IP Library › Granted Patent US 12,573,310
Granted Patent B2
US 12,573,310 · App. 18/394,298 · Granted Mar 10, 2026

Systems and methods for using a vocational mask with a hyper-enabled worker

Inventor: Arnold Kravitz (St. Petersburg, FL)
Assignee: BlueForge Alliance
G09B5/065A61F9/06G06F3/016G06F3/017G06T11/60G06V20/50G09G3/002H04R1/028H04R2499/15
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,573,310
App. No.
18/394,298
Granted
Mar 10, 2026
Kind
B2
Abstract

In one embodiment, a system includes a vocational mask configured to be worn by a user. The vocational mask includes a virtual retinal display, a memory device storing instructions, and a processing device communicatively coupled to the memory device and the virtual retinal display. The processing device executes the instructions to execute an artificial intelligence agent trained to perform at least one or more functions to determine certain information. The one or more functions include identifying perception-based objects and features, determining cognition-based scenery to identify one or more material defects, one or more assembly defects, one or more acceptable features, or some combination thereof, and determining one or more recommendations, instructions, or both. The processing device causes the certain information to be presented via the virtual retinal display.

Claims (61)

1 . A system comprising:

a mask configured to be worn by a user, wherein the mask comprises:

a virtual retinal display;

a memory device storing instructions;

a processing device communicatively coupled to the memory device and the virtual retinal display, wherein the processing device executes the instructions to:

execute an artificial intelligence agent trained to perform at least one or more functions to determine certain information, wherein the one or more functions comprise:

identifying perception-based objects and features,

determining cognition-based scenery to identify one or more material defects, one or more assembly defects, one or more acceptable features, or some combination thereof, and

determining one or more recommendations, instructions, or both; and

cause the certain information to be presented via the virtual retinal display on one or more retina of the user.

2 . The system of claim 1 , wherein the virtual retinal display projects an image onto at least one iris of the user to display alphanumeric data, graphic instructions, animated instructions, video instructions, or some combination thereof.

3 . The system of claim 1 , wherein the mask further comprises a network interface configured to enable bidirectional communication with a second network interface of a second mask, and the bidirectional communication enables transmission of real-time or near real-time audio and video data, recorded audio and video data, or some combination thereof.

4 . The system of claim 3 , further comprising a peripheral haptic device, wherein:

the mask further comprises a haptic interface, and wherein the haptic interface is configured to perform bidirectional haptic sensing and stimulation using the peripheral haptic device and the bidirectional communication, and wherein the stimulation comprises performing mimicked gestures via the peripheral haptic device.

5 . The system of claim 3 , wherein the bidirectional communication enables a master user of the second mask to view and/or listen to the real-time or near real-time audio and video data, recorded audio and video data, or some combination thereof, and to provide instructions to the user via the mask.

6 . The system of claim 1 , wherein bidirectional communication enables the user of the mask to provide instructions to a plurality of students via a plurality of masks.

7 . The system of claim 1 , wherein bidirectional communication enables the user of the mask to provide instructions to a plurality of students via a plurality of computing devices.

8 . The system of claim 1 , wherein bidirectional communication enables a collaborator or teacher to receive, using a computing device, audio data, video data, haptic data, or some combination thereof, from the mask being used by the user.

9 . The system of claim 1 , further comprising a cloud-based computing system communicatively coupled to the mask, wherein:

the cloud-based computing system determines one or more parameters by training a cloud-based artificial intelligence agent using training data to perform the one or more functions, and

the cloud-based computing system transmits the one or more parameters to the mask to train the artificial intelligence agent.

10 . The system of claim 1 , wherein the mask further comprises a haptic interface communicatively coupled to the processing device, wherein the haptic interface is configured to sense hand motions, texture, temperature, vibration, slipperiness, friction, wetness, pulsation, or some combination thereof.

11 . The system of claim 1 , wherein the system further comprises a welding helmet and the mask is coupled to the welding helmet.

12 . The system of claim 1 , wherein the mask further comprises a stereo speaker to emit audio pertaining to the certain information.

13 . The system of claim 1 , wherein the mask further comprises one or more sensors to provide information related to geographical position, pose of the user, rotational rate of pose of the user, or some combination thereof.

14 . The system of claim 1 , wherein the mask further comprises one or more sensors comprising vocation imaging band specific cameras, visual band cameras, stereo microphones, acoustic sensors, or some combination thereof.

15 . The system of claim 1 , wherein the mask further comprises an optical bench that aligns the virtual retinal display to one or more eyes of the user.

