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US20230008123A1 - Systems and methods for providing multiple carbon offset sources - Google Patents

Systems and methods for providing multiple carbon offset sources Download PDF

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Publication number
US20230008123A1
US20230008123A1 US17/935,253 US202217935253A US2023008123A1 US 20230008123 A1 US20230008123 A1 US 20230008123A1 US 202217935253 A US202217935253 A US 202217935253A US 2023008123 A1 US2023008123 A1 US 2023008123A1
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Prior art keywords
carbon offset
carbon
sources
total
user
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US17/935,253
Inventor
Kenneth Jason Sanchez
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Quanata LLC
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BlueOwl LLC
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Priority to US17/935,253 priority Critical patent/US20230008123A1/en
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Assigned to BlueOwl, LLC reassignment BlueOwl, LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: SANCHEZ, KENNETH JASON
Assigned to QUANATA, LLC reassignment QUANATA, LLC CHANGE OF NAME (SEE DOCUMENT FOR DETAILS). Assignors: BlueOwl, LLC
Abandoned legal-status Critical Current

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Definitions

  • Some embodiments of the present disclosure are directed to providing multiple carbon offset sources. More particularly, certain embodiments of the present disclosure provide methods and systems for providing various carbon offset sources to compensate for carbon emissions of a user.
  • the present disclosure has been applied to allowing the user to use one type carbon offset source as a common currency unit to compare between different types carbon offset sources. But it would be recognized that the present disclosure has much broader range of applicability.
  • Carbon emissions from vehicles represent a major contributor to climate change. While new vehicle technologies have been developed to curb carbon emissions, the continued use of vehicles for private transportation will cause the amount of carbon emissions to remain high or even increase. Hence it is desirable to have multiple carbon offset sources that can compensate for the release of these carbon emissions.
  • Some embodiments of the present disclosure are directed to providing multiple carbon offset sources. More particularly, certain embodiments of the present disclosure provide methods and systems for providing various carbon offset sources to compensate for carbon emissions of a user.
  • the present disclosure has been applied to allowing the user to use one type of carbon offset source as a common currency unit to compare between different types of carbon offset sources. But it would be recognized that the present disclosure has much broader range of applicability.
  • a method for providing carbon offset sources includes determining an amount of total carbon emission of a user and receiving a desired percentage of carbon offset for the amount of total carbon emission of the user. Also, the method includes determining a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset. Additionally, the method includes providing multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources. For each of the multiple carbon offset sources, the method includes receiving a respective number of carbon offset units corresponding to the predetermined carbon offset source and determining a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources. Moreover, the method includes providing a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
  • a computing device for providing carbon offset sources includes one or more processors and a memory that stores instructions for execution by the one or more processors.
  • the instructions when executed, cause the one or more processors to determine an amount of total carbon emission of a user and receive a desired percentage of carbon offset for the amount of total carbon emission of the user.
  • the instructions when executed, cause the one or more processors to determine a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset.
  • the instructions when executed, cause the one or more processors to provide multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources.
  • the instructions when executed, cause the one or more processors to receive a respective number of carbon offset units corresponding to the predetermined carbon offset source and determine a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources. Moreover, the instructions, when executed, cause the one or more processors to provide a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
  • a non-transitory computer-readable medium stores instructions for providing carbon offset sources.
  • the instructions are executed by one or more processors of a computing device.
  • the non-transitory computer-readable medium includes instructions to determine an amount of total carbon emission of a user and receive a desired percentage of carbon offset for the amount of total carbon emission of the user.
  • the non-transitory computer-readable medium includes instructions to determine a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset.
  • the non-transitory computer-readable medium includes instructions to provide multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources.
  • the non-transitory computer-readable medium includes instructions to receive a respective number of carbon offset units corresponding to the predetermined carbon offset source and determine a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources. Moreover, the non-transitory computer-readable medium includes instructions to provide a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
  • FIG. 1 is a simplified method for providing carbon offset sources according to certain embodiments of the present disclosure.
  • FIG. 2 is a simplified system for providing carbon offset sources according to some embodiments of the present disclosure
  • FIG. 3 is a simplified computing device for providing carbon offset sources according to certain embodiments of the present disclosure.
  • Some embodiments of the present disclosure are directed to providing multiple carbon offset sources. More particularly, certain embodiments of the present disclosure provide methods and systems for providing various carbon offset sources to compensate for carbon emissions of a user.
  • the present disclosure has been applied to allowing the user to use one type of carbon offset source as a common currency unit to compare between different types of carbon offset sources. But it would be recognized that the present disclosure has much broader range of applicability.
  • FIG. 1 is a simplified method for providing carbon offset sources according to certain embodiments of the present disclosure.
  • the diagrams are merely examples, which should not unduly limit the scope of the claims.
  • One of ordinary skill in the art would recognize many variations, alternatives, and modifications.
  • the method 100 includes process 110 for determining carbon emission, process 120 for receiving a desired percentage of carbon offset, process 130 for determining a total number of carbon offset units corresponding to a predetermined carbon offset source, process 140 for providing multiple carbon offset sources, process 150 for receiving a respective number of carbon offset units for each of the multiple carbon offset sources, process 160 for determining a respective cost for each of the multiple carbon offset sources, and process 170 for providing a total amount of cost.
  • an amount of total carbon emission of a user is determined according to some embodiments.
  • the amount of total carbon emission represents how much carbon pollution the user has generated by driving.
  • the amount of total carbon emission is calculated over a specified period (e.g., a year) and expressed as a numerical value (e.g., 2 tons of carbon dioxide).
  • driving data are analyzed to determine the amount of total carbon emission.
  • the driving data associated with one or more vehicle trips made by the user and indicate how the user drives, such as type of maneuvers that the user makes while driving (e.g., hard cornering, hard braking, sudden acceleration, smooth acceleration, slowing before turning, etc.), types of dangerous driving events (e.g., cell phone usage while driving, eating while driving, falling asleep while driving, etc.), and/or types of safe driving events (e.g., maintaining safe following distance, turning on headlights, observing traffic lights, yielding to pedestrians, obeying speed limits, etc.).
  • the way that the user drives can be indicative of how much carbon emissions have been generated.
  • the amount of total carbon emission is determined based at least in part upon the analyzed driving data.
  • the driving data are collected from one or more sensors associated with a vehicle operated by the user.
  • the one or more sensors include any type and number of accelerometers, gyroscopes, magnetometers, barometers, location sensors (e.g., GPS sensors), tilt sensors, yaw rate sensors, speedometers, brake sensors, airbag deployment sensors, headlight sensors, steering angle sensors, gear position sensors, proximity detectors, and/or any other suitable sensors that measure vehicle state and/or operation.
  • the one or more sensors are part of or located in the vehicle.
  • the one or more sensors are part of a mobile device connected to the vehicle while the vehicle is in operation.
  • the driving data are collected continuously or at predetermined time intervals.
  • the driving data are collected based on a triggering event. For example, the driving data are collected when each sensor has acquired a threshold amount of sensor measurements.
  • fuel-consumption data and/or vehicle data are analyzed to determine the amount of total carbon emission.
  • the fuel-consumption data indicate how much fuel (e.g., gasoline) has been consumed in operating the vehicle during the one or more vehicle trips.
  • the vehicle data indicate various vehicle specifications, such as model/year/make, type (e.g., hybrid), engine size, fuel economy (e.g., miles per gallon), etc.
  • an amount of fuel consumed by the type of vehicle can be indicative of how much carbon emissions have been generated.
  • the amount of total carbon emission is determined based at least in part upon the analyzed fuel-consumption data and/or the vehicle data.
  • the fuel-consumption data are collected from various sensors (e.g., fuel level sensors, exhaust sensors, speedometers, etc.) associated with the vehicle.
  • the vehicle data are derived from a unique identifier of the vehicle (e.g., vehicle identification number (VIN)), which may be supplied by the user or collected from a manufacturer of the vehicle.
  • VIN vehicle identification number
  • fueling data are analyzed to determine the amount of total carbon emission.
  • the fueling data indicate how much fuel was added during the one or more vehicle trips.
  • an amount of fuel added can be indicative of how much carbon emissions have been generated.
  • the amount of total carbon emission is determined based at least in part upon the analyzed fueling data.
  • the fueling data are supplied by the user.
  • the user manually inputs the amount of fuel that was added between a set of dates in which the one or more vehicle trips took place.
  • the fueling data are automatically collected from one or more sensors (e.g., a fuel gauge) associated with the vehicle.
  • relevant data e.g., driving data, fuel-consumption data, vehicle data, fueling data
  • a model e.g., a machine learning model, a statistical model, etc.
  • the model is an artificial neural network (e.g., a convolutional neural network, a recurrent neural network, a modular neural network, etc.).
