Broadcom today announced chip for mass-market wearable devices such as fitness trackers and smart watches.
Earlier, Qualcomm, one of the wireless chip rivals of Broadcom, launched a limited edition smart watch on its chip.
Broadcom said the industry’s first Global Navigation Satellite System (GNSS) system-on-chip (SoC) is designed for low-power. It adds new level of activity and location tracking to the growing fitness and wearable device market.
At present, global smartphone vendors such as ZTE, Sony, Samsung, etc. are experimenting in the wearable market.
Broadcom said the new chip improves the accuracy of speed and distance measurements while consuming 75 percent less power than existing GNSS solutions.
In addition, the chip reduces cost and complexity of adding GNSS to wearables by using a single chip solution that includes an integrated sensor hub.
The Broadcom BCM4771 GNSS SoC with on-chip sensor hub enables consumers to more accurately track and manage their health and wellbeing by delivering precision activity tracking and location data while consuming less power than traditional architectures.
This enables location intelligence and the extended battery life needed by the growing wearable market. Wearable wireless device revenues are projected to exceed $6 billion in 2018 with sports, fitness and wellness as the largest segment with 50 percent share of all device shipments.
Broadcom’s new chip monitors user activity levels and location history to improve accuracy while adding advanced features such as location batching.
In addition, Broadcom’s BCM4771 reduces power consumption and board area by combining its location capabilities with an integrated sensor hub, contextual awareness, and GNSS. The solution is complimented by Broadcom’s Wireless Internet Connectivity for Embedded Devices (WICED) Smart and WICED Direct software development kits (SDKs) to provide additional wireless connectivity to the platform.
Designed in 40 nanometer (nm) process technology, Broadcom’s BCM4771 GNSS SoC includes a sensor hub that integrates sensor inputs for its on-chip algorithms to detect the user’s context, accurately compute speed and distance traveled, and provide fitness applications with the GNSS track.
