# Overview

Note

The Qualcomm® sensing hub (QSH) is available only on [QCS5430](https://www.qualcomm.com/products/internet-of-things/industrial/industrial-automation/qcs5430) and [QCS6490](https://www.qualcomm.com/products/internet-of-things/industrial/building-enterprise/qcs6490).

The Qualcomm® system-on-chip (SoC) includes an application processor
that runs the Linux operating system, a low-power application digital signal processor (aDSP), and
other processors. The low-power processor runs the real-time operating
system (RTOS) for executing the QSH use cases.
The low-power processor supports the following for QSH operations:

- GPIOs configurable as serial bus: serial peripheral interface (SPI),
inter-integrated circuit (I^2^C), improved I^2^C (I^3^C), and universal asynchronous receiver/transmitter (UART).
- Serial buses in low-power mode.
- Dedicated local memory, also known as the island in QSH.

## QSH sensors

The QSH framework provides access to both
hardware-based and software-based sensors for the following
functionalities and capabilities:

- Hardware-based sensors are physical sensors that gather data by
directly measuring specific environmental properties, such as
acceleration, magnetic field, pressure, humidity, light, and angular
velocity.

    The following table lists the hardware-based sensors that the QSH
framework supports:

Table : Hardware-based sensors

    | Sensor name | Sensor type | Description | Proto API |
    | --- | --- | --- | --- |
    | Accelerometer | `accel` | Measures the acceleration applied to a device on all the 3 physical axes (x, y, and z) in meter/second square (m/s2) | `sns_accel.proto` |
    | Gyroscope | `gyro` | Measures the rate of rotation of a device around each of the 3 physical axes (x, y, and z) in radians/second (rad/s) | `sns_gyro.proto` |
    | Sensor temperature | `sensor_temperature` | Measures the temperature of the sensor in degreesCelsius (°C) | `sns_sensor_temperature.proto` |
    | Magnetometer | `mag` | Measures the ambient magnetic field for all the 3 physical axes (x, y, and z) in microtesla (μT) | `sns_mag.proto` |
    | Proximity | `proximity` | Measures the proximity of an object and provides *near/far* events | `sns_proximity.proto` |
    | Ambient light | `ambient_light` | Measures the ambient light level illumination in lux (lx) | `sns_ambient_light.proto` |
    | Pressure | `pressure` | Measures the ambient air pressure in hectoPascal (hPa) | `sns_pressure.proto` |
    | Humidity | `humidity` | Measures the relative ambient humidity in percentage (%) | `sns_humidity.proto` |
    | Ambient temperature | `ambient_temperature` | Provides the ambient room temperature in degreesCelsius (°C) | `sns_ambient_temperature.proto` |
    | Hall | `hall` | Measures the magnetic field and provides a magnet *near/far* indication | `sns_hall.proto` |
    | Capacitive proximity | `sar` | Detects human object proximity using change in capacitance and reports *near/ far* events | `sns_sar.proto` |
- Software-based sensors, also known as virtual sensors, are the
algorithms that gather data from one or more physical sensors and
generate the intended output. The common examples are gravity, step
counter, and game rotation vector.

    The following table lists the software-based sensors that the QSH framework supports:

