IP Library › Granted Patent US 12,507,739
Granted Patent B2
US 12,507,739 · App. 17/351,156 · Granted Dec 30, 2025

Vapor data repositories and methods for providing vapor data

Inventors: Aric Jennings (Los Angeles, CA); Steven L. Hecker (Los Angeles, CA); Kyle Patrick Crane Rodrigues (Los Angeles, CA)
Assignee: The Green Labs Group Inc.
A24F40/53A24F40/65A61M11/041A61M11/042A61M15/0021A61M15/0065A61M15/06G01N1/24G01N30/22G01N33/0062G06F16/22G06F16/2455G06F16/9535G06N20/00H01J49/0422A61M2205/3334A61M2205/3368A61M2205/3553A61M2205/502G01N2030/027G01N33/0068H04L67/10
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Quick Facts
Patent No.
US 12,507,739
App. No.
17/351,156
Granted
Dec 30, 2025
Kind
B2
Abstract

Vapor data repositories and methods for providing vapor data are disclosed herein. An embodiment of a vapor data repository (VDR) may include memory for vapor production data (VPD) from a vaporizer device and memory for vapor content data (VCD). The VPD may include a sample identifier associated with material having an active ingredient and vaping parameters. The VCD may include concentration of active ingredient data captured by a vapor sample collection apparatus. Another embodiment of a VDR may include memory for vapor correlation data having relationships between VPD and VCD, in which the VPD has production parameters from a vape session, in which the VCD is generated from analysis of captured vaporized material from the vape session on the vaporizer device, and a processor processes requests for the vapor correlation data from users. Methods for providing vapor data are also provided.

Claims (23)

1 . A vapor dose controller including a vapor data repository, comprising:

an electronic storage memory for vapor production data from a vaporizer device, the vapor production data comprising a sample identifier associated with material including an active ingredient as one of a plurality of components and vaping parameters comprising at least one of: crucible temperature, vapor temperature, vapor flow rate, vapor pressure, vapor flow duration, vapor density, heating duration, pressure differential, material age, and heating power;

an electronic storage memory for vapor content data comprising concentration of active ingredient data representing a concentration of the active ingredient captured by a vapor sample collection apparatus; and

a computing platform including a machine-learning model, the computing platform being configured to train the machine-learning model based on the vapor production data and the vapor content data to generate a device configuration instruction including correlation data representing a correlation between the vapor production data and the vapor content data, the device configuration instruction being configured to modify an operating parameter of the vaporizer device to administer a predefined dose of the active ingredient responsive to a dose request.

2 . The vapor dose controller of claim 1 , wherein the electronic storage memory for vapor production data and vapor content data is located on a remote cloud computing platform.

3 . The vapor dose controller of claim 1 , wherein the vapor data repository is located at a remote data center.

4 . The vapor dose controller of claim 1 , further comprising an electronic storage memory for storing the correlation data derived from the vapor production data and the vapor content data.

5 . The vapor dose controller of claim 4 , wherein the correlation data includes a correlation relationship of the vapor content data with the vapor production data represented by a polynomial equation.

6 . The vapor dose controller of claim 5 , wherein the correlation relationship of the vapor content data with the vapor production data is stored in a look-up table that stores information correlating the predefined dose of the active ingredient with at least one vapor production parameter of the vapor production data.

7 . A method for configuring a vapor device to provide a requested dose, comprising:

receiving a request for the requested dose of an active ingredient that is one of a plurality of components of a material from which the vapor device is configured to produce vapor;

retrieving, responsive to the received request, vapor correlation data from storage memory, the vapor correlation data comprising a correlation relationship between vapor production data and vapor content data, wherein the vapor production data comprises production parameters from a vape session on a vaporizer device, and wherein the vapor content data is generated from analysis of captured vaporized material from the vape session on the vaporizer device, and wherein the vapor correlation data was generated by a machine learning model trained using the vapor production data and the vapor content data;

determining a vapor device configuration instruction based on the retrieved vapor correlation data; and

transmitting the vapor device configuration instruction to the vapor device, wherein the vapor device configuration instruction is configured to modify an operating parameter of the vapor device to provide the requested dose.

