IP Library › Granted Patent US 12699078
Granted Patent B2
US 12699078 · App. 18/169,450 · Granted Aug 4, 2026

Systems, apparatuses, methods, and computer program products for emissions quantification

Inventors: Ramesh Murugan Natarajan (Chennai, IN); Shahrul Azman Bin Zainal Abidin (Kajang, MY); Madhukar Gundappa Madhavamurthy (Bangalore, IN)
Assignee: Honeywell International Inc.
G01N33/0062G01N33/0068
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 12699078
App. No.
18/169,450
Granted
Aug 4, 2026
Kind
B2
Abstract

Methods, apparatuses, and computer program products for generating optimized emissions quantification are provided. For example, a computer-implemented method may include identifying a first emissions data and a second emissions data associated with a plant. The first emissions data may be associated with first emissions data acquisition level of a plurality of emissions data acquisition levels and the second emissions data may be associated with a second emissions data acquisition level of the plurality of emissions data acquisition levels. The method may further include generating using a reconciliation model and based on the first emissions data and the second emissions data, optimized emissions quantification. The optimized emissions quantification may reflect reconciled emissions data with respect to the first emissions data and the second emissions data.

Claims (55)

1 . A computer-implemented method comprising:

receiving, from one or more sensors associated with one or more measuring devices of a plant, data indicative of emissions associated with the plant;

identifying, based on the received data, a first emissions data and a second emissions data, wherein the first emissions data is associated with first emissions data acquisition level of a plurality of emissions data acquisition levels and the second emissions data is associated with a second emissions data acquisition level of the plurality of emissions data acquisition levels, wherein the identification of the first emissions data and the second emissions data comprises parsing the received data to identify emissions data associated with the second emissions data acquisition level for a time period as the second emissions data, and identifying the first emissions data from the emissions data based on a timestamp associated with the second emissions data;

determining, by a reconciliation model, based on the first emissions data and the second emissions data, one or more adjustment values for one or more portions of the first emissions data or one or more portions of the second emissions data, wherein the one or more adjustment values are determined based on a historical operational data;

applying the one or more adjustment values to the one or more portions of the first emissions data or the one or more portions of the second emissions data to generate optimized emissions quantification;

generating, based on the one or more adjustment values, the optimized emissions quantification, wherein the optimized emissions quantification reflects reconciled emissions data with respect to the first emissions data and the second emissions data;

transmitting, based on the optimized emissions quantification, one or more commands to at least one computing device associated with the plant; and

initiating performance of one or more prediction-based actions by executing the one or more commands by the least one computing device, wherein the execution of the one or more commands controls one or more operations of the plant.

2 . The computer-implemented method of claim 1 , wherein initiating the performance of the one or more prediction-based actions comprises:

generating an emissions report based on the optimized emissions quantification.

3 . The computer-implemented method of claim 1 , wherein the first emissions data and the second emissions data are associated with substantially the same timestamp.

4 . The computer-implemented method of claim 1 , wherein generating the optimized emissions quantification comprises:

determining a difference measure between the first emissions data and the second emissions data; and

responsive to determining that the difference measure is a qualifying difference measure, generating the optimized emissions quantification based on the difference measure.

5 . The computer-implemented method of claim 4 , wherein generating the optimized emissions quantification based on the difference measure comprises:

applying the difference measure to the first emissions data.

6 . The computer-implemented method of claim 4 , wherein generating the optimized emissions quantification based on the difference measure comprises:

applying a first portion of the difference measure to the first emissions data; and

applying a second portion of the difference measure to the second emissions data.

7 . The computer-implemented method of claim 5 , wherein applying the difference measure to the first emissions data comprises:

applying the difference measure to one or more portions of the first emissions data based at least in part on weights associated with the one or more portions of the first emissions data.

8 . The computer-implemented method of claim 1 , wherein:

the first emissions data comprises a set of source-based emissions data,

each data value in the set of source-based emissions data is associated with an emissions source category of a plurality of emissions source categories for the plant and corresponds to a portion of the first emissions data, and

an aggregate of the set of source-based emissions data represents a first total emissions for the plant.

9 . The computer-implemented method of claim 8 , wherein the second emissions data comprise site-based emissions data and represents a second total emissions for the plant.

10 . The computer-implemented method of claim 1 , wherein the reconciliation model comprises a machine learning model trained based at least in part on one or more of historical operational data or historical emissions data.

