The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities

Support-vector networks

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The WEKA data mining software: an update

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TensorFlow: A system for large-scale machine learningPreprint

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Caffe: Convolutional Architecture for Fast Feature Embedding

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Identity mappings in deep residual networks

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Playing Atari with Deep Reinforcement Learning

Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D., & Riedmiller, M. (2013) · arXiv · doi:10.48550/arxiv.1312.5602 · Cited by 9,471

An Introduction to Kernel and Nearest-Neighbor Nonparametric Regression

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Fuzzy logic in control systems: fuzzy logic controller. I

Lee, C. C. (1990) · IEEE Transactions on Systems Man and Cybernetics · doi:10.1109/21.52551 · Cited by 5,630

Extreme Learning Machine for Regression and Multiclass Classification

Huang, G.-B., Zhou, H., Ding, X., & Zhang, R. (2011) · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · doi:10.1109/tsmcb.2011.2168604 · Cited by 5,575

Systematic Literature Reviews in Software Engineering—A Systematic Literature Review

Kitchenham, B., Pearl Brereton, O., Budgen, D., Turner, M., Bailey, J., & Linkman, S. (2009) · Information and Software Technology · doi:10.1016/j.infsof.2008.09.009 · Cited by 4,537

Digital Twin for Equipment Management of Intelligent Railway Station

Chen, R., Jin, C., Zhang, Y., Dai, J., & Lv, X. (2021) · IEEE International Conference on Digital Twins and Parallel Intelligence (DTPI) · doi:10.1109/dtpi52967.2021.9540153 · Cited by 14

Reference Architecture for Running Computationally Intensive Physics-Based Digital Twins of Heavy Equipment in a Heterogeneous Execution Environment

Zhidchenko, V., Startcev, E., & Handroos, H. (2022) · IEEE Access · doi:10.1109/access.2022.3176645 · Cited by 13

Synergistic integration of digital twins and artificial intelligence for sustainable energy and environmental systems: A comprehensive review

Raihan, A. (2026) · Sustainable Cities and Society Advances · doi:10.1016/j.scsadv.2026.100024 · Cited by 15

A modelling and simulation framework to assess integrated survivability of naval platforms in high threat environments

Woolley, A., & Whitehouse, T. (2022) · Ocean Engineering · doi:10.1016/j.oceaneng.2022.111479 · Cited by 12

Developing an integrated digital delivery framework for designing and planning construction projects: a review of interoperable digital technologies

Larbi, J. A., Tang, L., Ababio, B. K., & Antwi-Afari, P. (2024) · International Journal of Construction Management · doi:10.1080/15623599.2024.2322240 · Cited by 12

A review of in-situ measurement and simulation technologies for ceramic sintering: towards a digital twin sintering system

Chen, B., Ren, X., Diao, Q., Zou, H., Shi, X., Sui, T., Lin, B., & Yan, S. (2024) · Journal of Materials Science · doi:10.1007/s10853-024-09986-7 · Cited by 12

Critical review on integrated real-time energy management strategy and digital twin applied to hybrid electric UAVs

Cyrille, N. A., Calvin, N. J., Ghislain, M. M., & Thierry, S. M. O. (2024) · Electrical Engineering · doi:10.1007/s00202-024-02746-5 · Cited by 13

Reinforcement learning and digital twin-driven optimization of production scheduling with the digital model playground

Seipolt, A., Buschermöhle, R., Haag, V., Hasselbring, W., Höfinghoff, M., Schumacher, M., & Wilbers, H. (2024) · Discover Internet of Things · doi:10.1007/s43926-024-00087-0 · Cited by 12

Digital twin in poultry production: A framework for enhancing workforce to job market readiness

Nassar, F. S., & Abbas, A. O. (2025) · Poultry Science · doi:10.1016/j.psj.2025.105497 · Cited by 12

Digital Twins for Space Battery Management Systems: A Comprehensive Review of Different Approaches for Predictive Maintenance and Monitoring

Sbarra, R. G., Pasquali, M., Coppotelli, G., Gaudenzi, P., di Ienno, D., Ciancarelli, C., & Picci, N. (2025) · Energies · doi:10.3390/en18215858 · Cited by 12

Digital twin in the power generation industry

Choi, W., Hudachek, K., Koskey, S., Perullo, C. A., & Noble, D. R. (2024) · JMST Advances · doi:10.1007/s42791-024-00065-1 · Cited by 11

