# US 12,007,242 B2 · Systems and methods for providing carbon offsets

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- Number: US 12,007,242 B2
- Document ID: US12007242B2
- Status: Granted
- Kind: B2
- Application number: 17/828,117
- Filed: 2022-05-31
- Published: 2022-09-15
- Granted: 2024-06-11
- Earliest claimed: 2019-09-11
- Assignees: Blueowl, LLC
- Applicants: BlueOwl, LLC
- Inventors: Theobolt N. Leung; Eric Dahl; Kenneth Jason Sanchez
- Web page: https://patentgrep.com/patent/US12007242B2

## CPC

- G01C 21/3469: {Fuel consumption; Energy use; Emission aspects}
- G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202)
- B60W 10/06: including control of combustion engines
- B60W 40/09: Driving style or behaviour
- B60W 50/0097: {Predicting future conditions}
- B60W 50/08: Interaction between the driver and the control system
- B60W 50/10: Interpretation of driver requests or demands
- B60W 50/14: Means for informing the driver, warning the driver or prompting a driver intervention
- G01C 21/3484: {Personalized, e.g. from learned user behaviour or user-defined profiles}
- G01C 21/3492: {employing speed data or traffic data, e.g. real-time or historical (traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968)}
- G01C 21/3617: {using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement}
- G06Q 30/018: Certifying business or products
- G06Q 30/0201: Market modelling; Market analysis; Collecting market data
- G06Q 30/0224: {based on user history}
- G07C 5/04: using counting means or digital clocks
- G07C 5/0808: {Diagnosing performance data (testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005)}
- B60W 2510/0638: Engine speed
- B60W 2530/209: Fuel quantity remaining in tank
- B60W 2540/30: Driving style
- G06Q 50/06: Energy or water supply
- G06Q 50/40: Business processes related to the transportation industry (shipping G06Q10/083)
- G07C 5/008: {communicating information to a remotely located station (transmission systems for measured values G08C)}
- Y02T 10/40: Engine management systems
- G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S)
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- Y02T: CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION

## Abstract

Method and system for providing carbon offsets. For example, the method includes collecting mindful driving data for one or more vehicle trips made by a user, analyzing the mindful driving data to determine a level of mindful driving of the user, determining a level of carbon offset reward based at least in part upon the level of mindful driving of the user, determining an amount of total carbon emission of the user, and providing an amount of carbon offset reward based at least in part upon the level of carbon offset reward and the amount of total carbon emission.

## Claims

### Claim 1

A method for operating a computing device including one or more processors, the method comprising:
receiving, by the computing device, trip data defining occurrence of a vehicle trip by a user in a vehicle;
using a trained model, by the computing device using the trip data, to predict levels of mindful driving behavior, wherein the trained model is configured to be trained by:
collecting one or more sets of training data corresponding to levels of mindful driving behavior, the sets of training data adapted to be collected from one or more sensors associated with the vehicle;
processing the one or more sets of training data with the trained model to determine one or more mindful driving features;
generating a predicted level of mindful driving based on the one or more mindful driving features, the predicted level of mindful driving including one or more parameters; and
adjusting the one or more parameters associated with the predicted level of mindful driving to update the trained model;
receiving, by the computing device, fuel-consumption data, from the one or more sensors associated with the vehicle;
receiving, by the computing device, vehicle information of the vehicle;
receiving, by the computing device, mindful driving data including information related to a mindful driving behavior of the user;
processing the mindful driving data by the computing device using the trained model to determine a level of mindful driving behavior of the user during the vehicle trip;
calculating a level of carbon offset reward based upon the level of mindful driving behavior, wherein the level of carbon offset reward represents a percentage value;
determining, by the computing device in response to the trip data, an amount of total carbon emission of the vehicle during the vehicle trip based upon the fuel-consumption data and the vehicle information;
calculating, by the computing device, an amount of carbon offset reward based upon the level of carbon offset reward and the amount of total carbon emission; and
determining a monetary value associated with the amount of carbon offset reward to plant trees.

### Claim 2 (depends on 1)

The method of claim 1, wherein the amount of carbon offset reward corresponds to an amount of cost needed to recapture the amount of total carbon emission by planting the one or more trees.

### Claim 3 (depends on 1)

The method of claim 1, wherein the processing, by the computing device, the mindful driving data includes:
providing the mindful driving data;
processing information associated with the mindful driving data; and
determining the level of mindful driving behavior of the user based upon the mindful driving data.

### Claim 4 (depends on 1)

The method of claim 1, further comprising:
determining, by the computing device, a level of insurance discount based upon the level of mindful driving behavior of the user; and
generating, by the computing device, an adjustment to an insurance premium for the user based upon the level of insurance discount and an amount of insurance premium.

### Claim 5 (depends on 1)

The method of claim 1, further comprising:
determining, by the computing device, an insurance marketing offer, an eligibility qualification, or a quote amount based upon the level of mindful driving behavior of the user.

### Claim 6 (depends on 1)

The method of claim 1, wherein the level of carbon offset reward represents a percentage value of carbon offset.

### Claim 7 (depends on 6)

The method of claim 6, wherein the calculating, by the computing device, the amount of carbon offset reward includes:
determining the amount of carbon offset reward to be equal to an amount of cost needed to completely recapture the amount of total carbon emission multiplied by the percentage value of carbon offset.

