Blockchain and Machine Learning for Intelligent Traffic Management Systems in Urban Planning
计算机科学
块链
智能交通系统
人工智能
运输工程
计算机安全
工程类
作者
Vijilius Helena Raj,Y Manohar Reddy,Pushpendra Singh Danghi,H Pal Thethi,Muntather Muhsen,Praveen
标识
DOI:10.1109/csnt60213.2024.10545848
摘要
Managing traffic and urban development in today's densely populated cities is becoming more difficult. Fortunately, there is hope in the form of a novel approach to problem solving: the combination of blockchain and machine learning. This article delves at the potential of combining blockchain technology with machine learning for use in Smart City Intelligent Traffic Management Systems (ITMS). With blockchain technology, data can be managed safely and openly, allowing for authenticated, near-real-time monitoring of traffic data. Thus, the accuracy of traffic management data is improved, and the possibility of manipulation is reduced. Algorithms in machine learning enable data analysis and predictive analytics. Large-scale traffic data analysis can optimize traffic patterns to improve urban mobility. This article examines how machine learning and blockchain technology may complement each other. This study examines the benefits of the two technologies and how their combination strengthens IT management systems. The research also examines possible issues and benefits of a holistic approach. This innovative combination of technologies can improve urban traffic management and quality of life by improving data security, traffic forecast accuracy, and urban planning efficiency.