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MDASC 2019 - 2019 International Workshop on Mobility Data Analytics for Smart Cities

Date2019-06-10 - 2019-06-13

Deadline2019-03-04

VenueHong Kong, Hong Kong SAR Hong Kong SAR

Keywords

Websitehttps://smalloshin.wixsite.com/mdasc2019

Topics/Call fo Papers

Smart City concepts are based on the use of new technologies to improve cities’ efficiency, livability, inclusiveness, and sustainability. Citizens in smart cities today generate massive amount of data traces. These include: (i) sensor, image, and video data collected by the existing public transport infrastructure; (ii) train and bus trips recorded by electronic fare card systems; (iii) taxi bookings and taxi trips recorded by mobile apps; (iv) bicycle rental and biking trips recorded by bike sharing apps; and (v) social media posts on public transport events. These mobility data offer new opportunities for research in information retrieval, database, data mining and machine learning to develop cutting-edge technologies that empower cities to establish intelligent transportation networks and optimize urban mobility for citizens, such as identifying congestion and reroute traffic, alerting citizens to parking options, ensuring consistent transit vehicle operation with predictive maintenance, and developing programs to incentivize transit use.
The MDASC workshop aims to bring researchers and practitioners across different big data , artificial intelligence, and public transportation research communities together in a unique forum to share the state-of-the-art technologies.
It welcomes researchers and practitioners to share the latest breakthroughs in analysing transport related data for improving commuting experience in public transport systems. These could include data science studies on commuter behavior, public transport data analytics applications and systems, large-scale behavioural experiments on public transport users, and simulation and visualization using massive public transport data. The MDASC workshop will focus on application inspired novel findings, methods, systems and solutions which demonstrate the impact of big data analytics on public transport experience.

Last modified: 2019-02-12 15:43:18