Digital Twins: Simulation, Optimisation, and Automated Operations in the Built Environment
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (29 November 2021) | Viewed by 10659
Special Issue Editors
Interests: digital twins; smart infrastructure; augmented reality; virtual reality; machine learning; optimisation; technical simulations
Interests: specification and implementation of building/district/city data storage; Internet of Things (IoT) and its application to the monitoring and control of the built environment; data analytics, including machine learning and artificial intelligence; application of cloud/distributed computing to data storage and processing for built environment applications; semantics of data within the built environment
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The emergence of the Digital Twin paradigm for built assets has been possible, primarily, due to recent technological advances on sensors, the Internet of Things (IoT), and cloud computing. These technologies enable real-time data collection, communication, and computation, required by digital twins. However, beyond real-time monitoring of built assets, few advancements have been reported in the literature on simulation, optimisation, and automated operations approaches concerning built assets. Ideally, a Digital Twin will leverage real-time sensor data to simulate operations and change control parameters accordingly.
The purpose of this Special Issue is to contribute innovative research to the built environment field by showcasing simulation, optimisation, and automated operations approaches that leverage the Digital Twin paradigm across a wide range of built environment use-cases. Our objective is to compile an outstanding collection of research papers in the field of simulation, optimisation, and approaches for automated operations driven by Digital Twins in the built environment.
We encourage authors to consider this Special Issue as an opportunity to go beyond traditional disciplinary boundaries in computer science and the built environment; and to engage more broadly with varied approaches to simulation and automated operations. Researchers are invited to share their original research (theoretical and experimental), case studies, and comprehensive review papers addressing (but not limited to) the following subjects:
- Simulation approaches for Digital Twins
- Digital Twin approaches to optimal operations
- Digital Twin approaches to optimised designs
- Digital Twin approaches to automated operations
- Simulations that use real-time sensor data as inputs to adjust control parameters
- Validation approaches for Digital Twin simulations
- Calibration approaches for Digital Twin models
- Case studies addressing DT simulation, optimisation, and automated operations for any phase of built and infrastructure assets lifecycle.
Dr. Manuel Davila Delgado
Dr. Tom Beach
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- digital twin
- simulations
- optimisation
- model validation
- optimal operations
-
automated operations
-
data-driven modelling
-
real-time modelling
-
human–machine interaction
-
autonomous agents
-
multi-agent systems
-
Markov processes
-
behavioural cloning
-
inverse reinforcement learning
-
imitation learning
-
Q learning
-
deep reinforcement learning
-
reinforcement learning
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.