  • the model has been trained, and the trained model possesses existing knowledge of which features in the relevant data are desirable or useful in determining the amount of total carbon emission. For example, determining the amount of total carbon emission involves that the trained model analyzes the relevant data based upon the existing knowledge.
  • analyzing the relevant data includes various tasks such as performing feature extractions, applying pattern recognition, and/or other suitable tasks.
  • other suitable computational methods e.g., decision tree, Bayesian network, finite-state machine, support vector machine, etc.
  • the desired percentage of carbon offset for the amount of total carbon emission of the user is received according to some embodiments.
  • the desired percentage of carbon offset is received from the user.
  • the user indicates a certain percentage of the amount of total carbon emission that the user wants to offset (e.g., 20%).
  • the user may choose to offset 100% of the amount of total carbon emission in order to achieve carbon neutrality.
  • the total number of carbon offset units corresponding to the predetermined carbon offset source is determined based at least in part upon the desired percentage of carbon offset according to certain embodiments.
  • the predetermined carbon offset source corresponds to the planting of one or more trees.
  • the total number of carbon offset units would represent the number of trees needed to satisfy the desired percentage of carbon offset for the amount of total carbon emission.
  • each carbon offset unit corresponds to the planting of at least a first tree at a first time and a second tree at a second time.
  • the first time precedes the second time by a first time duration that is shorter than or equal to a first lifespan of the first tree.
  • each carbon offset unit includes a first amount and a second amount.
  • the first amount is used to plant the first tree at the first time and the second amount is invested (e.g., in stocks, mutual funds, savings account, etc.) during the first time duration.
  • the second amount is invested so that it can grow to become a third amount needed for the subsequent planting of new trees at later times.
  • the third amount includes a first part and a second part.
  • the first part of the third amount is used to plant the second tree at the second time.
  • the second part of the third amount is invested for planting a third tree at a third time.
  • the second time precedes the third time by a second time duration that is shorter than or equal to a second lifespan of the second tree.
  • the second part is invested so that it can grow to become a fourth amount that includes a third part and a fourth part.
  • the third part is used to plant the third tree at the third time, and the fourth part is again invested for the planting of additional or future trees (e.g., planting a fourth tree at a fourth time).
  • the planting of trees is carried out in a renewable fashion in which new trees are planted when already planted trees die. For example, when a tree dies, the carbon stored in the tree is released back to the atmosphere. As an example, the planting of a new tree will ensure that the carbon is permanently recaptured and stored in a tree.
  • each carbon offset unit is always divided into two parts, with one part being used to plant one or more present trees and the other part being invested such that additional trees are planted in the future to replace and/or supplement the one or more present trees.
  • the planting of trees is performed by an organization engaged in carbon emission reduction projects/programs.
  • the predetermined carbon offset source may correspond to any suitable carbon offset source besides the planting of trees (e.g., solar panels).
  • each carbon offset unit acts like a common currency unit (e.g., carbon currency) that can be used to compare different types of carbon offset sources and/or implement other forms of carbon offset source.
  • a common currency unit e.g., carbon currency
  • the predetermined carbon offset source and one or more additional carbon offset sources are provided as the multiple carbon offset sources according to some embodiments.
  • the one or more additional carbon offset sources include a hydropower plant, a solar panel plant, a wind farm, a geothermal plant, biogas from a landfill, and/or other suitable carbon offset sources.
  • the one or more additional carbon offset sources may include research projects into future carbon offset technologies.
  • each of the multiple carbon offset sources may be presented to the user as an image or icon displayed on a mobile device of the user. For example, the user can view the multiple carbon offset sources on the mobile device and select those sources that the user feels would have a strong impact on the environment.
  • the respective number of carbon offset units corresponding to the predetermined carbon offset source is received for each of the multiple carbon offset sources according to some embodiments.
  • the respective number of carbon offset units is received from the user.
  • the user indicates the number of carbon offset units that the user would like to assign to each of the multiple carbon offset sources.
  • the number of carbon offset units may be automatically assigned to each of the multiple carbon offset sources according to user preferences.
  • a total of the respective number of carbon offset units assigned to the multiple carbon offset sources is equal to the total number of carbon offset units.
  • the respective cost for each of the multiple carbon offset sources is determined based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources according to certain embodiments.
  • the respective cost is an equivalent amount of money associated with each of the multiple carbon offset sources.
  • the one or more characteristics for each of the multiple carbon offset sources include a carbon removal efficiency (e.g., ability for a carbon offset source to remove carbon emissions) and an implementation cost (e.g., cost associated with realizing the carbon offset source).
  • the total amount of cost is provided based at least in part upon the respective cost for each of the multiple carbon offset sources according to some embodiments.
  • the total amount of cost is an equivalent amount of money calculated by summing the respective cost associated with each of the multiple carbon offset sources.
  • the user can select any combination of carbon offset sources to compensate for the user's carbon emissions.
  • the predetermined carbon offset source is the planting of trees and one tree can capture one ton of carbon dioxide.
  • the amount of total carbon emission is 10 tons and the user has indicated the desired percentage of carbon offset to be 60% (or 6 tons)
  • 6 trees are needed to capture the 6 tons of carbon dioxide.
  • the user can assign the 6 trees to any combination of the multiple carbon offset sources presented to the user.
  • the user may decide to keep 50% of the carbon offset sources as just trees (e.g., 3 trees), but assign the remaining 50% to other carbon offset sources (e.g., 2 trees to solar panels and 1 tree to a landfill that generates biogas).
  • the cost associated with each carbon offset source is determined (e.g., $15 for the 3 trees, $20 for the solar panels, and $10 for the landfill).
  • the cost of the trees may be $15 (e.g., each tree at $5).
  • the cost of the solar panels may be $20 (e.g., 2 trees at $5 each plus the cost associated with building and installing the solar panels at $10).
  • the cost of the landfill may be $10 (e.g., one tree at $5 plus the cost associated with funding the landfill at $5).
  • the total amount of cost associated with the selected carbon offset sources is equal to $45.
  • a portfolio of carbon offset sources is created for the user.
  • the portfolio represents digital assets that the user can trade or exchange with other users in a carbon offset marketplace.
  • user A has $90 worth of carbon offset sources in user A's portfolio and user B has $45 worth of carbon offset sources in user B's portfolio.
  • user A can trade or exchange $45 in user A's portfolio with the $45 in user B's portfolio.
  • FIG. 2 is a simplified system for providing carbon offset sources according to certain embodiments of the present disclosure.
  • the system 200 includes a vehicle system 202 , a network 204 , and a server 206 .
  • vehicle system 202 includes a vehicle system 202 , a network 204 , and a server 206 .
  • server 206 a server 206 .
  • the above has been shown using a selected group of components for the system, there can be many alternatives, modifications, and variations. For example, some of the components may be expanded and/or combined. Other components may be inserted to those noted above. Depending upon the embodiment, the arrangement of components may be interchanged with others replaced.
  • the system 200 is used to implement the method 100 .
  • the vehicle system 202 includes a vehicle 210 and a client device 212 associated with the vehicle 210 .
  • the client device 212 is an on-board computer embedded or located in the vehicle 210 .
  • the client device 212 is a mobile device (e.g., a smartphone) that is connected (e.g., via wired or wireless links) to the vehicle 210 .
  • the client device 212 includes a processor 216 (e.g., a central processing unit (CPU), a graphics processing unit (GPU)), a memory 218 (e.g., random-access memory (RAM), read-only memory (ROM), flash memory), a communications unit 220 (e.g., a network transceiver), a display unit 222 (e.g., a touchscreen), and one or more sensors 224 (e.g., an accelerometer, a gyroscope, a magnetometer, a barometer, a GPS sensor).
  • a processor 216 e.g., a central processing unit (CPU), a graphics processing unit (GPU)
  • a memory 218 e.g., random-access memory (RAM), read-only memory (ROM), flash memory
  • a communications unit 220 e.g., a network transceiver
  • a display unit 222 e.g., a touchscreen
  • sensors 224 e.g., an accelerometer,
  • the vehicle 210 is operated by the user. In certain embodiments, multiple vehicles 210 exist in the system 200 which are operated by respective users.
  • the one or more sensors 224 monitor the vehicle 210 by collecting data associated with various operating parameters of the vehicle, such as speed, acceleration, braking, location, engine status, fuel level, as well as other suitable parameters.
  • the collected data include vehicle telematics data. According to some embodiments, the data are collected continuously, at predetermined time intervals, and/or based on a triggering event (e.g., when each sensor has acquired a threshold amount of sensor measurements). In various embodiments, the collected data represent the driving data, fuel-consumption data, and/or fueling data in the method 100 .
  • the collected data are stored in the memory 218 before being transmitted to the server 206 using the communications unit 220 via the network 204 (e.g., via a local area network (LAN), a wide area network (WAN), the Internet).