Current status and future challenges of digital twins for structural health monitoring in civil infrastructures

Parida, L., & Moharana, S. (2024) · Engineering Research Express · doi:10.1088/2631-8695/ad4aea · Cited by 11

Artificial Intelligence in Digital Twin Technology: Scientometric Insights on Architecture, Applications, and Tools

Bhatia, M., & Kumar, V. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3575476 · Cited by 15

Competencies for human–robot collaboration in the construction industry: perspectives from academia and industry

Olukanni, E. O., Akanmu, A. A., Jebelli, H., Ammar, A., & Okunola, A. (2025) · Construction Robotics · doi:10.1007/s41693-025-00156-y · Cited by 12

eXtended Reality and Artificial Intelligence in Medicine and Rehabilitation

Krilavičius, T., Paolis, L. T. D., Luca, V. D., & Spjut, J. (2025) · Information Systems Frontiers · doi:10.1007/s10796-025-10580-8 · Cited by 11

Towards enhanced cybersecurity in industrial control systems: a systematic review of context-based modeling, digital twins, and machine learning approaches

Abraham, D., Erceylan, G., Gkioulos, V., & Houmb, S. H. (2025) · International Journal of Information Security · doi:10.1007/s10207-025-01158-1 · Cited by 10

Review and Proposed Digital Twin Model for Sustainable Smart University Asset Management

Fashal, N. A., Khayat, G. A. E., & Elmorsy, S. A. (2023) · IEEE Afro-Mediterranean Conference on Artificial Intelligence (AMCAI) · doi:10.1109/amcai59331.2023.10431490 · Cited by 12

Investigating the Impact of Streetscape and Land Surface Temperature on Cycling Behavior

Qin, M., Xu, H., & Huang, J. (2024) · Sustainability · doi:10.3390/su16051990 · Cited by 10

Model-Driven Development Towards Distributed Intelligent Systems

Barriga, A., Barriga, J. A., Pérez, M. A., & Clemente, P. J. (2024) · ACM Transactions on Internet Technology · doi:10.1145/3687472 · Cited by 11

Enhancing 5G energy efficiency through digital twin networks: A comprehensive review

Maiwada, U. D., Danyaro, K. U., & Sarlan, A. B. (2024) · Digital twins and applications. · doi:10.1049/dgt2.12008 · Cited by 10

A Survey on Privacy Attacks Against Digital Twin Systems in AI-Robotics

Fernandez, I. A., Neupane, S., Chakraborty, T., Mitra, S., Mittal, S., Pillai, N., Chen, J., & Rahimi, S. (2024) · IEEE International Conference on Collaboration and Internet Computing (CIC) · doi:10.1109/cic62241.2024.00019 · Cited by 18

The development of a digital twin concept system

Duan, H., Gao, S., Yang, X., & Li, Y. (2025) · Digital Twin · doi:10.12688/digitaltwin.17599.3 · Cited by 10

Exploring the Evolution of Big Data Technologies: A Systematic Literature Review of Trends, Challenges, and Future Directions

Hakami, T. A., Alginahi, Y. M., & Sabri, O. (2025) · Future Internet · doi:10.3390/fi17090427 · Cited by 10

Virtual Energy Replication Framework for Predicting Residential PV Power, Heat Pump Load, and Thermal Comfort Using Weather Forecast Data

Minhas, D. M., Usman, M. T., Raja, I. B., Wakeel, A., Ali, M., & Frey, G. (2025) · Energies · doi:10.3390/en18185036 · Cited by 10

Advancements in fault detection and diagnosis methods for electric vehicles: a review

Kumar, M. P., Velpula, S., Saiprakash, C., & Sahoo, B. (2025) · Discover Applied Sciences · doi:10.1007/s42452-025-07758-9 · Cited by 16

Digital Twins: A Meta-Review on Their Conceptualization, Application, and Reference Architecture

Rossmann, A., & Hertweck, D. (2022) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2022.550 · Cited by 10

Prediction of photovoltaic power generation based on LSTM and transfer learning digital twin

Yang, H. L., & Wang, W. (2023) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2467/1/012015 · Cited by 12

Smart Farming Using Robots in IoT to Increase Agriculture Yields: A Systematic Literature Review

