Sensor Data Reconciliation via Source-Based Reliability Filtering
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Solution Overview
Problem
In environments monitored by multiple sensors with varying and overlapping sensing fields, existing technologies face challenges in handling and reconciling large volumes of sensor data with differing reliability, leading to conflicts and inefficiencies in data management.
Innovation Solution
A computer-implemented method for storing and reconciling sensor data from multiple sensors, where each data set includes a source identifier and a sensor identifier, allowing for the storage of data in a database and the deletion of entries based on sensor reliability criteria, ensuring only high-reliability data is retained, thereby managing data volume and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If sensor data from multiple sensors with overlapping visions is stored in the database, then the quantity of sensor data is increased, but data conflicts and reliability issues arise
Solution Approach 1:
The patent changes the parameter of data retention by introducing a temporal dimension - data is retained based on how long it has been since the last observation of the same source. This time-based parameter transformation allows the system to handle multiple sensor inputs by automatically prioritizing recent data, thus resolving conflicts between sensors with varying reliability without losing valuable observational data
Solution Approach 2:
The patent implements dynamic data management where the retention of sensor data is not static but changes over time. The system dynamically evaluates incoming sensor data against previously stored data from the same source, automatically updating or deleting entries based on recency. This dynamic approach allows the system to adapt to changing sensor reliability and environmental conditions, resolving the contradiction between maintaining large quantities of data and ensuring data reliability
2Loss of information
If all sensor data from multiple sensors is retained in the database, then data completeness is improved, but storage volume increases and management complexity rises
Solution Approach 1:
The patent applies the principle of discarding redundant sensor data while recovering essential information. When a source is observed by multiple sensors, the system discards older or less reliable observations and recovers only the most current and reliable data. This selective discarding and recovering mechanism maintains data completeness for critical information while significantly reducing storage volume by eliminating redundant duplicate observations
Solution Approach 2:
The patent implements partial retention of sensor data rather than retaining all data equally. By selectively keeping only the most recent or reliable observations for each source, the system performs a partial action that suffices for maintaining data completeness while avoiding the excessive storage burden of retaining all sensor inputs indefinitely. This partial retention strategy optimizes the balance between data completeness and storage efficiency
3Adaptability or versatility
If sensor data with different detection parameters is stored, then measurement coverage is improved, but data reconciliation difficulty increases
Solution Approach 1:
The patent segments sensor data management by source identifier, creating separate tracking for each observed source. This segmentation allows the system to handle diverse sensor inputs with different detection parameters by organizing data into discrete source-based units. Each source's data history is independently managed, making reconciliation simpler despite the variety of sensor types and parameters, thus maintaining measurement coverage while reducing overall system complexity
Data Source
AI summary
A computer-implemented method for storing and reconciling in a database sensor data from a plurality of sensors, the method comprising: repetitively receiving data sets for the plurality of sensors, each data set comprising sensor data detected by at least one of the plurality of sensors from a source during a sensing event, wherein a source identifier identifies the source, a sensor identifier identifies the at least one of the plurality of sensors, and wherein the sensor identifiers of at least two of the received data sets are different from each other, while both data sets comprise the same source identifier.