Load Center Mapping App Automates Device Identification

The patent replaces the manual mechanical process of identifying and labeling devices with an automated optical recognition system. The system uses a camera to capture images of the load center, applies image processing algorithms to detect device contours and positions, and uses optical character recognition (OCR) to automatically read and identify device labels, thereby eliminating the need for manual inspection and labeling.

The system enables the load center devices to identify themselves automatically. By capturing an image of the load center and using OCR to read the labels on the devices, the system allows the devices to provide their own identification information without requiring external manual intervention. The image processing system then automatically maps these self-provided identifiers to their respective slot positions.

The patent implements a multi-functional integrated system that combines image capture, image processing, device contour detection, and optical character recognition capabilities within a single identification system. This universal approach allows the system to handle various types of load center devices with different label formats and positions, making the system adaptable and reducing the need for multiple specialized tools or procedures.

The patent introduces an intermediary image processing layer between the physical devices and the identification system. Instead of directly reading device labels, the system captures images of the entire load center, processes these images to detect device positions and contours, and then uses OCR as an intermediary step to extract text information. This intermediary approach simplifies the overall system architecture by decoupling the image capture and text recognition functions.