Wall Diagnostic AI Training Data With Position-Specific Labeling

The patent introduces a position determination system as an intermediary component that bridges the sensor unit and the training dataset generation process. This system determines the position of the measuring device relative to the wall and associates this position information with the sensor data, enabling precise location-specific labeling without requiring direct integration between all system components. The intermediary handles the complex task of position tracking and data association separately, simplifying the overall system architecture while maintaining high precision.

The patent applies preliminary action by determining the position of the measuring device and associating position information with sensor data before the labeling process. By pre-processing the sensor data with position information, the system prepares the data in advance, making the subsequent labeling with ground truth information more efficient. This preliminary organization of data reduces the time required during the actual training dataset generation, as the data is already structured and ready for labeling without requiring additional processing steps.

The patent segments the data processing task by separating position determination from sensor data acquisition and labeling. The position determination system operates independently to generate position information, which is then associated with corresponding sensor data. This segmentation allows each component to be optimized separately - the position determination can use simplified methods while the sensor data processing focuses on detection and classification. The association step creates a structured link without requiring complex real-time processing, reducing overall computational requirements while maintaining high position detection accuracy.