### Claim 8

A computing device, comprising:
one or more processors; and
a memory storing instructions that, when executed by the one or more processors, cause the one or more processors to:
receive trip data defining occurrence of a vehicle trip by a user in a vehicle;
use a trained model, using the trip data, to predict levels of mindful driving behavior, wherein the trained model is configured to be trained by:
collecting one or more sets of training data corresponding to levels of mindful driving behavior, the sets of training data adapted to be collected from one or more sensors associated with the vehicle;
processing the one or more sets of training data with the trained model to determine one or more mindful driving features;
generating a predicted level of mindful driving based on the one or more mindful driving features, the predicted level of mindful driving including one or more parameters; and
adjusting the one or more parameters associated with the predicted level of mindful driving to update the trained model;
receive, fuel-consumption data, from the one or more sensors associated with the vehicle;
receive vehicle information of the vehicle;
receive mindful driving data including information related to a mindful driving behavior of the user;
process the mindful driving data using the trained model to determine a level of mindful driving behavior of the user;
calculate a level of carbon offset reward based upon the level of mindful driving behavior, wherein the level of carbon offset reward represents a percentage value;
determine, in response to the trip data, an amount of total carbon emission of the vehicle during the vehicle trip based upon the fuel-consumption data and the vehicle information;
calculate an amount of carbon offset reward based upon the level of carbon offset reward and the amount of total carbon emission; and
determine a monetary value associated with the amount of carbon offset reward to plant trees.

### Claim 9 (depends on 8)

The computing device of claim 8, wherein the amount of carbon offset reward corresponds to an amount of cost needed to recapture the amount of total carbon emission by planting the one or more trees.

### Claim 10 (depends on 8)

The computing device of claim 8, wherein the instructions that cause the one or more processors to process the mindful driving data further comprise instructions that cause the one or more processors to:
provide the mindful driving data;
process information associated with the mindful driving data; and
determine the level of mindful driving behavior of the user based upon the mindful driving data.

### Claim 11 (depends on 8)

The computing device of claim 8 wherein the instructions further comprise instructions that, when executed by the one or more processors, cause the one or more processors to:
determine a level of insurance discount based upon the level of mindful driving behavior of the user; and
generate an adjustment to an insurance premium for the user based upon the level of insurance discount and an amount of insurance premium.

### Claim 12 (depends on 8)

The computing device of claim 8, wherein the instructions further comprise instructions that, when executed by the one or more processors, cause the one or more processors to:
determine an insurance marketing offer, an eligibility qualification, or a quote amount based upon the level of mindful driving of the user.

### Claim 13 (depends on 8)

The computing device of claim 8 wherein the level of carbon offset reward represents a percentage value of carbon offset.

### Claim 14 (depends on 13)

The computing device of claim 13, wherein the instructions that cause the one or more processors to provide the amount of carbon offset reward further comprise instructions that cause the one or more processors to:
determine the amount of carbon offset reward to be equal to an amount of cost needed to completely recapture the amount of total carbon emission multiplied by the percentage value of carbon offset.

### Claim 15

A non-transitory computer-readable medium storing instructions, the instructions when executed by one or more processors of a computing device, cause the computing device to:
receive trip data defining occurrence of a vehicle trip by a user in a vehicle;
use a trained model, using the trip data, to predict levels of mindful driving behavior, wherein the trained model is configured to be trained by:
collecting one or more sets of training data corresponding to levels of mindful driving behavior, the sets of training data adapted to be collected from one or more sensors associated with the vehicle;
processing the one or more sets of training data with the trained model to determine one or more mindful driving features;
generating a predicted level of mindful driving based on the one or more mindful driving features, the predicted level of mindful driving including one or more parameters; and
adjusting the one or more parameters associated with the predicted level of mindful driving to update the trained model;
receive, fuel-consumption data, from one or more sensors associated with the vehicle;
receive vehicle information of the vehicle;
receive mindful driving data including information related to a mindful driving behavior of the user;
process the mindful driving data using the trained model to determine a level of mindful driving behavior of the user;
calculate a level of carbon offset reward based upon the level of mindful driving behavior, wherein the level of carbon offset reward represents a percentage value;
determine, in response to the trip data, an amount of total carbon emission of the vehicle during the vehicle trip based upon the fuel-consumption data and the vehicle information; and
calculate an amount of carbon offset reward based upon the level of carbon offset reward and the amount of total carbon emission; and
determine a monetary value associated with the amount of carbon offset reward to plant trees.

### Claim 16 (depends on 15)

The non-transitory computer-readable medium of claim 15, wherein the instructions when executed by the one or more processors that cause the computing device to process the mindful driving data to determine the level of mindful driving behavior of the user further cause the computing device to:
provide the mindful driving data;
process information associated with the mindful driving data; and
determine the level of mindful driving behavior of the user based upon the mindful driving data.

### Claim 17 (depends on 15)

The non-transitory computer-readable medium of claim 15, wherein the level of carbon offset reward represents a percentage value of carbon offset, and the instructions when executed by the one or more processors that cause the computing device to provide the amount of carbon offset reward based upon the level of carbon offset reward and the amount of total carbon emission further cause the computing device to:
determine the amount of carbon offset reward to be equal to an amount of cost needed to recapture the amount of total carbon emission multiplied by the percentage value of carbon offset.