Compressed IoT Data Interfaces for Faster AI Expansion
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Solution Overview
Problem
Current storage systems that use lossy compression for IoT data cannot access the compressor body or configuration information externally, hindering the use of high-speed expansion AI and increasing expansion time during analysis.
Innovation Solution
A data processing system with a compression/expansion unit that includes a compressor and expander, featuring a first interface for outputting compressor configuration information and a second interface for outputting compressed data, allowing for the generation and use of high-speed expansion AI without expanding the data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If lossy compression is used to reduce data volume for IoT data accumulation, then storage cost is reduced, but analysis speed with AI decreases due to required expansion processing
Solution Approach 1:
The patent extracts the compressor body and configuration information from the opaque storage system interface, making them accessible externally. This allows high-speed expansion AI to be trained on the specific compression algorithm used, enabling direct analysis of compressed data without full expansion, thus resolving the contradiction between compression and analysis speed
Solution Approach 2:
The patent introduces high-speed expansion AI as an intermediary component that sits between the compressed data storage and the analysis process. This AI model, trained with the compressor body, can rapidly process compressed data or selectively expand only portions needed for analysis, maintaining both compression benefits and analysis speed
2Ease of operation
If storage system performs compression and expansion transparently internally, then ease of operation is improved, but access to compressor body and configuration information is lost
Solution Approach 1:
The patent makes the compressor body and configuration information serve dual purposes: continuing to enable transparent compression/expansion operations while also providing external access for AI training and analysis. This multi-functionality resolves the contradiction by allowing the same components to serve both opacity for ease of use and accessibility for AI integration
3Loss of time
If compressed data is used directly for AI analysis, then expansion time is reduced, but compatibility with existing AI models is lost
Solution Approach 1:
The patent changes the input parameters of the AI analysis system by providing the compressor body and configuration information that describe the compressed data format. This allows the AI model to adapt to working directly with compressed data parameters rather than requiring expansion to standard formats, resolving the contradiction between time savings and compatibility
Data Source
AI summary
Provided is a data processing system comprising a compression/expansion unit configured by including a compressor which compresses data, and an expander which expands the data compressed by the compressor, wherein the compression/expansion unit comprises a first interface unit capable of outputting configuration information of the compressor, and a second interface unit capable of outputting the data compressed by the compressor.