Bluetooth GATT Characteristic Reference
Fitness Machine Feature (0x2ACC)
The Fitness Machine Feature characteristic is defined in the Fitness Machine Service Specification.
Quick Summary
No fixed value payload is declared in this XML; this entry defines metadata and profile structure. This page is generated from official GATT XML and presented as implementation-ready guidance.
At a Glance
Key reference details for BLE implementation, interoperability testing, and AI-assisted troubleshooting.
| Property | Value |
|---|---|
| Name | Fitness Machine Feature |
| UUID | 0x2ACC |
| Type | org.bluetooth.characteristic.fitness_machine_feature |
| XML Root | Characteristic |
| Source File | org.bluetooth.characteristic.fitness_machine_feature.xml |
| Field Count | 0 |
Use Cases and Integration Notes
BLE Telemetry
Map characteristic values into dashboards and alerts for device observability.
Firmware Regression
Compare decoded fields across builds to detect protocol or scaling changes.
App Integration
Build stable parsing paths that convert raw payloads into typed app models.
Implementation Checklist
- Validate payload length and mandatory fields before decode.
- Decode with Bluetooth-specified signedness, unit, and exponent handling.
- Convert units at presentation boundaries to avoid drift in business logic.
- Persist raw packets and decoded values for reproducible troubleshooting.
FAQ
What is Fitness Machine Feature in Bluetooth GATT?
Fitness Machine Feature is defined as a Bluetooth GATT characteristic entry with type org.bluetooth.characteristic.fitness_machine_feature and UUID 0x2ACC.
What UUID identifies Fitness Machine Feature?
The UUID for Fitness Machine Feature is 0x2ACC.
How should I parse Fitness Machine Feature?
Parse the structure and requirements from the XML definition, then enforce format/requirement rules in your BLE stack.
Where does this definition come from?
This page is generated from the Bluetooth SIG mirror XML in the oesmith/gatt-xml repository.
How does this page support BLE implementation?
The page combines structured tables, practical Q&A, and JSON-LD metadata to help teams validate integrations and troubleshoot consistently.