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
“CROSS SECTOR DATA DECENTRALIZED PLATFORM FOR SECURED DATA SHARE FOR CARBON AND ENERGY ACCOUNTING”

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 data decentralized platform and method, and more specifically related to a cross sector data decentralized platform and method for secured data share for carbon and energy accounting purpose.
BACKGROUND
[0002] There is a growing need for climate action worldwide. However, to better mitigate and plan for carbon and energy consumption, data must be captured for a given product lifecycle footprint. To enable this sustainable practice, organizations need to openly share their data across every step of the process without worrying about data privacy (individuals' or companies' right to keep their data to themselves). This can only happen if a system or platform finds a way to capture, refine, certify, secure, and provide accessibility to such data with complete immutability and trust, motivating entities to share data with confidence. Blockchain, as a technology, has proven very efficient for the immutability of data, however, the implementation of blockchain to serve the purpose of Data DeFi (Decentralized Finance) is the need of the hour. The data assets of firms can not only be shared for use and compliance but also monetized or used as collateral to drive value for the enterprise. Currently, most solutions and research focus on how blockchain can bring transparency, trust, and create ownership of an asset in the digital world. But the existing methods and platforms do not disclose anything about entities or users’ privacy concerns while sharing and monetizing data in the open market and public. Hence, there is a need for methods and platforms that address privacy concerns when sharing and monetizing data.
[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 provide a cross sector data decentralized platform and method for secured data share for carbon and energy accounting purpose.
[0005] Another objective of the embodiments herein is to address privacy concerns when sharing and monetizing data in a carbon and energy accounting purpose.
[0006] Another objective of the embodiments herein is to enable for adding a monetary value to data, being able to share it publicly without worrying about privacy concerns, and finally allowing control to individuals to decide on how to share data, while enabling citizen data scientists (people who would like to use publicly available data and perform various computations to drive valuable insights without being confined to a particular organization or firm ‘s business direction but are motivated for greater good) to access real world data using the proposed method and platform.
[0007] Another objective of the embodiments herein is to provide that a data publisher (e.g., dataset publisher engine) can safely and securely publishes their data in a platform without getting the data tampered or without compromising user privacy and at the same time also be able to monetize their data asset so that consumers can use/view the data assets.
SUMMARY
[0008] In one aspect, the objects are achieved by providing a method for secured data share during a carbon and energy accounting purpose. The method includes pushing, by a data provider controller of a cross sector data decentralized platform, the plurality of data sets through an onboarding application. Further, the method includes performing, by a data transformation engine of the cross sector data decentralized platform, a data pre-processing operation and a modelling operation upon the plurality of data sets is ingested in the cross sector data decentralized platform. The data pre-processing operation and the modelling operation are performed by applying a normalizations operation and a denormalization operation to the plurality of data sets dataset. Further, the method includes providing, by the data transformation engine of the cross sector data decentralized platform, the plurality of data sets into a common ontology after performing the data pre-processing operation and the modelling operation. Further, the method includes receiving, by a trusted layer engine of the cross sector data decentralized platform, the plurality of data sets from the data transformation engine using a blockchain technique. Further, the method includes encrypting and cataloguing, by the trusted layer engine of the cross sector data decentralized platform, the plurality of data sets dataset to provide a necessary data from the plurality of data sets. The necessary data from the plurality of data sets is obtained by an end user through a data consumer engine.
[0009] In yet another aspect the objects are achieved by providing a cross sector data decentralized platform for secured data share during a carbon and energy accounting purpose. The cross sector data decentralized platform includes a data provider controller pushing a plurality of data sets through an onboarding application. Further, the cross sector data decentralized platform includes a data transformation engine performing a data pre-processing operation and a modelling operation upon the plurality of data sets is ingested in the cross sector data decentralized platform. The data pre-processing operation and the modelling operation are performed by applying a normalizations operation and a denormalization operation to the plurality of data sets dataset. The data transformation engine provides the plurality of data sets into a common ontology after performing the data pre-processing operation and the modelling operation. Further, the cross sector data decentralized platform includes a trusted layer engine receiving the plurality of data sets from the data transformation engine using a blockchain technique. Further, the trusted layer engine encrypting and cataloguing the plurality of data sets dataset to provide a necessary data from the plurality of data sets. The necessary data from the plurality of data sets is obtained by an end user through a data consumer engine.
[0010] In an embodiment, the trusted layer engine enables easier search and retrieval through a digital identifier (ID) associated with each one of data set of the plurality of data sets.
