Description:
FORM 2
The Patent Act 1970
(39 of 1970)
&
The Patent Rules, 2005

COMPLETE SPECIFICATION
(SEE SECTION 10 AND RULE 13)

TITLE OF THE INVENTION

“METHOD AND CARBON TRANSACTION PLATFORM FOR SUGGESTING CARBON TRANSACTION VALUE FOR PRODUCT AND SERVICE”

APPLICANT:

Name : Revoluza Technologies Pvt Ltd

Nationality : Indian

Address : A 101, TINSELTOWN BY Kohinoor, Hinjewadi Phase 2, Pune, Maharashtra, India, 411057

The following specification particularly describes and ascertains the nature of this invention and the manner in which it is to be performed:-

FIELD OF INVENTION
[0001] The present invention relates to a carbon pricing system and method, and more specifically related to a method and a carbon transaction platform for suggesting a carbon transaction value for a product and a service.
BACKGROUND
[0002] Carbon pricing ("social cost of carbon") is a valuable instrument in a policy toolkit to promote clean energy transitions. The normalization of the carbon pricing around world is impossible. Hence, world organization could not create a common carbon pricing platform yet. Since the carbon pricing will be impacting all scale industry, there is huge gap in tracking the carbon emission right from internal Life Cycle Assessments (LCAs) to emission trading systems.
[0003] It is desired to address the above-mentioned disadvantages or other short comings or at least provide a useful alternative.
OBJECT OF INVENTION
[0004] The principal object of the embodiments herein is to a method and a carbon transaction platform for suggesting a carbon transaction value for a product and a service.
[0005] Another objective of the embodiments herein is to obtain a plurality of data comprising a product Life Cycle Assessment (LCA) data, an unit emission data, a transaction data and a supply chain data for the product and the service at a predefined interval.
[0006] Another objective of the embodiments herein is to aggregate the plurality of data comprising the product LCA data, the unit emission data, the transaction data and the supply chain data for the product and the service to generate a score value.
[0007] Another objective of the embodiments herein is to label the generated score value associated with the product and the service.
[0008] Another objective of the embodiments herein is to suggest the carbon transaction value for the product and the service based on the labelled score value using a parameter.
[0009] Another objective of the embodiments herein is to perform an end-to-end emission tracking associated with the product and the service based on the suggested carbon transaction value.
[0010] Another objective of the embodiments herein is to perform taxation policy monitoring associated with the product and the service based on the suggested carbon transaction value.
[0011] Another objective of the embodiments herein is to optimize the carbon transaction value over a period of time using a data driven model.
[0012] Another objective of the embodiments herein is to provide a suggested weight and bias correction for emissions and pricing data internal and government directed.
[0013] Another objective of the embodiments herein is to provide a schema validation and taxonomy alignment based on industry and reporting standards.
SUMMARY
[0014] In one aspect, the objects are achieved by providing a method for suggesting a carbon transaction value for a product and a service. The method includes obtaining, by a carbon transaction platform, a plurality of data comprising a product Life Cycle Assessment (LCA) data, an unit emission data, a transaction data and a supply chain data for the product and the service at a predefined interval. Further, the method includes aggregating, by the carbon transaction platform, the plurality of data comprising the product LCA data, the unit emission data, a transaction data and the supply chain data for the product and the service to generate a score value. Further, the method includes labelling, by the carbon transaction platform, the generated score value associated with the product and the service. Further, the method includes suggesting, by the carbon transaction platform, the carbon transaction value for the product and the service based on the labelled score value using at least one parameter.
[0015] In an embodiment, the method includes performing an end-to-end emission tracking associated with the product and the service based on the suggested carbon transaction value.
[0016] In another embodiment, the method includes performing taxation policy monitoring associated with the product and the service based on the suggested carbon transaction value. In another embodiment, the method includes optimizing the carbon transaction value over a period of time using a data driven model.
[0017] In an embodiment the at least one parameter includes at least one of an industry taxonomy parameter, an internally benchmarking transaction parameter, a local compliance parameter and a regulation parameter.
[0018] In yet another aspect the objects are achieved by providing a carbon transaction platform for suggesting a carbon transaction value for a product and a service. The carbon transaction platform includes a carbon transaction platform controller coupled with a microcontroller and a memory. The carbon transaction platform controller is configured to obtain a plurality of data comprising a product LCA data, an unit emission data, a transaction data and a supply chain data for the product and the service at a predefined interval. Further, the carbon transaction platform controller is configured to aggregate the plurality of data comprising the product LCA data, the unit emission data, the transaction data and the supply chain data for the product and the service to generate a score value. Further, the carbon transaction platform controller is configured to label the generated score value associated with the product and the service. Further, the carbon transaction platform controller is configured to suggest the carbon transaction value for the product and the service based on the labelled score value using at least one parameter.
[0019] These and other aspects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions, while indicating preferred embodiments and numerous specific details thereof, are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the embodiments, and the embodiments herein include all such modifications.
BRIEF DESCRIPTION OF FIGURES
[0020] The embodiments disclosed herein are illustrated in the accompanying drawings, throughout which like reference letters indicate corresponding parts in the various figures. The embodiments herein will be better understood from the following description with reference to the drawings, in which:
[0021] FIG. 1 is an example scenario in which operations of a carbon transaction platform is explained, in accordance with the present disclosed embodiments.