  • the collected data are transmitted directly to the server 206 via the network 204 .
  • the collected data are transmitted to the server 206 via a third party.
  • a data monitoring system stores any and all data collected by the one or more sensors 224 and transmits those data to the server 206 via the network 204 or a different network.
  • the server 206 includes a processor 230 (e.g., a microprocessor, a microcontroller), a memory 232 , a communications unit 234 (e.g., a network transceiver), and a data storage 236 (e.g., one or more databases).
  • the server 206 is a single server, while in certain embodiments, the server 206 includes a plurality of servers with distributed processing.
  • the data storage 236 is shown to be part of the server 206 .
  • the data storage 236 is a separate entity coupled to the server 206 via a network such as the network 204 .
  • the server 206 includes various software applications stored in the memory 232 and executable by the processor 230 .
  • these software applications include specific programs, routines, or scripts for performing functions associated with the method 100 .
  • the software applications include general-purpose software applications for data processing, network communication, database management, web server operation, and/or other functions typically performed by a server.
  • the server 206 receives, via the network 204 , the data collected by the one or more sensors 224 using the communications unit 234 and stores the data in the data storage 236 . For example, the server 206 then processes the data to perform one or more processes of the method 100 .
  • any related information determined or generated by the method 100 are transmitted back to the client device 212 , via the network 204 , to be provided (e.g., displayed) to the user via the display unit 222 .
  • one or more processes of the method 100 are performed by the client device 212 .
  • the processor 216 of the client device 212 processes the data collected by the one or more sensors 224 to perform one or more processes of the method 100 .
  • FIG. 3 is a simplified computing device for providing carbon offset sources according to certain embodiments of the present disclosure. This diagram is merely an example, which should not unduly limit the scope of the claims. One of ordinary skill in the art would recognize many variations, alternatives, and modifications.
  • the computing device 300 includes a processing unit 304 , a memory unit 306 , an input unit 308 , an output unit 310 , a communication unit 312 , and a storage unit 314 .
  • the computing device 300 is configured to be in communication with a user 316 and/or a storage device 318 .
  • the computing device 300 is configured to implement the method 100 of FIG. 1 .
  • the processing unit 304 is configured for executing instructions, such as instructions to implement the method 100 of FIG. 1 .
  • the executable instructions are stored in the memory unit 306 .
  • the processing unit 304 includes one or more processing units (e.g., in a multi-core configuration).
  • the processing unit 304 includes and/or is communicatively coupled to one or more modules for implementing the methods and systems described in the present disclosure.
  • the processing unit 304 is configured to execute instructions within one or more operating systems.
  • one or more instructions upon initiation of a computer-implemented method, one or more instructions is executed during initialization.
  • one or more operations is executed to perform one or more processes described herein.
  • an operation may be general or specific to a particular programming language (e.g., C, C++, Java, or other suitable programming languages, etc.).
  • the memory unit 306 includes a device allowing information, such as executable instructions and/or other data to be stored and retrieved.
  • the memory unit 306 includes one or more computer readable media.
  • the memory unit 306 includes computer readable instructions for providing a user interface, such as to the user 316 , via the output unit 310 .
  • a user interface includes a web browser and/or a client application. For example, a web browser enables the user 316 to interact with media and/or other information embedded on a web page and/or a website.
  • the memory unit 306 includes computer readable instructions for receiving and processing an input via the input unit 308 .
  • the memory unit 306 includes RAM such as dynamic RAM (DRAM) or static RAM (SRAM), ROM, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and/or non-volatile RAM (NVRAM).
  • RAM such as dynamic RAM (DRAM) or static RAM (SRAM)
  • ROM read-only memory
  • EPROM erasable programmable read-only memory
  • EEPROM electrically erasable programmable read-only memory
  • NVRAM non-volatile RAM
  • the input unit 308 is configured to receive input (e.g., from the user 316 ).
  • the input unit 308 includes a keyboard, a pointing device, a mouse, a stylus, a touch sensitive panel (e.g., a touch pad or touch screen), a gyroscope, an accelerometer, a position sensor (e.g., GPS sensor), and/or an audio input device.
  • the input unit 308 is configured to function as both an input unit and an output unit.
  • the output unit 310 includes a media output unit configured to present information to the user 316 .
  • the output unit 310 includes any component capable of conveying information to the user 316 .
  • the output unit 310 includes an output adapter such as a video adapter and/or an audio adapter.
  • the output unit 310 is operatively coupled to the processing unit 304 and/or a visual display device to present information to the user 316 (e.g., a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, a cathode ray tube (CRT) display, a projected display, etc.).
  • the output unit 310 is operatively coupled to the processing unit 304 and/or an audio display device to present information to the user 316 (e.g., a speaker arrangement or headphones).
  • the communication unit 312 is configured to be communicatively coupled to a remote device.
  • the communication unit 312 includes a wired network adapter, a wireless network adapter, a wireless data transceiver for use with a mobile phone network (e.g., 3G, 4G, 5G, Bluetooth, etc.), and/or other mobile data networks. In certain embodiments, other types of short-range or long-range networks may be used.
  • the communication unit 312 is configured to provide email integration for communicating data between a server and one or more clients.
  • the storage unit 314 is configured to enable communication between the computing device 300 and the storage device 318 .
  • the storage unit 314 is a storage interface.
  • the storage interface is any component capable of providing the processing unit 304 with access to the storage device 318 .
  • the storage unit 314 includes an advanced technology attachment (ATA) adapter, a serial ATA (SATA) adapter, a small computer system interface (SCSI) adapter, a RAID controller, a SAN adapter, a network adapter, and/or any other component capable of providing the processing unit 304 with access to the storage device 318 .
  • ATA advanced technology attachment
  • SATA serial ATA
  • SCSI small computer system interface
  • RAID controller a SAN adapter
  • SAN adapter a network adapter
  • the storage device 318 includes any computer-operated hardware suitable for storing and/or retrieving data.
  • the storage device 318 is integrated in the computing device 300 .
  • the storage device 318 includes a database such as a local database or a cloud database.
  • the storage device 318 includes one or more hard disk drives.
  • the storage device 318 is external and is configured to be accessed by a plurality of server systems.
  • the storage device 318 includes multiple storage units such as hard disks or solid state disks in a redundant array of inexpensive disks configuration.
  • the storage device 318 includes a storage area network and/or a network attached storage system.
  • a method for providing carbon offset sources includes determining an amount of total carbon emission of a user and receiving a desired percentage of carbon offset for the amount of total carbon emission of the user. Also, the method includes determining a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset. Additionally, the method includes providing multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources. For each of the multiple carbon offset sources, the method includes receiving a respective number of carbon offset units corresponding to the predetermined carbon offset source and determining a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources.
  • the method includes providing a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
  • the method is implemented according to at least FIG. 1 .
  • a computing device for providing carbon offset sources includes one or more processors and a memory that stores instructions for execution by the one or more processors.
  • the instructions when executed, cause the one or more processors to determine an amount of total carbon emission of a user and receive a desired percentage of carbon offset for the amount of total carbon emission of the user.
  • the instructions when executed, cause the one or more processors to determine a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset.
  • the instructions when executed, cause the one or more processors to provide multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources.
  • the instructions when executed, cause the one or more processors to receive a respective number of carbon offset units corresponding to the predetermined carbon offset source and determine a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources. Moreover, the instructions, when executed, cause the one or more processors to provide a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
  • the computing device is implemented according to at least FIG. 2 and/or FIG. 3 .
  • a non-transitory computer-readable medium stores instructions for providing carbon offset sources.
  • the instructions are executed by one or more processors of a computing device.
  • the non-transitory computer-readable medium includes instructions to determine an amount of total carbon emission of a user and receive a desired percentage of carbon offset for the amount of total carbon emission of the user.
  • the non-transitory computer-readable medium includes instructions to determine a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset.
  • the non-transitory computer-readable medium includes instructions to provide multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources.
  • the non-transitory computer-readable medium includes instructions to receive a respective number of carbon offset units corresponding to the predetermined carbon offset source and determine a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources. Moreover, the non-transitory computer-readable medium includes instructions to provide a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
  • the non-transitory computer-readable medium is implemented according to at least FIG. 1 . FIG. 2 , and/or FIG. 3 .
  • a processor or a processing element may be trained using supervised machine learning and/or unsupervised machine learning, and the machine learning may employ an artificial neural network, which, for example, may be a convolutional neural network, a recurrent neural network, a deep learning neural network, a reinforcement learning module or program, or a combined learning module or program that learns in two or more fields or areas of interest.
  • Machine learning may involve identifying and recognizing patterns in existing data in order to facilitate making predictions for subsequent data. Models may be created based upon example inputs in order to make valid and reliable predictions for novel inputs.
