MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202521054196 A) filed by Parul University; Dr. Jaydeep R. Tadhani; Jaydevsinh B. Vala; Dr. Vipul Vekariya; and Dr. Sunil J. Soni, Vadodara, Gujarat, on June 4, 2025, for 'ai-driven system and method for real-time defect detection in aluminium profile quality inspection.'
Inventor(s) include Dr. Jaydeep R. Tadhani; Jaydevsinh B. Vala; Dr. Vipul Vekariya; and Dr. Sunil J. Soni.
The application for the patent was published on Feb. 13, under issue no. 07/2026.
According to the abstract released by the Intellectual Property India: "The invention pertains to an AI-driven system and method for real-time defect detection in aluminum profile quality inspection. It integrates a machine vision system with a high-resolution image acquisition module to automate the inspection process. A YOLO object detection model processes images in a single pass to identify defect regions, while a Convolutional Neural Network (CNN) with ReLU activation functions and max-pooling layers classifies these defects. A threshold mechanism evaluates defect severity against predefined standards, and a cloud-based or edge computing platform stores and analyzes defect data for continuous improvement. An automated decision-making module triggers actions based on defect severity, such as rejecting products or adjusting production parameters. The system is designed for real-time processing, scalability, and flexibility, suitable for various manufacturing environments, and includes features like dynamic threshold adjustment and automated reporting for enhanced quality control."
Disclaimer: Curated by HT Syndication.
