Digital Twin Technology in Transportation Infrastructure: A Comprehensive Survey of Current Applications, Challenges, and Future Directions

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(4), P. 1911 - 1911

Published: Feb. 12, 2025

Transportation infrastructure is central to economic development and the daily lives of citizens. However, rapid urbanization, increasing vehicle ownership, growing concerns about sustainable have significantly heightened complexity managing these systems. Although digital twin (DT) technology holds great promise, most current research focuses on specific areas, lacking a comprehensive framework that spans entire lifecycle transportation infrastructure, from planning construction operation maintenance. The technical challenges integrating different DT systems remain unclear, which some extent limits potential in management infrastructure. To address this gap, review first summarizes fundamental concepts architectures involved for such as roads, bridges, tunnels, hubs. From perspective, are categorized based functional scope, data integration methods, application stages, their key technologies basic frameworks outlined. Subsequently, applications various stages infrastructure—planning construction, maintenance, decommissioning renewal—are analyzed, progress reviewed discussed. Finally, future directions achieving full system encompassing technical, operational, ethical aspects, discussed summarized. insights gained herein will be valuable researchers, urban planners, engineers, policymakers.

Language: Английский

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Review and Insights Toward Cognitive Digital Twins in Pavement Assets for Construction 5.0

Infrastructures, Journal Year: 2025, Volume and Issue: 10(3), P. 64 - 64

Published: March 15, 2025

With the movement of construction industry towards Construction 5.0, Digital Twin (DT) has emerged in recent years as a pivotal and comprehensive management tool for predictive strategies infrastructure assets. However, its effective adoption conceptual implementation remain limited this domain. Current review works focused on applications potentials DT general infrastructures. This focuses interpreting DT’s foundation flexible pavement asset context, including core components, considerations, methodologies. Existing implementations are evaluated to uncover their strengths, limitations, potential improvement. Based systematic review, study proposes cognitive framework management. It explores extent enhanced decision-making large-scale collaborative environment. also identifies current emerging challenges enablers, well highlights future research directions advance support alignment with transformative goals 5.0.

Language: Английский

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Digital Twin Approach for Operation and Maintenance of Transportation System – Systematic Review

Published: Aug. 5, 2024

There is a growing need to implement modern technologies, such as digital twinning, improve the efficiency of transport fleet maintenance processes and maintain company's operational capacity at required level. Therefore, paper reviews existing literature present an up-to-date content-relevant analysis in this field. The proposed methodology systematic review using Primo multi-search tool following Preferred Reporting Items for Systematic Reviews Meta-Analyzes (PRISMA) guidelines. main inclusion criteria included publication dates (studies published from 2012–2024) studies English. This resulted selection 201 most relevant papers area investigation. Finally, selected articles were categorized into seven groups: a) air transportation, b) railway c) land transportation (road), d) in-house logistics, e) water intermodal f) supply chain operation, g) other applications. One advantages study that results are obtained different scientific sources/databases thanks tool. Moreover, bibliometric was performed. have led authors specify research problems trends related analyzed identify gaps future investigation academic engineering perspectives. In addition, based on results, framework DT system developed. ends with conclusions directions.

Language: Английский

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Explainable AI Using OBDII Data for Urban Buses Maintenance Management: A Study Case About the DPF Regeneration

Information, Journal Year: 2025, Volume and Issue: 16(2), P. 74 - 74

Published: Jan. 21, 2025

Industry 4.0, leveraging tools like AI and the massive generation of data, is driving a paradigm shift in maintenance management. Specifically, realm Artificial Intelligence (AI), traditionally “black box” models are now being unveiled through explainable techniques, which provide insights into model decision-making processes. This study addresses underutilization these techniques alongside On-Board Diagnostics data by management teams urban bus fleets for addressing key issues affecting vehicle reliability needs. In context fleets, diesel particulate filter regeneration processes frequently operate under suboptimal conditions, accelerating engine oil degradation increasing costs. Due to limited documentation on control system filter, team faces obstacles proposing solutions based comprehensive understanding system’s behavior logic. The objective this analyze predict various states during process using Machine Learning artificial intelligence techniques. obtained aim with deeper filter’s logic, enabling them develop proposals grounded system. employs combination traditional models, including XGBoost, LightGBM, Random Forest, Support Vector Machine. target variable, representing three possible states, was transformed one-vs-rest approach, resulting binary classification tasks where each state individually classified against all other states. Additionally, such as Shapley Additive Explanations, Partial Dependence Plots, Individual Conditional Expectation were applied interpret visualize conditions influencing state. results successfully associate two specific operating establish operational thresholds variables, offering practical guidelines optimizing process.

Language: Английский

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Real-Time Automatic Identification of Plastic Waste Streams for Advanced Waste Sorting Systems

Sustainability, Journal Year: 2025, Volume and Issue: 17(5), P. 2157 - 2157

Published: March 2, 2025

Despite the significant recycling potential, a massive generation of plastic waste is observed year after year. One causes this phenomenon issue ineffective stream sorting, primarily arising from uncertainty in composition stream. The process cannot be carried out without proper separation different types plastics Current solutions field automated identification rely on small-scale datasets that insufficiently reflect real-world conditions. For reason, article proposes real-time model based CNN (convolutional neural network) and newly constructed, self-built dataset. was evaluated two stages. first stage separated validation dataset, second developed test bench, replica real system. under laboratory conditions, with strong emphasis maximally reflecting Once included sensor fusion, proposed approach will provide full information characteristics stream, which ultimately enable efficient mixed Improving significantly support United Nations’ 2030 Agenda for Sustainable Development.

Language: Английский

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NFT-Based Framework for Digital Twin Management in Aviation Component Lifecycle Tracking

Algorithms, Journal Year: 2024, Volume and Issue: 17(11), P. 494 - 494

Published: Nov. 2, 2024

The paper presents a novel framework for implementing decentralized algorithms based on non-fungible tokens (NFTs) digital twin management in aviation, with focus component lifecycle tracking. proposed approach uses NFTs to create unique, immutable representations of physical aviation components capturing real-time records component’s entire lifecycle, from manufacture retirement. This outlines detailed workflows key processes, including part tracking, maintenance records, certification and compliance, supply chain management, flight logs, ownership leasing, technical documentation, quality assurance. introduces class designed manage the complex relationships between components, their twins, associated NFTs. A unified model is presented demonstrate how are created updated across various stages ensuring data integrity, regulatory operational efficiency. also discusses architecture system, exploring sources, blockchain, NFTs, other critical components. It further examines main challenges NFT-based future research directions.

Language: Английский

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