  • machine learning programs may be trained by inputting sample data sets or certain data into the programs, such as images, object statistics and information, historical estimates, and/or actual repair costs.
  • the machine learning programs may utilize deep learning algorithms that may be primarily focused on pattern recognition and may be trained after processing multiple examples.
  • the machine learning programs may include Bayesian Program Learning (BPL), voice recognition and synthesis, image or object recognition, optical character recognition, and/or natural language processing.
  • BPL Bayesian Program Learning
  • voice recognition and synthesis image or object recognition
  • optical character recognition and/or natural language processing
  • the machine learning programs may also include natural language processing, semantic analysis, automatic reasoning, and/or other types of machine learning.
  • supervised machine learning techniques and/or unsupervised machine learning techniques may be used.
  • a processing element may be provided with example inputs and their associated outputs and may seek to discover a general rule that maps inputs to outputs, so that when subsequent novel inputs are provided the processing element may, based upon the discovered rule, accurately predict the correct output.
  • unsupervised machine learning the processing element may need to find its own structure in unlabeled example inputs.
  • some or all components of various embodiments of the present disclosure each are, individually and/or in combination with at least another component, implemented using one or more software components, one or more hardware components, and/or one or more combinations of software and hardware components.
  • some or all components of various embodiments of the present disclosure each are, individually and/or in combination with at least another component, implemented in one or more circuits, such as one or more analog circuits and/or one or more digital circuits.
  • the embodiments described above refer to particular features, the scope of the present disclosure also includes embodiments having different combinations of features and embodiments that do not include all of the described features.
  • various embodiments and/or examples of the present disclosure can be combined.
  • the methods and systems described herein may be implemented on many different types of processing devices by program code comprising program instructions that are executable by the device processing subsystem.
  • the software program instructions may include source code, object code, machine code, or any other stored data that is operable to cause a processing system to perform the methods and operations described herein.
  • Certain implementations may also be used, however, such as firmware or even appropriately designed hardware configured to perform the methods and systems described herein.
  • the systems' and methods' data may be stored and implemented in one or more different types of computer-implemented data stores, such as different types of storage devices and programming constructs (e.g., RAM, ROM, EEPROM, Flash memory, flat files, databases, programming data structures, programming variables, IF-THEN (or similar type) statement constructs, application programming interface).
  • storage devices and programming constructs e.g., RAM, ROM, EEPROM, Flash memory, flat files, databases, programming data structures, programming variables, IF-THEN (or similar type) statement constructs, application programming interface.
  • data structures describe formats for use in organizing and storing data in databases, programs, memory, or other computer-readable media for use by a computer program.
  • the systems and methods may be provided on many different types of computer-readable media including computer storage mechanisms (e.g., CD-ROM, diskette, RAM, flash memory, computer's hard drive, DVD) that contain instructions (e.g., software) for use in execution by a processor to perform the methods' operations and implement the systems described herein.
  • computer storage mechanisms e.g., CD-ROM, diskette, RAM, flash memory, computer's hard drive, DVD
  • instructions e.g., software
  • the computer components, software modules, functions, data stores and data structures described herein may be connected directly or indirectly to each other in order to allow the flow of data needed for their operations.
  • a module or processor includes a unit of code that performs a software operation, and can be implemented for example as a subroutine unit of code, or as a software function unit of code, or as an object (as in an object-oriented paradigm), or as an applet, or in a computer script language, or as another type of computer code.
  • the software components and/or functionality may be located on a single computer or distributed across multiple computers depending upon the situation at hand.
  • the computing system can include client devices and servers.
  • a client device and server are generally remote from each other and typically interact through a communication network.
  • the relationship of client device and server arises by virtue of computer programs running on the respective computers and having a client device-server relationship to each other.

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Abstract

Method and system for providing carbon offset sources. For example, the method includes determining an amount of total carbon emission of a user, receiving a desired percentage of carbon offset, determining a total number of carbon offset units corresponding to a predetermined carbon offset source, providing multiple carbon offset sources, receiving a respective number of carbon offset units corresponding to the predetermined carbon offset source for each of the multiple carbon offset sources, determining a respective cost for each of the multiple carbon offset sources, and providing a total amount of cost based upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units.

Description

    CROSS-REFERENCE TO RELATED APPLICATIONS
  • This application claims priority to U.S. Provisional Patent Application No. 63/000,874, filed Mar. 27, 2020, incorporated by reference herein for all purposes.
  • International PCT Application No. PCT/US21/18233, titled “System and Methods for Providing Renewing Carbon Offsets” is incorporated by reference herein for all purposes.
  • The following five applications, including this one, are being filed concurrently and the other four are hereby incorporated by reference in their entirety for all purposes:
  • 1. International PCT Application No. ______, titled “Systems and Methods for Offering Carbon Offset Rewards that Correspond to Users” (Attorney Docket Number BOL-00007A-PCT);
  • 2. International PCT Application No. ______, titled “Systems and Methods for Providing Multiple Carbon Offset Sources” (Attorney Docket Number BOL-00007B-PCT);
  • 3. International PCT Application No. ______, titled “Systems and Methods for Generating Tree Imagery” (Attorney Docket Number BOL-00007G-PCT);
  • 4. International PCT Application No. ______, titled “Systems and Methods for Validating Planting of Trees” (Attorney Docket Number BOL-00007H-PCT); and
  • 5. International PCT Application No. ______, titled “Systems and Methods for Providing Renewing Carbon Offsets for a User Driving Period” (Attorney Docket Number BOL-00007J-PCT).
  • FIELD OF THE DISCLOSURE
  • Some embodiments of the present disclosure are directed to providing multiple carbon offset sources. More particularly, certain embodiments of the present disclosure provide methods and systems for providing various carbon offset sources to compensate for carbon emissions of a user. Merely by way of example, the present disclosure has been applied to allowing the user to use one type carbon offset source as a common currency unit to compare between different types carbon offset sources. But it would be recognized that the present disclosure has much broader range of applicability.
  • BACKGROUND OF THE DISCLOSURE
  • Carbon emissions from vehicles represent a major contributor to climate change. While new vehicle technologies have been developed to curb carbon emissions, the continued use of vehicles for private transportation will cause the amount of carbon emissions to remain high or even increase. Hence it is desirable to have multiple carbon offset sources that can compensate for the release of these carbon emissions.
  • BRIEF SUMMARY OF THE DISCLOSURE
  • Some embodiments of the present disclosure are directed to providing multiple carbon offset sources. More particularly, certain embodiments of the present disclosure provide methods and systems for providing various carbon offset sources to compensate for carbon emissions of a user. Merely by way of example, the present disclosure has been applied to allowing the user to use one type of carbon offset source as a common currency unit to compare between different types of carbon offset sources. But it would be recognized that the present disclosure has much broader range of applicability.
  • According to certain embodiments, a method for providing carbon offset sources includes determining an amount of total carbon emission of a user and receiving a desired percentage of carbon offset for the amount of total carbon emission of the user. Also, the method includes determining a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset. Additionally, the method includes providing multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources. For each of the multiple carbon offset sources, the method includes receiving a respective number of carbon offset units corresponding to the predetermined carbon offset source and determining a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources. Moreover, the method includes providing a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
  • According to some embodiments, a computing device for providing carbon offset sources includes one or more processors and a memory that stores instructions for execution by the one or more processors. The instructions, when executed, cause the one or more processors to determine an amount of total carbon emission of a user and receive a desired percentage of carbon offset for the amount of total carbon emission of the user. Also, the instructions, when executed, cause the one or more processors to determine a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset. Additionally, the instructions, when executed, cause the one or more processors to provide multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources. For each of the multiple carbon offset sources, the instructions, when executed, cause the one or more processors to receive a respective number of carbon offset units corresponding to the predetermined carbon offset source and determine a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources. Moreover, the instructions, when executed, cause the one or more processors to provide a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
  • According to certain embodiments, a non-transitory computer-readable medium stores instructions for providing carbon offset sources. The instructions are executed by one or more processors of a computing device. The non-transitory computer-readable medium includes instructions to determine an amount of total carbon emission of a user and receive a desired percentage of carbon offset for the amount of total carbon emission of the user. Also, the non-transitory computer-readable medium includes instructions to determine a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset. Additionally, the non-transitory computer-readable medium includes instructions to provide multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources. For each of the multiple carbon offset sources, the non-transitory computer-readable medium includes instructions to receive a respective number of carbon offset units corresponding to the predetermined carbon offset source and determine a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources. Moreover, the non-transitory computer-readable medium includes instructions to provide a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
  • Depending upon the embodiment, one or more benefits may be achieved. These benefits and various additional objects, features and advantages of the present disclosure can be fully appreciated with reference to the detailed description and accompanying drawings that follow.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • FIG. 1 is a simplified method for providing carbon offset sources according to certain embodiments of the present disclosure.
