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FEP-AirSense: Medical IoT & Biometric Monitor 🌬️

🚀 Overview

A high-fidelity medical IoT application prototype designed for real-time monitoring of air quality and biometric data. This platform serves as a centralized dashboard for health-conscious environments, transforming raw sensor data into actionable health insights.

🏗️ Engineering Context

Developed as a Rapid MVP (Minimum Viable Product) to demonstrate the integration of AI-driven data interpretation with modern web interfaces. The focus was on creating a highly responsive, "glanceable" dashboard for critical health metrics.

🛠️ Tech Stack

  • Frontend: TypeScript + React
  • Styling: Tailwind CSS for medical-grade UI/UX clarity.
  • Logic: AI-orchestrated data simulation and visualization logic.
  • Platform: Deployed and hosted on Vercel.

📈 Key Features

  • Real-time Health Telemetry: Simulated live tracking of SpO2, Heart Rate, and Ambient Air Quality.
  • Anomalous Detection Logic: Integrated visual alerts for biometric readings outside of standard safety thresholds.
  • Cross-Platform Accessibility: Fully responsive design for both desktop clinical viewing and mobile patient monitoring.

💡 Vision

This prototype explores the future of Assisted Healthcare Engineering, where AI tools are used to rapidly scaffold complex monitoring interfaces, allowing engineers to focus on high-level data accuracy and user safety.

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A high-fidelity medical IoT application for monitoring air quality and biometric data.

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