IRO Journals
Journal of Electronics and Informatics

AI-Enabled Smart Bus System for Modern Urban Mobility

Open Access
Published: 29 April, 2026
Pages: 120-132
  • Vimala T. , Vimala T.
    Department of Electronics and Communication Engineering, Dr. M.G.R Educational and Research Institute, Chennai, India
    Department of Electronics and Communication Engineering, Dr. M.G.R Educational and Research Institute, Chennai, India
  • Raghul A. , Raghul A.
    Department of Electronics and Communication Engineering, Dr. M.G.R Educational and Research Institute, Chennai, India
    Department of Electronics and Communication Engineering, Dr. M.G.R Educational and Research Institute, Chennai, India
  • Sakthivel S. , Sakthivel S.
    Department of Electronics and Communication Engineering, Dr. M.G.R Educational and Research Institute, Chennai, India
    Department of Electronics and Communication Engineering, Dr. M.G.R Educational and Research Institute, Chennai, India
  • Sai Krishna M. Sai Krishna M.
    Department of Electronics and Communication Engineering, Dr. M.G.R Educational and Research Institute, Chennai, India
    Department of Electronics and Communication Engineering, Dr. M.G.R Educational and Research Institute, Chennai, India
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How to Cite

T., Vimala, Raghul A., Sakthivel S., and Sai Krishna M. 2026. “AI-Enabled Smart Bus System for Modern Urban Mobility”. Journal of Electronics and Informatics 8 (2): 120-32. https://doi.org/10.36548/jei.2026.2.002.
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Keywords

AI-Enabled Transport System
Internet of Things (IoT)
RFID Smart Card Ticketing
Machine Learning
GPS-Based Tracking
Cloud Computing
Passenger Monitoring and Safety

Abstract

The rapid urbanization and increasing demand for efficient public transportation systems necessitate the adoption of intelligent and automated solutions to overcome the limitations of conventional transport management. Traditional bus systems, which rely on manual ticketing and human supervision, often suffer from issues such as revenue leakage, lack of transparency, inefficient passenger monitoring, and security vulnerabilities. This research presents an AI-Enabled Smart Bus System for Modern Urban Mobility that integrates Internet of Things (IoT), cloud computing, and machine learning techniques to enhance operational efficiency, safety, and user experience. The proposed system utilizes an ESP32 microcontroller as the central processing unit, interfaced with RFID-based smart card technology for contactless ticketing, IR sensors for accurate passenger counting, GPS module for real-time vehicle tracking, and ESP32-CAM for surveillance and unauthorized access detection. Passenger data is continuously collected and transmitted to a cloud-based platform for real-time monitoring and storage. Machine learning algorithms implemented in Python are employed for anomaly detection, fraud identification, and passenger demand prediction, enabling data-driven decision-making and optimized route management. Furthermore, an auxiliary Arduino Uno module is incorporated to handle seat selection and stop request operations, thereby improving system responsiveness and reducing computational load. The proposed framework ensures high accuracy, reduced human intervention, enhanced security, and efficient resource utilization. The results demonstrate that the system is scalable, cost-effective, and well-suited for deployment in smart city environments, contributing to sustainable and intelligent urban transportation systems.

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