Table : Software-based sensors

    | Sensor name | Sensor type | Proto API | Description |
    | --- | --- | --- | --- |
    | Absolute motion detector | `amd` | `sns_amd.proto` | <ul class="simple"><br><li><p>Reports a stationary state event when the device is at absolute<br>rest. For example, the device is placed on a stationary object, such as desk or table.</p></li><br><li><p>Reports a moving state event when the device transitions from absolute rest to moving state.<br>For example, the device is being lifted from a desk or table.</p></li><br><li><p>Uses the accelerometer motion detect interrupts to reduce<br>the power.</p></li><br></ul> |
    | Relative motion detector | `rmd` | `sns_rmd.proto` | Reports a stationary state when the device is not moving significantly with respect to gravity. |
    | Significant motion detector | `sig_motion` | `sns_sig_motion.proto` | <ul class="simple"><br><li><p>Triggers when detecting a significant motion - a motion<br>that might lead to a change in the user location. For<br>example, walking, biking, or sitting in a moving car,<br>coach, or train.</p></li><br><li><p>The following examples do not trigger a significant<br>motion:</p><ul><br><li><p>The device is in a pocket and the person is not<br>moving.</p></li><br><li><p>The device is on a table and the table shakes a bit.</p></li><br></ul><br></li><br><li><p>Reporting mode: Single response, after the notification<br>sensor automatically disables itself.</p></li><br></ul> |
    | Pedometer | `pedometer` | `sns_pedometer.proto` | Reports the number of step counts to the client. |
    | Step detector | `step_detect` | `sns_step_detect.proto` | Detects steps and generates an event on each step. |
    | Tilt detector | `tilt` | `sns_tilt.proto` | Generates an event, each time there is a tilt. The direction of the 2-second window, with average gravity changing by at least 35 degrees since the activation or the last event generated by the sensor, defines a tilt event. |
    | Tilt to wake | `tilt_to_wake` | `sns_tilt_to_wake.proto` | Detects the substantial device rotation gesture event when the picked device is in a specific range of the pitch and roll angles. |
    | Gyroscope calibration | `gyro_cal` | `sns_gyro_cal.proto` | <ul class="simple"><br><li><p>A low-power dynamic calibration algorithm for gyroscopes.</p></li><br><li><p>Validated across multiple gyroscope parts from different<br>vendors.</p></li><br></ul> |
    | Magnetometer calibration | `mag_cal` | `sns_mag_cal.proto` | <ul class="simple"><br><li><p>A low-power dynamic calibration algorithm for the magnetometer sensor.</p></li><br><li><p>Validated across multiple magnetometer parts from<br>different vendors.</p></li><br></ul> |
    | Game rotation vector | `game_rv` | `sns_game_rv.proto` | <ul class="simple"><br><li><p>Reports the orientation of the device that is relative to<br>an unspecified coordinate frame.</p></li><br><li><p>Obtains the orientation through integration of<br>accelerometer and gyroscope readings. Therefore, the<br>Y-axis does not point north; instead, it points to an arbitrary<br>reference.</p></li><br></ul> |
    | Gravity/linear acceleration | `gravity` | `sns_gravity.proto` | <ul class="simple"><br><li><p>Provides a three-dimensional vector indicating the<br>direction and magnitude of gravity.</p></li><br><li><p>Typically, this sensor determines the relative<br>orientation of the device in space.</p></li><br></ul> |
    | 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` | Reports whether the device is in 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` | <ul class="simple"><br><li><p>Reports the orientation of the device relative to the East-North-Up coordinates frame.</p></li><br><li><p>Obtains orientation through the integration of accelerometer, gyroscope, and magnetometer readings.</p></li><br></ul> |
    | 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` | <ul class="simple"><br><li><p>Tracks the distance in meters, and reports the client when the requested distance is covered.</p></li><br><li><p>The client can query the accumulated distance anytime before the final distance is reached.</p></li><br></ul> |

QSH provides a framework to use data from a wide range of sensors. The
sensor data is useful in fields such as IoT, gaming, health, and
fitness. A device can have more than one sensor of a given type. For
example, a flip-phone has an accelerometer placed on each of the two
planes.

The published attributes or capabilities distinguish each accelerometer
sensor. You can access the availability, attributes, and capabilities of
a sensor on the platform using the QSH client APIs. Use the same QSH
client APIs to get the sensor data from the QSH framework.

The QSH framework APIs include QSH client APIs and sensor APIs, enabling
the following sensor-related tasks:

- Identify the sensors available on a development kit.
- Determine sensor capabilities using attributes, such as supported
sample rate, maximum range, manufacturer, power requirement, and
resolution.
- Collect and provide data according to the configuration, thereby enabling
sensors with a specified sample rate.

Last Published: Dec 24, 2024

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