MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641078903 A) filed by St. Peters Engineering College, Hyderabad, Telangana, India - on June 26, 2026, for Ai-Based Railway Reservation Management System For Reservation Forecasting And Dynamic Seat Allocation.
Inventors include Mrs. K. A. Manjusha; Mrs. S. Sarika; Dr. K Prasanna Kumar; Ms. Sandiri Swetha; Mrs. S. Madhavi; Mr. M Krishna; Mr. Nakka Venkatesh; and Ms. Arelli Shruthi.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The present invention discloses an AI-Based Railway Reservation Management System for Reservation Forecasting and Dynamic Seat Allocation, designed to improve the efficiency, accuracy, and adaptability of railway reservation operations through artificial intelligence and machine learning techniques. The proposed system integrates historical reservation records, real-time booking transactions, passenger travel patterns, train schedules, seasonal demand, cancellation history, coach occupancy data, and external factors such as holidays and weather conditions into a centralized intelligent framework. The collected data are preprocessed through cleaning, normalization, feature engineering, and validation before being analyzed using machine learning algorithms for reservation demand forecasting and cancellation prediction. Based on these predictive insights, a dynamic seat allocation engine optimally assigns available seats by considering passenger preferences, quota policies, seat availability, occupancy levels, and real-time reservation updates. The system continuously reallocates seats in response to cancellations, no-shows, and newly generated reservation requests, thereby minimizing waiting lists and maximizing seat utilization. A cloud-based administrative dashboard provides real-time monitoring, analytics, reporting, and operational decision support for railway authorities. The proposed framework significantly improves reservation accuracy, reduces vacant seats, enhances passenger satisfaction, increases operational efficiency, and maximizes railway revenue while supporting scalable deployment across large railway transportation networks. The invention is applicable to conventional, high-speed, metro, and intercity railway reservation systems requiring intelligent, data-driven seat management and demand forecasting.
Disclaimer: Curated by HT Syndication.
