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Digital Twins, Sensing Technologies and Automation in Industry 4.0

This special issue belongs to the section “Sensors and Robotics“.

Special Issue Information

Dear Colleagues,

This Special Issue aims to provide a comprehensive overview of the current practices of digital twin, digital transformation, sensing technologies, Internet of Things, engineering, and automation. In addition, the SI will include papers suggesting the future agenda based on an intensive literature review. This SI aims to collect all the practices that may help practitioners to improve their productivity, safety, or quality.

This Special Issue covers a wide range of technologies and methods that can be employed to analyse the data, explore patterns, and predict events, properties, and features of any phenomenon, and visualise the analysis outcome. The context of applications can be a city, urban transportation, construction, or project. This Special Issue welcomes submissions from diverse disciplines, including research projects with different approaches, including quantitative, computational, visual analytics, data mining, analysis of the spatial and morphological structure of cities, urban transportation, and construction systems and activities. We encourage authors to develop or clarify the implications of the following topics and technologies in smart cities, infrastructure, and construction.

Potential topics include but are not limited to the application of digital and sensing technologies, robotics, and automation to address the following objectives:

  • Automation in construction, mining, manufacturing, and smart cities;
  • Sensors and Internet of Things;
  • Improving Smart Cities and intelligence infrastructure;
  • Facilitating the implementation of Sustainable Development Goals;
  • Improving quality by detecting damages, cracks, and defects;
  • Automating the modular and off-site construction;
  • Implementing Industry 4.0 in different sectors;
  • Improving the resilience of supply chain management;
  • Improving safety and manage risks and hazards;
  • Monitoring disaster management.

You may choose our Joint Special Issue in Automation.

Dr. Samad Sepasgozar
Dr. Rafiq Ahmad
Dr Limao Zhang
Dr. Sara Shirowzhan

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 250 words) can be sent to the Editorial Office for assessment.

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. Sensors 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 2600 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 transformation, digitization
  • Hybrid and smart manufacturing
  • BIM advances and standards
  • Automation in design and construction operation
  • Visualization of digital information and services
  • Interoperability
  • Robotics and manipulator arms
  • Additive manufacturing (3D printing)
  • Automatic sensing
  • Data acquisition and sensor fusion
  • Sensor, smart devices, and IoT applications
  • Data analytics and wearable sensors
  • Unmanned aerial vehicles/drones
  • Machine learning
  • Artificial intelligence
  • Networking applications
  • Big data analytics
  • Mixed reality and immersive technologies
  • Computer vision
  • Simulation
  • Knowledge-based systems (ontologies)
  • Design for X (automation, additive manufacturing)
  • Smart manufacturing systems design and engineering

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Sensors - ISSN 1424-8220