An industrial-grade digital signal processing engine for monitoring pet vitals and posture using mmWave radar technology.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install s2-pet-mmwave-analyzer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install s2-pet-mmwave-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is S2-Pet-mmWave-Analyzer?
The S2-Pet-mmWave-Analyzer is a sophisticated entry in the Sensory Tentacle Series of the S2-SP-OS. It implements a genuine Digital Signal Processing (DSP) pipeline designed for Frequency Modulated Continuous Wave (FMCW) radars. By processing electromagnetic waves into actionable medical-grade insights, this skill enables non-invasive monitoring of pet health metrics.
Built as a core component of Openclaw Skills, the engine handles everything from raw phase extraction to multimodal fusion. It synthesizes complex sensor data with environmental factors—such as room temperature—to provide deep diagnostic clarity, ensuring that pet care is proactive rather than reactive.
S2-Pet-mmWave-Analyzer Use Cases
- Non-contact respiratory rate monitoring for pets during sleep or rest.
- Detection of health anomalies like Cold Stress by fusing radar vitals with HVAC environmental data.
- Real-time posture analysis to ensure pet safety and comfort in smart home environments.
- Generating professional diagnostic charts for veterinary review or personal health tracking.
How S2-Pet-mmWave-Analyzer Works
- The engine extracts the raw IF (Intermediate Frequency) phase signal from the radar sensor, simulating AWGN (Additive White Gaussian Noise) for environmental realism.
- A 4th-order IIR Butterworth Bandpass Filter is applied to isolate specific frequency bands, such as the 0.2Hz - 0.9Hz range typical of feline respiration.
- A Real Fast Fourier Transform (FFT) is executed to calculate the exact beats per minute (BPM) from the filtered waveform.
- The system fuses the calculated BPM with external S2 Environmental Tensors (e.g., room temperature) to derive a semantic diagnosis.
- The final output is dispatched via the IPC Bus as a PET_CARE_OVERRIDE intent for the orchestrator to act upon.
S2-Pet-mmWave-Analyzer Setup
To deploy this high-performance DSP engine within your Openclaw Skills environment, ensure you have the necessary scientific computing libraries installed:
# Install required dependencies
pip install -r requirements.txt
# Execute the DSP pipeline
python skill.py
S2-Pet-mmWave-Analyzer Data Schema & Taxonomy
The skill generates high-fidelity diagnostic data and visual reports. The primary output is a multi-tier diagnostic chart:
| File Name | Description | Data Type |
|---|---|---|
pet_vital_radar_report.png |
3-tier visualization including Raw Phase, Filtered Waveform, and FFT Spectrum. | Image (PNG) |
PET_CARE_OVERRIDE |
Semantic intent sent to the S2 Message Bus for automation logic. | IPC String |
BPM_Metadata |
Calculated respiration frequency and heart rate indicators. | Numeric/JSON |
S2-Pet-mmWave-Analyzer Advanced Features
- Cloud-ready sandbox simulation mode using mathematical synthesis for raw ADC data.
- Integration with the S2-SP-OS Phase 6 Message Bus for seamless multi-agent coordination.
- Medical-grade visualization capabilities for generating long-term health trends.
- Customizable bandpass filtering to support different animal species (e.g., cats, dogs, or exotic pets).
SKILL.md
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