SENtral Sensor Fusion Coprocessor

Sensor Fusion Coprocessor with the best algorithms at the lowest power

SENtral is a new kind of sensor hub. It’s a dedicated ultra-low power hardware accelerator optimized for high-demand computation from a broad variety of sensor and sensor fusion applications such as context, activity, gesture and indoor navigation.

SENtral comes complete with PNI Sensor’s embedded sensor fusion algorithms, which are sensor-agnostic.  This gives you the best of both worlds: top-of-the-line sensor fusion from PNI that works seamlessly with the sensors of your choice.

Why SENtral

Increasing use of gyroscopes, accelerometers and magnetic sensors is enabling greater functionality across a wide spectrum of mobile devices and applications. For many OEMs and ODMs, working out the subtleties of sensor integration, signal enhancement, calibration, magnetic interference, sensor drift and power consumption has proven to be time-consuming, difficult and expensive work. Additionally, effective fusion of these sensors running on an application processor or a general purpose processor will consume too much power for always-on applications or for wearable devices with small batteries.

Tapping its deep knowledge of sensor fusion algorithms in designing SENtral, PNI now offers the lowest-power sensor fusion coprocessor on the market.

In fact, SENtral consumes less than 1% of the power of the same algorithms running on a general purpose microprocessor.

And it reduces the need for complex algorithm development and calibration, freeing you to spend more time creating applications — instead of on sensor integration — so you can get new products to market that much faster.

How it works

SENtral acts like an intelligent sensor manager. For motion sensor fusion, it outputs heading and accurate absolute and relative motion tracking data — all with more accuracy and reliability than you’ve ever experienced. Using “constant calibration” technology, it polls the individual sensors, integrating, fusing and filtering their data with state-of-the-art patented Kalman filter algorithms. Created and designed by sensor fusion experts with extensive real-world experience, SENtral’s output is fast, accurate and very reliable.

SENtral is now available with a variety of algorithms for context- and location-awareness, including:

Mobile Sensor Fusion

  • Quaternion outputs from: 9-axis, 6-axis IMU, 6-axis e-compass and soft gyro
  • Background auto-calibration and magnetic anomaly rejection

Activity Monitoring

  • Type of step, step count and step detect
  • Activity state and level
  • Tilting

Device Orientation and Motion

  • How the device is held or carried: ear, handheld-in-front, handheld-at-side, in-pocket
  • Auto-detection of wrist-worn vs. not wrist-worn

Pedestrian Dead-Reckoning (available in 2016)

  • Directional accuracy while moving
  • Scaled step count
  • Accelerometer-based Direction of Travel (DOT)
  • Center of gravity
  • Changes in elevation

Works with the sensors you use

SENtral supports a wide variety of gyroscopes, accelerometers and magnetic sensors from multiple vendors – so you can use it with the sensors you already know and like. It’s easy to integrate and optimize up to 6 sensor ICs, as SENtral has GPIO pins for communication with additional sensors, such as heart rate or environmental sensors.

SENtral M&M Modules: To learn more about our new motion tracking and measurement platform integrating SENtral with other third-party motion sensors in a low-power system-on-board, please visit the SENtral M&M product page.

SENtral-A: To learn more about our new SENtral-A supporting Android 4.4 KitKat, please visit the SENtral-A Product Page.

Made with real-world expertise

It takes field-proven experience to make the industry’s best sensor fusion solution – and PNI has it. SENtral’s fusion technology is custom-engineered by PNI, arecognized leader in high-end sensor fusion. Plus it is built on an ultra-low power IC from EM Microelectronic, experts in producing ultra-low power microelectronic components.