[0022] FIG. 2 illustrates a block diagram of the carbon transaction platform, according to the embodiments as disclosed herein.
[0023] FIG. 3 is a flow chart illustrating a method for suggesting a carbon transaction value for a product and a service, according to the embodiment as disclosed herein.
[0024] FIG. 4 is an example scenario in which inferring a carbon price is explained, according to the embodiment as disclosed herein.
[0025] FIG. 5 is an example scenario in which the LCA data in a manufacturing environment is explained, according to the embodiment as disclosed herein.
[0026] FIG. 6 is an example scenario in which inferring the carbon price using the optimization function is explained, according to the embodiment as disclosed herein.
[0027] It may be noted that to the extent possible, like reference numerals have been used to represent like elements in the drawing. Further, those of ordinary skill in the art will appreciate that elements in the drawing are illustrated for simplicity and may not have been necessarily drawn to scale. For example, the dimension of some of the elements in the drawing may be exaggerated relative to other elements to help to improve the understanding of aspects of the invention. Furthermore, the one or more elements may have been represented in the drawing by conventional symbols, and the drawings may show only those specific details that are pertinent to the understanding the embodiments of the invention so as not to obscure the drawing with details that will be readily apparent to those of ordinary skill in the art having benefit of the description herein.
DETAILED DESCRIPTION OF INVENTION
[0028] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. Also, the various embodiments described herein are not necessarily mutually exclusive, as some embodiments can be combined with one or more other embodiments to form new embodiments. The term “or” as used herein, refers to a non-exclusive or, unless otherwise indicated. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein can be practiced and to further enable those skilled in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
[0029] As is traditional in the field, embodiments may be described and illustrated in terms of blocks which carry out a described function or functions. These blocks, which may be referred to herein as managers, units, modules, hardware components or the like, are physically implemented by analog and/or digital circuits such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hardwired circuits and the like, and may optionally be driven by a firmware. The circuits may, for example, be embodied in one or more semiconductor chips, or on substrate supports such as printed circuit boards and the like. The circuits constituting a block may be implemented by dedicated hardware, or by a processor (e.g., one or more programmed microprocessors and associated circuitry), or by a combination of dedicated hardware to perform some functions of the block and a processor to perform other functions of the block. Each block of the embodiments may be physically separated into two or more interacting and discrete blocks without departing from the scope of the disclosure. Likewise, the blocks of the embodiments may be physically combined into more complex blocks without departing from the scope of the disclosure.
[0030] The accompanying drawings are used to help easily understand various technical features and it should be understood that the embodiments presented herein are not limited by the accompanying drawings. As such, the present disclosure should be construed to extend to any alterations, equivalents and substitutes in addition to those which are particularly set out in the accompanying drawings. Although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are generally only used to distinguish one element from another.
[0031] In one aspect, the objects are achieved by providing a method for suggesting a carbon transaction value for a product and a service. The method includes obtaining, by a carbon transaction platform, a plurality of data comprising a product LCA data, an unit emission data, a transaction data and a supply chain data for the product and the service at a predefined interval. Further, the method includes aggregating, by the carbon transaction platform, the plurality of data comprising the product LCA data, the unit emission data, a transaction data and the supply chain data for the product and the service to generate a score value. Further, the method includes labelling, by the carbon transaction platform, the generated score value associated with the product and the service. Further, the method includes suggesting, by the carbon transaction platform, the carbon transaction value for the product and the service based on the labelled score value using at least one parameter.
[0032] The method can be used to recommend and suggest the carbon price determination for the product or the service using lifecycle data of the product or the service based on a machine learning (e.g., deep learning or the like). The method provides a single end to end product lifecycle carbon data traceability on the platform to accommodate changing legal and regulatory dimensions. The proposed method provides a suggested weight and bias correction for emissions and pricing data internal and government directed product and service. The proposed method facilities the schema validation and taxonomy alignment based on industry and reporting standards.
[0033] The method can be used to capture the emission and auditable process to cover whole life cycle of the product and the service covering multiple industries/sectors leading to fair carbon pricing specific to each industry type over Distributed Ledger Technology (DLT).
[0034] The method assists the carbon credits trading alone and attempts to address the gap between ETSs and pricing, with changing legal and statutory changes which is predicted. The proposed method can be used to provide carbon pricing platform for the end-to-end emission tracking, the LCA and the trade with complete control and immutability of data with no role of depositories and custodians, where entire supply chain including competition can trust the platform for data share.