Widianto, M. H., & Juarto, B. (2023) · Journal of Robotics and Control (JRC) · doi:10.18196/jrc.v4i3.18368 · Cited by 10

Big Data Analytics for Early Detection and Prevention of Age-Related Diseases in Elderly Healthcare

Daril, M. A. M., Qayyum, S., Abbas, A. F., & Vân, N. T. (2023) · International Journal of Online and Biomedical Engineering (iJOE) · doi:10.3991/ijoe.v19i16.45035 · Cited by 9

Blockchain-based digital twin management architecture for Internet of Medical Things Networks

Gore, S. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-34226-4.00017-4 · Cited by 9

VESPACE: A verifiable blockchain-based data space solution to empower the data economy

Costagliola, A. R., Mazzocca, C., Bujari, A., Montanari, R., & Bellavista, P. (2025) · Computer Communications · doi:10.1016/j.comcom.2025.108180 · Cited by 9

Digital Twin Road: value and implications involving data and application

Haverkamp, P., Anantheswar, A., May, M., Wadlig, G., Hildebrandt, J., Thiessat, K. A., Wollny, I., Traverso, M., Müller-Mall, S., Kaliske, M., et al. (2025) · Discover Applied Sciences · doi:10.1007/s42452-025-07018-w · Cited by 10

Challenging Digital Innovation Through the OMiLAB Community of Practice

Văidian, I., Jurczuk, A., Misiak, Z., Neidow, M., Petry, M., & Nemetz, M. (2022) · Springer eBooks · doi:10.1007/978-3-030-93547-4_3 · Cited by 9

A Digital Twin Approach for deepened Classification of Patients with Hepatitis, Fibrosis and Cirrhosis

Palaniappan, R., & Surendran, S. (2022) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2335/1/012034 · Cited by 10

Massive Twinning to Enhance Emergent Intelligence

Yuan, S., Han, B., Krummacker, D., & Schotten, H. D. (2022) · IEEE Symposium on Computers and Communications (ISCC) · doi:10.1109/iscc55528.2022.9912797 · Cited by 9

Data Analytics and Visualization in Smart Manufacturing Using AI‐Based Digital Twins

Sivakumar, M., Maranco, M., Krishnaraj, N., & Reddy, U. S. (2024) · doi:10.1002/9781394303601.ch12 · Cited by 9

Digital Twins-Enabling Technologies Including AI, Sensors, Cloud, and Edge Computing

Chandhana, T., Balija, A., Kumaran, S. R. R., & Singh, B. (2023) · Advances in computational intelligence and robotics book series · doi:10.4018/978-1-6684-6821-0.ch018 · Cited by 8

The Role of Artificial Intelligence and Robotic Solution Technologies in Metaverse Design

Gökçe, N. (2023) · Studies in big data · doi:10.1007/978-981-99-4641-9_4 · Cited by 10

Strategic Decision Support Systems for Enhancing Competitive Advantage in Small and Medium Enterprises

Owusu, J., Boateng, P. A., & Yeboah, N. (2024) · IEEE SmartBlock4Africa · doi:10.1109/smartblock4africa61928.2024.10779545 · Cited by 8

Digital twin-driven sustainable energy life cycles: Technical review and Guidelines

Rabaia, M. K. H., Semeraro, C., Soudan, B., Salameh, T. S. Z., Abdelkareem, M. A., & Olabi, A. G. (2025) · Energy Nexus · doi:10.1016/j.nexus.2025.100482 · Cited by 10

A comprehensive survey on big data privacy and Hadoop security: Insights into encryption mechanisms and emerging trends

Filaly, Y., Berros, N., mendili, F. E., & Idrissi, Y. E. B. E. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.106203 · Cited by 8

Graph-theoretical mapping of cortical and subcortical network alterations in preclinical neurodegeneration

Öğüt, E. (2025) · Discover Neuroscience · doi:10.1186/s13064-025-00214-9 · Cited by 9

Digital Twin-Enabled Framework for Intelligent Monitoring and Anomaly Detection in Multi-Zone Building Systems

Hodavand, F., Ramaji, I. J., Sadeghi, N., & Goharrizi, S. Z. (2025) · Buildings · doi:10.3390/buildings15224030 · Cited by 8

DDD-GenDT: Dynamic Data-Driven Generative Digital Twin Framework

Lin, Y.-Z., Shi, Q., Yang, Z., Latibari, B. S., Satam, S., Shao, S., Salehi, S., & Satam, P. (2025) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2025.3612920 · Cited by 10

