# NICU Warmer — Intelligent Patient Monitoring
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> Note!
> This application is for **reference and evaluation purposes**. It is
**not intended for direct use in clinical or diagnostic environments** and is not
validated as such.
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The NICU Warmer application is a reference solution that demonstrates how multiple AI models
can run simultaneously in a single GStreamer pipeline on Intel® hardware, providing workloads
that mimic real-time neonatal patient monitoring in a simulated hospital warmer bed scenario.
It combines several representative AI workloads:
- **Object Detection (×3):** Custom OpenVINO FP32 models for detecting patient presence,
caretaker presence, and warmer latch clip status — all running on Intel Arc GPU.
- **rPPG (Remote Photoplethysmography):** Contactless heart and respiratory rate
estimation from facial video using MTTS-CAN, running on CPU.
- **Action Recognition:** Kinetics-400 encoder/decoder model mapped to 11 NICU-specific
activity categories, running on Intel NPU (AI Boost).
- **Metrics Collector:** Gathers hardware and system telemetry (CPU, GPU, NPU, memory, power)
from the host.
- **UI:** Web-based React dashboard for visualizing detections, vital signs, activity, and
system performance in real time.
Together, these components illustrate how vision-based AI workloads can be orchestrated across
Intel GPU, NPU, and CPU, monitored, and visualized in a clinical-style scenario.
## Supporting Resources
- [Get Started](./get-started.md) – Step-by-step instructions to build and run the application
using `make` and Docker.
- [System Requirements](./get-started/system-requirements.md) – Hardware, software, and network
requirements, plus an overview of the AI models used by each workload.
- [How It Works](./how-it-works.md) – High-level architecture, service responsibilities, and
data/control flows.
- [Release Notes](./release-notes.md) – Version history and known issues.
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Get Started
How It Works
Release Notes
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