Smart Bus Tracking And Monitoring System: A Review Of Gps–Iot Vehicle Tracking, Arrival-Time Prediction And Passenger Information Services

Public bus services carry large numbers of passengers in Indian cities, yet passengers often wait at stops without knowing when the next bus will arrive, and operators lack real-time visibility of their fleets. A smart bus tracking and monitoring system uses GPS, IoT communication and web or mobile applications to provide live bus locations, routes, estimated arrival times and schedules to passengers and transport authorities. This paper reviews the technologies behind such systems. It covers GPS-based vehicle tracking, onboard IoT units with cellular communication, trajectory processing and map matching, and methods for predicting bus arrival times, from historical averages and Kalman filtering to artificial neural networks and recurrent models that account for traffic and multiple routes. Smartphone-based crowdsourced tracking and research on the effect of real-time information on passengers are reviewed, together with open data standards. A five-layer architecture comprising onboard units, communication, a central server with prediction, administrator tools and passenger applications is proposed. Research gaps, objectives, a comparison of prediction methods and challenges including GPS errors in dense areas, data costs and privacy are discussed. The review concludes that integrating AI-based prediction makes bus services more reliable and attractive.