EP-4736103-A1 - ARTIFICIAL NEURAL NETWORK-ASSISTED CARBON REMOVAL AND SEQUESTRATION ONBOARDING AND CERTIFICATION SYSTEM AND METHOD

Abstract

Membership services are provided to each of a plurality of users of a plurality of user computing devices, including via software that configures the plurality of user computing devices to operate within the membership services. An encrypted data pay load including information representing at least one of carbon removal and/or carbon sequestering is received by a configured user computing device, and the information is validated. As a function of machine learning and artificial intelligence, at least one of carbon removal and/or carbon sequestering associated with validated information is determined. A respective mandate is accessed and, as a function of the validated information and the respective mandate, a determination is made whether the respective user is compliant with the respective mandate. At least one operating feature of the configured user computing device is disabled or enabled, as a function of the user's compliance.

Inventors

• CHICHILNISKY, GRACIELA

Assignees

• Chichilnisky, Graciela

Dates

Publication Date

20260506

Application Date

20240621

Claims (19)

1. 1. A system, comprising: at least one data processing apparatus operatively coupled to one or more non-transitory processor readable media, wherein the non-transitory processor readable media have instructions for configuring the at least one data processing apparatus to perform the following steps: provide membership services, to each of a plurality of users of a plurality of user computing devices; provide, to each of the plurality of user computing devices, software having instructions that, when executed, configure the plurality of user computing devices to operate within the membership services; receive, from a configured user computing device of a respective user, an encrypted data payload including information representing at least one of carbon removal and/or carbon sequestering; validate, the information received in the encrypted data pay load; determine, as a function of machine learning and artificial intelligence, at least one of carbon removal and/or carbon sequestering associated with validated information in the encrypted data payload; access a respective mandate associated with the configured user computing device associated with at least one of carbon removal and carbon sequestering; determine, as a function of the validated information and the respective mandate, whether the respective user is compliant with the respective mandate; where the respective user is not compliant with the respective mandate: automatically disabling at least one operating feature of the configured user computing device; where the respective user is compliant with the respective mandate; automatically maintain the at least one operating feature of the configured computing device.
2. 2. The system of claim 1 , wherein the encrypted data pay load includes information representing the respective user’ s production and/or consumption of green goods, wherein the green goods include goods whose production decreases legacy carbon, and further wherein determining whether the respective user is compliant with the respective mandate is further in accordance with the information representing the respective user’s production and/or consumption of the green goods.
3. 3. The system of claim 2, wherein the encrypted data payload includes information representing the respective user’s production and/or consumption of non-green goods, wherein the non-green goods include goods whose production does not decrease legacy carbon, and further wherein determining whether the respective user is compliant with the respective mandate is further in accordance with the information representing the respective user’s production and/or consumption of the non-green goods.
4. 4. The system of claim 3, wherein the non-transitory processor readable media have instructions for configuring the at least one data processing apparatus to determine whether the respective user is compliant with the respective mandate by determining a net carbon effect.
5. 5. The system of claim 1 , wherein the encrypted data payload includes information representing at least one of: desalination; bottling; CO fuels; microalgae; concrete building materials; soil carbon sequestration; biochcar; and enhanced oil recovery.
6. 6. The system of claim 1, wherein the at least one data processing apparatus includes an artificial neural network, wherein the at least one artificial neural network includes at least one of a convolutional neural network, a recurrent neural network, and an auto encoder neural network.
7. 7. The system of claim 6, wherein the at least one artificial neural network operates to assign respective weights to at least some of the information in the encoded data payload, wherein the weights impact the determination of whether the respective user is in compliance with the respective mandate.
8. 8. The system of claim 1, wherein the non-transitory processor readable media have instructions for configuring the at least one data processing apparatus to validate at least some of the information received in the encrypted data pay load by: identifying the source of a key required to decrypt the at least some of the information in the encrypted data payload; receive, from the source, the key; decrypt the at least some of the information using the key; and validate the decrypted at least some of the information.
9. 9. The system of claim 1 , wherein the mandate is automatically generated by the at least one data processing apparatus as a function of onboarding the configured user computing device.
