Showing 4 open source projects for "rf"

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  • 1
    RuView

    RuView

    Turn WiFi signals into real-time human sensing and spatial awareness.

    ...Unlike traditional vision systems, RuView operates without cameras, wearables, or cloud connectivity, making it a privacy-first sensing solution. The system runs on low-cost hardware such as ESP32 sensor meshes and performs signal processing and machine learning directly at the edge. By learning the RF signature of each environment over time, RuView adapts automatically to different spaces and improves its sensing accuracy. Designed for applications ranging from healthcare monitoring to disaster response, it enables spaces to gain spatial awareness using the radio signals already present in the environment.
    Downloads: 738 This Week
    Last Update:
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  • 2
    WiFi DensePose

    WiFi DensePose

    Turn WiFi signals into real-time human pose estimation and detection

    ...The project demonstrates how commodity mesh routers and signal processing techniques can be leveraged to infer dense human pose information, even through obstacles such as walls. It is designed to showcase the emerging field of RF-based sensing, where machine learning models interpret wireless channel data to reconstruct human movement and posture. The repository includes components for data processing, model inference, and real-time visualization, making it suitable for research and experimental deployments. Its architecture emphasizes performance and reproducibility, allowing developers to explore non-visual motion capture systems using accessible hardware. ...
    Downloads: 116 This Week
    Last Update:
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  • 3
    NanoVNA

    NanoVNA

    Very Tiny Palmtop Vector Network Analyzer

    NanoVNA is a very tiny handheld Vector Network Analyzer (VNA). It is standalone with lcd display, portable device with battery. This project aims to provide an RF gadget but a useful instrument for an enthusiast.
    Downloads: 2 This Week
    Last Update:
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  • 4
    Library for handling XBee / XBee-PRO RF modules. The library is written in C and supports the following platforms: Linux (x86, MIPSel), Windows (x86), AT91 SAM7 microcontrollers.
    Downloads: 0 This Week
    Last Update:
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