  • FIG. 2 is a simplified system for providing carbon offset sources according to some embodiments of the present disclosure
  • FIG. 3 is a simplified computing device for providing carbon offset sources according to certain embodiments of the present disclosure.
  • DETAILED DESCRIPTION OF THE DISCLOSURE
  • Some embodiments of the present disclosure are directed to providing multiple carbon offset sources. More particularly, certain embodiments of the present disclosure provide methods and systems for providing various carbon offset sources to compensate for carbon emissions of a user. Merely by way of example, the present disclosure has been applied to allowing the user to use one type of carbon offset source as a common currency unit to compare between different types of carbon offset sources. But it would be recognized that the present disclosure has much broader range of applicability.
  • I. One or More Methods for Providing Carbon Offset Sources According to Certain Embodiments
  • FIG. 1 is a simplified method for providing carbon offset sources according to certain embodiments of the present disclosure. The diagrams are merely examples, which should not unduly limit the scope of the claims. One of ordinary skill in the art would recognize many variations, alternatives, and modifications. The method 100 includes process 110 for determining carbon emission, process 120 for receiving a desired percentage of carbon offset, process 130 for determining a total number of carbon offset units corresponding to a predetermined carbon offset source, process 140 for providing multiple carbon offset sources, process 150 for receiving a respective number of carbon offset units for each of the multiple carbon offset sources, process 160 for determining a respective cost for each of the multiple carbon offset sources, and process 170 for providing a total amount of cost. Although the above has been shown using a selected group of processes for the method, there can be many alternatives, modifications, and variations. For example, some of the processes may be expanded and/or combined. Other processes may be inserted to those noted above. Depending upon the embodiment, the sequence of processes may be interchanged with others replaced. For example, some or all processes of the method are performed by a computing device or a processor directed by instructions stored in memory. As an example, some or all processes of the method are performed according to instructions stored in a non-transitory computer-readable medium.
  • At the process 110, an amount of total carbon emission of a user is determined according to some embodiments. In various embodiments, the amount of total carbon emission represents how much carbon pollution the user has generated by driving. For example, the amount of total carbon emission is calculated over a specified period (e.g., a year) and expressed as a numerical value (e.g., 2 tons of carbon dioxide).
  • In some embodiments, driving data are analyzed to determine the amount of total carbon emission. For example, the driving data associated with one or more vehicle trips made by the user and indicate how the user drives, such as type of maneuvers that the user makes while driving (e.g., hard cornering, hard braking, sudden acceleration, smooth acceleration, slowing before turning, etc.), types of dangerous driving events (e.g., cell phone usage while driving, eating while driving, falling asleep while driving, etc.), and/or types of safe driving events (e.g., maintaining safe following distance, turning on headlights, observing traffic lights, yielding to pedestrians, obeying speed limits, etc.). As an example, the way that the user drives can be indicative of how much carbon emissions have been generated. For example, the amount of total carbon emission is determined based at least in part upon the analyzed driving data.
  • In certain embodiments, the driving data are collected from one or more sensors associated with a vehicle operated by the user. For example, the one or more sensors include any type and number of accelerometers, gyroscopes, magnetometers, barometers, location sensors (e.g., GPS sensors), tilt sensors, yaw rate sensors, speedometers, brake sensors, airbag deployment sensors, headlight sensors, steering angle sensors, gear position sensors, proximity detectors, and/or any other suitable sensors that measure vehicle state and/or operation. In some embodiments, the one or more sensors are part of or located in the vehicle. In certain embodiments, the one or more sensors are part of a mobile device connected to the vehicle while the vehicle is in operation. According to some embodiments, the driving data are collected continuously or at predetermined time intervals. According to certain embodiments, the driving data are collected based on a triggering event. For example, the driving data are collected when each sensor has acquired a threshold amount of sensor measurements.
  • In some embodiments, fuel-consumption data and/or vehicle data are analyzed to determine the amount of total carbon emission. For example, the fuel-consumption data indicate how much fuel (e.g., gasoline) has been consumed in operating the vehicle during the one or more vehicle trips. As an example, the vehicle data indicate various vehicle specifications, such as model/year/make, type (e.g., hybrid), engine size, fuel economy (e.g., miles per gallon), etc. For example, an amount of fuel consumed by the type of vehicle can be indicative of how much carbon emissions have been generated. As an example, the amount of total carbon emission is determined based at least in part upon the analyzed fuel-consumption data and/or the vehicle data.
  • In certain embodiments, the fuel-consumption data are collected from various sensors (e.g., fuel level sensors, exhaust sensors, speedometers, etc.) associated with the vehicle. In some embodiments, the vehicle data are derived from a unique identifier of the vehicle (e.g., vehicle identification number (VIN)), which may be supplied by the user or collected from a manufacturer of the vehicle.
  • In some embodiments, fueling data are analyzed to determine the amount of total carbon emission. For example, the fueling data indicate how much fuel was added during the one or more vehicle trips. As an example, an amount of fuel added can be indicative of how much carbon emissions have been generated. For example, the amount of total carbon emission is determined based at least in part upon the analyzed fueling data.
  • In certain embodiments, the fueling data are supplied by the user. As an example, the user manually inputs the amount of fuel that was added between a set of dates in which the one or more vehicle trips took place. In some embodiments, the fueling data are automatically collected from one or more sensors (e.g., a fuel gauge) associated with the vehicle.
  • In various embodiments, relevant data (e.g., driving data, fuel-consumption data, vehicle data, fueling data) are provided to a model (e.g., a machine learning model, a statistical model, etc.) to determine the amount of total carbon emission. In certain embodiments, the model is an artificial neural network (e.g., a convolutional neural network, a recurrent neural network, a modular neural network, etc.). In some embodiments, the model has been trained, and the trained model possesses existing knowledge of which features in the relevant data are desirable or useful in determining the amount of total carbon emission. For example, determining the amount of total carbon emission involves that the trained model analyzes the relevant data based upon the existing knowledge. As an example, analyzing the relevant data includes various tasks such as performing feature extractions, applying pattern recognition, and/or other suitable tasks. In certain embodiments, other suitable computational methods (e.g., decision tree, Bayesian network, finite-state machine, support vector machine, etc.) may be used to analyze the relevant data and determine the amount of total carbon emission.
  • At the process 120, the desired percentage of carbon offset for the amount of total carbon emission of the user is received according to some embodiments. In certain embodiments, the desired percentage of carbon offset is received from the user. For example, the user indicates a certain percentage of the amount of total carbon emission that the user wants to offset (e.g., 20%). In some embodiments, the user may choose to offset 100% of the amount of total carbon emission in order to achieve carbon neutrality.
  • At the process 130, the total number of carbon offset units corresponding to the predetermined carbon offset source is determined based at least in part upon the desired percentage of carbon offset according to certain embodiments. In some embodiments, the predetermined carbon offset source corresponds to the planting of one or more trees. For example, the total number of carbon offset units would represent the number of trees needed to satisfy the desired percentage of carbon offset for the amount of total carbon emission.
  • In some embodiments, each carbon offset unit corresponds to the planting of at least a first tree at a first time and a second tree at a second time. For example, the first time precedes the second time by a first time duration that is shorter than or equal to a first lifespan of the first tree.
  • In certain embodiments, each carbon offset unit includes a first amount and a second amount. For example, the first amount is used to plant the first tree at the first time and the second amount is invested (e.g., in stocks, mutual funds, savings account, etc.) during the first time duration. As an example, the second amount is invested so that it can grow to become a third amount needed for the subsequent planting of new trees at later times.
  • In some embodiments, the third amount includes a first part and a second part. For example, after the first time duration, the first part of the third amount is used to plant the second tree at the second time. As an example, the second part of the third amount is invested for planting a third tree at a third time. For example, the second time precedes the third time by a second time duration that is shorter than or equal to a second lifespan of the second tree.
  • In certain embodiments, the second part is invested so that it can grow to become a fourth amount that includes a third part and a fourth part. For example, the third part is used to plant the third tree at the third time, and the fourth part is again invested for the planting of additional or future trees (e.g., planting a fourth tree at a fourth time).
  • According to various embodiments, the planting of trees is carried out in a renewable fashion in which new trees are planted when already planted trees die. For example, when a tree dies, the carbon stored in the tree is released back to the atmosphere. As an example, the planting of a new tree will ensure that the carbon is permanently recaptured and stored in a tree. In some embodiments, each carbon offset unit is always divided into two parts, with one part being used to plant one or more present trees and the other part being invested such that additional trees are planted in the future to replace and/or supplement the one or more present trees. In certain embodiments, the planting of trees is performed by an organization engaged in carbon emission reduction projects/programs. In some embodiments, the predetermined carbon offset source may correspond to any suitable carbon offset source besides the planting of trees (e.g., solar panels).
