Review
Remote Sensing
Ville V. Lehtola, Mila Koeva, Sander Oude Elberink, Paulo Raposo, Juho-Pekka Virtanen, Faridaddin Vahdatikhaki, Simone Borsci
Summary: Digital twins are useful for improving efficiency and meeting the needs of cities. They should contain all information about the city and provide meaningful representations for specific applications. With the use of artificial intelligence techniques, digital twins can be autonomously updated.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Medicine, General & Internal
Filippo Pesapane, Anna Rotili, Silvia Penco, Luca Nicosia, Enrico Cassano
Summary: A digital twin is a virtual model that accurately reflects a physical thing or system, and can be applied in various fields such as healthcare to improve personalized medicine, conduct virtual clinical trials, and population studies. Its further development and application may revolutionize disease detection and management, although challenges remain in its development. The current operating models are undergoing structural modifications, with radiologists playing a key role in guiding the introduction of this technology into healthcare.
JOURNAL OF CLINICAL MEDICINE
(2022)
Review
Chemistry, Multidisciplinary
Adnane Drissi Elbouzidi, Abdessamad Ait El Cadi, Robert Pellerin, Samir Lamouri, Estefania Tobon Valencia, Marie-Jane Belanger
Summary: In the era of industry 5.0, digital twins (DTs) have become increasingly important in contemporary society, particularly in manufacturing, production, and operations. They have the ability to supervise system evolution, run simulations, and are highly compatible with artificial intelligence. Despite their potential benefits, the utilization of digital twins for warehouse management has been relatively neglected, despite its importance in ensuring supply chain and production uptime.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Analytical
Hawazin Faiz Badawi, Fedwa Laamarti, Abdulmotaleb El Saddik
Summary: This research introduces a new digital twin model aimed at filling the research gap in the field of city services. Designed using the ISO 37120 standard, the model ensures interoperability of city services and allows for easy comparison and analysis of services across cities. Comparisons of digital twin sequences for services in Boston and Quebec City show a 46.5% similarity, providing preliminary evidence for the feasibility of the proposed model and framework.
Article
Computer Science, Interdisciplinary Applications
Long Xi, Yan Zhao, Long Chen, Qing Hong Gao, Wen Tang, Tao Ruan Wan, Tao Xue
Summary: This paper proposes a novel deep learning-based computational framework for reconstructing high-quality 3D point clouds from single monocular endoscopic images. The proposed methods outperform both state-of-the-art learning-based and non-learning based methods for 3D point cloud reconstruction. The framework is capable of producing high-quality, dense 3D endoscopic point clouds from incomplete data.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2021)
Review
Health Care Sciences & Services
Parisa Gazerani
Summary: Intelligent digital twins resemble their real-life counterparts and enable real-time monitoring of patients in health and medical care. They collect diverse digital data using artificial intelligence, machine learning, IoT, and cloud computing, providing information on health conditions and therapeutic responses. Intelligent digital twins facilitate data-driven clinical decision making and personalized care.
JOURNAL OF PERSONALIZED MEDICINE
(2023)
Review
Materials Science, Multidisciplinary
Surya R. Kalidindi, Michael Buzzy, Brad L. Boyce, Remi Dingreville
Summary: This paper explores a new perspective on applying digital twins to accelerate materials innovation efforts, considering materials as complex multiscale physical systems. Digital twins can effectively capture the form and function of materials, revealing the evolution of structure, process, and performance over time.
FRONTIERS IN MATERIALS
(2022)
Article
Environmental Studies
Arman Hazrathosseini, Ali Moradi Afrapoli
Summary: The weaknesses of conventional simulations and the increasing capabilities offered by technological trends have driven the surface mining industry towards Mining 4.0. The Digital Twin concept, with its focus on real-time data exchange and cognitive decision-making, is seen as the key to the mines of the future. This research provides a comprehensive review of simulation applications in surface mining, dissects the concept of twinning, unveils an exemplary architecture for Digital Twin in surface mines, and explores the challenges and opportunities of this disruptive technology.