[0011] In an embodiment, the plurality of data sets is published onto a blockchain ledger, running on OCEAN protocol, which ensures encryption, easy search, and retrieval due to the digital ID associated with each of the plurality of data sets.
[0012] In an embodiment, the data consumer engine obtains access to the plurality of data sets in a form of downloadable content.
[0013] 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
[0014] 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:
[0015] FIG. 1 illustrates a cross sector data decentralized platform for secured data share during a carbon and energy accounting purpose, according to the embodiments as disclosed herein;
[0016] FIG. 2 illustrates a data asset publisher flow by using a dataset publisher engine, according to the embodiments as disclosed herein;
[0017] FIG. 3 illustrates a data asset consumer flow by using a data consumer engine, according to the embodiments as disclosed herein; and
[0018] FIG. 4 is a flow chart illustrating a method for secured data share during the carbon and energy accounting purpose, in accordance with the present disclosed embodiments.
[0019] 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
[0020] 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.
[0021] 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.
[0022] 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.
[0023] In yet another aspect the objects are achieved by providing a cross sector data decentralized platform for secured data share during a carbon and energy accounting purpose. The cross sector data decentralized platform includes a data provider controller pushing a plurality of data sets through an onboarding application. Further, the cross sector data decentralized platform includes a data transformation engine performing a data pre-processing operation and a modelling operation upon the plurality of data sets is ingested in the cross sector data decentralized platform. The data pre-processing operation and the modelling operation are performed by applying a normalizations operation and a denormalization operation to the plurality of data sets dataset. The data transformation engine provides the plurality of data sets into a common ontology after performing the data pre-processing operation and the modelling operation. Further, the cross sector data decentralized platform includes a trusted layer engine receiving the plurality of data sets from the data transformation engine using a blockchain technique. Further, the trusted layer engine encrypting and cataloguing the plurality of data sets dataset to provide a necessary data from the plurality of data sets. The necessary data from the plurality of data sets is obtained by an end user through a data consumer engine.
[0024] Referring now to the drawings, and more particularly to FIGS. 1 through 4, where similar reference characters denote similar or same elements throughout the figures, there are shown example embodiments.
[0025] FIG. 1 illustrates a cross sector data decentralized platform (1000) for secured data share during a carbon and energy accounting purpose, according to the embodiments as disclosed herein. In an embodiment, the cross sector data decentralized platform (1000) includes a dataset publisher engine (100) and a data consumer engine (200). The dataset publisher engine (100) communicates with the data consumer engine (200).
[0026] In an embodiment, the dataset publisher engine (100) includes a microcontroller (110), a communicator (120), a memory (130), a data driven controller (140), a data provider controller (150), a data transformation engine (160) and a trusted layer engine (170). The microcontroller (110) communicates with the communicator (120), the memory (130), the data driven controller (140), the data provider controller (150), the data transformation engine (160) and the trusted layer engine (170).
[0027] 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, the 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.
[0028] 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). The one or more processors 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.
[0029] 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.
[0030] 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.
[0031] 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.
[0032] 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 dataset publisher engine (100) and the data consumer engine (200) and with external devices via one or more networks.
[0033] The data provider controller (150), through the onboarding application (App)/application programing interface (API), pushes a plurality of data sets. Once the plurality of data sets is ingested, the data transformation engine (160) comes into perform an operation (e.g., data pre-processing operation and modelling operation, or the like). The data pre-processing operation and modelling operation are performed by applying multiple transformations like normalizations and denormalizations to the plurality of data sets dataset and brings the plurality of data sets into a common ontology. The common ontology for one being JSON structure, or XML data structures, or mapping it to a industry data structure like SQL structures. The plurality of data sets is then pushed to the trusted layer engine (170) using a blockchain technique. The trusted layer engine (170) encrypts and catalogues the plurality of data sets dataset which enables easier search and retrieval through the means of unique digital identifier (ID) associated with each one of data set of the plurality of data sets. Any application, carbon computing application for example, can interface with the layer through the APIs and fetch the necessary data from the plurality of data sets.
[0034] In other words, a data asset (e.g., plurality of data sets or the like) uploaded by the dataset publisher engine (100) could be in any one of the available formats like excel, spreadsheet, tabular data etc. The data asset undergoes transformations to bring it into common ontology such that the data asset should be fed into the cross sector data decentralized platform (1000) in a unified format. Further, the data asset is then published onto the blockchain ledger, running on OCEAN protocol, which ensures encryption, easy search, and retrieval due to the unique digital ID associated with each of the data asset. Once the data asset is published, the data consumer engine (200) can get access to the data asset in the form of downloadable content or run its computationally intensive key performance indicators (KPI) calculations on the data itself. All these operations are made possible only by approving each of the flow and operation and by paying gas fees. Through this data assets gets monetized and gives publisher the total autonomy of the data asset and at the same time flexibility of the extent to which they want to grant access to that data asset.
