/ 

PASSWORD RESET

Are you human? *


REGISTER


Are you human? *


Minimum number of posts is 5 for running text.

Wearable Chip Beats GPS In Tracking

296 0
Wearable Chip Beats GPS In Tracking

PNI Sensor introduced the first coprocessor for wearable devices that uses ultra-low power inertial sensors to track users when there is little or no GPS signal. The device is foreseen to provide a range of applications in wearables including wrist-worn devices, enhanced activity wristbands and smartwatches for athletes and fitness enthusiasts.

The ASIC provides truly accurate pedestrian tracking indoors, in urban canyons and in other areas with missing or inadequate GPS signal using PNI Sensor’s proprietary embedded algorithms. The device is said to dramatically reduce overall battery consumption by ten-fold by overriding and deactivating power-hungry GPS when it’s not needed.

SENtrace provides tracking to one-meter accuracy over 100 meters traveled, supplying step-by-step data instead of extrapolations between two location points. That’s a vast improvement over GPS, which tracks location to approximately 10 meters over 100 meters traveled.

“PNI Sensor has tapped more than two decades’ experience in military-grade location-tracking for robots, humans in combat situations, and unmanned vehicles to develop SENtrace,” said Becky Oh, president and CEO, PNI Sensor Corp.

“We also have years of perfecting the highest-accuracy, lowest-power 9-axis sensor fusion for wearables and smartphones. SENtrace is the result of our combined expertise. It stays accurate over time and through a wide range of conditions, so its data can be trusted to deliver precise results in real-world scenarios. Wearables manufacturers will finally be able to offer proven pedestrian-tracking to consumers — without having to worry about battery drain”, added Becky Oh.

The ASIC measures just 1.7mm x 1.7mm x 0.5mm and incorporates a 32-bit processor with a custom floating point unit (FPU) which has embedded fusion tracking algorithms to offload the tracking task from a device’s main processor, thereby saving battery power. These algorithms also allow manufacturers of wearable devices to select from widely available accelerometers, gyros and magnetic sensors.

Leave A Reply

Your email address will not be published.

Are you human? *