RuView transforms WiFi signals into real-time human pose estimation, vital sign monitoring, and presence detection without video cameras.
Source: README View on GitHub →RuView addresses the need for non-intrusive, privacy-preserving human sensing solutions. It fills the gap in WiFi-based sensing technology with its unique use of CSI data and neural networks, standing out for its edge computing approach and absence of cloud dependency.
Source: Synthesis of README and project traitsUtilizes WiFi signals to detect human presence, vital signs, and activities without video cameras, leveraging Channel State Information (CSI) from ESP32 sensors.
Source: READMERuns on edge hardware like ESP32, processing data locally without the need for cloud infrastructure, ensuring privacy and low latency.
Source: READMEAdapts to environments in under 30 seconds using spiking neural networks, optimizing for low-power and real-time performance.
Source: READMEEstimates human pose with 17 COCO keypoints using WiFlow architecture, trained without cameras.
Source: READMEThe architecture is modular, with separate components for sensing, data processing, and application logic. It uses a multi-frequency mesh for sensing and employs neural networks for data analysis. Key technical decisions include the use of CSI data and edge computing.
Source: Code tree + dependency filesinfra: ESP32 mesh, Cognitum Seed, Docker | key_deps: numpy, scipy, torch, torchvision, opencv-python, scikit-learn | language: Rust | framework: FastAPI, Uvicorn, Pydantic, SQLAlchemy, Redis, OpenCV, Scikit-learn
Source: Dependency files + code tree1. Smart buildings for occupancy and activity monitoring. 2. Healthcare for vital sign monitoring and fall detection. 3. Security systems for presence detection and intrusion alerting. 4. Smart homes for automated control based on human presence and activity.
Source: READMEv0.7.0 (2026-04-06): WiFlow Camera-Supervised Pose Model (92.9% PCK@20)
Source: GitHub ReleasesRuView is a promising project for developers and organizations seeking innovative solutions in human sensing and activity monitoring. Its unique approach to using WiFi signals for sensing and its edge computing capabilities make it suitable for a wide range of applications, particularly in environments where privacy and low latency are critical.