Showing 4 open source projects for "arduino-homekit-esp32"

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  • 1
    Homebridge

    Homebridge

    HomeKit support for the impatient

    Homebridge is a lightweight NodeJS server you can run on your home network that emulates the iOS HomeKit API. It supports Plugins, which are community-contributed modules that provide a basic bridge from HomeKit to various 3rd-party APIs provided by manufacturers of "smart home" devices. Since Siri supports devices added through HomeKit, this means that with Homebridge you can ask Siri to control devices that don't have any support for HomeKit at all. ...
    Downloads: 6 This Week
    Last Update:
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  • 2
    Homebridge UniFi Protect

    Homebridge UniFi Protect

    Complete HomeKit integration for UniFi Protect with full support

    ...This plugin attempts to bridge a gap in the UniFi Protect ecosystem by providing native HomeKit support on par with what you would expect from a first-party of native HomeKit solution. My north star is to create a plugin that just works with minimal required configuration by you to get up and running. The goal is to provide as close to a streamlined experience as you would expect from a first-party or native HomeKit solution.
    Downloads: 0 This Week
    Last Update:
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  • 3
    Ring

    Ring

    Unofficial packages for Ring Doorbells, Cameras, Alarm System

    ...The ring-client-API is a TypeScript package designed to be used by developers to create their own apps/programs which interact with Rings API. homebridge-ring allows users to integrate Ring products into Apple HomeKit via homebridge easily. With Ring you can control your home from your smartphone, tablet or PC. Each Ring device includes a camera, speakers, and an integrated microphone so you can view, listen, and speak to anyone on your property from anywhere. Ring's customizable motion sensors allow you to focus on the most important areas of your home. ...
    Downloads: 1 This Week
    Last Update:
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  • 4
    Porcupine

    Porcupine

    On-device wake word detection powered by deep learning

    ...It is using deep neural networks trained in real-world environments. Compact and computationally-efficient. It is perfect for IoT. Cross-platform. Arm Cortex-M, STM32, PSoC, Arduino, and i.MX RT. Raspberry Pi, NVIDIA Jetson Nano, and BeagleBone. Android and iOS. Chrome, Safari, Firefox, and Edge. Linux (x86_64), macOS (x86_64, arm64), and Windows (x86_64). Scalable. It can detect multiple always-listening voice commands with no added runtime footprint. Self-service. Developers can train custom wake word models using Picovoice Console. ...
    Downloads: 8 This Week
    Last Update:
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