Mixed reality-based multi-scenario visualization and control in automated terminals: a middleware and digital twin driven approach

Date

2025

Authors

Wang, Y.
Zhang, E.
Yang, A.
Du, K.
Gao, J.

Editors

Advisors

Journal Title

Journal ISSN

Volume Title

Type:

Journal article

Citation

Buildings, 2025; 15(21):1-28

Statement of Responsibility

Conference Name

Abstract

This study presents a Digital Twin–Mixed Reality (DT–MR) framework for the immersive and interactive supervision of automated container terminals (ACTs), addressing the fragmented data and limited situational awareness of conventional 2D monitoring systems. The framework employs a middleware-centric architecture that integrates heterogeneous subsystems—covering terminal operation, equipment control, and information management—through standardized industrial communication protocols. It ensures synchronized timestamps and delivers semantically aligned, low-latency data streams to a multi-scale Digital Twin developed in Unity. The twin applies level-of-detail modeling, spatial anchoring, and coordinate alignment (from Industry Foundation Classes (IFCs) to east–north–up (ENU) coordinates and Unity space) for accurate registration with physical assets, while a Microsoft HoloLens 2 device provides an intuitive Mixed Reality interface that combines gaze, gesture, and voice commands with built-in safety interlocks for secure human–machine interaction. Quantitative performance benchmarks—latency ≤100 ms, status refresh ≤1 s, and throughput ≥10,000 events/s—were met through targeted engineering and validated using representative scenarios of quay crane alignment and automated guided vehicle (AGV) rerouting, demonstrating improved anomaly detection, reduced decision latency, and enhanced operational resilience. The proposed DT–MR pipeline establishes a reproducible and extensible foundation for real-time, human-in-the-loop supervision across ports, airports, and other large-scale smart infrastructures.

School/Discipline

Dissertation Note

Provenance

Description

Access Status

Rights

Copyright 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. (https://creativecommons.org/licenses/by/4.0/)

License

Grant ID

Call number

Persistent link to this record