Digital Twin-driven Online Anomaly Detection for an Automation System Based on Edge Intelligence

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The Role of AI in Warehouse Digital Twins: Literature Review

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AI-enhanced digital twins in maintenance: Systematic review, industrial challenges, and bridging research–practice gaps

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Time Series Anomaly Detection in Power Electronics Signals with Recurrent and Convlstm Autoencoders

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Digital Twins for Wind Energy Conversion Systems: A Literature Review of Potential Modelling Techniques Focused on Model Fidelity and Computational Load

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GRU-based digital twin framework for data allocation and storage in IoT-enabled smart home networks

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Regulatory oversight and ethical concerns surrounding software as medical device (SaMD) and digital twin technology in healthcare

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Blockchain and digital twin empowered trustworthy self-healing for edge-AI enabled industrial Internet of things

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Digital Twin-Enabled Service Provisioning in Edge Computing via Continual Learning

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Digital Twin for Railway: A Comprehensive Survey

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Digital twin model for chiller fault diagnosis based on SSAE and transfer learning

Ma, X., Chen, F., Wang, Z., Li, K., & Tian, C. (2023) · Building and Environment · doi:10.1016/j.buildenv.2023.110718 · Cited by 41 · see citing works

Health monitoring of CNC machining processes using machine learning and wavelet packet transform

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Monitoring industrial control systems via spatio-temporal graph neural networks

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The perspective of offshore wind power: based hydrogen production, hydrogen storage, and hydrogen transportation

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Digital twins for the designs of systems: a perspective

van Beek, A., Karkaria, V. N., & Chen, W. (2022) · Structural And Multidisciplinary Optimization · doi:10.1007/s00158-023-03488-x · Cited by 38 · see citing works

Dissecting the Impact of Information and Communication Technologies on Digital Twins as a Service

Groshev, M., Guimarães, C., de la Oliva, A., & Gazda, R. (2021) · IEEE Access · doi:10.1109/access.2021.3098109 · Cited by 35 · see citing works

A comprehensive analysis of real-time video anomaly detection methods for human and vehicular movement

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Anomaly detection in smart manufacturing: An Adaptive Adversarial Transformer-based model

Orabi, M., Tran, K. P., Egger, P., & Thomassey, S. (2024) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2024.09.021 · Cited by 35 · see citing works

TWIN-ADAPT: Continuous Learning for Digital Twin-Enabled Online Anomaly Classification in IoT-Driven Smart Labs

Gupta, R., Tian, B., Wang, Y., & Nahrstedt, K. (2024) · Future Internet · doi:10.3390/fi16070239 · Cited by 33 · see citing works

AIDA—A holistic AI-driven networking and processing framework for industrial IoT applications

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A survey on security enhancing Digital Twins: Models, applications and tools

Qureshi, A., Asensio, A., Imran, M. A., García, J., & Masip‐Bruin, X. (2025) · Computer Communications · doi:10.1016/j.comcom.2025.108158 · Cited by 33 · see citing works

Automatic generation of structural geometric digital twins from point clouds

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Process Mining for Digital Twin Development of Industrial Cyber-Physical Systems

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Milling surface roughness monitoring using real-time tool wear data

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Industrial applications of digital twins: A systematic investigation based on bibliometric analysis

Ren, J., Ahmad, R., Li, D., Ma, Y., & Hui, J. (2025) · Advanced Engineering Informatics · doi:10.1016/j.aei.2025.103264 · Cited by 32 · see citing works

Digital Twin Framework for Lathe Tool Condition Monitoring in Machining of Aluminium 5052

GaneshKumar, S., Singh, B., Kumar, R. S., & Haldorai, A. (2023) · Defence Science Journal · doi:10.14429/dsj.73.18650 · Cited by 22 · see citing works

A Review of Digital Twinning for Rotating Machinery

Inturi, V., Ghosh, B., Rajasekharan, S., & Pakrashi, V. (2024) · Italian National Conference on Sensors · doi:10.3390/s24155002 · Cited by 29 · see citing works

The rapid construction method of the digital twin polymorphic model for discrete manufacturing workshop

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Real-world prototyping and evaluation of digital twins for predictive facility maintenance

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FPGA-Based Digital Twin Implementation for Power Converter System Monitoring

Nwoke, J., Milanesi, M., Viola, J., & Chen, Y. (2023) · IEEE International Conference on Digital Twins and Parallel Intelligence (DTPI) · doi:10.1109/dtpi59677.2023.10365466 · Cited by 24 · see citing works

An industrial edge computing architecture for Local Digital Twin

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State of the art and future directions of digital twin-enabled smart assembly automation in discrete manufacturing industries

Webb, L., Tokhi, O., & Alkan, B. (2024) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2024.2387775 · Cited by 25 · see citing works

A Performance Prediction Method for a High-Precision Servo Valve Supported by Digital Twin Assembly-Commissioning

Sun, X., Liu, S., Bao, J., Li, J., & Liu, Z. (2021) · Machines · doi:10.3390/machines10010011 · Cited by 21 · see citing works

Network Digital Twins: A Systematic Review

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A Novel Online Machine Learning Approach for Real-Time Condition Monitoring of Rotating Machines

Mostafavi, A., & Sadighi, A. (2021) · 2021 9th RSI International Conference on Robotics and Mechatronics (ICRoM) · doi:10.1109/icrom54204.2021.9663495 · Cited by 20 · see citing works

A matrix analytic approach for Bayesian network modeling and inference of a manufacturing system

