ITSBD2016

Scope of the workshop

All modes of transportation are now generating unprecedented amounts of data. While cargo and people are being transported across air, sea and land, a multitude of sensors are reporting on their constantly changing state. These firehoses of data, hold key knowledge for deciphering the complexity of transport, which amongst others includes capturing methods of optimizing supply chains, understanding fluctuations in demand, reducing emissions and improving safety and efficiency of operations. Unfortunately, current state of the art techniques and technologies are incapable of dealing with these growing volumes of high-speed, loosely structured, spatiotemporal data streams that require real-time analysis in order to produce actionable intelligence. It is a general belief that we currently lack infrastructures capable of storing, analyzing and correlating big data in a holistic way and under (even soft) real-time constraints. Extracting knowledge from diverse data sources requires the development of innovative algorithms, services and architectures capable of fusing and ingesting data at such volume, velocity and variety.

Intelligent solutions are in demand which exhibit the characteristics of autonomic and intelligent big data mining, capable of reducing data dimensionality and resolving the complexity of the problem state in an automatic or semi automatic way. A new dimension of possible services is revealing based on the innovative dynamics and perspectives of machine learning and automation of knowledge generation and exploitation. Collaborative research is necessary at the intersection of transport and the emerging Information and Communication Technology. This workshop invites research communities from a diverse set of scientific areas such as artificial intelligence, evolving and intelligent systems, big data, cloud computing, information fusion and distributed systems to publish their work and share opinions regarding real world applications, challenges and viable solutions to the potential new generation services emerging from the wealth of transportation data available today.

Today more than ever, collaborative research is necessary at the intersection of the transportation domain and Information and Communication Technology. This workshop invites research communities from a diverse set of scientific areas such as artificial intelligence, evolving and intelligent systems, big data, cloud computing, information fusion and distributed systems to publish their work and share opinions regarding real world applications, challenges and viable solutions to the potential new generation services emerging from the wealth of transportation data available today.

The topics of this workshop revolve around two interrelated themes,

• Real world applications and case studies of data driven intelligent transportation systems
• Algorithms and Architectures for data driven intellegent transportation systems

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Real world Data Driven transportation applications and architectures

I. Real world applications and systems deployed to solve intelligently big data issues in the transportation domain. This workshops invites papers describing case studies from all areas of transportation which benefit from big data processing including,

• Smart Ports and Shipping
• Smart Rail
• Smart Freight Transportation
• Smart Aviation

Including,

• Data driven implementations of Autonomous transportation
• Implementations of Intelligent Supply chains
• Applications and deployments of cloud computing and distributed platforms in transport
• Sensor networks and IOT implementations in transport

II. Algorithms & Methods

Intelligent algorithms for fusing, ingesting, learning and reducing the dimensionality of data in the transportation domain including

• Deep learning architectures
• Compression and dimensionality reduction
• Efficient learning and clustering at scale
• Time series prediction algorithms
• Statistical models
• Real-time forecasting
• Approaches of traffic simulation
• Prediction of chaotic time series
• Evolutionary algorithms for time series prediction

Instructions for authors

Papers submitted to the workshop should be written in English conforming to the Springer format. Original works submitted as a regular paper limited to a maximum of 14 pages in springer format will be published in the proceedings to be available electronically as a springer book in "Advances in intelligent systems and computing series".

Paper submission: May 15th May 30th (extended), 2016

Notification of paper acceptance: June 15th, 2016

The submission Web site for ITSBD2016 is HERE

Workshop proceedings will be published by Springer

Extended versions of selected papers which present an evolving aspect, will be invited by the program committee for publication, after further revision, in a Special Issue on Evolving Systems for Smart Transport and Big Data Analytics of the Journal of Evolving Systems (Springer).

Please email inquiries concerning the workshop to: dzissis_AT_aegean.gr or tserpes_AT_hua.gr

Support

This workshop is partly supported by