low power News - Page 25 of 36 - CNX Software

January 12, 2021January 12, 2021 by Jean-Luc Aufranc (CNXSoft) - 14 Comments

Intel Jasper Lake N-Series launched with 6W Celeron and 10W Pentium Silver processors

Pentium Silver J5040 vs Pentium Silver N6005

Intel has finally announced the Gemini Lake processor family successor at CES 2021 together with other processors. The Jasper Lake family currently comes with six different Celeron and Pentium Silver parts with respectively 6W and 10 TDP. The company positions those for the education market, but I’d expect them to also be found in various mini PCs, single board computers, and systems-on-module. The processors are manufactured with the company’s 10nm process, and are said to deliver up to 35% better overall application performance and up to 78% better graphics performance compared to Gemini Lake Refresh processors. The new parts listed on Ark are not really new for CNX Software readers as we published the list of Jasper Lake processors in September following a leak. But we know have more details, so let’s compare the top parts of both Gemini Lake Refresh (Pentium Silver J5040) and Jasper Lake (Pentium Silver N6005) […]

January 11, 2021August 24, 2021 by Jean-Luc Aufranc (CNXSoft) - No Comments

MKR SharkyPro BLE, Zigbee, OpenThread development board follows Arduino MKR form factor

Just a few days ago, we mentioned STMicro launched STM32WB5MMG wireless module to simplify Bluetooth LE, Zigbee, OpenThread connectivity by allowing 2-layer baseboards for the module. It turns out there’s also such a module from a third-party with namely Midatronics SharkyPro module based on STM32WB55, and the company also launched MKR SharkyPro I & II development boards following Arduino MKR form factor. MKR SharkyPro specifications: Wireless Module – SharkyPro module Wireless MCU – STMicro STM32WB55CG/CE dual-core Arm Cortex-M4 core at 64 MHz (application processor) and Arm Cortex-M0+ core at 32 MHz (network processor) with 512KB flash, 256KB SRAM Connectivity – Bluetooth 5.0 LE, Bluetooth Mesh 1.0, OpenThread, Zigbee, and other IEEE 802.15.4 proprietary protocols Antenna – Onboard chip antenna (SharkyPro I) or SMA antenna connector (SharkyPro I) Power 3.3V supply voltage Consumption – 13 nA in shutdown mode, 600 nA in Standby mode + RTC + 32 KB RAM Dimensions […]

January 11, 2021January 10, 2021 by Saumitra Jagdale - No Comments

DBM10 AI SoC is optimized for battery-powered voice and sensor processing

DSP Group announced DBM10 a low-power AI/ML-enabled dual-core SoC. The SoC is equipped with a DSP (Digital Signal Processor) and a dedicated nNetLite NN (Neural Network) processor that improves voice and sensor processing and ensures low-power consumption when working with sufficient-sized neural networks. Key Specifications of NN Processor Form factor: ~4 mm2 Ultra-low-power inference consumption – ~500 µW (typical) for voice NN algorithms Runs Hello Edge 30-word detection model @ 1 MHz (125 MHz available) Allows porting of large models (10s of megabytes) without significant accuracy loss using model optimization and compression. DBM10 AI SoC uses the combined functioning of machine learning, voice, and sensor parameters. This includes voice trigger (VT), voice authentication (VA), voice command (VC), noise reduction (NR), acoustic echo cancellation (AEC), sound event detection (SED), proximity and gesture detection, sensor data processing, and equalization. The DBM10 is suitable for battery-operated devices like smartphones, tablets, and wearables. It […]

January 8, 2021August 24, 2021 by Saumitra Jagdale - 3 Comments

STM32WB5MMG Wireless Module simplifies Bluetooth LE, Zigbee, OpenThread connectivity

The STM32WB5MMG (STM32) is a wireless microcontroller module by STMicroelectronics. It is a compact ultra-low-power module that allows customers to design 2-layer PCBs and integrates everything up to the antenna, including an IPD (integrated passive device) for reliable antenna matching in order to reduce the overall costs. The STM32 wireless module is compatible with BLE (Bluetooth Low Energy) 5.0, OpenThread, Zigbee 3.0, dynamic and static concurrent modes, and 802.15.4 proprietary protocols. It also supports simultaneous dual-protocol mode that allows IEEE 802.15.4 radio-based protocols like Zigbee 3.0 and OpenThread for direct connection with any BLE device. Overview of STM32 Wireless Module The STM32 wireless module is a SiP-LGA86 package (System in Package Land Grid Array) with various external components including: STMicro STM32WB55 Cortex-M4/M0+ wireless MCU LSE crystal HSE crystal Passive components for SMPS Antenna matching and antenna IPD for RF matching and harmonics rejection Key Features of STM32 Wireless Module Dedicated […]