Integration of digital twins and physical AI in cyber-physical systems

Biswas, P., Kim, T. M., & Kim, W. S. (2026) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2026.200649 · Cited by 10

Model-based digital twin engineering: insights, challenges, and future directions

Zech, P., Barat, S., Nast, B., Oakes, B., Michael, J., Zschaler, S., Barn, B., & Breu, R. (2026) · Software & Systems Modeling · doi:10.1007/s10270-026-01368-8 · Cited by 12

Wrapper Functions for Integrating Mathematical Models into Digital Twin Event Processing

Jedermann, R., & Lang, W. (2022) · Sensors · doi:10.3390/s22207964 · Cited by 8

KAPETÁNIOS: Automated Kubernetes Adaptation through a Digital Twin

Zerwas, J., Krämer, P., Ursu, R.-M., Asadi, N., Rodgers, P., Wong, L., & Kellerer, W. (2022) · International Conference on the Network of the Future (NOF) · doi:10.1109/nof55974.2022.9942649 · Cited by 8

Machine learning and digital twins: monitoring and control for dynamic security in power systems

Brosinsky, C., Karacelebi, M., & Cremer, J. L. (2023) · Elsevier eBooks · doi:10.1016/b978-0-32-399904-5.00010-7 · Cited by 8

Survey on Digital Twins: from concepts to applications

Heluany, J. B., & Gkioulos, V. (2023) · International Conference on Availability, Reliability and Security (ARES) · doi:10.1145/3600160.3605070 · Cited by 8

Neural networks in closed-loop systems: Verification using interval arithmetic and formal prover

Rossi, F., Bernardeschi, C., & Cococcioni, M. (2024) · Engineering applications of artificial intelligence · doi:10.1016/j.engappai.2024.109238 · Cited by 7

A Comprehensive Review of Intelligent Home Automation Systems Using Embedded Devices and IoT

Tareq, A. A., Mostofa, M. R., Rana, M. J., & Rahman, M. (2024) · Control Systems and Optimization Letters · doi:10.59247/csol.v2i2.110 · Cited by 12

Improving the resilience of socio-technical urban critical infrastructures with digital twins: Challenges, concepts, and modeling

Gebhard, T., Sattler, B. J., Gunkel, J., Marquard, M., & Tundis, A. (2024) · Sustainability Analytics and Modeling · doi:10.1016/j.samod.2024.100036 · Cited by 10

A smart simulation-optimization framework for solar-powered desalination systems

Aldaghi, A., Gheibi, M., Akrami, M., & Hajiaghaei–Keshteli, M. (2022) · Groundwater for Sustainable Development · doi:10.1016/j.gsd.2022.100861 · Cited by 8

Relationship between industry 4.0 and patents

Rita, L. P. S., da Silva, L. S. C. V., Kaczam, F., Macêdo, M. J. F. G., de Macêdo, Á. F. P., da Silva, W. V., & da Veiga, C. P. (2023) · World Patent Information · doi:10.1016/j.wpi.2023.102221 · Cited by 8

Digital Twin in complex operations environments: potential applications and research challenges

Ghanbarifard, R., Almeida, A., & Azevedo, A. L. (2023) · Asia Conference on Information Engineering (ACIE) · doi:10.1109/acie58528.2023.00022 · Cited by 8

Artificial Intelligence in Digital Twins - a Systematic Literature ReviewPreprint

Kreuzer, T., Papapetrou, P., & Zdravković, J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4681915 · Cited by 8

A Model-Based Deep Learning Approach for Self-Learning in Smart Production Systems

Yuwono, S., & Schwung, A. (2023) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa54631.2023.10275577 · Cited by 7

A Comprehensive Exploration of Digital Twinning in Spine Surgery

Lomax, N., Vinjamuri, S., Vinjamuri, S., Franco, D. M., Schroeder, G. D., & Harrop, J. S. (2024) · Clinical Spine Surgery A Spine Publication · doi:10.1097/bsd.0000000000001748 · Cited by 7

Sustainability and Resilience in the MICS SPOKE8 Project: The Role of the Digital Twin

