Micros

Apollo3 Blue Ideal for Hearables and Voice-Activated Edge Devices

15th November 2018
Jacqueline Regnier
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Fujitsu is expanding its product portfolio of Bluetooth Low Energy enabled ultra-low power product portfolio with newly released Apollo3 Blue device from Ambiq Micro. Apollo3 Blue Wireless SoC with integrated Bluetooth low energy comes with updated peripherals, additional memory, an advanced DMA engine & TurboSPOT. This new product extends the capabilities of Ambiq Micros Apollo Blue family of products and is available now for battery-powered and energy harvesting IoT, hearable, wearable and voice-activated edge devices.

The Apollo3 Blue TurboSPOT brings ground-breaking levels of energy efficiency to mobile, battery powered devices by increasing the computational capabilities of the ARM Cortex M4F core to 96MHz in turbo mode while lowering the active power consumption to <6µA/MHz in normal mode. An integrated DMA engine combined with the extra computing bandwidth gives designers the flexibility to add more complex sensor processing algorithms to their energy-sensitive products without sacrificing quality or battery life.

The Apollo3 Blue also provides a dedicated second core for the ultra-low power BLE5 connectivity platform providing superior RF throughput and leaving plenty of resources available for user applications. The radio performance and interoperability has already been proven to be reliable and robust in real-world consumer products which are currently shipping in massive volume. 

Ambiq Micro Sub-threshold Power Optimized Technology platform continues to bring unprecedented levels of energy efficiency to algorithm providers, ODMs and OEMs, said Aaron Grassian, Ambiq’s Vice President of Marketing. The Apollo family is already being used to bring neural networks to battery-powered hearables and remote controls with always-on voice assistant integration and commands.  The Apollo3 Blue further solidifies Ambiq Micros capabilities to meet the market demand of adding AI inference engines like voice and predictive sensory processing to ultra-low power edge devices.

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