AI-Based Development on Laser Based QR Code Marking on Track Fitting on Indian Railways

Abstract

The Indian Railways, one of the world’s largest transportation networks, relies on millions of track fittings and related components to ensure safe and uninterrupted rail operations. Effective identification and traceability of these components have become increasingly critical as the network expands and maintenance demands grow. Currently, track fittings are marked using conventional practices such as paint-based labels, stamping, or manual tagging. These methods are often prone to fading, corrosion, mislabeling, and tampering over time. Such inconsistencies lead to difficulties in asset tracking, inaccurate maintenance records, and inefficient replacement planning. To overcome these limitations, this project proposes the development of an integrated AI-driven laser‐based QR code marking system for railway track fittings. In this solution, precision laser engraving technology is used to mark durable and permanent QR codes on metallic fittings. These QR codes store essential information such as unique component identification numbers, manufacturing data, installation timelines, inspection logs, and maintenance histories. Laser-based marking ensures high resistance to environmental conditions including heat, moisture, and abrasion. The system leverages artificial intelligence for automated QR code recognition and classification through mobile scanning devices and automated inspection tools. AI algorithms enable fast and accurate data retrieval, integrity verification, and predictive analytics to identify wear patterns or potential structural failures. This digital ecosystem enables more efficient planning of maintenance activities, reduces manual labor, and minimizes the risk of human error. By establishing secure traceability and real-time monitoring of track components, the proposed system is expected to significantly enhance operational reliability, maintenance efficiency, and overall safety in the Indian Railways infrastructure. It also promotes data-driven decision-making, reduces cost overheads, and supports future expansion through seamless integration with asset management platforms. Therefore, this AI-based laser QR code marking framework represents a transformative step toward smart and sustainable railway maintenance systems in India.