Berti, N., Arman, A., Esmaili, P., Zeynivand, M., Battini, D., Bianchini, D., Cristaldi, L., de Giuli, L. B., Galeazzo, A., Gruosso, G., et al. (2024) · IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) · doi:10.1109/metroxraine62247.2024.10797155 · Cited by 7

Enhancing Digital Twins With Deep Reinforcement Learning: A Use Case in Maintenance Prioritization

Chen, S., Lopes, P. V., Marti, S., Rajashekarappa, M., Bandaru, S., Windmark, C., Bokrantz, J., & Skoogh, A. (2024) · Winter Simulation Conference · doi:10.1109/wsc63780.2024.10838867 · Cited by 9

Exploring digital twin in sustainable development: a scientometric analysis

Bhatia, M., & Kumar, R. (2025) · International Journal of Data Science and Analytics · doi:10.1007/s41060-025-00872-2 · Cited by 7

Evaluating CFIR 2.0 in identifying digital twin implementation challenges in healthcare: bridging the dichotomy between engineering and healthcare communities

Xames, M. D., Topcu, T. G., Parker, S. H., Zagarese, V., & Epling, J. W. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1611225 · Cited by 6

A model-based approach for co-simulation-driven digital twins in robotics

Gil, S., Badyal, A., Miyazawa, A., Larsen, P. G., & Cavalcanti, A. (2025) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2025.105240 · Cited by 7

Digital twins as decision infrastructure: evolution, architecture, and research roadmap

Yang, C. P., Malarvizhi, A. S., Masri, Y., Smith, J. S., Li, Z., Huang, Q., Liu, L., & Kim, J. (2026) · Big Earth Data · doi:10.1080/20964471.2026.2678046 · Cited by 10

Geometric and kinetic digital twin of a body-in-white assembly system for virtual commissioning

Stetter, R., Grüble, T., & Till, M. (2023) · Procedia CIRP · doi:10.1016/j.procir.2022.12.001 · Cited by 7

Simulation-based data reduction and data processing for sheet metal forming in the hybrid twin framework

Maier, L., Ünver, B., Volk, W., & Hartmann, C. (2024) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-024-14135-0 · Cited by 7

6G smart fog radio access network: Architecture, key technologies, and research challenges

Zhang, L., Zhang, M., Liu, X., & Guo, L. (2024) · Digital Communications and Networks · doi:10.1016/j.dcan.2024.10.002 · Cited by 8

Digital Twins-enabled model for Smart Farming

Chauhan, D., Bahad, P., & Jain, R. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-28884-5.00020-8 · Cited by 9

Charting the Course: Standardization of Quality Assurance in Digital Twin Applications Across Product Lifecycle

Milisavljevic-Syed, J., Khan, M., Xia, H., Li, J.-H., & Salonitis, K. (2024) · Procedia CIRP · doi:10.1016/j.procir.2024.10.154 · Cited by 8

Application of GIS in the Maritime-Port Sector: A Systematic Review

Isbaex, C., Costa, F. D. R. F., & Batista, T. (2025) · Sustainability · doi:10.3390/su17083386 · Cited by 7

The development of a digital twin concept system

Duan, H., Gao, S., Yang, X., & Li, Y. (2022) · Digital Twin · doi:10.12688/digitaltwin.17599.1 · Cited by 20

Digital Twins for Smart Cities: Case Study and Visualisation via Mixed Reality

Piper, W., Sun, H., & Jiang, J. S. (2022) · IEEE Vehicular Technology Conference · doi:10.1109/vtc2022-fall57202.2022.10012753 · Cited by 7

A Digital Twin Generic Architecture for Data-Driven Cyber-Physical Production Systems

Iliuţă, M.-E., Pop, E., Caramihai, S. I., & Moisescu, M. A. (2023) · Studies in computational intelligence · doi:10.1007/978-3-031-24291-5_6 · Cited by 8

Research and Application of Digital Twin and Simulation Teaching Methodology in DVOR

Xiang, Z., Tian, C., Dai, Y., Xiang, H., Huang, L., Liu, X., & Zhang, Y.-H. (2025) · IEEE Access · doi:10.1109/access.2025.3539709 · Cited by 6

Human-AI Teaming in a Digital Twin Model for Virtual Product Development

Orimi, A. G., Saralajew, S., Feng, J., Dai, Z., Hamlaoui, R., Stauß, T., & Lachmayer, R. (2025) · Zeitschrift für wirtschaftlichen Fabrikbetrieb · doi:10.1515/zwf-2024-0141 · Cited by 6