16 . The system of claim 1 , wherein the processing device executes the instructions to superposition the certain information on a display.

17 . The system of claim 1 , wherein the mask is configured to operate across both visible light and high intensity ultraviolet light conditions.

18 . The system of claim 1 , wherein the processing device is configured to record the certain information, communications with other devices, or both.

19 . The system of claim 1 , wherein the mask provides protection against welding flash.

20 . The system of claim 1 , wherein the processing device executes the instructions to map the mask in a physical space in which the mask is located.

21 . The system of claim 1 , wherein the mask comprises goggles.

22 . A mask configured to be worn by a user, wherein the mask comprises:

a virtual retinal display;

a memory device storing instructions;

a processing device communicatively coupled to the memory device and the virtual retinal display, wherein the processing device executes the instructions to:

execute an artificial intelligence agent trained to perform at least one or more functions to determine certain information, wherein the one or more functions comprise:

identifying perception-based objects and features,

determining cognition-based scenery to identify one or more material defects, one or more assembly defects, one or more acceptable features, or some combination thereof, and

determining one or more recommendations, instructions, or both; and

cause the certain information to be presented via the virtual retinal display on one or more retina of the user.

23 . The mask of claim 22 , wherein the virtual retinal display projects an image onto at least one iris of the user to display alphanumeric data, graphic instructions, animated instructions, video instructions, or some combination thereof.

24 . The mask of claim 22 , wherein the mask further comprises a network interface configured to enable bidirectional communication with a second network interface of a second mask, and the bidirectional communication enables transmission of real-time or near real-time audio and video data, recorded audio and video data, or some combination thereof.

25 . The mask of claim 24 , further comprising a peripheral haptic device, wherein:

the mask further comprises a haptic interface, and wherein the haptic interface is configured to perform bidirectional haptic sensing and stimulation using the peripheral haptic device and the bidirectional communication, and wherein the stimulation comprises performing mimicked gestures via the peripheral haptic device.

26 . The mask of claim 24 , wherein the bidirectional communication enables a master user of the second mask to view and/or listen to the real-time or near real-time audio and video data, recorded audio and video data, or some combination thereof, and to provide instructions to the user via the mask.

27 . The mask of claim 22 , wherein bidirectional communication enables the user of the mask to provide instructions to a plurality of students via a plurality of masks.

28 . The mask of claim 22 , wherein bidirectional communication enables the user of the mask to provide instructions to a plurality of students via a plurality of computing devices.

29 . A computer-implemented method comprising:

executing, by one or more processing devices of a mask, an artificial intelligence agent trained to perform at least one or more functions to determine certain information, wherein the one or more functions comprise:

identifying perception-based objects and features,

determining cognition-based scenery to identify one or more material defects, one or more assembly defects, one or more acceptable features, or some combination thereof, and

determining one or more recommendations, instructions, or both; and

causing, by the one or more processing devices, the certain information to be presented via a virtual retinal display of the mask on one or more retina of the user.

30 . A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to:

execute, by one or more processing devices of a mask, an artificial intelligence agent trained to perform at least one or more functions to determine certain information, wherein the one or more functions comprise:

identifying perception-based objects and features,

determining cognition-based scenery to identify one or more material defects, one or more assembly defects, one or more acceptable features, or some combination thereof, and