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Tool wear image on-machine detection based on trajectory planning of 6-DOF serial robot driven by digital twin

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A lightweight automatic sleep staging method for children using single-channel EEG based on edge artificial intelligence

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A novel transformer-enhanced and acoustic-based approach for wind turbine blade fault detection with integrated system implementation

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An IIoT approach for edge intelligence in production environments using machine learning and knowledge graphs

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Causality-guided counterfactual debiasing for anomaly detection of cyber-physical systems

Tang, W., Liu, J., Zhou, Y., & Ding, Z. (2024) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2023.3326544 · Cited by 16 · see citing works

An edge-based algorithm for tool wear monitoring in repetitive milling processes

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A Reduced-Order Digital Twin FPGA-Based Implementation With Self-Awareness Capabilities for Power Electronics Applications

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Digital Twin-assisted anomaly detection for industrial scenarios

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Optimized Task Scheduling and Virtual Object Management Based on Digital Twin for Distributed Edge Computing Networks

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A Deep Trajectory Controller for a Mechanical Linear Stage Using Digital Twin Concept

Chaiprabha, K., & Chancharoen, R. (2023) · Actuators · doi:10.3390/act12020091 · Cited by 14 · see citing works

An IoT Architecture Leveraging Digital Twins: Compromised Node Detection Scenario

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A comprehensive review of datasets for detection and localization of video anomalies: a step towards data-centric artificial intelligence-based video anomaly detection

Nayak, R., Pati, U. C., & Das, S. K. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-17889-z · Cited by 12 · see citing works

An adaptable Digital Twin model for manufacturing

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AI-based real-time anomaly detection in industrial engineering: A structured literature review, taxonomy, and research agenda

Stahmann, P., Nebel, M., & Janiesch, C. (2025) · Computers & Industrial Engineering · doi:10.1016/j.cie.2025.111236 · Cited by 12 · see citing works

A Deployable Edge Computing Solution for Machine Condition Monitoring

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Digital Twin-Driven VCTS Control: An Iterative Apporach Using Model-Based Reinforcement Learning

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Securing the Metaverse: Exploring the Role of Artificial Intelligence in Mitigating Emerging Threats in Manufacturing and Service Industries

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How digital twin technology may improve safety management: A multi-industry perspective

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Multi-modal digital twins for industrial anomaly detection: Framework, method, and application

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Physics-based modelling of robot’s gearbox including non-linear phenomena

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Digital Twins for a Sustainable Textile Industry: A Critical Analysis of Unexplored Applications and Future Directions

Angelova, R. A. (2025) · Textiles · doi:10.3390/textiles5040049 · Cited by 10 · see citing works

A framework for digital twin integration in biofabrication and a scaffold 3D bioplotting case study

Ahmed, N., Narayanan, L. K., & Shirwaiker, R. A. (2024) · Manufacturing Letters · doi:10.1016/j.mfglet.2024.09.144 · Cited by 13 · see citing works

Digital Twins in Human Activity Prediction on Gait Using Extreme Gradient Boosting Local Binary Pattern

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Acies-OS: A Content-Centric Platform for Edge AI Twinning and Orchestration

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Resource Requirements of an Edge-based Digital Twin Service: An Experimental Study

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Pervasive and Connected Digital Twins for Edge Computing Enabled Industrial Applications

Sanfilippo, F., Langås, E. F., Bukhari, H. Z., & Robstad, S. (2023) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2023.821 · Cited by 8 · see citing works

Digital twin exploration of a blended-wing-body underwater glider skeleton in the laboratory environment

Li, J., Dong, H., Long, W., Wang, P., & Wang, X. (2023) · Ships and Offshore Structures · doi:10.1080/17445302.2023.2238391 · Cited by 7 · see citing works

Ocean observing time-series anomaly detection based on DTW-TRSAX method

Wang, Y., Lyu, X., & Yang, S. (2024) · The Journal of Supercomputing · doi:10.1007/s11227-024-06183-w · Cited by 7 · see citing works

Digital Twin-Driven Physically Constrained Generative Adversarial Network for Industrial Boiler Fault Diagnosis

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A cloud-edge-based digital twin architecture for cyber-physical shop floors: design principles, function analysis, and case study

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Artificial Intelligence Enabled Digital Twin For Predictive Maintenance in Industrial Automation System: A Novel Framework and Case Study

Siddiqui, M., Kahandawa, G. C., & Hewawasam, H. S. (2023) · IEEE International Conference on Mechatronics (ICM) · doi:10.1109/icm54990.2023.10101971 · Cited by 18 · see citing works

Edge AI Based Anomaly Detection for Real Time Monitoring of IoT Enabled Industrial Systems

Aji, M. (2026) · Formosa Journal of Science and Technology · doi:10.55927/fjst.v5i9.162

A novel anomaly detection method for digital twin data using deconvolution operation with attention mechanism

Li, Z., Duan, M., Xiao, B., & Yang, S. (2023) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2022.3231923 · Cited by 45 · see citing works

TWINE: ISO 23247-compliant digital twin and explainable AI framework for anomaly detection

Iqbal, M., Suhail, S., Freudenthaler, S., Fahim, M., & Matulevičius, R. (2026) · Internet of Things · doi:10.1016/j.iot.2026.101976 · Cited by 1 · see citing works

Digital Twins for Anomaly Detection in the Industrial Internet of Things: Conceptual Architecture and Proof-of-Concept

Benedictis, A. D., Flammini, F., Mazzocca, N., Somma, A., & Vitale, F. (2023) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2023.3246983 · Cited by 85 · see citing works