[0035] FIG. 1 is an example scenario in which operations of a carbon transaction platform (100) is explained, in accordance with the present disclosed embodiments. The carbon transaction platform (100) obtains a plurality of data. The plurality of data includes a product Life Cycle Assessment (LCA) data, an unit emission data (e.g., emission to price conversion or the like), a transaction data (e.g., offsets data, trading data or the like), a supply chain data, and information related to the market participants, internal CO2 price, emissions monitoring, emissions allowances allocation, reporting and verification, and regulations and compliances. The information of the regulations and compliances includes enforcement, trading compliance, cap setting, and government price for CO2 for a product and a service at a predefined interval. The predefined interval is set by the user or the carbon transaction platform (100). The product can be, for example, but not limited to, a grocery item, a textile product, a food product, a medicine related product or the like. The service can be, for example, but not limited to, a communication service, a manufacturing service, a finance related service or the like. The plurality of data including the product LCA data, the unit emission data, the transaction data and the supply chain data is obtained using a blockchain based data collection technique. The plurality of data is added with timestamp data.
[0036] Further, the carbon transaction platform (100) aggregates the plurality of data including the product LCA data, the unit emission data, the transaction data and the supply chain data for the product and the service to generate the score value. Further, the carbon transaction platform (100) labels the generated score value associated with the product and the service. Further, the carbon transaction platform (100) suggests the carbon transaction value for the product and the service based on the labelled score value using a parameter. The parameter includes an industry taxonomy parameter, an internally benchmarking transaction parameter, a local compliance parameter and a regulation parameter.
[0037] In an embodiment, the carbon transaction platform (100) performs an end-to-end emission tracking associated with the product and the service based on the suggested carbon transaction value. In another embodiment, the carbon transaction platform (100) performs taxation policy monitoring associated with the product and the service based on the suggested carbon transaction value. In another embodiment, the carbon transaction platform (100) optimizes the carbon transaction value over a period of time using a data driven model.
[0038] FIG. 2 illustrates a block diagram of the carbon transaction platform (100), according to the embodiments as disclosed herein. The carbon transaction platform (100) includes a microcontroller (110), a communicator (120), a memory (130), a carbon transaction platform controller (140) and a data driven controller (150). The microcontroller (110) is coupled with the communicator (120), the memory (130), the carbon transaction platform controller (140) and the data driven controller (150).
[0039] The carbon transaction platform controller (140) obtains the plurality of data. The plurality of data includes the product LCA data, the unit emission data, the transaction data, the supply chain data, and the information related to the market participants, the internal CO2 price, the emissions monitoring, the emissions allowances allocation, the reporting and verification, and the regulations and compliances.
[0040] Further, the carbon transaction platform controller (140) aggregates the plurality of data including the product LCA data, the unit emission data, the transaction data and the supply chain data for the product and the service to generate the score value. Further, the carbon transaction platform controller (140) labels the generated score value associated with the product and the service. Further, the carbon transaction platform controller (140) suggests the carbon transaction value for the product and the service based on the labelled score value using the parameter.
[0041] In an embodiment, the carbon transaction platform controller (140) performs an end-to-end emission tracking associated with the product and the service based on the suggested carbon transaction value. In another embodiment, the carbon transaction platform controller (140) performs taxation policy monitoring associated with the product and the service based on the suggested carbon transaction value. In another embodiment, the carbon transaction platform controller (140) optimizes the carbon transaction value over a period of time using the data driven model. The data driven model is operated using the data driven controller (150).
[0042] The memory (130) stores instructions to be executed by the microcontroller (110). The memory (130) includes non-volatile storage elements. Examples of such non-volatile storage elements include magnetic hard disc, optical discs, floppy discs, flash memories, or forms of Electrically Programmable Memories (EPROM) or Electrically Erasable and Programmable Memories (EEPROM). In addition, the memory (130) in some examples, be considered a non-transitory storage medium. The term “non-transitory” indicates that the storage medium is not embodied in a carrier wave or a propagated signal. The term “non-transitory” is not be interpreted that the memory (130) is non-movable. In some examples, the memory (130) stores larger amounts of information. In certain examples, a non-transitory storage medium stores data that can, over time, change (e.g., in Random Access Memory (RAM) or cache). The microcontroller (110) includes one or a plurality of processors.
[0043] The one or more microcontroller (110) is a general-purpose processor, such as a central processing unit (CPU), an application processor (AP), or the like, a graphics processing unit such as a graphics processing unit (GPU), a Visual Processing Unit (VPU), and/or an AI dedicated processor such as a neural processing unit (NPU). The microcontroller (110) includes multiple cores and executes the instructions stored in the memory (130).
[0044] The one or more processors or the microcontroller (110) control the processing of the input data in accordance with a predefined operating rule or AI model stored in the non-volatile memory and the volatile memory. The predefined operating rule or artificial intelligence model is provided through training or learning.
[0045] Here, being provided through learning means that, by applying a learning algorithm to a plurality of learning data, a predefined operating rule or AI model of a desired characteristic is made. The learning may be performed in a device itself in which AI according to an embodiment is performed, and/o may be implemented through a separate server/system.
[0046] The AI model may consist of a plurality of neural network layers. Each layer has a plurality of weight values, and performs a layer operation through calculation of a previous layer and an operation of a plurality of weights. Examples of neural networks include, but are not limited to, convolutional neural network (CNN), deep neural network (DNN), recurrent neural network (RNN), restricted Boltzmann Machine (RBM), deep belief network (DBN), bidirectional recurrent deep neural network (BRDNN), generative adversarial networks (GAN), and deep Q-networks.
