STM Journals Peer-reviewed research from Consortium e-Learning Network

International Journal of Satellite Remote Sensing Original Research

Smart Shuttle System: An IoT and Machine Learning Based Approach

  1. M. Divya Teja Department of Electronics and Communication Engineering, Vellore Institute of Technology, Katpadi, Vellore, Tamil Nadu, India
  2. Nuthalapati Ganesh Department of Electronics and Communication Engineering, Vellore Institute of Technology, Katpadi, Vellore, Tamil Nadu, India
  3. Keerthi Uppalapati Department of Electronics and Communication Engineering, Vellore Institute of Technology, Katpadi, Vellore, Tamil Nadu, India

Abstract

The Smart Shuttle System is an IoT-based system designed to provide a hassle-free, cashless payment experience for students using the shuttle service. The system utilizes RFID (Radio Frequency Identification) technology to identify students and deduct the fare amount from their account. Radio Frequency Identification (RFID) technology is being considered as an alternative to traditional money and Unified Payments Interface (UPI) for making payments due to several advantages it provides over traditional methods. RFID tags provide a more convenient and efficient way of making payments compared to traditional methods like cash or UPI, which require users to have access to a mobile device or a bank account. RFID tags can be easily carried in a wallet or purse and can be used to make payments with just a tap. The system also incorporates machine learning algorithms to predict income for a particular date. This paper presents the design and implementation of the Smart Shuttle System, including hardware setup, software installation, RFID tag registration, Wi-Fi communication, balance verification, data logging, and web interface. The results of the system performance show that it can handle up to 23 transactions in 90 seconds, providing a fast and efficient payment method for students.

Keywords

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