10. 10. A method, comprising: providing, by at least one data processing apparatus operatively coupled to one or more non-transitory processor readable media that configure the at least one data processing apparatus, membership services, to each of a plurality of users of a plurality of user computing devices; providing, by the at least one data processing apparatus to each of the plurality of user computing devices, software having instructions that, when executed, configure the plurality of user computing devices to operate within the membership services; receiving, by the at least one data processing apparatus from a configured user computing device of a respective user, an encrypted data payload including information representing at least one of carbon removal and/or carbon sequestering; validating, by the at least one data processing apparatus, the information received in the encrypted data payload; determining, by the at least one data processing apparatus as a function of machine learning and artificial intelligence, at least one of carbon removal and/or carbon sequestering associated with validated information in the encrypted data payload; accessing, by the at least one data processing apparatus, a respective mandate associated with the configured user computing device associated with at least one of carbon removal and carbon sequestering; determining, by the at least one data processing apparatus as a function of the validated information and the respective mandate, whether the respective user is compliant with the respective mandate; where the respective user is not compliant with the respective mandate: automatically, disabling by the at least one data processing apparatus, at least one operating feature of the configured user computing device; where the respective user is compliant with the respective mandate; automatically maintaining, by the at least one data processing apparatus, the at least one operating feature of the configured computing device.
11. 11. The method of claim 10, wherein the encrypted data payload includes information representing the respective user’s production and/or consumption of green goods, wherein the green goods include goods whose production decreases legacy carbon, and further wherein determining whether the respective user is compliant with the respective mandate is further in accordance with the information representing the respective user’s production and/or consumption of the green goods.
12. 12. The method of claim 11, wherein the encrypted data payload includes information representing the respective user’s production and/or consumption of non-green goods, wherein the non-green goods include goods whose production does not decrease legacy carbon, and further wherein determining whether the respective user is compliant with the respective mandate is further in accordance with the information representing the respective user’s production and/or consumption of the non-green goods.
13. 13. The method of claim 12, further comprising: determining, by the at least one data processing apparatus, whether the respective user is compliant with the respective mandate by determining a net carbon effect.
14. 14. The method of claim 10, wherein the encrypted data payload includes information representing at least one of: desalination; bottling; CO2 fuels; microalgae; concrete building materials; soil carbon sequestration; biochcar; and enhanced oil recovery.
15. 15. The method of claim 10, wherein the at least one data processing apparatus includes an artificial neural network, wherein the at least one artificial neural network includes at least one of a convolutional neural network, a recurrent neural network, and an auto encoder neural network.
16. 16. The method of claim 15, wherein the at least one artificial neural network operates to assign respective weights to at least some of the information in the encoded data payload, wherein the weights impact the determination of whether the respective user is in compliance with the respective mandate.
17. 17. The method of claim 10, wherein validating at least some of the information received in the encrypted data pay load includes: identifying, by the at least one data processing apparatus, the source of a key required to decrypt the at least some of the information in the encrypted data payload; receiving by the at least one data processing apparatus from the source, the key; decrypting, by the at least one data processing apparatus, the at least some of the information using the key; and validating, by the at least one data processing apparatus, the decrypted at least some of the information.
18. 18. The method of claim 10, further comprising: generating, by the at least one data processing apparatus, the mandate as a function of onboarding the configured user computing device.
19. 19. A method, comprising: receiving from at least one computing device, by at least one processor operatively coupled to one or more non-transitory processor readable media having instructions for configuring the at least one processor, information representing allocated amounts of atmospheric carbon to be removed and stored respectively by each of a plurality of parties; receiving, by the at least one computing device from at least one computing device, information representing amounts of atmospheric carbon physically removed and stored respectively by each of a plurality of parties; processing, by the at least one computing device, the information representing the allocated amounts of atmospheric carbon and the information representing amounts of atmospheric carbon physically removed to determine, for each of the respective parties a net carbon effect; determining, by the at least one computing device for each of the respective parties, an amount of capital that is owed by or is due to be received by each of the respective parties, as a function of each respective party’s net carbon effect; receiving, by the at least one computing device from each respective party that owes capital, a respective amount of capital respectively owed; and disbursing, by the at least one computing device to each respective party that is due to receive capital, a respective amount of capital respectively to be received.