[0047] The learning algorithm is a method for training a predetermined target device (for example, an edge device) using a plurality of learning data to cause, allow, or control the target device to make a determination or prediction. Examples of learning algorithms include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning.
[0048] In an embodiment, the communicator (120) includes an electronic circuit specific to a standard that enables wired or wireless communication. The communicator (120) communicates internally between internal hardware components of the carbon transaction platform (100) and with external devices via one or more networks.
[0049] Although the FIG. 2 shows various hardware components of the carbon transaction platform (100) but it is to be understood that other embodiments are not limited thereon. In other embodiments, the carbon transaction platform (100) may include less or more number of components. Further, the labels or names of the components are used only for illustrative purpose and does not limit the scope of the invention. One or more components can be combined together to perform same or substantially similar function in the carbon transaction platform (100).
[0050] FIG. 3 is a flow chart (S300) illustrating a method for suggesting the carbon transaction value for the product and the service, according to the embodiment as disclosed herein. The operations (S302-S308) are handled by the carbon transaction platform controller (140). At S302, the method includes obtaining the plurality of data including the product LCA data, the unit emission data, the transaction data and the supply chain data for the product and the service at the predefined interval. At S304, the method includes aggregating the plurality of data including the product LCA data, the unit emission data, the transaction data and the supply chain data for the product and the service to generate the score value. At S306, the method includes labeling the generated score value associated with the product and the service. At S308, the method includes suggesting the carbon transaction value for the product and the service based on the labelled score value using the parameter.
[0051] The method can be used to compute the CO2 pricing that is optimized and can be audited. The method can be used to adheres to the industry dynamics, internal operations and government pricing. The proposed method is scalable to changing taxation policies. The proposed method provides an industry templates for ease of CO2 referential pricing. The proposed method takes product LCA into account and optimization function helps with right inference. The proposed method enables immutability, auditability and traceability via the DLT for data. The proposed method is used for various custom applications
[0052] The method can be used to help in inferring the CO2 price by considering unknown and known data (e.g., LCA, Industry data, Supply Chain etc.,) to suggest the most optimized price of CO2 that can then be used to declare or report.
[0053] The proposed method explains at the process methodology undertaken to arrive the carbon price recommendation. Unlike traditional methods, where carbon price is only a derivative of the international price that has been set, and internal calculations, the proposed method can be used to suggest to consider three sixty view of the data that a product lifecycle assessment and movement generates, which includes cradle to cradle, including its packaging and second use for amortization.
[0054] FIG. 4 is an example scenario (S400) in which inferring the carbon price is explained, according to the embodiment as disclosed herein. The carbon price is determined by using the LCA, the CO2 price, the emission score, the applicable tax, the optimization function, and the trade. The proposed method can be used to emphasize on introduction of the optimization function that considers internal carbon price, the industry price, the biogenic emissions, the upcycle, the re-cycle, the LCA data of the product and its ingredients. By ingredients, the method can be used to ensure that is milk is being used to manufacture yogurt, then only the proportion or percentage of milk that will be used for a batch of yogurt should be used for carbon price of yogurt and milk not the entire milk or the yogurt. Transfer of rest of the milk to say chocolate production should take over the rest of the price and carbon emissions thereby. Based on the proposed method, the optimization function will help determine such costs by considering the entire features and impact factors.
[0055] FIG. 5 is an example scenario (S500) in which the LCA data in a manufacturing environment is explained, according to the embodiment as disclosed herein. The FIG. 5 explains how an industry leader in cloud computing uses various processes to calculate their carbon price and product LCA from cradle to grave.
[0056] FIG. 6 is an example scenario (S600) in which inferring the carbon price using the optimization function is explained, according to the embodiment as disclosed herein. In the FIG. 6, the user has taken a product Yogurt and it's packaging and showcased how product LCA will impact the carbon price which is a view and differentiation the user would like to bring across. The proposed method has not just considered the LCA but also other impacts to the overall carbon price like dynamic price, material input, biogenic emissions and packaging.
[0057] The various actions, acts, blocks, steps, or the like in the flow charts (S300) may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some of the actions, acts, blocks, steps, or the like may be omitted, added, modified, skipped, or the like without departing from the scope of the invention.
[0058] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the scope of the embodiments as described herein.
, Claims:CLAIMS
We claim:
1. A method for suggesting a carbon transaction value for at least one of a product and a service, comprising:
obtaining, by a carbon transaction platform (100), a plurality of data comprising a product Life Cycle Assessment (LCA) data, an unit emission data, a transaction data and a supply chain data for at least one of the product and the service at a predefined interval;
aggregating, by the carbon transaction platform (100), the plurality of data comprising the product LCA data, the unit emission data, the transaction data and the supply chain data for at least one of the product and the service to generate a score value;
labeling, by the carbon transaction platform (100), the generated score value associated with at least one of the product and the service; and
suggesting, by the carbon transaction platform (100), the carbon transaction value for at least one of the product and the service based on the labelled score value using at least one parameter.