11 . An apparatus comprising at least one processor and at least one non-transitory memory comprising program code stored thereon, wherein the at least one non-transitory memory and the program code are configured to, with the at least one processor, cause the apparatus to at least:

receive from one or more sensors associated with one or more measuring devices of a plant, data indicative of emissions associated with the plant;

identify based on the received data, a first emissions data and a second emissions data, wherein the first emissions data is associated with first emissions data acquisition level of a plurality of emissions data acquisition levels and the second emissions data is associated with a second emissions data acquisition level of the plurality of emissions data acquisition levels, wherein the identification of the first emissions data and the second emissions data comprises parsing the received data to identify emissions data associated with the second emissions data acquisition level for a time period as the second emissions data, and identifying the first emissions data from the emissions data based on a timestamp associated with the second emissions data;

determine by a reconciliation model, based on the first emissions data and the second emissions data, one or more adjustment values for one or more portions of the first emissions data or one or more portions of the second emissions data, wherein the one or more adjustment values are determined based on a historical operational data;

apply the one or more adjustment values to the one or more portions of the first emissions data or the one or more portions of the second emissions data to generate optimized emissions quantification;

generate, based on the one or more adjustment values, the optimized emissions quantification, wherein the optimized emissions quantification reflects reconciled emissions data with respect to the first emissions data and the second emissions data;

transmit based on the optimized emissions quantification, one or more commands to at least one computing device associated with the plant; and

initiate performance of one or more prediction-based actions by executing the one or more commands by the least one computing device, wherein the execution of the one or more commands controls one or more operations of the plant.

12 . The apparatus of claim 11 , wherein the at least one non-transitory memory and the program code are configured to, with the at least one processor, to initiate the performance of the one or more prediction-based actions by generating an emissions report based on the optimized emissions quantification.

13 . The apparatus of claim 11 , wherein the first emissions data and the second emissions data are associated with substantially the same timestamp.

14 . The apparatus of claim 11 , wherein the at least one non-transitory memory and the program code are configured to, with the at least one processor, cause the apparatus to generate the optimized emissions quantification using the reconciliation model comprises:

determining a difference measure between the first emissions data and the second emissions data; and

responsive to determining that the difference measure is a qualifying difference measure, generating the optimized emissions quantification based on the difference measure.

15 . The apparatus of claim 14 , wherein the at least one non-transitory memory and the program code are configured to, with the at least one processor, cause the apparatus to generate the optimized emissions quantification based on the difference measure comprises:

applying the difference measure to the first emissions data.

16 . The apparatus of claim 14 , wherein the at least one non-transitory memory and the program code are configured to, with the at least one processor, cause the apparatus to generate the optimized emissions quantification based on the difference measure comprises:

applying a first portion of the difference measure to the first emissions data; and

applying a second portion of the difference measure to the second emissions data.

17 . The apparatus of claim 15 , wherein applying the difference measure to the first emissions data comprises:

applying the difference measure to one or more portions of the first emissions data based at least in part on reliability weights associated with the one or more portions of the first emissions data.

18 . A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising an executable portion configured to:

receive, from one or more sensors associated with one or more measuring devices of a plant, data indicative of emissions associated with the plant;

identify, based on the received data, a first emissions data and a second emissions data, wherein the first emissions data is associated with first emissions data acquisition level of a plurality of emissions data acquisition levels and the second emissions data is associated with a second emissions data acquisition level of the plurality of emissions data acquisition levels, wherein the identification of the first emissions data and the second emissions data comprises parsing the received data to identify emissions data associated with the second emissions data acquisition level for a time period as the second emissions data, and identifying the first emissions data from the emissions data based on a timestamp associated with the second emissions data;

determine, by a reconciliation model, based on the first emissions data and the second emissions data, one or more adjustment values for one or more portions of the first emissions data or one or more portions of the second emissions data, wherein the one or more adjustment values are determined based on a historical operational data;

apply the one or more adjustment values to the one or more portions of the first emissions data or the one or more portions of the second emissions data to generate optimized emissions quantification;

generate, based on the one or more adjustment values, the optimized emissions quantification, wherein the optimized emissions quantification reflects reconciled emissions data with respect to the first emissions data and the second emissions data;

transmit based on the optimized emissions quantification, one or more commands to at least one computing device associated with the plant; and

initiate performance of one or more prediction-based actions by executing the one or more commands by the least one computing device, wherein the execution of the one or more commands controls one or more operations of the plant.