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International Research Journal of Engineering and Technology (IRJET)

e-ISSN: 2395-0056

Volume: 12 Issue: 06 | Jun 2025

p-ISSN: 2395-0072

www.irjet.net

College Bus Automation System Pranjal S. Kamble1, Gauravi K. Kadam2, Ishita U. Kadekar3, Prachi R. Arage4 1,2,3,4 Students, Department of Computer Science & Engineering Padmabhooshan Vasantraodada Patil Institute of

Technology (PVPIT), Budhgaon ( Sangli ), India ---------------------------------------------------------------------***---------------------------------------------------------------------

Abstract - In an era where automation is essential for

administrators to monitor operations via a centralized digital portal.

operational efficiency, traditional methods of managing college bus transportation and student attendance continue to suffer from several drawbacks, including manual errors, delays, lack of real-time monitoring, and additional dependency on physical verification methods. To address these issues, we present a comprehensive and cost-effective *College Bus Automation System* that leverages face recognition for student attendance, an admin portal for centralized data and fund management, and a reward-based monthly payment system to encourage consistent bus usage. The proposed system ensures seamless attendance marking without requiring any contact or physical input from students, thereby enhancing safety and efficiency. Using widely available libraries such as Python, OpenCV, and NumPy, the system eliminates the need for costly biometric or RFID hardware. The admin portal allows real-time tracking of student data, fund management, and monitoring attendance trends, while also calculating student-specific reward points to apply payment discounts. The project was successfully implemented and tested with real-world scenarios, showcasing high accuracy, reliability, and user satisfaction. The modular architecture also ensures easy scalability, paving the way for future integrations like GPS tracking, mobile app support, and instant parent notifications. This paper discusses the complete development lifecycle of the system, from design methodology and implementation to testing, analysis, and future prospects.

2. OBJECTIVES The main objectives of this project are as follows: - To develop a touchless face recognition-based attendance system that records student entries as they board the bus. - To create an admin dashboard that allows administrators to manage students' data, monitor attendance, and view funds. - To implement a reward system that encourages timely and consistent use of transportation through a pointsbased discount model. - To reduce dependency on expensive RFID/biometric hardware and use cost-effective open-source software alternatives. - To ensure data security, modular design, and future scalability with minimal operational cost.

3. MODULES OF PROJECT The proposed College Bus Automation System comprises the following primary modules: - Face Recognition Module

Key Words: College transportation, face recognition, attendance system, admin portal, automation, Python, OpenCV, real-time monitoring, reward system, student safety.

- Admin Portal Module - Reward and Payment Module

1. INTRODUCTION

- Database Module

The management of student attendance in college transportation systems has traditionally relied on manual processes or biometric technologies that often face issues such as errors, delays, hardware costs, and lack of scalability. With growing concerns around data accuracy, security, and operational efficiency, it becomes essential to leverage smarter, touchless, and more robust technologies that simplify attendance tracking and fund management in real time. This project proposes an advanced system that replaces traditional attendance systems with a face recognition-based alternative while enabling

Impact Factor value: 8.315

Each module is designed to enhance efficiency and streamline workflows specific to its user group.

SECURITY AND PRIVACY

The College Bus Automation System prioritizes the security and privacy of student data throughout its lifecycle. The facial recognition module only processes image data locally during authentication and avoids storing unnecessary visual data. All sensitive information, including student profiles, attendance logs, and financial

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