[0035] The dataset publisher engine (100) can safely and securely publish their data in a platform without getting the data tampered or without compromising user privacy and at the same time also be able to monetize their data asset so that consumers can use/view the data assets. Privacy is protected by the design of blockchain and minimal access rights. Blockchain ensures that every action is catalogued and audited with owner and action details. Data publisher can tag a monetary value of choice whether in Bitcoin or CBDC and publish it, and only when the user pays for it can they access the data, also we have an additional protection where published can choose to allow data download or only data view, which means that the data always remains on the platform if the data publisher chooses view only, where the compute needed to perform any AI operations is shared by the computer providers.
[0036] The proposed cross sector data decentralized platform (1000) addresses the much-needed “trust as a platform” while leveraging the flexibility of users to control data access and adding economic value to assets. The proposed cross sector data decentralized platform (1000) can be used to evaluate the frameworks and modelled it for an enterprise use to enable adding a monetary value to data, being able to share it publicly without worrying about privacy concerns, and finally allowing control to individuals to decide on how to share data, while enabling citizen data scientists to access real world data using their custom technique. This helps in achieving trust for data exchanges, and motivation for sharing data when data can be associated with a monetary value, organizations that promote data sharing will outperform their peers on most business value metrics. The proposed cross sector data decentralized platform (1000) provides a feasibility to provision a digital platform that can be leveraged for a Carbon Trading, Accounting.
[0037] In an embodiment, the data provider controller (150) is a sophisticated hardware entity vested with the responsibility of directing and managing the flow of data between two distinct entities. In the realm of computing, this device may take on the form of microchips, cards, or other separate hardware mechanisms, each designed to oversee a gamut of electronic device operations (computing device operations). In essence, the data provider controller (150) serves as an intermediary linking two electronic devices, actively managing and directing communication between said devices.
[0038] In an embodiment, the data transformation engine (160) is a sophisticated hardware entity vested with the responsibility of directing and managing the flow of data between two distinct entities. In the realm of computing, this device may take on the form of microchips, cards, or other separate hardware mechanisms, each designed to oversee a gamut of electronic device operations (computing device operations). In essence, the data transformation engine (160) serves as an intermediary linking two electronic devices, actively managing and directing communication between said devices.
[0039] In an embodiment, the trusted layer engine (170) is a sophisticated hardware entity vested with the responsibility of directing and managing the flow of data between two distinct entities. In the realm of computing, this device may take on the form of microchips, cards, or other separate hardware mechanisms, each designed to oversee a gamut of electronic device operations (computing device operations). In essence, the trusted layer engine (170) serves as an intermediary linking two electronic devices, actively managing and directing communication between said devices.
[0040] FIG. 2 illustrates a data asset publisher flow (S200) by using the dataset publisher engine (100), according to the embodiments as disclosed herein. The dataset publisher engine (100), through the onboarding app/API, pushes the data set. Once the plurality of data set is cleaned and transformed from the data ETL, it is pushed to the trusted layer engine over the blockchain technique. The trusted layer engine encrypts and catalogue the plurality of dataset which enables easier search and retrieval through the means of unique Digital ID associated with each one of them. The carbon accounting application, for example, can interface with the trusted layer engine through APIs and fetch the necessary data from the plurality of dataset. Th necessary data is provided based on the context not from the general keyword using data driven controller.
[0041] FIG. 3 illustrates a data asset consumer flow (S300) by using the data consumer engine (200), according to the embodiments as disclosed herein. The data consumer engine (200), through the onboarding app/API, searches for the relevant dataset. Once found, the data consumer engine (200), would then spend data token to run the KPI on that dataset and the result would be available to the consumer (i.e., end user). This way the dataset is not made available to the consumer but can be used for running computations on it thereby monetizing the dataset and the publisher likewise.
[0042] FIG. 4 is a flow chart (S400) illustrating a method for secured data share during the carbon and energy accounting purpose, in accordance with the present disclosed embodiments. At step S402, the method includes pushing, by the data provider controller (150) of the cross sector data decentralized platform (1000), the plurality of data sets through the onboarding application. At S404, the method includes performing, by the data transformation engine (160) of the cross sector data decentralized platform (1000), the data pre-processing operation and the modelling operation upon the plurality of data sets is ingested in the cross sector data decentralized platform (1000). The data pre-processing operation and the modelling operation are performed by applying the normalizations operation and the denormalization operation to the plurality of data sets dataset. At S406, the method includes providing, by the data transformation engine (160) of the cross sector data decentralized platform (1000), the plurality of data sets into the common ontology after performing the data pre-processing operation and the modelling operation.
