[GitHub Trending] ruvnet/RuView
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WiFi-based spatial intelligence is novel but not directly relevant to the reader's focus on AI/cloud engineering.
RuView is an open-source WiFi sensing platform that uses Channel State Information from low-cost ESP32 sensors to detect presence, vital signs, and activity through walls without cameras or wearables. It runs entirely on edge hardware (as low as $9 per node), leveraging spiking neural networks that adapt in under 30 seconds, and cryptographically attests every measurement via an Ed25519 witness chain. The pretrained presence model achieves 100% validation accuracy in 8 KB (4-bit quantized), and the system can harness neighboring routers as free radar illuminators across 6 WiFi channels.
- Evaluate RuView for contactless sensing workloads that demand privacy, low latency, and zero cloud dependency — its $9-per-node edge architecture and 100% accurate presence detection make it a strong candidate for ambient monitoring systems.
For a solutions architect focused on edge AI, privacy-first sensing, and IoT infrastructure, RuView demonstrates a production-ready pattern: combining commodity hardware (ESP32), local spiking NN adaptation, and cryptographic attestation to build a scalable, cloud-free spatial intelligence layer — directly applicable to healthcare, smart building, and security use cases.
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