2. The method as claimed in claim 1, wherein the method comprises:
performing, by the carbon transaction platform (100), at least one of:
an end-to-end emission tracking associated with at least one of the product and the service based on the suggested carbon transaction value;
taxation policy monitoring associated with at least one of the product and the service based on the suggested carbon transaction value; and
optimizing the carbon transaction value over a period of time using a data driven model.

3. The method as claimed in claim 1, wherein the at least one parameter comprises at least one of an industry taxonomy parameter, an internally benchmarking transaction parameter, a local compliance parameter and a regulation parameter.

4. The method as claimed in claim 1, wherein the plurality of data comprising the product LCA data, the unit emission data, the transaction data and the supply chain data is obtained using a blockchain based data collection technique, and wherein the plurality of data is added with timestamp data.

5. A carbon transaction platform (100) for suggesting a carbon transaction value for at least one of a product and a service, wherein the carbon transaction platform (100) comprises:
a microcontroller (110);
a memory (130); and
a carbon transaction platform controller (140), coupled with the microcontroller (110) and memory (130), configured to:
obtain a plurality of data comprising a product Life Cycle Assessment (LCA) data, an unit emission data, a transaction data and a supply chain data for at least one of the product and the service at a predefined interval,
aggregate the plurality of data comprising the product LCA data, the unit emission data, a transaction data and a supply chain data for at least one of the product and the service to generate a score value,
label the generated score value associated with at least one of the product and the service, and
suggest the carbon transaction value for at least one of the product and the service based on the labelled score value using at least one parameter.

6. The carbon transaction platform (100) as claimed in claim 5, wherein the carbon transaction platform controller (140) is configured to:
perform at least one of:
an end-to-end emission tracking associated with at least one of the product and the service based on the suggested carbon transaction value;
taxation policy monitoring associated with at least one of the product and the service based on the suggested carbon transaction value; and
optimize the carbon transaction value over a period of time using a data driven model.

7. The carbon transaction platform (100) as claimed in claim 5, wherein the at least one parameter comprises at least one of an industry taxonomy parameter, an internally benchmarking transaction parameter, a local compliance parameter and a regulation parameter.

8. The carbon transaction platform (100) as claimed in claim 5, wherein the plurality of data comprising the product LCA data, the unit emission data, the transaction data and the supply chain data is obtained using a blockchain based data collection technique, and wherein the plurality of data is added with timestamp data.