# Features Source: [https://docs.qualcomm.com/doc/80-70014-7/topic/supported_features.html](https://docs.qualcomm.com/doc/80-70014-7/topic/supported_features.html) The following table lists the QSH features and their impact on the QSH: Table : QSH features | Feature | Enable or disable? | Impact | Description | | --- | --- | --- | --- | | OS and hardware independent | This feature is for information purposes only. |

Development is easy

Plug and play of QSH-compliant sensors across the targets

QSH drivers or algorithms are compliant across Snapdragon platforms.

APIs are generic and abstract the underlying OS.

| | Sensors in local memory | This feature can be enabled or disabled. |

Saves power by enabling the local memory

Due to the limited local memory, only finite sensors can be fitted in
here

Enables QSH to operate in ultralow power mode, meeting the low-power
requirements of the industry.

Suitable for background use cases.

| | Sensors in Normal mode | Sensors can be configured to use either local or main memory. |

More memory and more on-chip resources are available.

Higher power consumption due to more on-chip resources being active.

Access to the larger main memory allowing integration of more sensors.

Supports cycle intensive operations.

QSH supports calibration for hardware-based sensors.

Calibration standardizes equipment for precise results, which ensures that the
sensor values matches the baseline.

Recalibration maintains sensor accuracy and adjusts for sensitivity changes
over time.

For more information, see Calibrate.

| ### Software-based sensors The following table lists the software-based sensors supported by the QSH framework: Table : Software-based sensors | Sensor name | Sensor type | Proto API | Description | | --- | --- | --- | --- | | Absolute motion detector | `amd` | `sns_amd.proto` |

Reports a stationary state when the device is at absolute rest. For example,
on a desk or a table.

Uses the accelerometer motion detect interrupts to reduce the power.

Triggers when detecting a significant motion - a motion that might lead
to a change in the user location. For example, walking, biking, or sitting in a
moving car, coach, or train.

The following examples do not trigger a significant motion:
- Phone is in the pocket and the person is not moving.
- Phone is on a table and the table shakes a bit due to nearby traffic or
  washing machine.

Reporting mode: Single response, after the notification sensor automatically
disables itself.

A low-power dynamic calibration algorithm for gyroscopes.

Validated across multiple gyroscope parts from different vendors.

A low-power dynamic calibration algorithm for magnetometers.

Validated across multiple magnetometer parts from different vendors.

A game rotation vector sensor reports the orientation of the device relative
to an unspecified coordinate frame.

It obtains the orientation through integration of accelerometer and gyroscope
readings. Therefore, the Y-axis does not point north but instead to an arbitrary
reference.

| | Gravity/linear acceleration | `gravity` | `sns_gravity.proto` | Provides a three-dimensional vector indicating the direction and magnitude of
gravity. Typically, this sensor determines the relative orientation of the device in
space. | | Persistent stationary detector | `persist_stationary_detect` | `sns_persist_stationary_detect.proto` | Reports an event when the device is stationary for at least 5 seconds. | | Persistent motion detector | `persist_motion_detect` | `sns_persist_motion_detect.proto` | Reports an event when the device is in motion for at least 5 seconds. | | Device orientation | `device_orient` | `sns_device_orient.proto` | Provides information about whether the device is in a portrait mode or
landscape mode. | | Geo-mag rotation vector (RV) | `geomag_rv` | `sns_geomag_rv.proto` | Reports the orientation of the device relative to the East-North-Up coordinates
frame; obtained through the integration of accelerometer and magnetometer
readings. | | Rotation vector | `rotv` | `sns_rotv.proto` | Reports the orientation of the device relative to the East-North-Up coordinates
frame; obtained through the integration of accelerometer, gyroscope, and
magnetometer readings. | | Device position classifier | `device_position_classi fier` | `sns_dpc.proto` | Provides the device position information. | | Activity recognition algorithm | `activity_recognition` | `sns_activity_recognition.proto` | Determines relative stationary, such as walk, run, bike, car, nonmotorized
vehicle, and motorized vehicle states and classifications. | | Distance bound | `distance_bound` | `sns_distance_bound.proto` |

Tracks the distance in meters, and reports the client when the requested
distance is covered.

Client can query the accumulated distance any time before the final distance
is reached.

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