Efficient Data Management for Intelligent Urban Mobility Systems

TL;DR

This paper introduces an integrated, cloud-based data management framework for urban mobility systems, addressing challenges in handling large-scale spatiotemporal data for transit agencies.

Contribution

It presents a novel cloud-centric architecture with data integrity monitoring and visualization tools tailored for intelligent urban mobility applications.

Findings

Effective handling of large-scale multivariate data streams

Enhanced data integrity monitoring methods

Practical visualization dashboards for transit agencies

Abstract

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.