Control Tower Data Encoding for Distributed Product Networks
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Solution Overview
Problem
The proliferation of data from IoT sensors and other sources in value chain networks overwhelms traditional centralized data collection methods, leading to complexity and inefficiencies in data management and decision-making.
Innovation Solution
A method for processing queries in a distributed database using edge devices, which store queries on a dynamic ledger, generate approximate responses based on summary data, and transmit these responses, leveraging technologies like blockchain and neural networks for efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If centralized data collection methods are used to manage value chain network data, then data can be aggregated in one location for processing, but the system becomes overwhelmed by the proliferation of data from IoT sensors and other sources, leading to complexity and inefficiencies
Solution Approach 1:
The patent segments the centralized data collection system into a distributed network of edge devices deployed across the value chain. Each edge device independently processes and manages data locally, dividing the overwhelming data handling task into smaller, manageable units distributed throughout the network, thereby reducing central system overload and improving processing efficiency
Solution Approach 2:
The patent transitions from a single-dimensional centralized collection model to a multi-dimensional distributed architecture where data is collected, processed, and managed across multiple spatial and organizational dimensions. Edge devices are positioned at various points in the value chain (manufacturing, logistics, retail), creating a three-dimensional data management structure that reduces complexity by distributing the burden across different layers of the network
2Loss of information
If all data from IoT sensors and other sources is collected and transmitted to centralized systems, then complete data sets are available for analysis, but the volume and proliferation of data overwhelm traditional data collection methods, leading to inefficiencies in data management and decision-making
Solution Approach 1:
The patent extracts the data processing function from the centralized system and places it at the edge devices throughout the value chain. By taking out the computation and analysis capabilities from the central location and distributing them to edge devices, the system maintains complete data availability locally while dramatically improving data management efficiency and reducing the overhead of transmitting and managing all data centrally
Solution Approach 2:
The patent implements preliminary data processing and filtering at the edge devices before data is transmitted or stored. Edge devices perform initial analysis, aggregate data, and prepare insights in advance, so that when data moves through the network, it is already processed to a useful state. This preliminary action reduces the burden on centralized systems and improves overall data management efficiency while preserving complete information
Data Source
AI summary
A digital product network system includes a set of digital products each having a product processor, a product memory, and a product network interface. The digital product network system includes a product network control tower having a control tower processor, a control tower memory, and a control tower network interface. The product processor and the control tower processor collectively include non-transitory instructions that program the digital product network system to generate product level data at the product processor, transmit the product level data from the product network interface, receive the product level data at the control tower network interface, encode the product level data as a product level data structure configured to convey parameters indicated by the product level data across the set of digital products, and write the product level data structure to at least one of the product memory and the control tower memory.