Article
Computer Science, Information Systems
Florian Stadtmann, Adil Rasheed, Trond Kvamsdal, Kjetil Andre Johannessen, Omer San, Konstanze Kolle, John Olav Tande, Idar Barstad, Alexis Benhamou, Thomas Brathaug, Tore Christiansen, Anouk-Letizia Firle, Alexander Fjeldly, Lars Froyd, Alexander Gleim, Alexander Hoiberget, Catherine Meissner, Guttorm Nygard, Jorgen Olsen, Havard Paulshus, Tore Rasmussen, Elling Rishoff, Francesco Scibilia, John Olav Skogas
Summary: This article provides a comprehensive overview of the applications of digital twin technology and its capability levels in the wind energy industry, and identifies the challenges and future research needs in this field.
Article
Remote Sensing
ShaoCong Liu, Tao Wang, Yan Zhang, Ruqin Zhou, Chenguang Dai, Yongsheng Zhang, Haozhen Lei, Hanyun Wang
Summary: This study focuses on the detection of 3D keypoints for large-scale point clouds using deep learning. Four different detection methods based on the D3Feat framework are discussed and evaluated on indoor and outdoor point cloud datasets. The results show that the Multi-layer Perceptron (MLP) based method achieves the best inlier ratios and performs state-of-the-art registration in large-scale point cloud applications.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Computer Science, Artificial Intelligence
Mohammad (Behdad) Jamshidi, Saleh Sargolzaei, Salimeh Foorginezhad, Omid Moztarzadeh
Summary: A new approach to the digital twinning of bacteria has been presented in this research, using deep learning models to speed up bacteria research and reduce diagnostic errors, improving the efficiency of treatment.
APPLIED SOFT COMPUTING
(2023)
Review
Pharmacology & Pharmacy
Maria Bordukova, Nikita Makarov, Raul Rodriguez-Esteban, Fabian Schmich, Michael P. Menden
Summary: The concept of Digital Twins in drug development and clinical trials has the potential to advance precision medicine by improving efficiency and supporting biomarker discovery. Generative artificial intelligence plays a crucial role in creating realistic and complex data for Digital Twins.
EXPERT OPINION ON DRUG DISCOVERY
(2023)
Article
Engineering, Manufacturing
D. R. Gunasegaram, A. B. Murphy, A. Barnard, T. Debroyy, M. J. Matthews, L. Ladani, D. Gu
Summary: This article discusses the application of artificial intelligence in digital manufacturing processes, particularly in the realm of metal additive manufacturing. Digital Twins will play a crucial role in autonomously supervising processes and providing optimal processing routes for practitioners. Overcoming technical barriers, such as developing multi-scale multi-physics models, and non-technical barriers, such as standardization and collaboration across different types of institutions, are essential for successful implementation of AI capabilities in manufacturing processes.
ADDITIVE MANUFACTURING
(2021)
Review
Computer Science, Information Systems
Homa Masoumi, Sara Shirowzhan, Paria Eskandarpour, Christopher James Pettit
Summary: The field of City Digital Twins has rapidly evolved with the support of digital infrastructure and IoT technologies. However, there is a gap in systematic reviews and the maturity of City Digital Twins on an urban scale. In our work, we conducted a literature review and found that the majority of studies are at initial to medium stages of maturity, focusing on 3D modeling and visualization. To achieve higher maturity levels, advanced technologies such as cloud computing, AI, BIM, and GIS are needed. Further research should include real-time data analytics, public participation capabilities, and improved storage and computation infrastructure.
Article
Chemistry, Multidisciplinary
Ibrahim Yitmen, Sepehr Alizadehsalehi, Ilknur Akiner, Muhammed Ernur Akiner
Summary: In the digital transformation era in the Architecture, Engineering, and Construction (AEC) industry, Cognitive Digital Twins (CDT) are introduced to support decision-making in building lifecycle management (BLM) as part of Construction 4.0. However, there are challenges in understanding the real impact of integrating CDT with Machine Learning, Cyber-Physical Systems, Big Data, Artificial Intelligence, and Internet of Things technologies for process optimization in the building asset lifecycle.
APPLIED SCIENCES-BASEL
(2021)