  • In certain embodiments, each carbon offset unit acts like a common currency unit (e.g., carbon currency) that can be used to compare different types of carbon offset sources and/or implement other forms of carbon offset source.
  • At the process 140, the predetermined carbon offset source and one or more additional carbon offset sources are provided as the multiple carbon offset sources according to some embodiments. In various embodiments, the one or more additional carbon offset sources include a hydropower plant, a solar panel plant, a wind farm, a geothermal plant, biogas from a landfill, and/or other suitable carbon offset sources. In certain embodiments, the one or more additional carbon offset sources may include research projects into future carbon offset technologies. In various embodiments, each of the multiple carbon offset sources may be presented to the user as an image or icon displayed on a mobile device of the user. For example, the user can view the multiple carbon offset sources on the mobile device and select those sources that the user feels would have a strong impact on the environment.
  • At the process 150, the respective number of carbon offset units corresponding to the predetermined carbon offset source is received for each of the multiple carbon offset sources according to some embodiments. In certain embodiments, the respective number of carbon offset units is received from the user. For example, the user indicates the number of carbon offset units that the user would like to assign to each of the multiple carbon offset sources. In some embodiments, the number of carbon offset units may be automatically assigned to each of the multiple carbon offset sources according to user preferences. In various embodiments, a total of the respective number of carbon offset units assigned to the multiple carbon offset sources is equal to the total number of carbon offset units.
  • At the process 160, the respective cost for each of the multiple carbon offset sources is determined based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources according to certain embodiments. For example, the respective cost is an equivalent amount of money associated with each of the multiple carbon offset sources. In various embodiments, the one or more characteristics for each of the multiple carbon offset sources include a carbon removal efficiency (e.g., ability for a carbon offset source to remove carbon emissions) and an implementation cost (e.g., cost associated with realizing the carbon offset source).
  • At the process 170, the total amount of cost is provided based at least in part upon the respective cost for each of the multiple carbon offset sources according to some embodiments. For example, the total amount of cost is an equivalent amount of money calculated by summing the respective cost associated with each of the multiple carbon offset sources.
  • According to various embodiments, the user can select any combination of carbon offset sources to compensate for the user's carbon emissions. For example, assume the predetermined carbon offset source is the planting of trees and one tree can capture one ton of carbon dioxide. As an example, if the amount of total carbon emission is 10 tons and the user has indicated the desired percentage of carbon offset to be 60% (or 6 tons), then 6 trees are needed to capture the 6 tons of carbon dioxide. For example, the user can assign the 6 trees to any combination of the multiple carbon offset sources presented to the user. As an example, the user may decide to keep 50% of the carbon offset sources as just trees (e.g., 3 trees), but assign the remaining 50% to other carbon offset sources (e.g., 2 trees to solar panels and 1 tree to a landfill that generates biogas). For example, after selecting the carbon offset sources, the cost associated with each carbon offset source is determined (e.g., $15 for the 3 trees, $20 for the solar panels, and $10 for the landfill). For example, the cost of the trees may be $15 (e.g., each tree at $5). As an example, the cost of the solar panels may be $20 (e.g., 2 trees at $5 each plus the cost associated with building and installing the solar panels at $10). For example, the cost of the landfill may be $10 (e.g., one tree at $5 plus the cost associated with funding the landfill at $5). As an example, the total amount of cost associated with the selected carbon offset sources is equal to $45.
  • In some embodiments, once the user has chosen the carbon offset sources, a portfolio of carbon offset sources is created for the user. For example, the portfolio represents digital assets that the user can trade or exchange with other users in a carbon offset marketplace. As an example, user A has $90 worth of carbon offset sources in user A's portfolio and user B has $45 worth of carbon offset sources in user B's portfolio. For example, user A can trade or exchange $45 in user A's portfolio with the $45 in user B's portfolio.
  • II. One or More Systems for Providing Carbon Offset Sources According to Certain Embodiments
  • FIG. 2 is a simplified system for providing carbon offset sources according to certain embodiments of the present disclosure. This diagram is merely an example, which should not unduly limit the scope of the claims. One of ordinary skill in the art would recognize many variations, alternatives, and modifications. The system 200 includes a vehicle system 202, a network 204, and a server 206. Although the above has been shown using a selected group of components for the system, there can be many alternatives, modifications, and variations. For example, some of the components may be expanded and/or combined. Other components may be inserted to those noted above. Depending upon the embodiment, the arrangement of components may be interchanged with others replaced.
  • In various embodiments, the system 200 is used to implement the method 100. According to certain embodiments, the vehicle system 202 includes a vehicle 210 and a client device 212 associated with the vehicle 210. For example, the client device 212 is an on-board computer embedded or located in the vehicle 210. As an example, the client device 212 is a mobile device (e.g., a smartphone) that is connected (e.g., via wired or wireless links) to the vehicle 210. As an example, the client device 212 includes a processor 216 (e.g., a central processing unit (CPU), a graphics processing unit (GPU)), a memory 218 (e.g., random-access memory (RAM), read-only memory (ROM), flash memory), a communications unit 220 (e.g., a network transceiver), a display unit 222 (e.g., a touchscreen), and one or more sensors 224 (e.g., an accelerometer, a gyroscope, a magnetometer, a barometer, a GPS sensor).
  • In some embodiments, the vehicle 210 is operated by the user. In certain embodiments, multiple vehicles 210 exist in the system 200 which are operated by respective users. As an example, during vehicle trips, the one or more sensors 224 monitor the vehicle 210 by collecting data associated with various operating parameters of the vehicle, such as speed, acceleration, braking, location, engine status, fuel level, as well as other suitable parameters. In certain embodiments, the collected data include vehicle telematics data. According to some embodiments, the data are collected continuously, at predetermined time intervals, and/or based on a triggering event (e.g., when each sensor has acquired a threshold amount of sensor measurements). In various embodiments, the collected data represent the driving data, fuel-consumption data, and/or fueling data in the method 100.
  • According to certain embodiments, the collected data are stored in the memory 218 before being transmitted to the server 206 using the communications unit 220 via the network 204 (e.g., via a local area network (LAN), a wide area network (WAN), the Internet). In some embodiments, the collected data are transmitted directly to the server 206 via the network 204. In certain embodiments, the collected data are transmitted to the server 206 via a third party. For example, a data monitoring system stores any and all data collected by the one or more sensors 224 and transmits those data to the server 206 via the network 204 or a different network.
  • According to certain embodiments, the server 206 includes a processor 230 (e.g., a microprocessor, a microcontroller), a memory 232, a communications unit 234 (e.g., a network transceiver), and a data storage 236 (e.g., one or more databases). In some embodiments, the server 206 is a single server, while in certain embodiments, the server 206 includes a plurality of servers with distributed processing. In FIG. 2 , the data storage 236 is shown to be part of the server 206. In some embodiments, the data storage 236 is a separate entity coupled to the server 206 via a network such as the network 204. In certain embodiments, the server 206 includes various software applications stored in the memory 232 and executable by the processor 230. For example, these software applications include specific programs, routines, or scripts for performing functions associated with the method 100. As an example, the software applications include general-purpose software applications for data processing, network communication, database management, web server operation, and/or other functions typically performed by a server.
  • According to various embodiments, the server 206 receives, via the network 204, the data collected by the one or more sensors 224 using the communications unit 234 and stores the data in the data storage 236. For example, the server 206 then processes the data to perform one or more processes of the method 100.
  • According to certain embodiments, any related information determined or generated by the method 100 (e.g., amount of total carbon emission, each of the multiple carbon offset sources, respective cost of each carbon offset source, total amount of cost, etc.) are transmitted back to the client device 212, via the network 204, to be provided (e.g., displayed) to the user via the display unit 222.
  • In some embodiments, one or more processes of the method 100 are performed by the client device 212. For example, the processor 216 of the client device 212 processes the data collected by the one or more sensors 224 to perform one or more processes of the method 100.
  • III. One or More Computing Devices for Providing Carbon Offset Sources According to Certain Embodiments
  • FIG. 3 is a simplified computing device for providing carbon offset sources according to certain embodiments of the present disclosure. This diagram is merely an example, which should not unduly limit the scope of the claims. One of ordinary skill in the art would recognize many variations, alternatives, and modifications. The computing device 300 includes a processing unit 304, a memory unit 306, an input unit 308, an output unit 310, a communication unit 312, and a storage unit 314. In various embodiments, the computing device 300 is configured to be in communication with a user 316 and/or a storage device 318. In some embodiments, the computing device 300 is configured to implement the method 100 of FIG. 1 . Although the above has been shown using a selected group of components for the system, there can be many alternatives, modifications, and variations. For example, some of the components may be expanded and/or combined. Other components may be inserted to those noted above. Depending upon the embodiment, the arrangement of components may be interchanged with others replaced.
