PORTfolio
SPIRO
AI-Powered Respiratory Monitoring for Embedded Systems
Compact, intelligent respiratory analysis for real-time health insights
SPIRO
Overview
SPIRO is an AI-powered medical device that provides automatic respiratory system assessment based on tidal breathing. It combines the functions of a stethoscope and a spirometer, enabling fast and reliable lung evaluation. Using deep learning algorithms trained on real patient data, SPIRO identifies characteristic breathing patterns for each condition.
How It Helps
Detects respiratory disorders such as asthma, COPD, and emphysema.
Provides non-invasive monitoring and patient tracking.
Reduces diagnosis time from minutes to seconds.
Enables remote healthcare and early intervention.
Works offline on compact embedded devices.
Why This Architecture Matters
The system is built around a compact convolutional neural network optimized for embedded use. It integrates full MLOps capabilities — from ETL and model training to quantization, deployment, and OTA updates. SPIRO demonstrates a unique fusion of AI reasoning, embedded optimization, and medical-grade reliability.
Key Benefits
01
Fully automated end-to-end MLOps pipeline.
02
Real-time analysis on embedded hardware.
03
Post-training quantization and QAT for efficiency.
04
Continuous monitoring and early disease detection.
05
Cloud and edge integration via AWS IoT Jobs.
Interested in a Product Demo?
Tech Stack
Python · PyTorch · NumPy · OpenCV · FastAPI · Edge Impulse · Renode · Mlflow · W&B; · Evidently
AI · Grafana · Prometheus · AWS IoT Jobs · GitHub Actions · TFLite · ONNX
End-to-End MLOps pipeline for embedded AI — from data ingestion and model training to OTA
deployment and real-time monitoring.
