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Public transportation is essential for city travel, but many bus systems face ongoing problems like irregular arrival times, unclear fare structures, and limited communication with passengers. The project called “Smart Bus Route Management System with Real-Time Tracking and Passenger Assistance” addresses these issues by using mobile tracking, cloud computing, and AI/ML technologies. Instead of relying on costly GPS hardware, the system uses smartphones placed in buses to send live location data to a central cloud database. Passengers can easily access real-time bus locations, estimated arrival times, and fare information through a dedicated mobile app. Meanwhile, operators can manage fleet operations through a web-based dashboard. AI-driven prediction models improve the accuracy of arrival time estimates and enable the system to send automated alerts for delays or emergencies. This smartphone-based, cloud-enabled approach allows for low-cost deployment, scalability, and better service reliability, ultimately improving the travel experience for both passengers and transport operators.
Keywords:
Smart transportation, mobile tracking, real-time bus monitoring, cloud computing, AI/ML prediction, passenger assistance, public transport management, smart cities.
Cite Article:
"Smart Bus Route Management System with Real-Time Tracking and Passenger Assistance", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 11, page no.b334-b338, November-2025, Available :http://www.ijrti.org/papers/IJRTI2511142.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator