We presented our work on data-driven smart mobility at the Workshop on Smart Cities & Connected Communities. This Workshop aims to bring together leaders in community and economic development, government, science, and technology to chart a course for future R&D investment and build collaborative private, non-profit, and public sector partnerships that address sustainability challenges for livable communities.
Our work combined social media and open data,data from physical sensors collected in a sub-area controlled by an adaptive urban traffic control system. The aim was to disclose how we could utilize the combined data for a better understanding on urban mobility networks and activity patterns in urban environments, and how we may take advantage of such combined data and use data analytics and machine learning to improve various urban mobility applications such as anomaly traffic detection and reasoning, crash analysis, incident impact analysis, and traffic demand analysis.
These knowledge would significantly contribute to deeper understandings and potential improvements that lead to smart cities with connected communities.