8 . The method for configuring a vapor device of claim 7 , further comprising verifying a user of the vapor device in a database.

9 . The method for configuring a vapor device of claim 8 , further comprising:

determining the user is a subscriber to a vapor correlation data subscription service; and

enabling the transmitting the vapor device configuration instruction, responsive to the determining the user is a subscriber to the vapor correlation data subscription.

10 . The method for configuring a vapor device of claim 7 ,

wherein vapor production data comprises a sample identifier associated with material having an active ingredient and vaping parameters comprising at least one of: crucible temperature, vapor temperature, vapor flow rate, vapor pressure, vapor flow duration, vapor density, heating duration, pressure differential, material age, and heating power, and

wherein vapor content data comprises concentration of active ingredient data captured by a vapor sample collection apparatus.

11 . The method for configuring a vapor device of claim 7 , wherein the correlation relationship of the vapor content data with the vapor production data is represented by a polynomial equation.

12 . The method for configuring a vapor device of claim 7 , wherein the correlation relationship of the vapor content data with the vapor production data is stored in a look-up table that stores information correlating the requested dose of the active ingredient with at least one vapor production parameter.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 20, 2026
From: THE GREEN LABS GROUP, INC.
To: CS CAPITAL LIMITED
Reel/Frame 075329/0716 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 22, 2021
From: JENNINGS, ARIC; HECKER, STEVEN L; CRANE RODRIGUES, KYLE PATRICK
To: THE GREEN LABS GROUP, INC.
Reel/Frame 056620/0100 →
Continuity (4)
Continuation In Part PCTUS2021022787 · Mar 17, 2021
Provisional Application 62993211 · Mar 23, 2020
Provisional Application 62990769 · Mar 17, 2020
Related Publication 20210307405A1 · Oct 7, 2021
References Cited (27)
US 11633554B1 · Puviani · 2023 [cited by examiner]
US 12349738B2 · Achtien · 2025 [cited by examiner]
US 20090293892A1 · Williams et al. · 2009 [cited by applicant]
US 20130247910A1 · Postma · 2013 [cited by applicant]
US 20140174383A1 · Kesten et al. · 2014 [cited by applicant]
US 20160211693A1 · Stevens et al. · 2016 [cited by applicant]
US 20160235124A1 · Krietzman · 2016 [cited by applicant]
US 20160370337A1 · Blackley · 2016 [cited by applicant]
US 20170091853A1 · Cameron · 2017 [cited by examiner]
US 20170304563A1 · Adelson · 2017 [cited by applicant]
US 20180093054A1 · Bowen et al. · 2018 [cited by applicant]
US 20190167927A1 · Dagnello · 2019 [cited by examiner]
US 20190240430A1 · Jackson et al. · 2019 [cited by applicant]
US 20200329775A1 · Doyle · 2020 [cited by examiner]
US 20210089946A1 · Pegors · 2021 [cited by examiner]
CN 204273249U · 2015 [cited by applicant]
CN 105411004A · 2016 [cited by applicant]
EP 3205220A1 · 2017 [cited by applicant]
WO 2006082571A1 · 2006 [cited by applicant]
WO 2012040512A2 · 2012 [cited by applicant]
WO 2013102609A2 · 2013 [cited by applicant]
WO 2019204812A1 · 2019 [cited by applicant]
International search report and written opinion of international searching authority for PCT application PCT/US2021/022787 mailed Jul. 21, 2021. [cited by applicant]
CN-201780075323.9 Chinese First Office Action of Chinese Patent Office dated Jan. 18, 2021. [cited by applicant]
EP-17784383.6 European first office action dated Feb. 10, 2021. [cited by applicant]
PCT/GB2017/053049 International search report and written opinion of international searching authority mailed Jan. 17, 2018. [cited by applicant]
PCT/US2021/022787 Invitation to Pay Additional Fees of the international searching authority mailed Jun. 2, 2021. [cited by applicant]