IIoT Fleet Telemetry System

Full documentation: docs/PROJECT_OVERVIEW.md — architecture, key design decisions, DevOps/infrastructure, the AI-assisted development workflow, project history, and getting started, all in one onboarding document.

Process: docs/SDD_WORKFLOW.md — the Spec-Driven Development loop this project follows: requirements → sprint files → task execution → verification → changelog.

Project Overview:

• What: A high-performance real-time fleet telemetry system consisting of a .NET 8 SignalR backend simulator and a Next.js 15 frontend dashboard for visualizing and interacting with large-scale vehicle telemetry.
• Why: To demonstrate a production-ready pipeline capable of tracking 10,000+ vehicles with low-latency updates, GPU-accelerated map rendering, and efficient UI virtualization.
• Who: Backend engineers (simulation, SignalR), frontend engineers (Mapbox/Deck.gl, React/Next.js), and system architects evaluating real-time telemetry designs.

Architecture

• Backend: backend — an ASP.NET Core 8 app that simulates vehicle telemetry, hosts a SignalR hub (/fleethub) and exposes REST metadata/log endpoints. It supports MessagePack for efficient payloads.
• Frontend: frontend — a Next.js 15 app (App Router) that connects to the SignalR hub, renders 10k+ vehicles using GPU-accelerated map layers and a virtualized sidebar list.

System Design (high level)

• Data Flow: Backend simulation loop mutates in-memory vehicle state → broadcasts updates via SignalR (MessagePack optional) → Frontend buffers/throttles updates and commits to state every ~100ms.
• Scalability Techniques: ConcurrentDictionary and object reuse on the backend to reduce GC pressure; Mapbox symbol layers and virtualized lists on the frontend to avoid DOM bloat; throttled state commits to prevent React thrashing.
• Real-time Considerations: Designed for sub-500ms broadcast loops and frontend commit windows tuned for 60FPS UI responsiveness under heavy update rates.

Quickstart

• Backend (from backend):

cd backend
dotnet restore
dotnet run

• Frontend (from frontend):

cd frontend
npm install
npm run dev

Docker

• See DOCKER_README.md for full Docker instructions and notes.
• See docs/HELM_GUIDE.md for deploying to Kubernetes via Helm.
• Quick Docker compose (builds images and starts both services):

docker-compose up --build

After startup:

• Frontend UI: http://localhost:3000
• Backend API: http://localhost:8080

Useful Files & Paths

• Backend README: backend/README.md
• Frontend README: frontend/README.md
• SignalR Hub: backend/Hubs/FleetHub.cs
• Frontend Map + Components: frontend/components

Next Steps / Tips

• Toggle MessagePack in client and server to compare bandwidth and latency.
• Adjust frontend throttling interval (SignalRPipeline/buffer commit) to balance latency vs. UI stability.
• Use the included dummy data in frontend/data for offline UI testing.

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