From Half-Built to Live: How I Completed My Vaccine Cold Chain Dashboard

Yashvendra Nirwan completed VaxSafe AI, a real-time vaccine cold chain monitoring dashboard that connects to IoT temperature sensors via the Blynk Cloud API. The system features a 3D interactive dashboard with Three.js visualization, an intelligent state engine that tracks temperature change rates for predictive warnings, and automatic simulation fallback when sensors are offline. The project, built as a single HTML file for simplified deployment, includes audio alarms, vaccine lifecycle tracking, and a lid animation that opens during critical temperature alerts.

Vaccines are fragile. A few degrees too warm for a few hours can silently destroy an entire batch — and nobody knows until it's too late. That's the problem I wanted to solve. VaxSafe AI is a real-time cold chain monitoring dashboard that connects directly to an IoT temperature sensor via the Blynk Cloud API. It watches vaccine storage conditions 24/7, visualizes everything in a 3D interactive dashboard, and raises the alarm the moment something goes wrong — before any damage is done. Features: 🔗 Live site: https://yashvendranirwan-alt.github.io/vaxsafesite/ https://yashvendranirwan-alt.github.io/vaxsafesite/ The live site connects to my actual IoT device. If the sensor is offline, simulation mode kicks in automatically — you'll still see the full dashboard, trend analysis, and alarm system in action. To connect your own sensor: paste your Blynk auth token into the header field and hit Connect . Virtual pin V0 should publish your temperature value. This project started as a rough prototype — a basic temperature gauge that pinged a sensor and showed a number. Functional, but completely bare. No context, no visual feedback, nothing that would tell a real healthcare worker whether to panic or relax. Before the finish-up sprint: Here's what changed: Three.js cold storage visualization — I built a full 3D animated vaccine box with a canvas-texture medical label, frost particles that shift color by state, and a lid that physically opens when a critical alert fires. Drag to rotate, works on mobile. Intelligent state engine — instead of a simple threshold alert, the system now tracks the rate of temperature change over a rolling window. Rising at 0.6°/interval inside the safe range? The AI message already tells you to pre-cool the storage — before the breach happens. Simulation fallback — if the IoT device is offline or you're just demoing , the dashboard simulates a realistic cold-chain sine-wave pattern so the UI is always live and demonstrable. Audio alarm — Web Audio API square-wave beep that fires and loops only on critical state, stops cleanly on recovery. Vaccine lifecycle panel — batch ID, manufacture date, expiry countdown, and a colour-shifting progress bar green → amber → red as expiry approaches . It turned scaffolding into a conversation. Three.js geometry suggestions — when I was building the vaccine box, I described what I wanted and Copilot filled in the corner strip coordinates and lid hinge group structure. Getting the spatial math right manually would have taken an hour of trial and error. // Described: "I need 4 vertical corner strips on a 2.2 x 1.5 x 1.3 box" // Copilot suggested the coordinates — I verified and adjusted: -1.12,-.05,-0.655 , 1.12,-.05,-0.655 , -1.12,-.05,0.655 , 1.12,-.05,0.655 Web Audio API boilerplate — the alarm beep function uses oscillator nodes and gain ramps. Copilot drafted the structure; I tuned the frequency and interval to get a sound that feels urgent without being ear-splitting. Chart.js custom plugin — the safe-zone highlight band behind the temperature graph is a custom beforeDatasetsDraw plugin. Copilot got me 80% there and I finished the pixel calculations for the safe range overlay. Where I still had to think for myself: the state machine logic especially the trend-based warnings vs. raw threshold alerts , the Three.js lid animation lerp, and making the simulation fallback feel realistic rather than robotic. Copilot is great at structure and boilerplate — the product decisions are still yours to make. No npm install. Just a single HTML file that works anywhere — because in healthcare infrastructure, the simpler the deployment, the better. Built for the GitHub Finish-Up-A-Thon Challenge on DEV.to