Multi-Sensor Classification Conflict Resolution via Plane Node Mediation
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Solution Overview
Problem
In distributed networks with multiple sensors, misclassifications of data occur due to factors like low-quality sensors, poor lighting, and model drift, leading to conflicts in classification results across nodes, which can result in resource wastage and decreased system efficiency.
Innovation Solution
The system identifies conflicts in classification data across nodes, designates a verified node to determine accurate classifications, and performs mitigation actions such as adjusting sensor settings, retraining models, or powering down inaccurate nodes to improve accuracy and conserve resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors are deployed across distributed nodes to increase system coverage and redundancy, then system reliability and availability are improved, but classification conflicts and misclassifications increase due to varying sensor quality and environmental factors
Solution Approach 1:
The patent introduces a plane node as an intermediary that receives classification results from multiple sensor nodes, resolves conflicts between conflicting classifications, and determines the accurate classification. This mediator coordinates the distributed sensors, allowing the system to maintain high reliability through multiple sensors while achieving accurate classifications by centralizing the resolution process at the plane node level.
2Speed
If all nodes continuously process and transmit sensor data for classification, then system responsiveness and detection capability are improved, but resource consumption and system efficiency deteriorate due to processing inaccurate or conflicting data
Solution Approach 1:
The patent segments the data processing function by designating specific plane nodes to handle classification resolution rather than having all sensor nodes perform full processing. Sensor nodes transmit data to plane nodes, which then resolve conflicts and determine accurate classifications. This segmentation allows responsive data collection across all nodes while concentrating computational resources at plane nodes, reducing overall system resource consumption.
Solution Approach 2:
The patent implements partial action by having sensor nodes perform only data collection and transmission rather than full classification processing. The plane nodes perform the classification resolution function. This partial action at sensor nodes reduces their resource consumption while maintaining system responsiveness through distributed data gathering.
3Area of stationary object
If low-quality sensors or sensors in poor environmental conditions are used to expand system coverage, then area coverage and system versatility are improved, but measurement precision and classification reliability deteriorate
Solution Approach 1:
The patent merges classification results from multiple sensors including low-quality ones at the plane node level. By combining data from multiple sensors and resolving conflicts centrally, the system can utilize low-cost sensors to expand coverage while maintaining overall classification accuracy through the collective input of multiple sensors rather than relying on individual sensor quality.
Data Source
AI summary
Methods, apparatus, systems, and articles of manufacture to facilitate collaborative learning in a multi-sensor environment are disclosed. An example computer readable medium comprises instructions at least one programmable circuit to after determining that first data from a first device conflicts with second data from a second device: validate the first device based on third data from a validated device; and mitigate the second device based on the third data.