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The article shows how to run practical AI automations on low‑powered Linux boxes (Raspberry Pi, old minis) by picking efficient models and using quantization and lean runtimes (ONNX Runtime, TFLite/OpenVINO). It details containerized deployment, cron/systemd scheduling, MQTT messaging, caching, and monitoring, with examples like vision, speech, and anomaly detection that deliver useful results on minimal budgets and watts.