Description

ARTIFICIAL NEURAL NETWORK-ASSISTED CARBON REMOVAL AND SEQUESTRATION ONBOARDING AND CERTIFICATION SYSTEM AND METHOD Field [0001] The present disclosure relates, generally, to legacy carbon management and, more particularly, to a system and method providing membership services including interactive, computer-management of prevention, removal and storage of carbon emissions and legacy carbon from the earth’s atmosphere. Background [0002] Parties have entered into agreements regarding amounts of carbon dioxide (“CO2”) emissions produced annually, per party. A division of the total amount of CO2 allowed per each of a number (N) participating parties is defined via such agreements. For example, each participating party is allotted a respective measurable amount of CO2 it is allocated to produce, with parties that historically produce larger amounts of CO2 having limits on their emissions that are larger than parties that historically emit less or no CO2. [0003] In operation of such agreements that are associated with limiting CO2 emissions, parties commit to payment of capital to one or more other parties in the event, in any given year, a party exceeds its maximum allotted CO2 emissions. In one or more arrangements, such parties commit to payment to other parties whose emissions contributions are lower than respectively allowed amounts. In this way, a combined level of CO2 emissions of two or more parties can remain the same, year after year, while parties that emit less carbon into the atmosphere are compensated by those that emit more. Effectively, therefore, a price of CO2 in a carbon market is established as a function of the agreements, which can provide effective incentive to reduce CO2 emissions. While such known agreements can be effective to reduce carbon emissions occurring over time, the amount of carbon presently existing in the atmosphere at a given point time, referred to herein generally as “legacy carbon” or “legacy CO2” is not impacted. Unfortunately, CO2 degrades slowly and distributes uniformly in the earth’s atmosphere. Accordingly, while agreements covering current CO2 emissions can be effective to reduce the amount of carbon emitted into the earth’ s atmosphere, the amount of legacy carbon in the atmosphere still increases. [0004] In addition to urgent environmental concerns regarding CO2, the current water crisis shines a stark spotlight on 2 billion people in the world with limited or no access to drinkable water. Climate change, including as a function of carbon buildup and shortages of water, is an existential risk, which can define the geological scope of human civilization and the future of oxygen-driven forms of life on planet Earth. As in the past, the poorer nations of the world bear consequences, because drinking water can be produced for those who can pay to desalinate the ocean’s water. [0005] It is with respect to these and other considerations that the disclosure made herein is presented. Brief Summary [0006] Accordingly, the present disclosure includes systems and methods that include at least one data processing apparatus operatively coupled to one or more non-transitory processor readable media. In one or more example implementations of the present disclosure, the non-transitory processor readable media have instructions for configuring the at least one data processing apparatus to perform one or more steps, including providing membership services to each of a plurality of users of a plurality of user computing devices. Further, the at least one data processing apparatus can be configured to provide, to each of the plurality of user computing devices, software having instructions that, when executed, configure the plurality of user computing devices to operate within the membership services. The at least one data processing apparatus can be further configured to receive, from a configured user computing device of a respective user, an encrypted data payload including information representing at least one of carbon removal and/or carbon sequestering. Further, the at least one data processing apparatus can be configured to validate, the information received in the encrypted data payload. Moreover, Further, the at least one data processing apparatus can be configured to determine, as a function of machine learning and artificial intelligence, at least one of carbon removal and/or carbon sequestering associated with validated information in the encrypted data payload. Further, the at least one data processing apparatus can be configured to access a respective mandate associated with the configured user computing device associated with at least one of carbon removal and carbon sequestering. Still further, the at least one data processing apparatus can be configured to determine, as a function of the validated information and the respective mandate, whether the respective user is compliant with the respective mandate. Where the respective user is not compliant with the respec