January 5, 2021 by Saumitra Jagdale - 1 Comment

BHI260AP is an AI smart sensor with built-in IMU by Bosch Sensortec

BHI260AP AI smart sensor integrates a 6-axis IMU, a 32-bit customizable programmable microcontroller, and various software functionalities. The AI smart sensor has embedded AI with on-sensor applications such as fitness tracking, navigation, machine learning analytics, and orientation estimation. The dimensions of the miniaturized AI smart sensor are 4.1mm x 3.6mm x 0.83 mm. Hardware Features of BHI260AP AI Smart Sensor ARC EM4 CPU includes ARCv2 16/32 bit instruction set working up to a frequency of 3.6 MHz. The core also integrates Floating Point Unit (FPU) and Memory Protection Unit (MPU) with 4 channel micro DMA controller. CPU has two modes of AI functioning at 25Hz and 50Hz with 249µA and 386µA of current consumption respectively. Integrated sensor (6-DoF IMU) includes 16-bit 3 axis accelerometer and 16-bit 3 axis gyroscope. The sensor works at an operating voltage of 1.8 V with a standby current value of 8µA, hence the power consumption […]

December 27, 2020December 26, 2020 by Saumitra Jagdale - 1 Comment

LG launches LG8111 AI SoC and development board for Edge AI processing

LG Electronics has designed LG8111 AI SoC for on-device AI inference and introduced the Eris Reference Board based on the processor. The chip supports hardware processing in artificial intelligence functions such as video, voice, and control intelligence. LG8111 AI development board is capable of implementing neural networks for deep learning specific algorithms due to its integrated “LG-Specific AI Processor.” Also, the low power and the low latency feature of the chip enhances its self-learning capacity. This enables the products with LG8111 AI chip to implement “On-Device AI.” Components and Features of the LG8111 AI SoC LG Neural engine, the AI accelerator has an extensive architecture for “On-Device” Inference/Leaning with its support on TensorFlow, TensorFlow Lite, and Caffe. The CPU of the board comes with four Arm Cortex A53 cores clocked at 1.0 GHz, with an L1 cache size of 32KB and an L2 cache size of 1MB. The CPU also […]

December 24, 2020December 24, 2020 by Saumitra Jagdale - 4 Comments

Himax WE-I Plus EVB AI development board supports TFLite for microcontrollers

Himax WE-I Plus EVB Endpoint AI Development Board

Himax WE-I Plus EVB is a low-power AI development board focused on machine learning and deep learning applications with its support for the TensorFlow Lite framework for Microcontrollers. It consists of majorly two significant components. First, HX6537-A ASIC is an ultra-low-power microcontroller designed for battery-powered TinyML applications. Second, HM0360 VGA mono camera with ultra-low power and CMOS image sensing features for CV(Computer Vision) based applications like object classification and recognition. The All in One AI Development Board The Development Board consists of HX6537-A ASIC, with built-in ARC EM9D DSP working at 400MHz frequency. It contains internal 2MB ultra-low leakage SRAMs for system and program usage. It also contains two LEDs to display classification results. Connections with external sensors/devices can be established using I2C and GPIOs interface present in its expansion header. “The all-in-one WE-I Plus EVB includes an AI processor, HM0360 AoS VGA camera, 2 microphones, and a 3-axis accelerometer […]

December 2, 2020 by Jean-Luc Aufranc (CNXSoft) - No Comments

Power Profiler Kit II measures power consumption in Nordic Semi based embedded systems

If you’re developing battery-powered products it’s important to optimize your application to consume as little power as possible to extend battery life. As we’ve seen with Qoitech Otii Developer Tool, getting the right tool for development can help developers work more efficiently, and save countless man hours. If you’re specifically working on products based on Nordic Semi nRF51, nRF52, nRF53 or nRF91 wireless chips, the company has just announced the Power Profiler Kit II (PPK2) that enables easy and affordable power measurement of average and dynamic power consumption in embedded solutions based on the aforementioned wireless SoC’s/SiP’s. Power Profiler Kit II key features: 200nA to 1A measurement range Resolution varies between 100nA and 1mA depending on the measurement range Instantaneous and average current measurement for all Nordic DKs, in addition to custom HW Ampere meter and source modes Built-in programmable regulator with a 0.8V to 5V output range and up […]