The latest articles on DEV Community by Mohammed-Fayaz-Ahamed (@mohammedfayazahamed). https://dev.to/mohammedfayazahamed https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F4025087%2F69223a23-6b92-43a0-a0c6-2e9c40b29297.png https://dev.to/mohammedfayazahamed en Mohammed-Fayaz-Ahamed Sat, 11 Jul 2026 11:26:01 +0000 https://dev.to/mohammedfayazahamed/building-a-telemetry-ingestion-api-for-evtol-prototyping-with-fastapi-and-pydantic-2l8 https://dev.to/mohammedfayazahamed/building-a-telemetry-ingestion-api-for-evtol-prototyping-with-fastapi-and-pydantic-2l8 <p>Every eVTOL startup I talk to has the same problem: flight test data scattered across spreadsheets, CSVs, and custom scripts that break every other week. No standard format. No validation. No easy way to query what happened during Test 47.</p> <p>I hit this wall myself. So I built <strong>aero-telemetry</strong>, a lightweight, open-source telemetry ingestion API for aerospace prototyping.</p> <h2> What It Does </h2> <ul> <li> <strong>Ingest sensor data</strong> via HTTP: battery state, GPS, IMU, motor RPM</li> <li> <strong>Validate everything</strong>: voltage ranges, motor counts, coordinate bounds</li> <li> <strong>Query by session</strong>, time range, aircraft</li> <li> <strong>Batch ingest</strong> for time-series analysis</li> <li> <strong>Zero config</strong>: SQLite default, runs on a laptop</li> </ul> <h2> Why FastAPI + Pydantic </h2> <p>FastAPI gives async request handling and auto-generated OpenAPI docs. Pydantic gives type-safe validation with clear error messages. Together they mean I spend zero time on boilerplate and all time on aerospace logic.</p> <p>Example: battery voltage below 10V triggers a validation error. For eVTOL packs running 400-800V, a 3.7V reading is either a sensor fault or a wrong unit and the API catches it before it corrupts your dataset.</p> <h2> Architecture </h2> <p>Three core models:</p> <ul> <li> <strong>Aircraft</strong>: static config (mass, propulsion type, MTOM)</li> <li> <strong>TestSession</strong>: a single test event (hover, transition, endurance)</li> <li> <strong>TelemetryPoint</strong>: sensor snapshot with optional nested data</li> </ul> <p>SQLite storage with SQLAlchemy 2.0 async. Repository pattern for clean separation. 26 pytest tests covering CRUD, validation, and edge cases.</p> <h2> Demo </h2> <p>2-minute walkthrough:</p> <p><a href="https://www.loom.com/share/58a0bf51b5794c879bed101aaac82753" rel="noopener noreferrer">https://www.loom.com/share/58a0bf51b5794c879bed101aaac82753</a></p> <h2> Current Status </h2> <p>v0.1.0 released. Apache-2.0 licensed.</p> <p><strong>GitHub</strong>: <a href="https://github.com/Mohammed-Fayaz-Ahamed/aero-telemetry" rel="noopener noreferrer">github.com/Mohammed-Fayaz-Ahamed/aero-telemetry</a></p> <h2> What's Next </h2> <ul> <li>PostgreSQL support for production deployments</li> <li>WebSocket streaming for real-time telemetry</li> <li>Grafana dashboard integration</li> <li>Time-series aggregation endpoints</li> </ul> <h2> Who This Is For </h2> <p>eVTOL startups doing prototype testing. Drone fleet operators. Graduate researchers building UAM simulations. Anyone who needs structured flight test data without enterprise overhead.</p> <p>If you're building in this space, I'd love your feedback what's missing, what's wrong, what would you actually use?</p> api opensource python showdev