Plugin Name
homebridge-stream-sensors
Link To GitHub Repo
https://github.com/nkatchik/homebridge-stream-sensors
Plugin Icon (Optional)
No response
The plugin does not offer the same nor less functionality than that of any existing verified plugin.
🟢 Yes
The plugin successfully installs and does not start unless it is configured.
🟢 Yes
The plugin does not require the user to run Homebridge in a TTY or with non-standard startup parameters, even for initial configuration.
🟢 Yes
The plugin does not contain any analytics or calls that enable you to track the user.
🟢 Yes
If the plugin needs to write files to disk (cache, keys, etc.), it stores them inside the Homebridge storage directory.
🟢 Yes
The plugin does not throw unhandled exceptions, the plugin must catch and log its own errors.
🟢 Yes
More Information
Note on 32-bit platform support
This plugin runs on-device object detection via onnxruntime-node, which only ships prebuilt native binaries for:
| OS |
Architectures |
| macOS |
x64, arm64 |
| Linux |
x64, arm64 |
| Windows |
x64, arm64 |
There is no build for 32-bit ARM (armv7/armhf) — including the legacy 32-bit Raspberry Pi OS. This is an upstream limitation of onnxruntime-node, not something the plugin can work around without swapping the inference runtime.
The plugin is built to fail gracefully rather than crash Homebridge on an unsupported platform:
- It checks
process.platform / process.arch before loading the native runtime and, if unsupported, logs a clear, actionable error and stays idle.
- A
try/catch backstop around the native import surfaces any other binding failure (corrupt download, glibc mismatch, etc.) with platform context instead of an opaque stack trace.
- The error message and the README both direct Raspberry Pi users to the 64-bit (arm64) Raspberry Pi OS, which is fully supported.
Example log on an unsupported host:
onnxruntime-node has no prebuilt binary for linux/arm. Supported: macOS (x64/arm64),
Linux (x64/arm64), Windows (x64/arm64). On a Raspberry Pi, install the 64-bit (arm64)
Raspberry Pi OS — the 32-bit (armv7) build is not supported.
Supported platforms (macOS x64/arm64, Linux x64/arm64, Windows x64/arm64) install and run normally. The supported/unsupported matrix is documented in the README under Supported platforms.
Plugin Name
homebridge-stream-sensors
Link To GitHub Repo
https://github.com/nkatchik/homebridge-stream-sensors
Plugin Icon (Optional)
No response
The plugin does not offer the same nor less functionality than that of any existing verified plugin.
🟢 Yes
The plugin successfully installs and does not start unless it is configured.
🟢 Yes
The plugin does not require the user to run Homebridge in a TTY or with non-standard startup parameters, even for initial configuration.
🟢 Yes
The plugin does not contain any analytics or calls that enable you to track the user.
🟢 Yes
If the plugin needs to write files to disk (cache, keys, etc.), it stores them inside the Homebridge storage directory.
🟢 Yes
The plugin does not throw unhandled exceptions, the plugin must catch and log its own errors.
🟢 Yes
More Information
Note on 32-bit platform support
This plugin runs on-device object detection via
onnxruntime-node, which only ships prebuilt native binaries for:There is no build for 32-bit ARM (armv7/armhf) — including the legacy 32-bit Raspberry Pi OS. This is an upstream limitation of
onnxruntime-node, not something the plugin can work around without swapping the inference runtime.The plugin is built to fail gracefully rather than crash Homebridge on an unsupported platform:
process.platform/process.archbefore loading the native runtime and, if unsupported, logs a clear, actionable error and stays idle.try/catchbackstop around the native import surfaces any other binding failure (corrupt download, glibc mismatch, etc.) with platform context instead of an opaque stack trace.Example log on an unsupported host:
Supported platforms (macOS x64/arm64, Linux x64/arm64, Windows x64/arm64) install and run normally. The supported/unsupported matrix is documented in the README under Supported platforms.