The article addresses the challenge of improving the efficiency of urban public transport management. It proposes an approach based on integrating data from heterogeneous sources: telematics platforms, driver state monitoring systems, subsystems for monitoring the technical condition of vehicles, and components of intelligent transportation systems.
passenger flow, monitoring, urban public transport, intelligent transport systems, telematics, big data, machine learning, route optimization, sensor data
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