Industrial IoT, Logistics & Vehicle Telematics•5 Weeks Delivery•London & Tangier

Atlasvision — Industrial IoT & Real-Time Fleet Telemetry

Real-Time Edge Telematics Processing with Sub-50ms Map Rerendering

Architected a high-throughput telematics ingestion pipeline handling 45,000 sensor events/second at the edge, paired with a GPU-accelerated 60 FPS vector map visualization dashboard.

Peak Ingestion Throughput45,000/sTelemetry events ingested without queue backlog

End-to-End Latency< 48msVehicle CAN-bus trigger to dispatch UI update

Map Frame Rate60 FPSHardware-accelerated WebGL vector rendering

Infrastructure Uptime99.99%Zero unplanned outages across 12 months

The Architectural Challenge

Atlasvision monitors over 12,000 commercial vehicles transmitting high-frequency GPS, accelerometer, and CAN-bus engine diagnostics every 250 milliseconds. Their existing Node.js architecture was collapsing under peak ingestion bursts, causing telemetry lag spikes up to 4 minutes and browser lockups on dispatch maps.

Core Bottlenecks Identified During Technical Audit:

WebSocket connection exhaustion under 12,000 continuous vehicle streams.

PostgreSQL write-amplification and table locking during ingestion surges.

Browser DOM throttling when rendering thousands of animated GPS vectors simultaneously.

No edge-filtering mechanism to drop redundant stationary sensor pings.

The Engineering Solution

We deployed an edge-first ingestion tier on Cloudflare Workers utilizing WebSockets and Durable Objects. Stationary pings are filtered at the edge, reducing ingestion load by 42%. Raw telematics events are batched into a distributed TimescaleDB time-series cluster via Kafka queues. The operator visualization interface was engineered using Next.js 15 and WebGL/MapLibre GL, streaming delta updates to render thousands of moving vehicles at a solid 60 FPS without dropping frames.

Edge Filtering with Cloudflare Workers

Filtering duplicate telemetry events at the network edge cut database write I/O by 42% and saved over $3,500/month in cloud infrastructure costs.

WebGL Vector Engine vs SVG/DOM Map Markers

Replacing standard Leaflet DOM markers with WebGL-buffered particle layers allowed smooth 60fps pan and zoom even with 10,000+ vehicle clusters on screen.

Architecture Highlights & Deliverables:

Distributed edge ingestion absorbing 45,000 telemetry events per second.

MapLibre GL WebGL-accelerated rendering capable of displaying 15,000 active units.

Sub-50ms end-to-end latency from vehicle sensor ping to dispatch monitor display.

Automated geofencing alert triggers evaluated at the edge in under 12 milliseconds.

Core Web Vitals & Telemetry Audit

Lighthouse Perf98/100

Largest Contentful Paint0.74s

Interaction to Next Paint32ms

Edge Response (TTFB)28ms

Technology Stack

Edge IngestionCloudflare Workers

Real-Time StateDurable Objects

Time-Series StoreTimescaleDB

Operator DashboardNext.js 15

GPU VisualizationMapLibre GL (WebGL)

Message BrokerApache Kafka

"The difference was night and day. We went from our dispatch maps freezing when 500 trucks updated at once to tracking 12,000 vehicles in real-time at 60 FPS. TripleW's architectural precision is unmatched."

Edward ThorntonChief Technology Officer, Atlasvision Fleet Systems

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