Tyler August writes that The Masked Bear's open-source wifisense-pi project uses an ESP32-S3 sampling the 2.4 GHz WiFi channel 100 times per second with a Raspberry Pi 4 for signal processing to detect subtle body motions via WiFi disturbances, effectively sensing breathing or presence through walls without dedicated hardware.
- Can detect a perfectly still human by breathing, but presence can be hidden by holding breath
- Single sensor provides no position information and cannot reliably distinguish one vs multiple people
- Works by sniffing existing 2.4 GHz signals and functions through walls
- Not the first WiFi-based presence project; prior work includes ESP32 person sensors and millimeter-wave alternatives
- Can detect a perfectly still human by breathing, but presence can be hidden by holding breath
- Single sensor provides no position information and cannot reliably distinguish one vs multiple people
- Works by sniffing existing 2.4 GHz signals and functions through walls
- Not the first WiFi-based presence project; prior work includes ESP32 person sensors and millimeter-wave alternatives
This article details a project where the author successfully implemented OpenClaw, an AI agent, on a Raspberry Pi. OpenClaw allows the Raspberry Pi to perform real-world tasks, going beyond simple responses to actively controlling applications and automating processes. The author demonstrates OpenClaw's capabilities, such as ordering items from Blinkit, creating and saving files, listing audio files, and generally functioning as a portable AI assistant. The project utilizes a Raspberry Pi 4 or 5 and involves installing and configuring OpenClaw, including setting up API integrations and adjusting system settings for optimal performance.
