Editorial: Data sciences in transportation and transit systems

Chayut Ngamkhanong, Nam Huynh, Elias Kassa, Hitoshi Tsunashima, Sakdirat Kaewunruen*

*Corresponding author for this work

Research output: Contribution to journalEditorialpeer-review

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Abstract

isruptions in the operation of our countries’ infrastructure may put the functioning of our societies and their economies at risk. Such disruptions may result from many kinds of hazards and physical and/or cyberattacks on installations and systems. Recent events have demonstrated the increased interconnection among the impact of hazards, of the two kinds of attacks and, conversely, the usefulness for operators of combining cyber and physical security solutions to protect installations of the critical infrastructure globally. New ideas and innovation for comprehensive yet installation-specific approaches are necessary to secure the integrity of existing or future, public or private, connected and interdependent assets, installations, and infrastructure systems.

This Research Topic on “Data Science in Transportation and Transit Systems” enables transparent, fair, rapid communication of research that highlights the role of big data, data sciences, artificial intelligence, and engineering in multidisciplinary areas across materials science, physics, and engineering. Emphasis is on the impact, depth, and originality of new concepts, methods, and observations at the forefront of applied sciences and engineering technologies. This topic will help us to achieve our carbon neutrality roadmap by deploying specialist technology to create a digital twin of the infrastructure system to identify the optimal pathway to net zero, which will be achieved by combining digital sensor and analytic technologies, artificial intelligence, environmental and energy footprints, and concepts that help change users’ behaviour to transform transportation and transit systems.
Original languageEnglish
Article number1066433
Number of pages2
JournalFrontiers in Built Environment
Volume8
DOIs
Publication statusPublished - 28 Oct 2022

Keywords

  • data science
  • transportation
  • transit system
  • decarbonisation
  • digital transformation (DT)

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