Tags: smart home*

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  1. Building an affordable Home Assistant dashboard does not require expensive hardware. This guide explores several low-cost methods to create functional control panels and information displays using existing or cheap equipment.

    Ways to build a budget dashboard include:
    * Repurposing old tablets, phones, or even Kindles from your junk drawer using kiosk browsers or the Home Assistant companion app.
    * Purchasing second-hand hardware like older tablets or digital photo frames through online marketplaces.
    * Using small ESP32 touchscreen modules for low-power desktop dashboards.
    * Implementing E-Ink displays for minimal, always-on information such as weather and calendars.
    * Jailbreaking used smart displays to bypass manufacturer limitations and run custom software.
  2. Google has discontinued its popular and budget-friendly Nest Mini smart speaker alongside the launch of the new Google Home Speaker. This transition leaves a gap in the market as the $99 new device does not serve as a direct or affordable replacement for the previous entry-level model. The move suggests that Google is pivoting toward a hardware lineup designed to support its Gemini AI era rather than simply updating existing product tiers.
  3. The author explores creating a privacy-focused AI concierge for a Reolink video doorbell using locally hosted tools. By integrating Home Assistant with Piper for text-to-speech, Whisper for speech-to-text, and Ollama to run local large language models, the project aimed to automate interactions with visitors when no one is home. Although real-time two-way conversations were hindered by hardware performance and model latency, a functional system was developed that transcribes visitor messages and sends them as notifications to the owner's phone.
    Main points:
    Implementing local AI in smart home devices for privacy
    Using Home Assistant to orchestrate TTS, STT, and LLM components
    Overcoming hardware bottlenecks in real-time speech processing
    Automating visitor message transcription and mobile notifications
    2026-05-17 Tags: , , by klotz
  4. An exploration of an experiment involving connecting a local Large Language Model to Home Assistant to control a smart light bulb. By assigning the AI a specific persona through custom system prompts, the author attempted to make the lighting respond emotionally to environmental data. While successful in creating reactive lighting, the experience ultimately became unsettling as the model made autonomous decisions without direct input.
    - Connecting local LLMs via LM Studio and Home Assistant
    - Using system prompts to define device personalities
    - Automating smart bulb color and brightness through AI reasoning
    - The psychological impact of unsupervised AI autonomy in a smart home environment
  5. An exploration of using Claude Code to develop a Google Nest Hub-like device with an ESP32-P4, highlighting the challenges and limitations of AI-assisted development for niche hardware.
  6. This article details how to run a 120B parameter LLM locally with 24GB of VRAM and 64GB of system RAM, using a setup with Proxmox LXCs, Whisper for voice transcription, and integration with Home Assistant for smart home automation.
  7. Elecrow has launched a 2.8-inch round IPS display with a mini HDMI input and CNC aluminum housing, suitable for various applications like creative displays and industrial control interfaces.
    2025-11-29 Tags: , , , , by klotz
  8. A step-by-step guide on how to set up a voice-controlled Home Assistant using add-ons like Whisper, Piper, and openWakeWord, along with the necessary hardware and configuration steps.
  9. This article explains how to set up a Home Assistant voice assistant that mimics GLaDOS's voice and personality, using add-ons like Whisper and Piper for speech synthesis and recognition.
  10. This article details how to set up a custom voice pipeline in Home Assistant using free self-hosted tools like Whisper and Piper, replacing cloud-based services for full control over speech-to-text and text-to-speech processing.

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