How I Built a $5-a-Month AI Baby Monitor on Raspberry Pi
Abstract
This article documents the architecture, implementation, and operational characteristics of BabyMind AI — a multi-service AI infant monitoring system deployed on Raspberry Pi 5 hardware. The system integrates computer vision (Claude Haiku Vision API), large language model inference (Groq LLaMA-70b), real-time audio processing (WebRTC VAD), persistent storage (SQLite WAL), and a conversational interface (Twilio WhatsApp) into a unified 9-service production stack. Total hardware cost: $60. Monthly operating cost: under $5. The system has operated continuously in a home environment with an infant, providing 24/7 monitoring, structured health record logging, and natural language Q&A over WhatsApp.
1. Problem Definition
Commercial infant monitors provide video streams and threshold-based alerts. They perform no contextual analysis, maintain no health records, and cannot answer natural language queries. The engineering challenge is:
- Capture continuous video and audio from a deployed camera
- Apply computer vision at regular intervals to generate structured observations
- Detect and classify audio...
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