Real-Time Signal Segmentation for Low-Bandwidth Data Compression
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Solution Overview
Problem
Existing data compression techniques in industries like hydrocarbons often require buffering large amounts of data before compression and transmission, which is inefficient, especially when dealing with real-time and detailed sensor data, and are limited by bandwidth constraints.
Innovation Solution
The method involves segmenting sensor data into minimal parameter sets using techniques that recompute the best segmentation with each new data sample, allowing for efficient transmission and storage of real-time and historical data, with the ability to update segmentations and reconstruct the original signal with minimal data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If data is buffered in large amounts before compression and transmission, then compression efficiency is improved, but real-time processing capability deteriorates
Solution Approach 1:
The patent segments the data compression process into two distinct modes: real-time compression for immediate transmission and batch compression for historical data. This segmentation allows the system to handle real-time data without buffering delays while still achieving efficient compression for non-time-critical data, thus resolving the contradiction between real-time processing and compression efficiency.
2Quantity of substance
If entire dataset is compressed as a block, then compression ratio is improved, but processing speed and adaptability to new data deteriorates
Solution Approach 1:
The patent implements a dynamic compression strategy where the system adapts its processing mode based on data characteristics and requirements. For real-time data streams, it applies continuous compression with immediate transmission capability, while for historical datasets, it switches to block compression for higher ratios. This dynamic approach allows the system to optimize between compression ratio and processing speed based on specific needs.
3Measurement precision
If more sensors provide more detailed information, then data quality and information content are improved, but bandwidth requirements and storage needs worsen
Solution Approach 1:
The patent extracts and transmits only the most relevant and changed data elements rather than transmitting entire datasets. The system identifies significant changes in sensor readings and transmits only those changes along with necessary contextual information, thereby maintaining high measurement precision while significantly reducing bandwidth consumption and storage requirements.
Data Source
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AI summary
Systems, methods, and devices are provided for compressing a variety of signals, such as measured signals from a hydrocarbon operation, that may be stored and/or transmitted in compressed form. Segmentation tools and techniques are used to compress the signals. Segmentation techniques include breaking a signal into segments and representing the data samples of the signal as segment boundary points, which may reflect where changes occur in the signal, and segment parameters, which may be utilized to model the segmented data. Embodiments can be used in real-time or in batch modes. New data samples can influence previous segment boundary points and/or segment parameters in some cases. Systems may modify what has already been stored or displayed as a result in revising segmentation information based on analysis utilizing the new data samples. Embodiments may utilize different Bayesian analysis techniques including the use of prior probability distributions and maximum a posteriori analyses.