Twin Inference Data Reconstruction for Low-Bandwidth Collection
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Solution Overview
Problem
Existing data collection systems face challenges in managing data transmission, leading to increased communication bandwidth consumption and energy usage, particularly in distributed environments where data collectors transmit large volumes of data to data aggregators.
Innovation Solution
Implementing a system with data collectors and aggregators using twin inference models to predict data, allowing collectors to transmit only differences rather than full data, reconstructed using local inferences and hosted models, thereby reducing data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all measurement data is transmitted from data collectors to data aggregators, then data accuracy and completeness are improved, but communication bandwidth consumption and energy usage increase
Solution Approach 1:
The patent extracts only the essential information needed for decision-making by computing differences between measurements and inferences at the data collector side, transmitting only these compact difference values rather than complete measurement datasets, thereby reducing energy consumption while preserving necessary information
Solution Approach 2:
The patent creates and transmits copies of twin inference models to data collectors, enabling them to generate local inferences and compute differences without needing to transmit or process complete measurement datasets at the aggregator side, reducing communication bandwidth and energy usage
2Loss of information
If all measurement data is transmitted from data collectors to data aggregators, then data accuracy is improved, but communication bandwidth consumption increases
Solution Approach 1:
The patent extracts only the essential information needed for decision-making by computing differences between measurements and inferences, transmitting only these compact difference values rather than complete measurement datasets, thereby reducing data transmission volume while preserving necessary information accuracy
Solution Approach 2:
The patent transforms the data representation from raw measurement values to difference values (measurement - inference), which typically have smaller magnitudes and can be encoded more efficiently, reducing the quantity of data that needs to be transmitted while maintaining accuracy
3Quantity of substance
If twin inference models are deployed at both data aggregators and collectors, then data transmission is reduced, but device complexity increases
Solution Approach 1:
The patent segments the data processing function by deploying simplified twin inference models at data collectors and a corresponding model at the data aggregator, allowing each component to perform localized inference and difference computation rather than requiring one component to handle all processing complexity
Solution Approach 2:
The patent creates and transmits copies of twin inference models to data collectors, enabling them to generate local inferences and compute differences without needing to transmit or process complete measurement datasets at the aggregator side, reducing communication bandwidth and energy usage
4Loss of energy
If only difference values are transmitted instead of complete measurement data, then energy consumption is reduced, but data accessibility for reconstruction purposes is worsened
Solution Approach 1:
The patent implements a feedback mechanism where the data aggregator uses the transmitted difference values along with its own twin inference model to reconstruct measurement data, ensuring that data accessibility is maintained for decision-making purposes while energy consumption is reduced through selective transmission
Data Source
AI summary
Methods and systems for managing data collection are disclosed. To manage data collection, a system may include a data aggregator and a data collector. The data aggregator and data collector may utilize identical copies of a twin inference model to predict the future operation of the data collector. To minimize data transmission, the data collector may transmit a difference to the data aggregator. The data aggregator may reconstruct data from the data collectors using the difference from the data collector, and an inference generated by the copy of the twin inference model hosted by the data aggregator.