INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
In the realism of urban mobility, our innovative bus routine prediction technology emerges as a
groundbreaking solution aimed at redefining the public transportation experience. This project is centered
around the meticulous analysis of extensive historical data encompassing bus arrival and departure times,
complemented by a comprehensive examination of contextual factors such as traffic patterns and temporal
events. By harnessing the power of advanced machine learning algorithms, this system transcends
traditional scheduling approaches, providing commuters with highly accurate predictions for bus arrival
times at specific locations. The integration of real-time data sources, including live traffic updates and GPS
information from buses, further enhances the precision and adaptability of predictions, ensuring that users
receive timely and relevant information. The user interface, designed with utmost attention to user
experience, is not only intuitive but also seamlessly accessible on mobile devices, catering to the dynamic
needs of users on the move. Beyond its technological prowess, the project fosters community engagement
by incorporating feedback mechanisms, allowing users to actively contribute to the system's improvement.
This scalable and user-centric technology not only optimizes the planning and execution of urban
commuting but also represents a significant step towards a future where public transportation is
characterized by predictability, efficiency, and a heightened user experience.
Keywords:
Bus Routine Prediction Technology
Cite Article:
"Bus Routine Prediction Technology", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.d404-d411, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403352.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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