<p>In the realm of smart cities, intelligent transportation systems, a crucial facilitator in this field, depend on precise data and reliable operations to enhance service quality and increase commuter reliance. This study reports beyond typical pattern matching algorithm which is essential to overcome various on sight issues of city public transport operations. Urban bus operates in mixed traffic without adhere to clear map traces: many times stops are logged under many nearby coordinates, buses legitimately halt at neighbour points rather exact locations due to congestion, handling of parent–child routes overlap, and bus crosses station during off peak hours in sampling gap of GPS. Our algorithm is expressly built for these failure modes: it canonicalizes coordinate scatter, admits optional valid waypoints while keeping the route pattern compulsory, blocks parent-route false detection via direction-specific invalid stations, and stabilizes coverage with a station-level threshold to absorb sparse sampling. We provide a detailed explanation of the algorithm, including its time complexity analysis, to illustrate its computational efficiency. We implemented and rigorously tested the proposed method on real-world data by achieving an accuracy of over 99%, which highlights on ground capabilities. This system generates an output file that not only validates trips but also supports dashboard visualizations, travel time forecasting, arrival time predictions, and dwell time analysis.</p>