Screen Inspection Robot for Self-Service Terminal Fault Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for checking the state of terminal screens in self-service branches are labor-intensive and time-inefficient, often missing small issues like cracks, and rely on user feedback which can be incomplete and subjective, leading to poor accuracy and time-effectiveness.
Innovation Solution
An automatic screen state detection robot equipped with a processor, memory, and camera that moves into preset areas, sends a graphic code to detect circuit faults, and analyzes images for abnormalities like cracks, lines, and blobs, using techniques such as inverse perspective transformation, noise-filtering enhancement, and Hough Transform for accurate detection without manual participation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual inspection is used to check screen state, then labor cost is reduced, but detection accuracy and time-effectiveness deteriorate
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated robot system equipped with camera and image processing capabilities. The robot autonomously navigates to service devices, captures screen images, and uses computer vision algorithms (including inverse perspective transformation, noise filtering, and Hough transform) to detect abnormalities, thereby improving both efficiency and accuracy simultaneously.
2Reliability
If user feedback is collected to detect screen issues, then user involvement is increased, but detection completeness and objectivity deteriorate
Solution Approach 1:
The system enables self-service detection where the robot autonomously performs screen inspection without requiring user participation. The robot independently navigates, captures images, processes them through multiple algorithms, and generates detection reports, eliminating the time loss and reliability issues associated with collecting user feedback.
3Measurement precision
If comprehensive screen inspection is performed to detect all abnormalities, then detection coverage is improved, but inspection time and complexity increase
Solution Approach 1:
The detection process is segmented into multiple specialized stages: image acquisition, inverse perspective transformation to correct distortion, noise filtering to remove interference, Hough transform for line detection, and blob analysis for spot detection. Each segment focuses on specific abnormality types, achieving comprehensive coverage while managing complexity through modular processing.
Data Source
AI summary
The application discloses an automatic screen state detection robot, comprising a memory having an automatic screen state detection program stored thereon and a processor, and the automatic screen state detection program being executed by the processor to implement the operations of: controlling the robot to move into a preset area of each of service devices in a self-service branch respectively; detecting whether a service device has a circuit fault or not if the robot moves into the preset area of the service device; and controlling the service device to display an image according to preset display parameters if the display screen has no circuit fault, and analyzing the image displayed on the display screen to find whether the display screen of the service device has an abnormality of a preset type. The application also provides an automatic screen state detection method and a computer-readable storage medium.