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@ -175,20 +175,7 @@ Thank you, Dad. Your patience, muscle, and willingness to get your hands dirty m
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### Bringing It All Together – The Architecture
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```mermaid
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graph LR
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L[Camera]
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A[Camera] --> D[Frigate NVR]
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D --> B[Frigate Object Detections]
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B --> C[Send snapshot to Ollama -qwen3-vl-4b- for semantic search AI enhancement]
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D --> E[Home Assistant -MQTT- ]
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E --> F[ -MQTT- Object Detection from Frigate]
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F --> G[Copy Image to Home Assistant]
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G --> H[Send image to Ollama -qwen3-vl-2b- for context enhancement]
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H --> I[Send response back via Matrix]
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J[Camera]
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K[Future Camera]
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```
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<img alt="CCTV Architecture" height="auto" width="100%" src="{attach}/images/CCTV_ARCH.png">
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---
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@ -198,4 +185,4 @@ Building an AI‑enhanced CCTV system from the ground up has been a rewarding bl
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If you’re a hobbyist, a small‑business owner, or anyone who values data sovereignty, the stack described here offers a solid foundation. Start with a single camera, get comfortable with Frigate’s YAML configuration, and gradually layer on the AI components. Remember that the most valuable part of the journey is the learning curve: each tweak teaches you something new about video streaming, inference workloads, and the quirks of your own network.
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So, roll up your sleeves, grab a ladder (or enlist a dad), and give your home the eyes it deserves—without handing the footage over to a faceless cloud. The future of home surveillance is local, intelligent, and, most importantly, under your control. Cheers!
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So, roll up your sleeves, grab a ladder (or enlist a dad), and give your home the eyes it deserves—without handing the footage over to a faceless cloud. The future of home surveillance is local, intelligent, and, most importantly, under your control. Cheers!
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