Data Collection Device Compression for Network Congestion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Data transmission from sensor devices to remotely located data processing platforms often leads to network congestion and resource overload, resulting in processing delays, connectivity issues, and potential data loss due to insufficient storage capacity and network limitations.
Innovation Solution
Implementing a data compression technique in data collection devices that discards readings based on a maximum difference calculation, allowing for reduced data transmission and storage while maintaining minimal information loss, thereby alleviating network congestion and resource burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all sensor readings are transmitted to the data processing platform, then complete data information is preserved, but network congestion and resource overload occur
Solution Approach 1:
The patent extracts and transmits only the maximum and minimum values from sensor readings during offline periods, rather than transmitting all readings. This selective extraction reduces data volume significantly while preserving the most important information needed for accurate representation of the sensor data range.
Solution Approach 2:
The patent changes the parameter representation by storing and transmitting extreme values (max and min) rather than individual reading values. This parameter transformation allows the system to capture the essential data range with fewer data points, reducing network traffic while maintaining information quality.
2Quantity of substance
If data compression is applied by discarding readings, then network traffic and storage requirements are reduced, but information loss increases
Solution Approach 1:
The system extracts only the maximum and minimum values from the sensor readings during offline periods. This extraction approach reduces data transmission volume significantly while preserving the most critical information about the data range and variability, minimizing information loss.
Solution Approach 2:
The patent creates a simplified copy of the sensor data by storing max and min values that represent the entire dataset. This compressed representation serves as an effective surrogate for the full dataset, enabling accurate reconstruction of data characteristics without transmitting all original readings.
3Loss of information
If storage capacity is increased to store all readings, then data completeness is maintained, but device complexity and cost increase
Solution Approach 1:
The patent extracts only the essential information (max and min values) from the sensor readings for storage during offline periods. This extraction strategy maintains data completeness for the most important metrics while dramatically reducing storage capacity requirements and device complexity.
Data Source
AI summary
A data collection device can determine that a connection is unavailable between the data collection device and a data processing platform. The data collection device can obtain, after the connection is unavailable, a plurality of readings. The data collection device can determine, based on determining that the connection is unavailable, to discard one or more readings from the plurality of readings to form a set of readings. The data collection device can store, based on determining that the connection is unavailable, the set of readings without storing the one or more readings. The data collection device can determine, after storing the set of readings, that the connection is available. The data collection device can transmit, based on determining that the connection is available, the set of readings to the data processing platform.