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Publication Type : Conference Proceedings
Publisher : 2016 IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2016,
Source : 2016 IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2016, Institute of Electrical and Electronics Engineers Inc. (2017)
ISBN : 9781509021932
Keywords : Bus drivers, Buses, Dijkstra's algorithms, Dynamic shortest path, Estimated time of arrivals, Fleet management, Fleet operations, Graph theory, Hardware, Hardware solutions, MQTT, Neural networks, Public transport information systems, Real time control, Real-time implementations, Smart city
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2017
Abstract : The need for a real-time public transport information system is growing steadily. People want to plan their city commutes and do not like waiting for long hours, nor take a long route to reach their destination. The proposed hardware solution in this paper computes the shortest path to reach the destination in real time and gives that information to the bus driver. Artificial Neural Networks (ANN) is used to give an accurate estimate of the arrival time (ETA) to the commuter by means of an application. ETA to the next stop is communicated to the commuter using the MQTT (Message Queuing Telemetry Transport) protocol, by the hardware mounted on the bus. The proposed solution also adds a fleet management console to the administrators, making them manage and monitor the fleet of buses in real time. The prototype thus developed makes sure the commuting in cities is pleasant, and hassle free. © 2016 IEEE.
Cite this Research Publication : S. Sharad, Dr. Bhagavathi Sivakumar P., and Anantha Narayanan V., “The smart bus for a smart city - A real-time implementation”, 2016 IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2016. Institute of Electrical and Electronics Engineers Inc., 2017.