IoT & Embedded Cameras
Custom rPPG for IoT & Embedded Cameras
We build custom preprocessing and training models that extract reliable vitals from hardware other vendors reject — sub-720p feeds, high compression, noisy sensors. Smart home cameras, elderly care sensors, industrial safety.
Generic rPPG SDKs are trained on high-resolution smartphone cameras and fail when deployed on inexpensive embedded hardware. We train models specifically for the signal characteristics of your exact camera module and processing constraints.
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Core Capabilities
What We Build
Sub-720p Signal Extraction
Custom models trained on low-resolution feeds that other rPPG vendors reject. We extract usable blood volume pulse from 320x240 and even lower resolution cameras.
Noise-Resilient Preprocessing
Algorithms built for the high noise floor and compression artifacts of inexpensive embedded cameras — MJPEG artifacts, rolling shutter, fixed-pattern noise.
Edge TPU Acceleration
Optimized models for Google Coral, Intel Movidius, and other edge AI accelerators — hardware-accelerated inference at the device level with no cloud dependency.
ARM/RISC-V Deployment
Model inference optimized for resource-constrained processors — ARM Cortex-A53/A72, RISC-V cores, and custom microcontrollers with as little as 256MB RAM.
Elderly Care Integration
Purpose-built for senior living and aging-in-place monitoring — passive vital sign capture from room cameras, fall detection integration, caregiver alert pipelines.
Smart Home API Output
Native integration with smart home platforms — MQTT, Home Assistant, Matter/Thread compatible output for ambient health monitoring ecosystems.
Built for Resource-Constrained Hardware
Every component is engineered for the constraints of embedded deployment — minimal RAM, low power budgets, limited processing headroom. Our custom builds deliver reliable vital sign extraction on hardware that generic SDKs cannot support.
Camera Types
USB 2.0 webcams, CSI/MIPI embedded cameras, IP cameras via RTSP, analog cameras via capture cardsProcessing Targets
ARM Cortex-A53/A72, RISC-V, Google Coral TPU, Intel Movidius, Raspberry Pi 4/5Min Resolution
320x240 @ 10fps minimum viablePower Budget
Under 2W total system power for battery-powered deploymentsOutput
MQTT, REST API, Home Assistant, Matter/Thread, custom JSONConnectivity
WiFi, BLE, Zigbee, LoRa compatibleIoT & Embedded Camera FAQ
Common questions about custom rPPG for IoT and embedded camera systems
With custom preprocessing and models trained specifically on low-res data, yes. Generic SDKs fail because they're trained on HD smartphone cameras. Our models are purpose-built for the signal characteristics of your specific low-res sensor.
ARM Cortex-A53 with 256MB RAM for CPU-only inference, or lighter with edge TPU acceleration. We optimize the model architecture to fit your hardware constraints.
Room-mounted camera captures periodic measurements without requiring the subject to face the camera directly. Custom preprocessing handles varying distances, angles, and partial face visibility.
We output via MQTT, REST API, or custom protocols. Native Home Assistant integration available. Matter/Thread support for modern smart home ecosystems.
Capture gating and signal preparation can run on-device, with immediate frame disposal after signal extraction and deployment-specific processing controls.
Related Custom Builds
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See how contactless vitals can transform your healthcare delivery.