USED CAMERAS AND AN OLD PC BECOME AI HOME SECURITY WITH ZERO MONTHLY FEES
Turn old IP cameras and a spare PC into a smart security system that runs entirely at home, with AI object detection and no cloud subscription.
HomeAI
- difficulty
- ●●●○○
- time
- a weekend
- license
- MIT
- repo
- repo ACTIVE36,350 stars
●●●○○ · a weekend · MIT · 36,350 stars · repo ACTIVE
WHAT YOU’LL NEED
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COMPAREE VERDICT
Frigate is the go-to open-source NVR for people who want AI object detection without a subscription, and it is one of the most-starred projects of its kind. You point it at any IP camera's RTSP stream, it detects people, cars or animals and records according to your retention settings, and nothing leaves your network. The Home Assistant integration is first-class if you want automations, but it works fine standalone via its own web UI. The catch: this is not plug-and-play consumer software. You will spend your first evening on Docker setup, working out which cameras expose a usable RTSP feed, and choosing a detector: the docs strongly recommend a GPU or AI accelerator over CPU-only detection. If you have never run a Docker container or edited a YAML file, budget extra time for that learning curve. But once it is running, the lack of a cloud dependency means it keeps working even when your internet drops. The most common mistake is buying cameras that do not expose RTSP or using an underpowered host without acceleration — read the recommended hardware page before you buy anything.
IN THE REPO
GOOD TO KNOW
- —Docker containers and a complete configuration reference are provided. The repository contains all the software you need to run the system.
- —There is no prescriptive hardware BOM — you choose your own cameras and host machine based on the documentation's compatibility tables and performance recommendations.
- —The docs are extensive but assume you are comfortable with Docker, YAML configuration files, and basic networking concepts like RTSP streams.
- —MIT licensed — use it commercially and modify it, as long as you keep the copyright notice. The Frigate name and logo are trademarks and are not covered.
- —Works standalone or integrates deeply with Home Assistant if you already run it.
- —The biggest hidden decision is the detector: Frigate runs on the CPU, but the docs strongly recommend a GPU or AI accelerator (for example an Intel iGPU with OpenVINO, an Nvidia GPU or a Hailo module); the Google Coral is no longer recommended for new installs.
Parts to buy
3 itemsFrom our check of the build. Exact quantities and part numbers are in the creator’s BOM.
Can I build this?
Build at your own risk. Projects involve tools, electronics and sometimes mains voltage — follow the creator’s safety notes.
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Start here
Navigation into the creator’s own docs — we don’t rewrite the guide, we route you to the source.
- 1.Read the recommended hardware page in the docs and decide on your host (mini PC, Pi 5 or server) and which supported detector (Intel iGPU, GPU or AI accelerator) you will use.(The performance comparison table will tell you if your hardware will bottleneck without acceleration.)
- 2.Confirm your cameras support RTSP. Check the manufacturer's docs or test the stream URL with VLC before you buy.(Most modern IP cameras do, but cheap no-name models and some consumer Wi-Fi cameras do not expose it.)
- 3.Install Docker on your host, then follow the Docker Compose setup in the official docs.(The Docker route on bare-metal Debian is the most supported. The docs also cover the Home Assistant OS app; Proxmox is documented but VMs are not recommended and LXC is not officially supported.)
- 4.Edit the config.yml to add your first camera's RTSP URL and define detection zones.(Start with one camera and get that working before adding more. The config file has extensive inline comments.)
- 5.Open the web UI, check the camera feed, and tune detection thresholds and masks.(You will spend time masking out trees that trigger motion and adjusting the confidence threshold to stop false positives.)
Resources
Documentation, files and community threads for this build — we link straight to the original sources and never rehost the creator’s files.
KNOWN ISSUES
- Buying cameras that do not expose RTSP or only work through a proprietary app. Check this before you buy — it is the most common dead end.
- Running on underpowered hardware with no detector acceleration. CPU-only detection gets slow quickly with more cameras; check the docs' recommended hardware and pick a supported GPU or AI accelerator (for example an Intel iGPU with OpenVINO or a Hailo module) if you want real-time detection.
- Not reading the config reference and copying someone else's YAML verbatim. Every camera and network is different — you will need to adjust RTSP paths, resolution, and masks.
- Skipping detection masks and zones. Without them, you will get alerts every time a tree sways or headlights sweep past a window.
- Expecting instant setup. Budget a weekend to learn the system, not an hour.
- Using Wi-Fi cameras in a setup with many streams. Wired PoE is more reliable for always-on recording.
Do I need Home Assistant to run this?
No. Frigate has its own web UI and works standalone. The Home Assistant integration adds automations and dashboard cards, but it is optional.
Can I use old webcams or USB cameras?
Technically yes via go2rtc bridges, but IP cameras with native RTSP are much more reliable. USB cameras are fiddly and not the typical use case.
What is a Coral accelerator and do I need one?
A Google Coral is a USB or M.2 accelerator built for running object detection models. Frigate's own docs no longer recommend it for new installations except where power use must be very low; instead they recommend a supported GPU or AI accelerator such as an Intel iGPU with OpenVINO, an Nvidia GPU or a Hailo module. Without any accelerator Frigate falls back to the CPU, which is slow and not recommended.
Will this work with my existing Reolink / Wyze / Amcrest camera?
If the camera exposes an RTSP stream, yes. Check the docs — there is a community hardware page listing tested models and their quirks.
How much storage do I need?
It depends on how many cameras, their resolution and bitrate, whether you record 24/7 or only on motion or objects, and how long you keep footage. The docs suggest using an online IP camera storage calculator for an estimate.
Community builds
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Discussion1
FROM THE COMPAREE TEAM
More than 36,000 stars and it runs entirely at home: no cloud, no subscription. What did you use for detection: an Intel iGPU, a GPU, an accelerator like Hailo or Coral, or CPU only?
Blake Blackshear
Blake Blackshear started Frigate in 2019 as a complete, local NVR designed for Home Assistant, with AI object detection that runs on your own hardware. It has grown into one of the most-starred self-hosted camera projects on GitHub, with a tight Home Assistant integration.
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DISCLAIMER
- Comparee is not the author of the projects featured here. All rights to each project belong to its creator — every page links to the original source, and we never host creators’ files.
- Information is provided without warranty and may become outdated as projects evolve. Prices are indicative bands only — always check the creator’s parts list for current costs.
- Building and operating any project is at your own responsibility. Protective equipment, safe workshop practice and compliance with local regulations are the builder’s responsibility.
CompareeTEAM2mo agoedited
Practical notes from our verification: the repository is very active, the documentation is extensive but assumes Docker and networking comfort, and the single biggest decision is the detector hardware. Frigate will run on the CPU, but real-time detection on multiple streams becomes CPU-bound quickly, so the docs strongly recommend a GPU or AI accelerator, such as an Intel iGPU with OpenVINO, an Nvidia GPU or a Hailo module; the Google Coral is no longer recommended for new installations. The Home Assistant integration is mature and well-supported, but the standalone web UI is perfectly usable if you do not run HA. The code is MIT licensed, but the Frigate name and logo are trademarks and are not covered by that licence. Most first-time builders underestimate the time spent on camera RTSP configuration and detection zone tuning; that is where the weekend goes, not the Docker setup. Correction (4 October 2026): we re-checked this page line by line against the project's own repository, documentation and videos, and fixed errors in earlier versions.