From Sensing Technology towards Digital Twin in Applications
A special issue of Inventions (ISSN 2411-5134). This special issue belongs to the section "Inventions and Innovation in Design, Modeling and Computing Methods".
Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 20621
Special Issue Editor
Interests: human interface sensor; self-powered sensor; wearable sensor; digital twin; data confusion
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Sensing technology drives the motivation of innovation in digital technology, especially the technology in data acquisition, machine learning, digital twin, and sustainable materials-based electronics. With the aid of the new technologies in sensing, human–machine connection, data handling, machine learning, and digital twin in the industrial area, a general conclusion on these technologies needs to be concluded for researchers in further thinking. Therefore, sensing towards digital twin technology has been studied and integrated into many fields in extensive application in traditional industrial fields, such as automatic driving, smart city, medical care, intelligent robot, etc.
This Special Issue is aimed at providing selected contributions on advances in physical sensing in machine learning, human–machine interface, data confusion, and various potential applications from sensors towards digital twin innovation. Potential topics include, but are not limited to:
- Physical sensing technologies, such as wearable sensors, nano/microsensors;
- Data confusion and machine learning;
- Modeling and simulation technology of virtual space;
- Human–computer interaction and collaboration between virtual models and physical entities;
- Intelligent decision-making based on digital twin technology;
- Human factors analysis and optimization related to a digital twin.
Special thanks to Dr. Wenyu Wu for his assistance and great support in this Special Issue.
Dr. Jianxiong Zhu
Guest Editor
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Keywords
- physical sensing
- machine learning
- data management
- human–computer interaction and collaboration
- dynamic evaluation
- intelligent decision-making
- visualization
- digital twin
- smart system
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