Orbit OS - An Android-like Platform for Linux Edge Devices

The Problem

Every IoT or embedded Linux project starts the same way: SSH into the device, install dependencies, configure services, set up OTA updates, manage networking, and repeat the same process for every new project.

The same infrastructure gets rebuilt from scratch over and over again.

After going through this cycle too many times, I decided to solve it once — for all projects.

What is Orbit OS?

Orbit OS is an embedded Linux platform that brings an Android-like experience to edge devices. The core idea is simple: install it once, and you get a fully managed runtime with an App Store, OTA updates, fleet management, and a unified SDK.

Think of it like Android — but for Raspberry Pi and other edge devices.

The core runtime is called Gravity RT. It weighs just 30MB and handles everything: app lifecycle, API services, security, and communication with the Orbit OS Store.

How It Works

After installing Orbit OS on your device, you get access to the Launcher — a web interface accessible from any browser on your network.

From there, you can install apps remotely from the Orbit OS Store with a single click, with no SSH, no Docker, and no manual configuration.

Applications are distributed as signed .orb packages through the Orbit OS Store. Each app is verified, sandboxed, and managed by the runtime.

The SDK

The Orbit OS SDK gives developers a unified API to access device capabilities such as:

• GPIO, PWM, I²C, SPI, UART
• WiFi, Ethernet, Bluetooth
• Camera access
• AI inference with built-in TFLite and ONNX support
• Firewall and VPN management
• OTA and fleet management

The SDK is currently available in Go (stable) and Java (beta), with Python and C++ support coming soon.

TFLite and ONNX are built directly into the platform — applications only need to provide the model and the logic. The AI Manager automatically selects the correct inference backend based on the model type.

API Reference:
https://www.orbit-os.org/api-reference.htm

Orbit Studio

Orbit Studio is a VS Code extension for developing Orbit OS applications directly from your laptop.

One of its most powerful features is real-time remote development — write code locally and run it instantly against live hardware with no deploy step, no SSH access, and no file transfers required.

With Orbit Studio, any developer can start a new project in seconds with just two or three clicks, going from setup to running code on live hardware almost instantly. The video below demonstrates this workflow in practice.

Orbit OS — Orbit Studio First App | Real-Time Remote Development, GPIO LED Control & Deploy

▶️ [Orbit OS — Orbit Studio Create your First App | GPIO example]

Orbit OS Store

The Orbit OS Store allows users to remotely install and manage applications on all devices linked to their account. Applications are distributed as signed .orb packages and can be deployed with a single click directly from the browser.

The platform handles installation, updates, permissions, and application lifecycle automatically through the Gravity RT runtime, eliminating the need for SSH access, Docker containers, or manual configuration.

The same application can run across different hardware platforms, allowing developers to target multiple edge devices using a unified SDK and deployment system.

Any developer can also submit their own applications to the store, making them available to other users and devices linked to their accounts.

You can see in: store.orbit-os.org

Apps Available Today

• KS0212 4-Channel Relay Shield** — Web UI, Modbus TCP server, MQTT with Home Assistant auto-discovery. One click, zero configuration.
• Mochi MQTT Broker** — Lightweight MQTT broker with integrated Web UI. Configure ports, users and settings from the browser.
• Edge AI — Smart Image Detection** — YOLOv8 COCO object detection using TFLite. Runs locally, no cloud, no external APIs.
• Edge AI — Face Recognition** — Real-time face recognition with any connected camera. Enroll faces in under 10 seconds. 100% offline.
• MCP server to manage the device with AI Agents.
• And more

An App example:

Edge AI – Smart Image Detection is an Orbit OS application that performs real-time object detection locally on edge devices using YOLOv8 TensorFlow Lite models.

Users can remotely install the application from the Orbit OS Store with a single click on any device linked to their account.

After being installed in seconds, users can upload images directly from the browser, detect and label objects with bounding boxes, inspect inference timing, and view the raw JSON output generated by the AI service.

The application runs entirely on-device through the Orbit OS AI Manager API using YOLOv8 / COCO TensorFlow Lite models, with no cloud processing, Docker containers, or manual setup required.

This video demonstrates the application running simultaneously on two different devices: a Raspberry Pi 5 and an Arduino UNO Q.

Same App, same Model. Diferent hardware, diferent performance.

▶️ [Orbit OS — Edge AI Object Detection | YOLOv8 | Raspberry Pi 5 & Arduino UNO Q | No Cloud]

Supported Hardware for now

• Raspberry Pi 3, 4, 5 and Zero 2W
• Arduino UNO Q (Qualcomm QRB2210)

What's Coming

• Java, Python and C++ SDK

Try It

Orbit OS Community Edition is available now at orbit-os.org.

We are looking for developers who want to try building their first

app with the Orbit OS SDK — would love early feedback.

Demo Videos

▶️ [Orbit OS — How to Install | Raspberry Pi 3, 4, 5, Zero 2w & Arduino UNO Q]

▶️ [Orbit OS — Link Your Account & Install Your First App from the Store]

▶️ [Orbit OS — Mochi MQTT Broker App Review | One-Click Install,| Arduino UNO Q]

▶️ [Orbit OS — KS0212 4-Channel Relay App Review | Modbus TCP, MQTT & Home Assistant]