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Paper Title
UNIVERSITY TRANSPORT CONNECT: REAL-TIME UNIVERSITY BUS TRACKING SYSTEM USING FLASK WEBSOCKET,AND MACHINE LEARNING PREDICTIVE ANALYSIS .
Authors
Karthik C , Praveen Kumar N , Mrs. S. Scinthia Clarinda
Keywords
Flask framework, WebSocket technology, Machine learning predictive analytics, Flask-SocketIO
Abstract
"University Transport Connect" (UTC)
innovates campus transportation with real-time bus tracking
and predictive analytics, Its primary objective is to streamline
the commuting experience for users by delivering precise bus
arrival times and ensuring seamless mobility. This solution
addresses the critical need for improved mobility and time
management within universities, surpassing existing systems
that often lack precision and timely updates. University
Transport Connect (UTC) integrates machine learning
algorithms within Python's Flask framework and WebSocket
technology to predict bus arrival times reliably. Starting with
linear regression models, the project plans to advance to more
sophisticated ensemble methods for increased prediction
accuracy. Flask-SocketIO facilitates seamless
communication between servers and clients, ensuring real-
time updates on interactive maps powered by the Google
Maps API. Each bus is uniquely identifiable for precise
tracking, with location data stored in a scalable database
system to ensure reliability. University Transport Connect
(UTC) also offers personalized notifications, route
optimization algorithms, and seamless integration with
mobile platforms, enhancing user experience. Beyond
educational institutions, Connect (UTC) also offers
personalized notifications, route optimization algorithms, and
seamless integration with mobile (UTC) sets a precedent for
smart transportation solutions in urban environments,
demonstrating technology's transformative potential in
improving daily commutes and supporting sustainable
campus mobility initiatives.
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How To Cite
Choose the style your journal or department asks for, then copy it. Every version below is generated from this paper's own record.
IJRTI — journal style
"UNIVERSITY TRANSPORT CONNECT: REAL-TIME UNIVERSITY BUS TRACKING SYSTEM USING FLASK WEBSOCKET,AND MACHINE LEARNING PREDICTIVE ANALYSIS .", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.10, Issue 1, page no.a892-a895, January-2025, Available :https://ijrti.org/papers/IJRTI2501107.pdf
APA — 7th edition
C, K., N, P. K., & Clarinda, S. S. (2025). UNIVERSITY TRANSPORT CONNECT: REAL-TIME UNIVERSITY BUS TRACKING SYSTEM USING FLASK WEBSOCKET,AND MACHINE LEARNING PREDICTIVE ANALYSIS . International Journal for Research Trends and Innovation, 10(1), a892-a895. https://ijrti.org/viewpaperforall.php?paper=IJRTI2501107
MLA — 9th edition
C, Karthik, et al. "UNIVERSITY TRANSPORT CONNECT: REAL-TIME UNIVERSITY BUS TRACKING SYSTEM USING FLASK WEBSOCKET,AND MACHINE LEARNING PREDICTIVE ANALYSIS ." International Journal for Research Trends and Innovation, vol. 10, no. 1, 2025, pp. a892-a895, https://ijrti.org/viewpaperforall.php?paper=IJRTI2501107.
Chicago — 17th, bibliography
C, Karthik, Praveen Kumar N, and S. Scinthia Clarinda. "UNIVERSITY TRANSPORT CONNECT: REAL-TIME UNIVERSITY BUS TRACKING SYSTEM USING FLASK WEBSOCKET,AND MACHINE LEARNING PREDICTIVE ANALYSIS ." International Journal for Research Trends and Innovation 10, no. 1 (2025): a892-a895. https://ijrti.org/viewpaperforall.php?paper=IJRTI2501107.
Harvard — author–date
C, K., N, P.K. and Clarinda, S.S. (2025) 'UNIVERSITY TRANSPORT CONNECT: REAL-TIME UNIVERSITY BUS TRACKING SYSTEM USING FLASK WEBSOCKET,AND MACHINE LEARNING PREDICTIVE ANALYSIS', International Journal for Research Trends and Innovation, 10(1), pp. a892-a895. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI2501107
IEEE — numbered reference
K. C, P. K. N and S. S. Clarinda, "UNIVERSITY TRANSPORT CONNECT: REAL-TIME UNIVERSITY BUS TRACKING SYSTEM USING FLASK WEBSOCKET,AND MACHINE LEARNING PREDICTIVE ANALYSIS," IJRTI, vol. 10, no. 1, pp. a892-a895, Jan. 2025.
Vancouver — biomedical
C K, N PK, Clarinda SS. UNIVERSITY TRANSPORT CONNECT: REAL-TIME UNIVERSITY BUS TRACKING SYSTEM USING FLASK WEBSOCKET,AND MACHINE LEARNING PREDICTIVE ANALYSIS . IJRTI. 2025 Jan;10(1):a892-a895.
AMA — 11th edition
C K, N PK, Clarinda SS. UNIVERSITY TRANSPORT CONNECT: REAL-TIME UNIVERSITY BUS TRACKING SYSTEM USING FLASK WEBSOCKET,AND MACHINE LEARNING PREDICTIVE ANALYSIS . IJRTI. 2025;10(1):a892-a895. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI2501107
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2501107,
author = {Karthik C and Praveen Kumar N and S. Scinthia Clarinda},
title = {UNIVERSITY TRANSPORT CONNECT: REAL-TIME UNIVERSITY BUS TRACKING SYSTEM USING FLASK WEBSOCKET,AND MACHINE LEARNING PREDICTIVE ANALYSIS .},
journal = {International Journal for Research Trends and Innovation},
volume = {10},
number = {1},
pages = {a892-a895},
year = {2025},
month = {January},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI2501107}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - C, Karthik
AU - N, Praveen Kumar
AU - Clarinda, S. Scinthia
TI - UNIVERSITY TRANSPORT CONNECT: REAL-TIME UNIVERSITY BUS TRACKING SYSTEM USING FLASK WEBSOCKET,AND MACHINE LEARNING PREDICTIVE ANALYSIS .
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 10
IS - 1
PY - 2025
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI2501107
SP - a892-a895
ER -
Issue
Volume 10 Issue 1,
January-2025
Pages : a892-a895
Other Publication Details
Paper Reg. ID
IJRTI_200502
Published Paper ID
IJRTI2501107
Downloads
205,645
Research Area
Science & Technology
Country
Chennai, Tamilnadu , India
Published
January 2025
Published Paper PDF
https://ijrti.org/papers/IJRTI2501107.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2501107
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
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Open
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Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