determining one or more recommendations, instructions, or both; and

cause, by the one or more processing devices, the certain information to be presented via a virtual retinal display of the mask.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 18, 2024
From: KRAVITZ, ARNOLD
To: BLUEFORGE ALLIANCE
Reel/Frame 066165/0607 →
Continuity (2)
Provisional Application 63607354 · Dec 7, 2023
Related Publication 20250191483A1 · Jun 12, 2025
References Cited (106)
US 5306893A · Morris et al. · 1994 [cited by applicant]
US 7962967B2 · Becker et al. · 2011 [cited by applicant]
US 8428926B2 · Choquet · 2013 [cited by applicant]
US 9641569B2 · Domke et al. · 2017 [cited by applicant]
US 9684303B2 · Lamers et al. · 2017 [cited by applicant]
US 9767712B2 · Postlethwaite et al. · 2017 [cited by applicant]
US 9773429B2 · Boulware et al. · 2017 [cited by applicant]
US 9786193B2 · Falash et al. · 2017 [cited by applicant]
US 9836987B2 · Postlethwaite et al. · 2017 [cited by applicant]
US 9881520B2 · Ullrich et al. · 2018 [cited by applicant]
US 9922236B2 · Moore et al. · 2018 [cited by applicant]
US 9939234B1 · Glauber · 2018 [cited by applicant]
US 9965973B2 · Peters et al. · 2018 [cited by applicant]
US 9994228B2 · Krueger · 2018 [cited by applicant]
US 10012962B2 · Lamers et al. · 2018 [cited by applicant]
US 10056010B2 · Salsich et al. · 2018 [cited by applicant]
US 10688589B2 · Svendsen et al. · 2020 [cited by applicant]
US 11633539B1 · Badik et al. · 2023 [cited by applicant]
US 11733667B2 · Mehrotra et al. · 2023 [cited by applicant]
US 11769421B2 · Wallace et al. · 2023 [cited by applicant]
US 11769423B2 · Galasso et al. · 2023 [cited by applicant]
US 11771371B1 · Lisy et al. · 2023 [cited by applicant]
US 11783724B1 · Shubrick et al. · 2023 [cited by applicant]
US 11783727B1 · Kelly et al. · 2023 [cited by applicant]
US 11839781B1 · Dashevsky et al. · 2023 [cited by applicant]
US 20080038702A1 · Choquet · 2008 [cited by applicant]
US 20090325131A1 · Cernasov et al. · 2009 [cited by applicant]
US 20100271298A1 · Vice et al. · 2010 [cited by applicant]
US 20110117527A1 · Conrardy et al. · 2011 [cited by applicant]
US 20130194083A1 · Rao et al. · 2013 [cited by applicant]
US 20140272839A1 · Cutler · 2014 [cited by applicant]
US 20150170539A1 · Chica et al. · 2015 [cited by applicant]
US 20150190887A1 · Becker et al. · 2015 [cited by applicant]
US 20150260474A1 · Rublowsky et al. · 2015 [cited by applicant]
US 20150375327A1 · Becker et al. · 2015 [cited by applicant]
US 20160034764A1 · Connor · 2016 [cited by applicant]
US 20160163221A1 · Sommers et al. · 2016 [cited by applicant]
US 20160267806A1 · Hsu et al. · 2016 [cited by applicant]
US 20170032281A1 · Hsu · 2017 [cited by applicant]
US 20170150127A1 · High et al. · 2017 [cited by applicant]
US 20170200394A1 · Albrecht · 2017 [cited by applicant]
US 20170294140A1 · Chica et al. · 2017 [cited by applicant]
US 20180126476A1 · Meess et al. · 2018 [cited by applicant]
US 20180130376A1 · Meess et al. · 2018 [cited by applicant]
US 20180180893A1 · Gupta · 2018 [cited by applicant]
US 20180185110A1 · Kumar et al. · 2018 [cited by applicant]
US 20180225993A1 · Buras et al. · 2018 [cited by applicant]
US 20190076700A1 · Quillin · 2019 [cited by applicant]
US 20190163274A1 · Sun et al. · 2019 [cited by applicant]
US 20190340954A1 · Schneider · 2019 [cited by applicant]
US 20190380792A1 · Poltaretskyi et al. · 2019 [cited by applicant]
US 20200128348A1 · Eronen et al. · 2020 [cited by applicant]
US 20200269065A1 · Broeng · 2020 [cited by examiner]
US 20200273365A1 · Wallace et al. · 2020 [cited by applicant]
US 20200337407A1 · Hsu · 2020 [cited by applicant]
US 20200349770A1 · Kuehne · 2020 [cited by examiner]
US 20200368904A1 · Aldridge et al. · 2020 [cited by applicant]
US 20200371737A1 · Leppänen et al. · 2020 [cited by applicant]
US 20210216773A1 · Bohannon et al. · 2021 [cited by applicant]
US 20210343086A1 · Long, III · 2021 [cited by applicant]
US 20220016776A1 · Lonsberry et al. · 2022 [cited by applicant]
US 20220258268A1 · Becker · 2022 [cited by applicant]
US 20220404819A1 · Ba et al. · 2022 [cited by applicant]