[0043] At S408, the method includes receiving, by the trusted layer engine (170) of the cross sector data decentralized platform (1000), the plurality of data sets from the data transformation engine (160) using the blockchain technique. At S410, the method includes encrypting and cataloguing, by the trusted layer engine (170) of the cross sector data decentralized platform (1000), the plurality of data sets dataset to provide a necessary data from the plurality of data sets. The necessary data from the plurality of data sets is obtained by an end user through the data consumer engine (200).
[0044] The various actions, acts, blocks, steps, or the like in the flow charts (S200-S400) 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.
[0045] 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 cross sector data decentralized platform (1000) for secured data share during a carbon and energy accounting purpose, comprising:
a data provider controller (150) pushing a plurality of data sets through an onboarding application;
a data transformation engine (160):
performing a data pre-processing operation and a modelling operation upon the plurality of data sets is ingested in the cross sector data decentralized platform (1000), wherein the data pre-processing operation and the modelling operation are performed by applying a normalizations operation and a denormalization operation to the plurality of data sets dataset, and
providing the plurality of data sets into a common ontology after performing the data pre-processing operation and the modelling operation; and
a trusted layer engine (170):
receiving the plurality of data sets from the data transformation engine (160) using a blockchain technique, and
encrypting and cataloguing the plurality of data sets dataset to provide a necessary data from the plurality of data sets, wherein the necessary data from the plurality of data sets is obtained by an end user through a data consumer engine (200).
2. The cross sector data decentralized platform (1000) as claimed in claim 1, wherein the trusted layer engine (170) enables easier search and retrieval through a digital identifier (ID) associated with each one of data set of the plurality of data sets.
3. The cross sector data decentralized platform (1000) as claimed in claim 1, wherein the plurality of data sets is published onto a blockchain ledger, running on OCEAN protocol, which ensures encryption, easy search, and retrieval due to the digital ID associated with each of the plurality of data sets.
4. The cross sector data decentralized platform (1000) as claimed in claim 1, wherein the data consumer engine (200) obtains access to the plurality of data sets in a form of downloadable content.
5. The cross sector data decentralized platform (1000) as claimed in claim 1, wherein a privacy of the plurality of data sets is protected by a design of blockchain and minimal access rights, wherein the blockchain technique ensures that every action is catalogued and audited with owner and action details.
6. A method for secured data share during a carbon and energy accounting purpose, comprising:
pushing, by a data provider controller (150) of a cross sector data decentralized platform (1000), a plurality of data sets through an onboarding application;
performing, by a data transformation engine (160) of the cross sector data decentralized platform (1000), a data pre-processing operation and a modelling operation upon the plurality of data sets is ingested in the cross sector data decentralized platform (1000), wherein the data pre-processing operation and the modelling operation are performed by applying a normalizations operation and a denormalization operation to the plurality of data sets dataset;
providing, by the data transformation engine (160) of the cross sector data decentralized platform (1000), the plurality of data sets into a common ontology after performing the data pre-processing operation and the modelling operation;
receiving, by a trusted layer engine (170) of the cross sector data decentralized platform (1000), the plurality of data sets from the data transformation engine (160) using a blockchain technique;
encrypting and cataloguing, by the trusted layer engine (170) of the cross sector data decentralized platform (1000), the plurality of data sets dataset to provide a necessary data from the plurality of data sets, wherein the necessary data from the plurality of data sets is obtained by an end user through a data consumer engine (200).
7. The method as claimed in claim 6, wherein the trusted layer engine (170) enables easier search and retrieval through a digital identifier (ID) associated with each one of data set of the plurality of data sets.
8. The method as claimed in claim 6, wherein the plurality of data sets is published onto a blockchain ledger, running on OCEAN protocol, which ensures encryption, easy search, and retrieval due to the digital ID associated with each of the plurality of data sets.
9. The method as claimed in claim 6, wherein the data consumer engine (200) obtains access to the plurality of data sets in a form of downloadable content.
10. The method as claimed in claim 6, wherein a privacy of the plurality of data sets is protected by a design of blockchain and minimal access rights, wherein the blockchain technique ensures that every action is catalogued and audited with owner and action details.