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Railway Track Cleaning: Using Artificial Intelligence Methods

Publish Year: 1402
Type: Conference paper
Language: English
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SETIET04_039

Index date: 16 August 2023

Railway Track Cleaning: Using Artificial Intelligence Methods abstract

This article explores the application of artificial intelligence (AI) techniques in the cleaning of railway tracks and its impact on operational efficiency and safety. By leveraging AI-enabled robots, predictive analytics, real-time monitoring, and automated track inspection systems, railways can achieve enhanced cleanliness, optimized cleaning schedules, and proactive maintenance measures. AI-powered robots equipped with advanced sensors and machine learning algorithms autonomously identify and remove debris, minimizing the risk of accidents and ensuring uninterrupted train operations. Predictive analytics models analyze historical data and passenger flow information to optimize cleaning schedules, reducing disruptions and improving efficiency. Real-time monitoring systems detect potential maintenance issues in advance, allowing for timely preventive measures. Automated track inspection systems powered by AI proactively detect anomalies, ensuring a higher level of quality assurance and facilitating prompt repairs. As AI technology advances, the railway industry can anticipate further innovations, revolutionizing track maintenance and contributing to a more reliable and safe transportation system.

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Railway Track Cleaning: Using Artificial Intelligence Methods authors

Behzad Ghasemi Parvin

Ataturk University, Faculty of Engineering, Department of Mechanical Engineering, Erzurum, ۲۵۲۴۰, Turkey

Leila Ghasemi Parvin

Ankara Hacı Bayram Veli University, Faculty of Tourism, Department of Gastronomy and Culinary Arts, Ankara, ۰۶۹۰۰,Turkey