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Paper ID:IJSREM60007

REAL-TIME BUS TRACKING AND ATTENDANCE MONITORING SYSTEM WITH ML

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM60007

Volume:

10 |

4 |

April 2026

Pages:

1-4

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM60007

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SM

Shreeganesh More

Computer Engineering

Sinhgad Academy of Engineering, Pune

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PMN

Prof. M.K. Nivangune

Computer Engineering

Sinhgad Academy of Engineering, Pune

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MM

Mansi Mamdyal

Computer Engineering

Sinhgad Academy of Engineering, Pune

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PR

Payal Raut

Computer Engineering

Sinhgad Academy of Engineering, Pune

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PW

Pranoti Wale

Computer Engineering

Sinhgad Academy of Engineering, Pune

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Abstract

This study introduces an intelligent system aimed at improving the safety of school transportation and simplifying attendance tracking through the use of QR codes and Machine Learning techniques. Each student is provided with a unique QR code printed on their identification card, which is scanned when entering and leaving the school bus. This process enables automatic recording of attendance without manual intervention. The system immediately informs parents about their child’s boarding notifications. It also prepares periodic attendance summaries that help school administrators analyze student travel patterns. In addition, GPS-based tracking allows real-time monitoring of bus location, while a Machine Learning model is used to estimate arrival times more accurately.

KEYWORDS

QRcode Attendance Monitoring Notification Tracking Automation Bus arrival time prediction.

Cite This Article

Shreeganesh More, Prof. M.K. Nivangune, Mansi Mamdyal, Payal Raut, Pranoti Wale, "REAL-TIME BUS TRACKING AND ATTENDANCE MONITORING SYSTEM WITH ML," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, pp. 1-4, April 2026. https://doi.org/10.55041/IJSREM60007

Full Article/Conclusion

The proposed Real-Time College Bus Tracking and Student Attendance System provides an efficient approach to improving transportation management in educational institutions. It simplifies the process of monitoring student movement by automatically recording boarding and drop-off details, eliminating the need for manual attendance methods. The system enhances safety by enabling continuous tracking of the bus and ensuring that accurate information is available to both parents and administrators. By integrating multiple functionalities into a single platform, it increases transparency and reduces operational complexity. In summary, this solution offers a practical and modern alternative to traditional systems, supporting better management and improved student security. Future improvements can focus on incorporating advanced identification techniques such as facial recognition, applying data-driven methods for route planning, and ensuring consistent performance in areas with limited network connectivity.

References

M. Sowndharya, Yuvaraj K, Rahul S, Srichandiran S, and Sriram S, "Smart College Bus Tracker: RealTime Location and ETA Predictor," International Journal of Scientific Research and Engineering Development, vol. 8, no. 3, pp. 488–491, May 2025.   2.  Subash Gokul, "Student Tracking System in College Bus Using Face Recognition and IoT," International Journal of Science and Technology, vol. 25, no. 2, pp. 1–5, Feb. 2025.   3.   B. Sandhiya, VVK Ravichandra, V Siddhartha, M Vanathi, J Karthika, "Real-Time College Bus Tracking and Notification System for Student Convenience," International Journal of Advanced Research in Computer and Communication Engineering, vol. 7, no. 7, pp. 1–5, Jul. 2025.   M. Pranavi Reddy, Abhishek Peeri, N Srinu, K Anil Kumar, "RFID-Based Attendance Monitoring System with Real-Time Notifications," International Journal of Innovative Science and Research Technology, vol. 5, no. 5, pp. 1–5, May 2025

Editorial & Review Transparency

Publication Date

4/25/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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