Blockchain Environmental Data Integrity via Intermediary Segmentation
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Solution Overview
Problem
Current systems lack a reliable and secure method to track and verify environmental data, particularly carbon emissions, which is crucial for making long-term financial and business decisions, due to the unsecured and mutable nature of existing data formats.
Innovation Solution
A data collection and processing system that aggregates environmental, financial, and non-financial data using blockchain technology to store it in a secure and verifiable manner, employing machine learning and risk modeling techniques to enrich and analyze the data, enabling secure reporting and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If environmental data is collected using conventional systems, then data collection is possible, but the data cannot be secured in an immutable format and is susceptible to unwanted changes and manipulations
Solution Approach 1:
The patent introduces a blockchain as an intermediary layer between data collection points and users. The blockchain serves as a trusted intermediary that records environmental data in an immutable manner, mediating between the complexity of data collection systems and the need for data integrity. This intermediary structure allows conventional data collection methods to produce reliable, tamper-proof records without requiring complete system redesign.
Solution Approach 2:
The patent implements multiple copies of environmental data across the blockchain network. Instead of storing data in a single centralized location that could be manipulated, the system creates and distributes copies of the data across multiple nodes. This copying mechanism ensures data integrity while maintaining the ability to access and verify the same data through the network, effectively resolving the contradiction between reliability and complexity.
2Reliability
If environmental data is not secured in an immutable format, then data collection and processing is simpler, but the data becomes difficult to rely on for long term plans and decisions
Solution Approach 1:
The patent implements feedback mechanisms that allow users to verify the immutability and trustworthiness of environmental data stored on the blockchain. The system provides feedback to users about the integrity status of the data, enabling them to confidently use the data for long-term planning while maintaining ease of access. The feedback loop ensures that data remains both reliable and operationally convenient.
Solution Approach 2:
The patent changes the fundamental parameter of data storage from mutable to immutable formats. By transforming how environmental data is stored and structured on the blockchain, the system achieves data trustworthiness without significantly impacting ease of operation. The parameter change enables long-term reliability while maintaining accessibility through standardized blockchain interfaces and query mechanisms.
3Reliability
If conventional data formats are used for environmental information, then data collection is straightforward, but the data cannot be securely stored for verification in financial environments
Solution Approach 1:
The patent segments the environmental data storage function from the broader financial verification system. By using blockchain as a dedicated segmentation layer, the system stores environmental data in a specialized, verifiable format that can be reliably accessed by financial systems without complicating the entire financial infrastructure. This segmentation allows straightforward data collection while ensuring secure, verifiable storage.
Data Source
AI summary
A system and method for monitoring and assessing the carbon footprint of an enterprise. The system aggregates data, such as for example environmental data, enriches the data and then stores the data along with additional information in a blockchain. The additional information stored in the blockchain can include third party data, the types of risk models and machine learning techniques employed by the system, emissions data, attribute data, and the like.