Dear colleagues, we would like to bring to your attention the following Special Session, organised within the 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) conference, to take place in Naples, Italy, in June 2017.
http://www.mt-its2017.org/index.php/8-special-sessions/8-big-data-for-its-experiences-from-the-field-and-academia
Big Data for ITS: experiences from the field and academia
Francisco Camara Pereira, Antoniou Constantinos
It has now been 18 years, since John Mashey[1] reportedly associated the term "Big Data” with large, heterogeneous and/or intensively streamed datasets. In this session, we make a balance of the role of Big Data in Models and Technologies for ITS systems through sharing experiences and case studies ranging from “classical” (but sometimes massive) datasets like vehicle counters to cellphone, Bluetooth or WiFi based traffic counters; from structured and well-defined data types such as smartcard social demographic information, to unstructured and subjective data, such as text and social media; from infrastructure and surveillance data (e.g. cameras) to contextual and crowd sourced data, such as weather information, environmental sensing.
Are we taking advantage of such data to the best? What are the greatest challenges and limitations? What are the key research needs for the coming years?
1. Steve Lohr (1 February 2013). "The Origins of 'Big Data': An Etymological Detective Story". New York Times. Retrieved 28 September 2016.
With best regards,
Francisco Pereira
Machine Learning for Mobility group
Transport Modeling Division
Technical University of Denmark (DTU)
