Distributed Database with Smart Contracts for Trusted Machine Data
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Solution Overview
Problem
The challenge lies in effectively utilizing data from manufacturing processes, especially in trustless environments, to optimize machine operation and maintenance, while ensuring data integrity and security, particularly in industries like additive manufacturing and stream engines.
Innovation Solution
A distributed database system, incorporating a smart contract, is used to collect, store, and analyze data from various sources, ensuring data integrity through encryption and blockchain technology, allowing secure data exchange and automated actions based on predefined conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is collected and stored from multiple data sources in a centralized database, then data utilization and analysis capabilities are improved, but data security and integrity protection deteriorate due to potential manipulation and unauthorized access
Solution Approach 1:
The patent segments the centralized database into multiple distributed nodes across a peer-to-peer network. Each node stores copies of the data, eliminating the single point of failure and manipulation risk inherent in centralized systems. This segmentation ensures that no single entity can compromise the entire data integrity while maintaining reliable access through multiple pathways.
Solution Approach 2:
The patent introduces cryptographic hash functions and consensus mechanisms as intermediaries between data sources and the distributed database. These intermediaries verify data integrity through hashing and ensure reliable consensus on data validity before acceptance, protecting against manipulation while enabling trustworthy data utilization across the network.
2Productivity
If manual data selection and amendment are performed before transmission to the database, then data quality and relevance are improved, but processing time and operational complexity increase
Solution Approach 1:
The patent enables data sources to autonomously transmit their data to the distributed database without requiring manual selection or amendment. The system self-regulates data quality through cryptographic verification and consensus mechanisms, eliminating time-consuming manual preparation while maintaining high data standards through automated validation processes.
Solution Approach 2:
The patent performs preliminary cryptographic hashing and validation of data at the source before transmission. This preliminary action ensures data integrity is established upfront, eliminating the need for time-consuming manual verification and amendment processes later, thereby improving overall processing efficiency.
3Ease of operation
If access to customer systems is required to provide improved service, then service quality and customization are improved, but system complexity and security risks increase
Solution Approach 1:
The patent introduces the distributed database as an intermediary layer between service providers and customer systems. Instead of direct access to customer systems, service providers query the distributed database which contains verified manufacturing and operational data. This intermediary approach maintains high service quality through data-driven insights while avoiding the complexity and security risks of direct system integration.
Solution Approach 2:
The patent creates copies of customer data in the distributed database through cryptographic verification rather than requiring access to the original customer systems. Service providers work with these verified copies, maintaining service quality through accurate data representation while eliminating the need for complex integrations with customer systems.
4Ease of operation
If traditional centralized databases are used for data storage, then ease of access and management are improved, but vulnerability to manipulation and security breaches increases
Solution Approach 1:
The patent segments the centralized database into multiple distributed nodes, each maintaining copies of the data. This segmentation preserves ease of access through multiple entry points while fundamentally improving protection against manipulation, as compromising any single node does not affect the overall data integrity verified through cryptographic hashing and consensus mechanisms.
Solution Approach 2:
The patent implements feedback mechanisms where each node continuously verifies data integrity through cryptographic hashing and reports to the network. This feedback loop maintains ease of access through standardized query interfaces while providing real-time detection and prevention of manipulation attempts, enhancing reliability without complicating access procedures.
Data Source
AI summary
The invention refers to a distributed database and a kit containing such distributed database and a data source. Furthermore, the invention refers to a method of monitoring a machine. Furthermore, it refers to the use of a distributed database to improve the utilization of a component of a machine.