Mobility Data Stream Processing Beyond the Cloud
The propagation of Internet-of-Things (IoT) sensors aboard mov ing objects has led to continuous spatiotemporal data streams that demand on-device, low-latency analysis. However, the underly ing systems for processing this streaming data are ill-prepared. On the one hand, common stream processing engines lack sup port for spatiotemporal operations. On the other hand, existing libraries for spatiotemporal data are optimized for historical data rather than real-time processing. To bridge this gap, we present MobilityNebula, an integration between MEOS (Mobility Engine Open Source), a lightweight C library for spatiotemporal data man agement, and NebulaStream, a stream processing system designed for the edge–fog–cloud continuum. We evaluated MobilityNebula by deploying the system on edge devices, ingesting data from the Belgian railway operator (SNCB) trains, and performing real-time geospatial processing for point-based queries.