  • In various embodiments, the processing unit 304 is configured for executing instructions, such as instructions to implement the method 100 of FIG. 1 . In some embodiments, the executable instructions are stored in the memory unit 306. In certain embodiments, the processing unit 304 includes one or more processing units (e.g., in a multi-core configuration). In some embodiments, the processing unit 304 includes and/or is communicatively coupled to one or more modules for implementing the methods and systems described in the present disclosure. In certain embodiments, the processing unit 304 is configured to execute instructions within one or more operating systems. In some embodiments, upon initiation of a computer-implemented method, one or more instructions is executed during initialization. In certain embodiments, one or more operations is executed to perform one or more processes described herein. In some embodiments, an operation may be general or specific to a particular programming language (e.g., C, C++, Java, or other suitable programming languages, etc.).
  • In various embodiments, the memory unit 306 includes a device allowing information, such as executable instructions and/or other data to be stored and retrieved. In some embodiments, the memory unit 306 includes one or more computer readable media. In certain embodiments, the memory unit 306 includes computer readable instructions for providing a user interface, such as to the user 316, via the output unit 310. In some embodiments, a user interface includes a web browser and/or a client application. For example, a web browser enables the user 316 to interact with media and/or other information embedded on a web page and/or a website. In certain embodiments, the memory unit 306 includes computer readable instructions for receiving and processing an input via the input unit 308. In some embodiments, the memory unit 306 includes RAM such as dynamic RAM (DRAM) or static RAM (SRAM), ROM, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and/or non-volatile RAM (NVRAM).
  • In various embodiments, the input unit 308 is configured to receive input (e.g., from the user 316). In some embodiments, the input unit 308 includes a keyboard, a pointing device, a mouse, a stylus, a touch sensitive panel (e.g., a touch pad or touch screen), a gyroscope, an accelerometer, a position sensor (e.g., GPS sensor), and/or an audio input device. In certain embodiments, the input unit 308 is configured to function as both an input unit and an output unit.
  • In various embodiments, the output unit 310 includes a media output unit configured to present information to the user 316. In some embodiments, the output unit 310 includes any component capable of conveying information to the user 316. In certain embodiments, the output unit 310 includes an output adapter such as a video adapter and/or an audio adapter. For example, the output unit 310 is operatively coupled to the processing unit 304 and/or a visual display device to present information to the user 316 (e.g., a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, a cathode ray tube (CRT) display, a projected display, etc.). As an example, the output unit 310 is operatively coupled to the processing unit 304 and/or an audio display device to present information to the user 316 (e.g., a speaker arrangement or headphones).
  • In various embodiments, the communication unit 312 is configured to be communicatively coupled to a remote device. In some embodiments, the communication unit 312 includes a wired network adapter, a wireless network adapter, a wireless data transceiver for use with a mobile phone network (e.g., 3G, 4G, 5G, Bluetooth, etc.), and/or other mobile data networks. In certain embodiments, other types of short-range or long-range networks may be used. In some embodiments, the communication unit 312 is configured to provide email integration for communicating data between a server and one or more clients.
  • In various embodiments, the storage unit 314 is configured to enable communication between the computing device 300 and the storage device 318. In some embodiments, the storage unit 314 is a storage interface. For example, the storage interface is any component capable of providing the processing unit 304 with access to the storage device 318. In certain embodiments, the storage unit 314 includes an advanced technology attachment (ATA) adapter, a serial ATA (SATA) adapter, a small computer system interface (SCSI) adapter, a RAID controller, a SAN adapter, a network adapter, and/or any other component capable of providing the processing unit 304 with access to the storage device 318.
  • In various embodiments, the storage device 318 includes any computer-operated hardware suitable for storing and/or retrieving data. In certain embodiments, the storage device 318 is integrated in the computing device 300. In some embodiments, the storage device 318 includes a database such as a local database or a cloud database. In certain embodiments, the storage device 318 includes one or more hard disk drives. In some embodiments, the storage device 318 is external and is configured to be accessed by a plurality of server systems. In certain embodiments, the storage device 318 includes multiple storage units such as hard disks or solid state disks in a redundant array of inexpensive disks configuration. In some embodiments, the storage device 318 includes a storage area network and/or a network attached storage system.
  • IV. Examples of Certain Embodiments of the Present Disclosure
  • According to certain embodiments, a method for providing carbon offset sources includes determining an amount of total carbon emission of a user and receiving a desired percentage of carbon offset for the amount of total carbon emission of the user. Also, the method includes determining a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset. Additionally, the method includes providing multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources. For each of the multiple carbon offset sources, the method includes receiving a respective number of carbon offset units corresponding to the predetermined carbon offset source and determining a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources. Moreover, the method includes providing a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units. For example, the method is implemented according to at least FIG. 1 .
  • According to some embodiments, a computing device for providing carbon offset sources includes one or more processors and a memory that stores instructions for execution by the one or more processors. The instructions, when executed, cause the one or more processors to determine an amount of total carbon emission of a user and receive a desired percentage of carbon offset for the amount of total carbon emission of the user. Also, the instructions, when executed, cause the one or more processors to determine a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset. Additionally, the instructions, when executed, cause the one or more processors to provide multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources. For each of the multiple carbon offset sources, the instructions, when executed, cause the one or more processors to receive a respective number of carbon offset units corresponding to the predetermined carbon offset source and determine a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources. Moreover, the instructions, when executed, cause the one or more processors to provide a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units. For example, the computing device is implemented according to at least FIG. 2 and/or FIG. 3 .
  • According to certain embodiments, a non-transitory computer-readable medium stores instructions for providing carbon offset sources. The instructions are executed by one or more processors of a computing device. The non-transitory computer-readable medium includes instructions to determine an amount of total carbon emission of a user and receive a desired percentage of carbon offset for the amount of total carbon emission of the user. Also, the non-transitory computer-readable medium includes instructions to determine a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset. Additionally, the non-transitory computer-readable medium includes instructions to provide multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources. For each of the multiple carbon offset sources, the non-transitory computer-readable medium includes instructions to receive a respective number of carbon offset units corresponding to the predetermined carbon offset source and determine a respective cost based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources. Moreover, the non-transitory computer-readable medium includes instructions to provide a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources, where a total of the respective number of carbon offset units is equal to the total number of carbon offset units. For example, the non-transitory computer-readable medium is implemented according to at least FIG. 1 . FIG. 2 , and/or FIG. 3 .
  • V. Examples of Machine Learning According to Certain Embodiments
  • According to some embodiments, a processor or a processing element may be trained using supervised machine learning and/or unsupervised machine learning, and the machine learning may employ an artificial neural network, which, for example, may be a convolutional neural network, a recurrent neural network, a deep learning neural network, a reinforcement learning module or program, or a combined learning module or program that learns in two or more fields or areas of interest. Machine learning may involve identifying and recognizing patterns in existing data in order to facilitate making predictions for subsequent data. Models may be created based upon example inputs in order to make valid and reliable predictions for novel inputs.
  • According to certain embodiments, machine learning programs may be trained by inputting sample data sets or certain data into the programs, such as images, object statistics and information, historical estimates, and/or actual repair costs. The machine learning programs may utilize deep learning algorithms that may be primarily focused on pattern recognition and may be trained after processing multiple examples. The machine learning programs may include Bayesian Program Learning (BPL), voice recognition and synthesis, image or object recognition, optical character recognition, and/or natural language processing. The machine learning programs may also include natural language processing, semantic analysis, automatic reasoning, and/or other types of machine learning.
  • According to some embodiments, supervised machine learning techniques and/or unsupervised machine learning techniques may be used. In supervised machine learning, a processing element may be provided with example inputs and their associated outputs and may seek to discover a general rule that maps inputs to outputs, so that when subsequent novel inputs are provided the processing element may, based upon the discovered rule, accurately predict the correct output. In unsupervised machine learning, the processing element may need to find its own structure in unlabeled example inputs.
  • VI. Additional Considerations According to Certain Embodiments
  • For example, some or all components of various embodiments of the present disclosure each are, individually and/or in combination with at least another component, implemented using one or more software components, one or more hardware components, and/or one or more combinations of software and hardware components. As an example, some or all components of various embodiments of the present disclosure each are, individually and/or in combination with at least another component, implemented in one or more circuits, such as one or more analog circuits and/or one or more digital circuits. For example, while the embodiments described above refer to particular features, the scope of the present disclosure also includes embodiments having different combinations of features and embodiments that do not include all of the described features. As an example, various embodiments and/or examples of the present disclosure can be combined.
