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AI and Blockchain for Smart Traffic Management: A Decentralized and Intelligent Framework

Authors

Sujata Patil

Department of Computer Science, Dr. D. Y. Patil Arts, Commerce and Science College, Pimpri Pune-18, Maharashtra, India (IN)

Vidya Shinde

Department of Computer Science, Dr. D. Y. Patil Arts, Commerce and Science College, Pimpri Pune-18, Maharashtra, India (IN)

Article Information

DOI: 10.51583/IJLTEMAS.2025.1413SP007

Subject Category: Computer Science

Volume/Issue: 14/13 | Page No: 26-31

Publication Timeline

Submitted: 2025-10-22

Published: 2025-10-22

Abstract

Abstract: The exponential growth in urban populations has placed tremendous stress on existing traffic infrastructures. As a result, cities are experiencing increased traffic congestion, extended travel times, and increased levels of pollution. To address these challenges, this paper proposes a novel intelligent traffic management framework that integrates Artificial Intelligence (AI) and Blockchain technology for enhanced urban mobility and system security. The primary objective of this study is to develop a decentralized and automated traffic control system that can optimize signal timing and predict congestion in real-time while maintaining secure and transparent data communication across stakeholders. The methodology involves a multi-phase approach starting with data collection from CCTV cameras, IoT-based road sensors, and GPS-equipped vehicles. These diverse data streams can processed using Convolutional Neural Networks (CNNs) for vehicle detection and traffic density classification, and Long Short-Term Memory (LSTM) networks for time-series forecasting of congestion patterns. A private Ethereum blockchain can be deployed using tools like Ganache, where smart contracts developed in Solidity manage access control, log AI-generated decisions, and automate responses such as emergency vehicle prioritization. Integration of AI and blockchain components allows system nodes—such as smart traffic lights and control centers—to autonomously execute verified decisions. The proposed system will be implemented to improve traffic flow efficiency, minimize waiting times, and enable reliable vehicle prioritization across various traffic scenarios through AI-driven control mechanisms. The blockchain layer will be deployed to ensure tamper-proof and auditable records of all transactions and decision-making processes.


In conclusion, the proposed AI-Blockchain integrated system enhances the efficiency, transparency, and robustness of urban traffic management, representing a scalable and secure solution for future smart cities.

Keywords

Artificial Intelligence, Blockchain Technology, Traffic Congestion, Real-time Data Analysis, Intelligent Traffic Control Systems

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References

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