A Perspective on the Challenges and Opportunities for Privacy-Aware Big Transportation Data

Autor:	Zachary Patterson, Godwin Badu-Marfo, Bilal Farooq
Rok vydání:	2019
Předmět:	FOS: Computer and information sciences Computer Science - Computers and Society Computer science Scale (chemistry) Computers and Society (cs.CY) Perspective (graphical) Inference Computational intelligence General Medicine Data science
Zdroj:	Journal of Big Data Analytics in Transportation. 1:1-23
ISSN:	2523-3564 2523-3556
DOI:	10.1007/s42421-019-00001-z
Popis:	In recent years, and especially since the development of the smartphone, enormous amounts of data relevant for transportation have become available. These data hold out the potential to redefine how transportation system (i.e. design, planning and operations) is done. While researchers in both academia and industry are making advances in using this data to transportation system ends (e.g. information inference from collected data), little attention has been paid to four larger scale challenges that will need to be overcome if the potential for Big Transportation Data is to be harnessed for transportation decision-making purposes. This paper aims to provide awareness of these large-scale challenges and provides insight into how we believe these challenges are likely to be met. Comment: Accepted for publication in the Journal of Big Data Analytics in Transportation
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd399e8a9b9d1d2249507e8df0f7d5d6 https://doi.org/10.1007/s42421-019-00001-z Zobrazit plný text záznamu