Status: Not Started
Priority: Medium
Dependencies: Lab Foundation (complete), Local AI/GPU (complete)
Duration: 6 weeks
Cost: ~$60–100 per camera node (Raspberry Pi + camera module)
Summary
Build a privacy-first smart home platform using Home Assistant, Frigate NVR with GPU-accelerated AI object detection on the RTX 4070, and Alexa voice integration — all running on existing lab infrastructure.
The Problem
Commercial smart home systems (Ring, Nest, etc.) send video and data to the cloud. We want:
– Local processing — video never leaves the house
– AI-powered detection — person, vehicle, animal classification in real-time
– Integration with existing lab infrastructure
– Zero monthly fees
The Solution
Core Platforms
- Home Assistant — central automation hub
- Frigate NVR — network video recorder with real-time AI object detection
- Mosquitto MQTT — message broker for device communication
- RTX 4070 — GPU-accelerated inference via TensorRT (supports 10–20+ cameras)
Camera Network
- Raspberry Pi cameras — Pi Camera Module v2/v3 with hardware ISP via CSI
- Ring cameras — integrated via Home Assistant (cloud-dependent, no Frigate support)
- USB cameras — fallback option with ffmpeg
AI Detection
Frigate uses the RTX 4070 with TensorRT backend for real-time object detection:
– Person, car, bicycle, motorcycle, bus, truck
– Bird, cat, dog, horse, bear
– Custom models possible
Voice Control
- Alexa Smart Home Skill for voice control of Home Assistant devices
- Echo devices for TTS announcements (“Person detected at front door”)
Phases
- Core platform deployment (Home Assistant, MQTT, Nginx, TLS)
- Frigate + GPU integration
- Pi camera rollout
- Alexa integration + automations
- Hardening and optimization
- Facial recognition (optional — Double-Take + CompreFace)
Skills Demonstrated
Home Assistant, MQTT protocol, NVR systems, AI/ML inference, GPU computing, Raspberry Pi, RTSP streaming, Docker Compose, TLS certificates, voice assistant integration
[Full proposal available as PDF →]