raspberry pi

Turn a spare Linux mini PC into a private, low-latency AI workstation with four hands-on builds: a local Ollama chatbot, real-time YOLO webcam detection, an offline Vosk + espeak-ng voice assistant, and CLIP-based photo tagging. Includes system prep, Python venvs, copy-paste commands, optional GPU/TPU, systemd autostart, and performance tips—no cloud bills, no data leaks.

A hands-on guide to hardening an always-on Raspberry Pi and using on-device AI for defense: apply a quick security baseline (updates, SSH keys, firewall, Fail2ban, unattended upgrades), then build a TensorFlow Lite “AI camera sentinel” for local person detection or run Frigate NVR in Docker (with/without Coral). Covers sandboxing, least-privilege, egress control, backups, and troubleshooting.

Build a lightweight, on-device monitoring guardrail for Raspberry Pi: Bash telemetry logs temp, load, memory, disk, and throttling to CSV, while a tiny scikit-learn Isolation Forest learns your baseline and flags anomalies. Run via cron each minute and alert to Slack/Discord or syslog—no cloud, minimal overhead, auditable scripts; baselines beat thresholds.

Hands-on guide to building a lightweight, reliable edge‑AI stack on a Raspberry Pi/Linux SBC: set up a reproducible environment across apt/dnf/zypper, install TFLite and OpenCV, run a quantized MobileNet image classifier, add a real‑time camera loop, and tune threads, input size, and thermals for fast, private, offline inference—plus use cases, troubleshooting, and next steps.