Advanced Cognitive Computing and Big Data Systems in Intelligent Transportation
A special issue of Electronics (ISSN 2079-9292).
Deadline for manuscript submissions: closed (15 May 2025)
Special Issue Editors
Interests: deep learning; machine learning; data augmentation; big data; data analytics
Special Issue Information
Dear Colleagues,
The transport sector stands at a critical juncture, facing immense challenges such as congestion, environmental impacts, safety concerns, and the need for sustainable practices. As one of the most resource-intensive industries globally, the transportation landscape demands innovative solutions that can adapt to rapidly changing dynamics. In this context, cognitive computing and big data technologies emerge as transformative forces capable of revolutionizing how we approach transportation.
This Special Issue aims to delve into the groundbreaking intersection of these advanced technologies with Intelligent Transportation Systems (ITS). By simulating human thought processes and analyzing vast datasets, cognitive computing and big data analytics offer unparalleled opportunities to enhance real-time decision-making and operational efficiency. The urgency to adopt these technologies has never been more pronounced, as cities grow increasingly congested and the imperative for sustainable transport solutions becomes critical.
In light of these pressing issues, this Special Issue seeks to foster a vibrant dialog among researchers, practitioners, and policymakers. We invite original research articles and comprehensive review articles that not only highlight innovative ITS solutions, but also demonstrate the practical implications of cognitive computing and big data in tackling real-world transportation problems. The objective is to inspire a new wave of interdisciplinary research that bridges technological advancements with tangible outcomes in the transport sector.
Potential submission topics include, but are not limited to, the following:
- Cognitive computing.
- Big data analytics.
- Intelligent Transportation Systems (ITS).
- Autonomous vehicles.
- Traffic management.
- Predictive maintenance.
- Smart logistics.
- Real-time data processing.
- Transportation efficiency.
- Data-driven solutions.
- Connected vehicles.
- Machine learning.
- Artificial intelligence.
- Mobility as a Service (MaaS).
- Sensor technologies.
- Urban mobility.
- Sustainable transportation.
- Data visualization.
- Transport policy.
- Fleet management.
- Route optimization.
- Infrastructure development.
- Smart cities.
- User-centric design.
Dr. Teerath Kumar
Dr. Malika Bendechache
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. Electronics 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
- Intelligent Transportation Systems
- big data analytics
- cognitive computing
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