IoTSharp is an open-source industrial IoT platform for device access, telemetry collection, rule-chain processing, visualization, multi-tenant operations, and product delivery.
IoTSharp brings together the core building blocks needed to run an IoT platform in production:
- Device and gateway connectivity with HTTP, MQTT, CoAP, and extensible protocol integration.
- Telemetry, attributes, alarms, products, assets, and tenant-aware management models.
- Rule-chain driven processing for transformation, notification, automation, and business actions.
- Relational and time-series storage options for different deployment and scaling needs.
- Multiple delivery modes including Docker, Windows service, Linux service, installer flows, and release artifacts.
- The roadmap now also treats AI workbench, MCP tools, and agent-assisted operations as a cross-cutting capability for collection, rules, and release workflows.
The current main application targets .NET 10, and the web console is maintained as an IoTSharp-branded Vue 3 application.
IoTSharp is not a single platform application but an open-source product matrix covering three layers plus an AI foundation:
| Layer | Project | Description |
|---|---|---|
| Platform | IoTSharp (this repo) | Control plane for device access, telemetry, rule chains, multi-tenancy, EdgeNode management, and release operations |
| Edge | IoTEdge | Edge gateway runtime: single-host executable with a local management UI, built-in Modbus, OPC UA, and mainstream PLC collection drivers plus script-based transformation; integrates with the platform for registration, heartbeat, capability reporting, collection-config rollout, and task receipts |
| Device | IoTEmbedded | Embedded device runtime for MCU/RTOS targets: firmware-level runtime with a built-in BASIC script engine, Modbus RTU, and MQTT access, supporting dual-slot script storage with failure rollback |
| AI foundation | Tomur | Local model runtime: hosts the platform's AI capabilities in offline/intranet environments, with GGUF LLM, speech, image, and OCR multimodal inference behind OpenAI-compatible APIs, deployable as a single file |
All layers are open source and independently usable, and together they form an end-to-end industrial collection and operations solution; in offline or intranet scenarios, combining SonnetDB and Tomur enables a fully functional deployment with zero external dependencies.
The recommended documentation entry points are:
- Product docs: https://iotsharp.net/docs/intro
- Installation options: https://iotsharp.net/docs/getting-started/installation-options
- Installer guide: https://iotsharp.net/docs/getting-started/installer
- Docker Desktop extension: https://iotsharp.net/docs/deployment/docker-desktop-extension
For frontend development, the current local dev server default is:
- Frontend:
http://localhost:27915
- Chinese README: README.zh.md
- Roadmap: ROADMAP.md
- Changelog: CHANGELOG.md
Contributions are welcome through issues and pull requests:
- Pull requests: https://github.com/IoTSharp/IoTSharp/pulls
- Issues: https://github.com/IoTSharp/IoTSharp/issues
Before contributing, please review the codebase structure, related documentation, and the current release/distribution direction in the docs site.
If you need help using or deploying IoTSharp, community channels are available in the docs and community materials:
- GitHub: https://github.com/IoTSharp/IoTSharp
- Gitee: https://gitee.com/IoTSharp/IoTSharp
- Official site: https://iotsharp.net
IoTSharp is released under the Apache 2.0 license. If you would like to support the project, you can back it through:
- OpenCollective: https://opencollective.com/IoTSharp
- Afdian: https://afdian.net/a/maikebing
- Backers list: BACKERS.md
- May you do good and not evil.
- May you find forgiveness for yourself and forgive others.
- May you share freely, never taking more than you give.
