Intellectual Property India Publishes Patent Application for System And Method For Performance Evaluation And Prioritization Of Urban Bus Routes Using Integrated Passenger Perception And Operational Data

MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202621091675 A) filed by Mr. Mayursinh B. Jadeja; Dr. Hemantkumar G. Sonkusare; Dr. Nirav V. Vyas; Dr. Devang M. Sarvaiya; Dr. Mayank M. Parekh; Mr. Hardik P. Pujara; Mr. Ashraf M. Mathkiya; and Mrs. Siddhi D. Parkhiya on July 28, 2026, for System And Method For Performance Evaluation And Prioritization Of Urban Bus Routes Using Integrated Passenger Perception And Operational Data.

Inventors include Mr. Mayursinh B. Jadeja; Dr. Hemantkumar G. Sonkusare; Dr. Nirav V. Vyas; Dr. Devang M. Sarvaiya; Dr. Mayank M. Parekh; Mr. Hardik P. Pujara; Mr. Ashraf M. Mathkiya; and Mrs. Siddhi D. Parkhiya.

The application for the patent was published on September 18, 2026, under issue no. 38/2026.

Abstract: SYSTEM AND METHOD FOR PERFORMANCE EVALUATION AND PRIORITIZATION OF URBAN BUS ROUTES USING INTEGRATED PASSENGER PERCEPTION AND OPERATIONAL DATA The present invention discloses a system and method for performance evaluation and prioritization of urban bus routes using integrated passenger perception and operational data to improve the efficiency, reliability, and sustainability of public transportation networks. The proposed system collects and integrates heterogeneous data from multiple sources, including passenger feedback surveys, mobile applications, GPS-enabled vehicle tracking systems, automated passenger counting devices, ticketing records, travel time logs, route schedules, traffic conditions, and service frequency databases. The collected data undergo preprocessing, normalization, and validation to eliminate inconsistencies and missing values before being analyzed through a multi-criteria evaluation framework. The framework computes comprehensive performance indicators encompassing passenger satisfaction, service reliability, accessibility, punctuality, occupancy levels, operational cost, travel time efficiency, route coverage, and environmental impact. Artificial intelligence and machine learning algorithms identify hidden patterns, forecast route demand, and determine performance trends, while a weighted decision-making model dynamically ranks and prioritizes bus routes based on predefined operational and commuter-centric criteria. The system generates real-time dashboards, route performance scores, optimization recommendations, and predictive maintenance alerts to support transport authorities in strategic planning and resource allocation. Additionally, the invention enables continuous learning through periodic integration of updated operational and passenger feedback data, thereby adapting to changing urban mobility patterns. By combining subjective passenger perceptions with objective operational metrics within a unified analytical framework, the proposed invention facilitates data-driven decision-making, enhances passenger experience, optimizes fleet utilization, reduces service inefficiencies, minimizes operational costs, and supports sustainable urban transportation planning. The invention is applicable to municipal transport corporations, smart city infrastructures, public transit agencies, and metropolitan transportation authorities seeking intelligent, scalable, and automated solutions for bus route performance assessment and prioritization

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