Architecture patterns for ingesting LoRaWAN, NB-IoT, and MQTT sensor data into PostGIS, and rendering it on interactive maps in sub-200ms.
A spatial IoT stack has three distinct layers: ingestion from heterogeneous sensor networks, spatial storage that keeps location and time queryable together, and rendering that stays responsive as the sensor fleet grows into the thousands.
On ingestion, LoRaWAN and NB-IoT devices typically arrive via a network-server webhook, while other fleets speak MQTT directly. We normalise both into a common event schema before they ever touch the database, so downstream code does not need to know which transport a reading came from.
PostGIS is the natural home for the resulting data: spatial and temporal indexes on the same table let you query "which sensors reported abnormal readings in this polygon in the last hour" without a separate time-series database bolted on the side.
For rendering, the goal is sub-200ms map interactions even as sensor counts climb. Vector tiles generated on a schedule (or on write, for lower-volume fleets), combined with clustering at low zoom levels, keep the front end fast without pre-aggregating away the detail engineers need at high zoom.
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