Image Processing and Computer Vision Sensing Technologies in Engineering Applications and Digital Twins

Dear Colleagues,

Digital twins comprise virtual replicas of physical instances aiming to accurately simulate and predict functionalities and responses to external stimuli based on real data. This multidisciplinary technology capitalizes on the progress performed in both AI technologies and embedded sensor collection and big data analysis. Depending on the application itself, different sensor modalities can be utilized to provide input data to the involved simulators. Considerable effort from the research community is dedicated to the representation accuracy for the physical products and real-time processing of the acquired data using low-cost and widely used cameras. In this direction, it is of paramount importance for such systems and applications to design, develop and incorporate solutions that inherently exploit the basic principles of a Digital Twin. For applications where the digital replica of its visualization is required, various technologies that process visual and/or similar optronics data can be used while the same components can be used as sensing technologies to feed the Digital Twin with necessary information for the simulation process.

This Special Issue aims to explore recent advances in Optronics Sensing Technologies focusing though in relevant to Digital Twins domains such as 3D re-construction models and multi-object detection and localization. Specifically, novel contributions that will explore their validity and applicability for a Digital Twin for visual data, independently of the application (e.g., maintenance, construction, surveillance) as well as review articles that can facilitate the community towards a more effective research building are requested to contribute to the objectives of this Special Issue.

Dr. Stefanos Vrochidis
Dr. Konstantinos Ioannidis
Dr. Nikolaos I. Dourvas
Guest Editors

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• real-time 3D reconstruction using visual data
• AI-based digital counterparts of physical objects
• SLAM techniques
• real-time multi-object detection and localization
• aerial imagery and photogrammetry
• simulations for predictions on visual data
• smart optronics systems