US 20230129708A1 · Stone et al. · 2023 [cited by applicant]
US 20230131469A1 · Karaaslan et al. · 2023 [cited by applicant]
US 20230260415A1 · Greunke · 2023 [cited by applicant]
US 20230270344A1 · Leboeuf et al. · 2023 [cited by applicant]
US 20230343310A1 · Seim et al. · 2023 [cited by applicant]
US 20230347186A1 · Klatt et al. · 2023 [cited by applicant]
US 20240119345A1 · Everman et al. · 2024 [cited by applicant]
US 20240207982A1 · Becker et al. · 2024 [cited by applicant]
US 20250191485A1 · Kravitz · 2025 [cited by applicant]
AU 2022203028A1 · 2022 [cited by applicant]
CN 111653136A · 2020 [cited by applicant]
DE 102020206308A1 · 2021 [cited by applicant]
EP 0741346A2 · 1996 [cited by applicant]
EP 2099588B1 · 2011 [cited by applicant]
EP 3812105A1 · 2021 [cited by applicant]
EP 3929894A1 · 2021 [cited by applicant]
EP 3682393B1 · 2023 [cited by applicant]
JP 2012520521A · 2012 [cited by applicant]
KR 100934614B1 · 2009 [cited by applicant]
KR 20150092444A · 2015 [cited by applicant]
WO 2006131827A2 · 2006 [cited by applicant]
WO 2015033152A2 · 2015 [cited by applicant]
WO 2015195303A1 · 2015 [cited by applicant]
WO 2017151778A1 · 2017 [cited by applicant]
WO 2021229927A1 · 2021 [cited by applicant]
WO 2022208595A1 · 2022 [cited by applicant]
WO 2022266245A1 · 2022 [cited by applicant]
WO 2023118877A1 · 2023 [cited by applicant]
International Search Report and Written Opinion dtd Aug. 7, 2025 for PCT/US2025/026395, dtd Aug. 7, 2025, 10 pages. [cited by applicant]
International Search Report and Written Opinion dtd Jun. 30, 2025 for PCT/US2025/025298, dtd Jun. 30, 2025, 20 pages. [cited by applicant]
International Search Report and Written Opinion dtd Jun. 30, 2025 for PCT/US2025/023118, dtd Jun. 30, 2025, 6 pages. [cited by applicant]
International Search Report dtd Jun. 30, 2025 for PCT/US2025/024263, dtd Jun. 30, 2025, 6 pages. [cited by applicant]
International Search Report and Written Opinion dtd Jun. 30, 2025 for PCT/US2025/023990, dtd Jun. 30, 2025, 11 pages. [cited by applicant]
International Search Report and Written Opinion dtd Jun. 30, 2025 for PCT/US2025/024512, dtd Jun. 30, 2025, 14 pages. [cited by applicant]
International Search Report and Written Opinion dtd Jun. 30, 2025 for PCT/US2025/025300, dtd Jun. 30, 2025, 21 pages. [cited by applicant]
Schume, Philipp, “Artificial Intelligence in Industrial Welding Produces Near-Real-Time Insights Through Virtually 100% Sample Sizes”, AWS for Industries, published Oct. 26, 2023, available at: https://aws.amazon.com/bl… [cited by applicant]
Su, Yun-Peng et al., “Integrating Virtual, Mixed, and Augmented Reality into Remote Robotic Applications: A Brief Review of Extended Reality-Enhanced Robotic Systems for Intuitive Telemanipulation and Telemanufacturing … [cited by applicant]
Gonzalez, Claudia et al., Advanced Teleoperation and Control System for Industrial Robots Baased on Augmented Virtuality and Haptic Feedback, Journal of Manufacturing Systems, vol. 59, pp. 283-298, published Apr. 30, 20… [cited by applicant]
Wang, Q. et al., “Modeling of Human Welders' Operations in Virtual Reality Human-Robot Interaction”, IEEE Robotics and Automation Letters, vol. 4, Issue 3, published Jun. 10, 2019, available at: https://ieeexplore.ieee.… [cited by applicant]
Johnson, Tate et al., “Augmenting Welding Training: an XR Platform to Foster Muscle Memory and Mindfulness for Skills Development”, ISS Companion '23: Companion Proceedings of the 2023 Conference on Interactive Surfaces… [cited by applicant]
Chan, Vei Siang et al., “VR and AR Virtual Welding for Psychomotor Skills: A Systematic Review”, Multimedia Tools and Applications, vol. 81, pp. 12459-12493, published Feb. 19, 2022, available at: https://link.springer.… [cited by applicant]
Y. Wang, Y. Chen, Z. Nan and Y. Hu, “Study on Welder Training by Means of Haptic Guidance and Virtual Reality for Arc Welding,” 2006 IEEE International Conference on Robotics and Biomimetics, Kunming, China, 2006, pp. 9… [cited by applicant]
International Search Report and Written Opinion for PCT/US2025/026401 dated Aug. 22, 2025, 18 pages. [cited by applicant]