Edge AI Embedded Systems for Predictive Maintenance: TinyML SpO₂ & HRV On-Device Screening
Introduction: The Challenge
Ambulatory devices must balance clinical fidelity for arrhythmia/HRV metrics with long battery life and reliable artifact rejection. Clinicians require compact, annotated event summaries rather than continuous raw traces. This demanded a high-efficiency approach to IoT product engineering to create a scalable smart infrastructure solution for remote health monitoring.
Solution Overview: AI-Powered Edge Intelligence
EurthTech delivered a production-ready ambulatory SpO2 + HRV device, built on AI-powered embedded systems. The solution runs robust PPG preprocessing and a TinyML classifier locally (apnea/AF screening), combining local short-window FFT/HRV analysis. By uploading only event-summaries, the system minimizes data, preserves patient privacy, and enables fast clinician triage—a powerful application of AI for smart infrastructure in healthcare.
Technical Implementation & GeoAI:
The custom hardware uses synchronous LED timing and high-SNR AFE. Our embedded systems development team deployed firmware that performs matched filtering, beat detection, and robust artifact masking. HRV features are computed on-device and compressed. Event detection uses a small quantised CNN and rule-based fusion. This technical expertise, driven by our Embedded AI India team, demonstrates advanced GeoAI principles by using dynamic sensor data for high-accuracy local processing.
Results & Impact: This AI engineering solution validated clinical claims via bench testing against pulse-ox and ECG reference standards, providing flagged summaries for efficient clinician use. The on-device intelligence drastically reduces measurement drift and enables per-unit calibration. This highly efficient, privacy-centric design positions the device as a cornerstone for future Digital twin smart city health applications and confirms EurthTech as a leading smart city solutions provider focused on scalable, reliable infrastructure.
Validation & Security Path:
Bench validation against clinical reference is required for claims; for wellness SKUs the device provides flagged summaries. Security & Update Path: We use secure OTA with signed images and a small recovery bootloader. Looking ahead, planning for NIST PQC moves ensures crypto-agility, reflecting the architectural robustness demanded for any large-scale smart infrastructure solution deployment, which often relies on geospatial engineering services for asset management.