Digital twin for intelligent tunnel construction

Automation in Construction, Год журнала: 2023, Номер 158, С. 105210 - 105210

Опубликована: Ноя. 30, 2023

Язык: Английский

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

Applied Sciences, Год журнала: 2025, Номер 15(4), С. 1911 - 1911

Опубликована: Фев. 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.

Язык: Английский

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Transforming the maintenance of underground infrastructure through Digital Twins: State of the art and outlook

Tunnelling and Underground Space Technology, Год журнала: 2025, Номер 161, С. 106508 - 106508

Опубликована: Март 6, 2025

Язык: Английский

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Shifting research from defect detection to defect modeling in computer vision-based structural health monitoring

Automation in Construction, Год журнала: 2024, Номер 164, С. 105481 - 105481

Опубликована: Май 21, 2024

Язык: Английский

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Comprehensive digital twin for infrastructure: A novel ontology and graph-based modelling paradigm

Advanced Engineering Informatics, Год журнала: 2024, Номер 62, С. 102747 - 102747

Опубликована: Июль 30, 2024

Язык: Английский

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Urban digital twin-based solution using geospatial information for solid waste management

Sustainable Cities and Society, Год журнала: 2024, Номер unknown, С. 105798 - 105798

Опубликована: Сен. 1, 2024

Язык: Английский

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Integrated natural language processing method for text mining and visualization of underground engineering text reports

Automation in Construction, Год журнала: 2024, Номер 166, С. 105636 - 105636

Опубликована: Июль 24, 2024

Язык: Английский

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Digital twin for smart metro service platform: Evaluating long-term tunnel structural performance

Automation in Construction, Год журнала: 2024, Номер 167, С. 105713 - 105713

Опубликована: Авг. 26, 2024

Язык: Английский

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Dynamic risk early warning system for tunnel construction based on two-dimensional cloud model

Expert Systems with Applications, Год журнала: 2024, Номер 255, С. 124799 - 124799

Опубликована: Июль 14, 2024

Язык: Английский

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IoT-Enabled Predictive Maintenance for Sustainable Transportation Fleets

E3S Web of Conferences, Год журнала: 2024, Номер 511, С. 01012 - 01012

Опубликована: Янв. 1, 2024

This research examines the profound effects of integrating IoT-enabled predictive maintenance in sustainable transportation fleets. By using real-time sensor data, this implementation aims to enhance fleet dependability and operational efficiency. The fleet, including a variety vehicles such as electric buses, hybrid cars, trucks, CNG-powered vans, is constantly monitored IoT sensors that capture important characteristics like engine temperature, battery voltage, brake wear percentages. algorithms adapt schedules response live enabling proactive strategy tackles prospective problems before they result major failures. examination records reveals prompt actions, showcasing system’s efficacy reducing interruptions improving overall fleet. Moreover, percentage change confirms flexibility, demonstrating its capacity anticipate fluctuations wear. findings highlight ability various operating situations contribution lowering expenses while enhancing effectiveness. established approach incorporates ethical issues, data security privacy, ensure responsible adoption technology. study has broader ramifications beyond particular dataset, providing detailed plan for incorporating IoTenabled into contemporary infrastructures. study’s offer valuable insights potential strategies transform industry towards sustainability. contributes future where fleets operate with increased efficiency, reduced environmental impact, improved reliability.

Язык: Английский

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