Related papers: Digital twin, physics-based model, and machine lea…
Current autonomous building research primarily focuses on energy efficiency and automation. While traditional artificial intelligence has advanced autonomous building research, it often relies on predefined rules and struggles to adapt to…
The simulation of a physical system in a virtual replica, known as a digital twin, is a useful way to interrogate the system non-invasively, providing the ability to perform predictive maintenance and surveillance, and to investigate…
Fully harvesting the gain of multiple-input and multiple-output (MIMO) requires accurate channel information. However, conventional channel acquisition methods mainly rely on pilot training signals, resulting in significant training…
The recent advances in the data science field in the last few decades have benefitted many other fields including Structural Health Monitoring (SHM). Particularly, Artificial Intelligence (AI) such as Machine Learning (ML) and Deep Learning…
Recent research has shown that Machine Learning/Deep Learning (ML/DL) models are particularly vulnerable to adversarial perturbations, which are small changes made to the input data in order to fool a machine learning classifier. The…
Smart maintenance of historic buildings involves integration of digital technologies and data analysis methods to help maintain functionalities of these buildings and preserve their heritage values. However, the maintenance of historic…
Smart Digital twins (SDTs) are being increasingly used to virtually replicate and predict the behaviors of complex physical systems through continual data assimilation enabling the optimization of the performance of these systems by…
The proliferation of electronic devices has greatly transformed every aspect of human life, such as communication, healthcare, transportation, and energy. Unfortunately, the global electronics supply chain is vulnerable to various attacks,…
Accurate and safety-conscious trajectory prediction is a key technology for intelligent transportation systems, especially in V2X-enabled urban environments with complex multi-agent interactions. In this paper, we created a digital…
Quantitative comparison of the quality of photoacoustic image reconstruction algorithms remains a major challenge. No-reference image quality measures are often inadequate, but full-reference measures require access to an ideal reference…
Digital Twins are part of the vision of Industry 4.0 to represent, control, predict, and optimize the behavior of Cyber-Physical Production Systems (CPPSs). These CPPSs are long-living complex systems deployed to and configured for diverse…
Digitizing physical objects into the virtual world has the potential to unlock new research and applications in embodied AI and mixed reality. This work focuses on recreating interactive digital twins of real-world articulated objects,…
Robotic systems have become integral to smart environments, enabling applications ranging from urban surveillance and automated agriculture to industrial automation. However, their effective operation in dynamic settings - such as smart…
Quantifying the uncertainty in predictive models is critical for establishing trust and enabling risk-informed decision making for personalized medicine. In contrast to one-size-fits-all approaches that seek to mitigate risk at the…
Industrial Internet of Things (IoT) enables distributed intelligent services varying with the dynamic and realtime industrial devices to achieve Industry 4.0 benefits. In this paper, we consider a new architecture of digital twin empowered…
A new network named the "Digital Twin Network" (DTN) uses the "Digital Twin" (DT) technology to produce virtual twins of real things. The network load and size continue to grow as a result of the development of 5G, the Internet of Things,…
In the context of Industry 4.0, the physical and digital worlds are closely connected, and robots are widely used to achieve system automation. Digital twin solutions have contributed significantly to the growth of Industry 4.0. Combining…
The concept of creating digital twins, connected digital models of physical systems, is gaining increasing attention for modeling and simulation of whole cities. The basis for building a digital twin of a city is the generation of a 3D city…
Human digital twins (HDTs) are dynamic, data-driven virtual representations of individuals, continuously updated with multimodal data to simulate, monitor, and predict health trajectories. By integrating clinical, physiological, behavioral,…
Calibration of dynamic models to data is an important step in building building digital twins of HVAC equipment, thermal loads and control systems. Sometimes, when a model fails to calibrate to data, a possible cause is that the model has…