  • Additionally, the methods and systems described herein may be implemented on many different types of processing devices by program code comprising program instructions that are executable by the device processing subsystem. The software program instructions may include source code, object code, machine code, or any other stored data that is operable to cause a processing system to perform the methods and operations described herein. Certain implementations may also be used, however, such as firmware or even appropriately designed hardware configured to perform the methods and systems described herein.
  • The systems' and methods' data (e.g., associations, mappings, data input, data output, intermediate data results, final data results) may be stored and implemented in one or more different types of computer-implemented data stores, such as different types of storage devices and programming constructs (e.g., RAM, ROM, EEPROM, Flash memory, flat files, databases, programming data structures, programming variables, IF-THEN (or similar type) statement constructs, application programming interface). It is noted that data structures describe formats for use in organizing and storing data in databases, programs, memory, or other computer-readable media for use by a computer program.
  • The systems and methods may be provided on many different types of computer-readable media including computer storage mechanisms (e.g., CD-ROM, diskette, RAM, flash memory, computer's hard drive, DVD) that contain instructions (e.g., software) for use in execution by a processor to perform the methods' operations and implement the systems described herein. The computer components, software modules, functions, data stores and data structures described herein may be connected directly or indirectly to each other in order to allow the flow of data needed for their operations. It is also noted that a module or processor includes a unit of code that performs a software operation, and can be implemented for example as a subroutine unit of code, or as a software function unit of code, or as an object (as in an object-oriented paradigm), or as an applet, or in a computer script language, or as another type of computer code. The software components and/or functionality may be located on a single computer or distributed across multiple computers depending upon the situation at hand.
  • The computing system can include client devices and servers. A client device and server are generally remote from each other and typically interact through a communication network. The relationship of client device and server arises by virtue of computer programs running on the respective computers and having a client device-server relationship to each other.
  • This specification contains many specifics for particular embodiments. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations, one or more features from a combination can in some cases be removed from the combination, and a combination may, for example, be directed to a subcombination or variation of a subcombination.
  • Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.
  • Although specific embodiments of the present disclosure have been described, it will be understood by those of skill in the art that there are other embodiments that are equivalent to the described embodiments. Accordingly, it is to be understood that the present disclosure is not to be limited by the specific illustrated embodiments.

Claims (20)

What is claimed is:
1. A method for providing carbon offset sources, the method comprising:
determining, by a computing device, an amount of total carbon emission of a user;
receiving, by the computing device, a desired percentage of carbon offset for the amount of total carbon emission of the user;
determining, by the computing device, a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset;
providing, by the computing device, multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources;
receiving, by the computing device, for each of the multiple carbon offset sources, a respective number of carbon offset units corresponding to the predetermined carbon offset source;
determining, by the computing device, a respective cost for each of the multiple carbon offset sources based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources; and
providing, by the computing device, a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources;
wherein a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
2. The method of claim 1, wherein the determining, by the computing device, the amount of total carbon emission of the user includes:
analyzing driving data associated with one or more vehicle trips made by the user; and
determining the amount of total carbon emission of the user based at least in part upon the driving data.
3. The method of claim 1, wherein the receiving, by the computing device, the desired percentage of carbon offset for the amount of total carbon emission of the user includes receiving the desired percentage of carbon offset from the user.
4. The method of claim 1, wherein:
the predetermined carbon offset source corresponds to planting of one or more trees;
each carbon offset unit corresponds to planting at least a first tree at a first time and a second tree at a second time;
the first tree corresponds to a lifespan;
the first time precedes the second time by a time duration; and
the time duration is shorter than or equal to the lifespan.
5. The method of claim 4, wherein the one or more additional carbon offset sources include at least one carbon offset source selected from a group consisting of hydropower plant, solar panel, wind farm, geothermal plant, and biogas from landfill.
6. The method of claim 1, wherein the receiving, by the computing device, for each of the multiple carbon offset sources, the respective number of carbon offset units corresponding to the predetermined carbon offset source includes receiving the respective number of carbon offset units corresponding to the predetermined carbon offset source for each of the multiple carbon offset sources from the user.
7. The method of claim 1, wherein the one or more characteristics of each of the multiple carbon offset sources include a carbon removal efficiency associated with each of the multiple carbon offset sources and an implementation cost associated with each of the multiple carbon offset sources.
8. A computing device for providing carbon offset sources, the 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:
determine an amount of total carbon emission of a user;
receive a desired percentage of carbon offset for the amount of total carbon emission of the user;
determine a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset;
provide multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources;
receive, for each of the multiple carbon offset sources, a respective number of carbon offset units corresponding to the predetermined carbon offset source;
determine a respective cost for each of the multiple carbon offset sources based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources; and
provide a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources;
wherein a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
9. The computing device of claim 8, wherein the instructions that cause the one or more processors to determine the amount of total carbon emission of the user further comprise instructions that cause the one or more processors to:
analyze driving data associated with one or more vehicle trips made by the user; and
determine the amount of total carbon emission of the user based at least in part upon the driving data.
10. The computing device of claim 8, wherein the instructions that cause the one or more processors to receive the desired percentage of carbon offset for the amount of total carbon emission of the user further comprise instructions that cause the one or more processors to receive the desired percentage of carbon offset from the user.
11. The computing device of claim 8, wherein:
the predetermined carbon offset source corresponds to planting of one or more trees;
each carbon offset unit corresponds to planting at least a first tree at a first time and a second tree at a second time;
the first tree corresponds to a lifespan;
the first time precedes the second time by a time duration; and
the time duration is shorter than or equal to the lifespan.
12. The computing device of claim 11, wherein the one or more additional carbon offset sources include at least one carbon offset source selected from a group consisting of hydropower plant, solar panel, wind farm, geothermal plant, and biogas from landfill.
13. The computing device of claim 8, wherein the instructions that cause the one or more processors to receive, for each of the multiple carbon offset sources, the respective number of carbon offset units corresponding to the predetermined carbon offset source further comprise instructions that cause the one or more processors to receive the respective number of carbon offset units corresponding to the predetermined carbon offset source for each of the multiple carbon offset sources from the user.
14. The computing device of claim 8, wherein the one or more characteristics of each of the multiple carbon offset sources include a carbon removal efficiency associated with each of the multiple carbon offset sources and an implementation cost associated with each of the multiple carbon offset sources.
15. A non-transitory computer-readable medium storing instructions for providing carbon offset sources, the instructions when executed by one or more processors of a computing device, cause the computing device to:
determine an amount of total carbon emission of a user;
receive a desired percentage of carbon offset for the amount of total carbon emission of the user;
determine a total number of carbon offset units corresponding to a predetermined carbon offset source based at least in part upon the desired percentage of carbon offset;
provide multiple carbon offset sources including the predetermined carbon offset source and one or more additional carbon offset sources;
receive, for each of the multiple carbon offset sources, a respective number of carbon offset units corresponding to the predetermined carbon offset source;
determine a respective cost for each of the multiple carbon offset sources based at least in part upon the respective number of carbon offset units and one or more characteristics of each of the multiple carbon offset sources; and
provide a total amount of cost based at least in part upon the respective cost for each of the multiple carbon offset sources;
wherein a total of the respective number of carbon offset units is equal to the total number of carbon offset units.
16. 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 receive the desired percentage of carbon offset further cause the computing device to:
analyze driving data associated with one or more vehicle trips made by the user; and
determine the amount of total carbon emission of the user based at least in part upon the driving data.
17. 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 receive the desired percentage of carbon offset for the amount of total carbon emission of the user further cause the computing device to receive the desired percentage of carbon offset from the user.
18. The non-transitory computer-readable medium of claim 15, wherein:
the predetermined carbon offset source corresponds to planting of one or more trees;
each carbon offset unit corresponds to planting at least a first tree at a first time and a second tree at a second time;
the first tree corresponds to a lifespan;
the first time precedes the second time by a time duration; and
the time duration is shorter than or equal to the lifespan.
19. The non-transitory computer-readable medium of claim 18, wherein the one or more additional carbon offset sources include at least one carbon offset source selected from a group consisting of hydropower plant, solar panel, wind farm, geothermal plant, and biogas from landfill.
20. The non-transitory computer-readable medium of claim 15, wherein the one or more characteristics of each of the multiple carbon offset sources include a carbon removal efficiency associated with each of the multiple carbon offset sources and an implementation cost associated with each of the multiple carbon offset sources.
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WO2021195056A1 (en) 2021-09-30
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US20230020291A1 (en) 2023-01-19
WO2021195007A1 (en) 2021-09-30
US12373849B2 (en) 2025-07-29
US20230016696A1 (en) 2023-01-19
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US20230013701A1 (en) 2023-01-19
US20230016022A1 (en) 2023-01-19
EP4128108A1 (en) 2023-02-08
WO2021195019A1 (en) 2021-09-30
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US20230131645A1 (en) 2023-04-27

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