in the industrial environment. (paragraph 0039, & 0072)
With regards to claim 74, Hershey et al. US 2017/0286572 teaches the controlling the at least one device includes initiating a corrective action by the at least one device. (repair; paragraph 0060)
With regards to claims 75 and 78, Hershey et al. US 2017/0286572 teaches the at least one device includes at least one of a machine in the industrial environment, a robot in the industrial environment, an HVAC system of the industrial environment, or an alarm system of the industrial environment.(paragraph 0039)
With regards to claim 76, Hershey et al. US 2017/0286572 teaches a system for monitoring an industrial environment, the system comprising:
a digital twin I/O system configured to receive imported data, wherein the imported data includes real-time sensor data: (s110; figure 1B) (paragraph 0089)
a digital twin management system configured to generate an environmental twin based at least in part, on the imported data; (paragraph 0053)
a digital twin dynamic model system configured to update the environmental twin based on the real-time sensor data received by the digital twin I/O system;(paragraph 0055-0056)
a cognitive intelligence system configured to determine an environmental control instruction based on the updated environmental twin;(Paragraph 0071) and
an environmental control module configured to control at least one device in the industrial environment based at least in part on the environmental control instruction. (paragraph 0055-0056)
With regards to claim 77, Hershey et al. US 2017/0286572 teaches the controlling the at least one device includes initiating a corrective action on the at least one device. (repair; paragraph 0060)
Conclusion
10. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Galera et al. US 10,445,944 teaches augmented reality safety automation zone system and method.
11. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ADITYA S BHAT whose telephone number is (571)272-2270. The examiner can normally be reached on Monday-Friday 8 am-6pm.
12. 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.
13. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John Breene can be reached on 571-272-4107. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
14. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ADITYA S BHAT/Primary Examiner, Art Unit 2857 May 30, 2026
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