Home Automation

Home Assistant90.6k★

Home Assistant runs your smart home on your own hardware instead of somebody else's cloud. Lights, thermostats, cameras, locks, sensors, media players, vacuums: one dashboard and one automation engine sitting on top of more than a thousand built-in integrations covering thousands of device brands. Apache 2.0, free forever, no feature tiers. Everything stays local by default, which is the actual reason to run it. Your motion sensor data does not leave the house unless you send it somewhere. Install Home Assistant OS on a dedicated box and it manages its own updates and add-ons; run the Docker container instead and you own the update cycle. Either way, plan on a weekend for the first setup. YAML is mostly gone from daily use but still turns up in advanced automations. Hardware is where the math changed in 2026. Home Assistant Green is $199 with the OS preinstalled, plus $49 for the Connect ZBT-2 dongle if you want Zigbee or Thread. Building on a Raspberry Pi 5 used to undercut that easily, but two memory-driven price hikes this year pushed the 16GB board to $305, so official hardware is now the cheaper path unless you already own a spare machine. Home Assistant Cloud (Nabu Casa) stays $6.50/mo or $65/yr for remote access, voice assistants, and automatic SSL, and it funds the project. The catch: integrations break. Releases ship monthly and a vendor API change can take a device offline until somebody patches it. 2026.8 alone dropped Volvo On Call and Permobil and forced a UniFi Protect upgrade. This maintains itself about as well as any hobby does.

integration7.7k★

HACS is the app store Home Assistant never shipped with. Home Assistant is the open source brain a lot of people run their smart homes on, and the official integrations only cover so much. HACS gives you a UI to find, install, and update the thousands of community-built add-ons that fill the gaps. Free, MIT licensed, community run. Without it, installing a custom component means copying files into the right folder by hand and remembering to do it again every time there's an update. HACS turns that into a few clicks: browse, install, update, remove, with links straight to each project's repo and issue tracker. It's the difference between maintaining a smart home and fighting one. Run Home Assistant and ever wanted a device or dashboard it didn't support out of the box? This is the first thing to install after Home Assistant itself. Solo tinkerers and whole households alike, it's free for everyone and no version costs money. The catch is the same as any unofficial store: you're installing code from strangers. HACS doesn't vet what's in those repos, it just makes them easy to get. Most community components are fine, but you own the trust decision, and an abandoned add-on can break after a Home Assistant core update with nobody on the hook to fix it.

skylight3.3k★

Skylight projects the aircraft flying over your house onto your ceiling in real time, with the actual sky behind them: sun, moon, bright stars, and the ISS. It reads ADS-B signals from a cheap software-defined radio, enriches each plane with its airline and route, and renders the whole thing as a live ceiling display. MIT licensed and free. This is a hardware project, so the cost is parts and patience, not software. You need an RTL-SDR radio with an antenna, a Raspberry Pi 5, and a projector pointed up. You can try it with no radio at all using a free public flight API, which is the smart way to see if you like it before buying anything. The docs and deploy scripts are solid, but configuring the Pi and aligning the projector is real setup work. There is no team-size calculus here. This is a personal project, an art installation, and a genuinely fun way to learn how ADS-B and software-defined radio actually work. If you have ever wondered what is flying overhead, build it. If you want a practical tool for shipping software, this is not one, and that is exactly the point. The catch is the hardware tax and the radio reality. Local ADS-B reception depends on your antenna and line of sight, so a bad spot means spotty planes. A commercial ready-made kit is in the works, which is fine, but the free path is the source code and your own parts bin.

esp32cam-rtsp1.2k★

esp32cam-rtsp turns a cheap ESP32-CAM board into a network camera. Flash this firmware onto the chip and it serves a live video stream over RTSP (the protocol VLC and most CCTV recorders speak), plus a browser-viewable Motion JPEG feed and still-image snapshots, all configured through a built-in web page. It supports a wide range of ESP32-CAM variants, from the common AI Thinker board to M5Stack and Seeed XIAO modules. Running it means real hardware work. You compile and upload with PlatformIO, put the board into download mode to flash it, then connect to its setup access point to enter WiFi and camera settings. From there it exposes brightness, contrast, exposure, and gain controls. Once flashed it just runs, but the initial bring-up assumes you're comfortable with embedded toolchains and finicky USB flashing. Solo tinkerers and small teams building a DIY camera or a vision project: this is a clean, well-supported way to do it for the price of a board. Large teams: fine for prototypes, not for anything needing fleet management or security guarantees. The catch: the repo declares no license, so "open source" is doing a lot of work here. The code is public and free to use, but without a stated license your legal right to redistribute or build a product on it is unclear. For a weekend project that's irrelevant. For anything commercial, ask the maintainer before you ship.

Anima1.0k★

Anima is a local brain for a Xiaomi smart home. Instead of writing rigid "if motion, then light" rules, you run an LLM agent that figures out what your devices are and decides what to do based on context and learned habits. Apache-2.0 licensed and self-hosted, you bring your own LLM API key. Setup is real work. You need the Python and Node stack running, an MQTT broker, an LLM key, and physical Xiaomi or MIoT hardware with the device tokens and local IPs sorted out. Once running, it discovers devices, plans actions through the LLM, and keeps an evidence-based memory of your preferences over time. There's a React dashboard and a full REST API. The obvious comparison is Home Assistant, which is more mature, hardware-agnostic, and has years of community behind it. Anima's bet is that an LLM agent beats hand-written automations. If you're deep in Xiaomi gear and like living on the edge, try it. Everyone else: Home Assistant, possibly with an LLM layer bolted on. The catch: it's days old, Xiaomi-only, and self-described as early-stage. The cloud login handles discovery, but actual control still needs each device reachable by local IP and token. Promising direction, very green.

gpt-home649★

Turns a Raspberry Pi into a voice assistant powered by ChatGPT. Plug in a microphone and speaker, run the install script, and you've got a smart speaker that uses OpenAI's API instead of Alexa or Google Home. Say something, it sends it to GPT, speaks the response back. The setup is a Docker container on a Raspberry Pi (3B+ or 4 recommended). It handles wake word detection, speech-to-text, GPT completion, and text-to-speech in a pipeline. Supports Home Assistant integration so you can control smart home devices by voice. Completely free software. Your cost is hardware (a Pi you probably already have) and OpenAI API usage. At casual home use (maybe 20-30 queries a day), expect $1-3/mo in API costs. The catch: this is a hobby project. It works, but don't expect Alexa-level reliability or polish. Wake word detection isn't perfect. Latency is noticeable; you're making a round trip to OpenAI's API for every query. There's no offline fallback. And if OpenAI changes their API or pricing, you're dependent on the maintainer updating. For a more robust self-hosted voice assistant, Home Assistant's own voice pipeline is more mature.