Modern intelligent urban mobility applications are underpinned by large-scale, multivariate, spatiotemporal data streams. Working with this data presents unique challenges of data management, processing and presentation that is often overlooked by researchers. Therefore, in this work we present an integrated data management and processing framework for intelligent urban mobility systems currently in use by our partner transit agencies. We discuss the available data sources and outline our cloud-centric data management and stream processing architecture built upon open-source publish-subscribe and NoSQL data stores. We then describe our data-integrity monitoring methods. We then present a set of visualization dashboards designed for our transit agency partners. Lastly, we discuss how these tools are currently being used for AI-driven urban mobility applications that use these tools.
@article{arxiv.2101.09261,
title = {Efficient Data Management for Intelligent Urban Mobility Systems},
author = {Michael Wilbur and Philip Pugliese and Aron Laszka and Abhishek Dubey},
journal= {arXiv preprint arXiv:2101.09261},
year = {2021}
}