RF-Based Sensing and AI Decision Support for Stroke Patient Monitoring: A Digital Twin Approach

Khan, S., Anwar, U., Khan, A., & Arslan, T. (2025) · IEEE Access · doi:10.1109/access.2025.3564887 · Cited by 6

Industry perception of competencies for human—robot collaboration in the construction industry: A Delphi study

Olukanni, E. O., Akanmu, A. A., & Jebelli, H. (2025) · Frontiers of Engineering Management · doi:10.1007/s42524-025-4224-x · Cited by 8

A replica for our democracies? On using digital twins to enhance deliberative democracy

Novelli, C., Sánchez–Vaquerizo, J. A., Helbing, D., Rotolo, A., & Floridi, L. (2025) · AI & Society · doi:10.1007/s00146-025-02511-7 · Cited by 11

A Multi-Purpose Simulation Layer for Digital Twin Applications in Mechatronic Systems

Nezzi, C., Marchi, M. D., Vidoni, R., & Rauch, E. (2025) · Machines · doi:10.3390/machines13080671 · Cited by 6

Combining simulation and virtual reality for enabling interoperable digital twins in collaborative human–robot workspaces

Cimino, A., Longo, F., Nicoletti, L., & Solina, V. (2025) · International Journal of Production Research · doi:10.1080/00207543.2025.2541018 · Cited by 7

Toward Trustworthy Digital Twinning: Taxonomy, Analysis, and Open Challenges

Azzedin, F. A., Alhazmi, T. A., & Rahman, M. M. S. (2025) · Electronics · doi:10.3390/electronics14234732 · Cited by 7

Integrating Digital Twins, Data Management and Artificial Intelligence for Predictive Maintenance in Aviation: A Comprehensive Review

Mehdipour, S., Habibzadeh, A., Esmi, N., Heravi, P., Mirsaraee, M., Shahbahrami, A., & Javanmardi, Z. (2026) · Digital twins and applications. · doi:10.1049/dgt2.70029 · Cited by 10

THE EFFECT OF OUTDOOR INQUIRY PROGRAM FOR LEARNING BIOLOGY USING DIGITAL TWIN TECHNOLOGY

Byeon, J.-H., & Kwon, Y.-J. (2023) · Journal of Baltic Science Education · doi:10.33225/jbse/23.22.781 · Cited by 7

Navigating the Ethical Landscape: Considerations in Implementing AI-ML Systems in Human Resources

Basnet, S. (2024) · International Journal of Research Publication and Reviews · doi:10.55248/gengpi.5.0324.0755 · Cited by 9

Energy 4.0: Challenges and Enablers of Digital Twin Application in Power Plant

Shah, B. S. M. I., Ishak, A. J., Hassan, M. K., & Norsahperi, N. M. H. (2024) · ELEKTRIKA- Journal of Electrical Engineering · doi:10.11113/elektrika.v23n1.487 · Cited by 6

AI Explainability Methods in Digital Twins: A Model and a Use Case

Kreuzer, T., Papapetrou, P., & Zdravković, J. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-78338-8_1 · Cited by 8

A Comprehensive Review of Challenges Using AI for Smart Manufacturing

Sharma, A., Sim, K. Y., & Chandrasekaran, S. (2025) · International Conference on Computer and Automation Engineering · doi:10.1109/iccae64891.2025.10980576 · Cited by 6

The Strategic Corporal, the Tactical General, and the Digital Coup d’oeil – Military Decision-Making and Organizational Competences in Future Military Operations

Bollmann, A. T., & Heltberg, T. (2023) · Scandinavian Journal of Military Studies · doi:10.31374/sjms.190 · Cited by 6

A Systematic Mapping Study of Digital Twins for Diagnosis in Transportation

Prikler, L. M., & Wotawa, F. (2023) · International Conference on Dependable Systems and Their Applications (DSA) · doi:10.1109/dsa59317.2023.00058 · Cited by 6

Digital Twin for Health Monitoring of a Cantilever Beam Using Support Vector Machine

Harikumar, V., & Bijudas, C. R. (2025) · Journal of Vibration Engineering & Technologies · doi:10.1007/s42417-024-01608-5 · Cited by 5

From blueprint to reality: how digital twins are shaping the architecture, engineering, and construction landscape

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