I’ve just been notified about an inexpensive board (HLK-W806) based on WinnerMicro W806 32-bit XT804 (XuanTie E804) microcontroller clocked at up to 240 MHz and equipped with 1MB flash and 288KB RAM. XuanTie is the microcontroller family from Alibaba’s subsidiary T-Head Semiconductor, notably XuanTie RISC-V cores, but I’ve just learned not all XuanTie cores are based on the RISC-V architecture, and as we’ll see below, Xuantie E804 core appears to be based on the C-Sky architecture. It may still be interesting, as it’s in the STM32 board price range (pre-2020), but with a much higher frequency, so let’s have a look. HLK-W806 development board specifications: MCU – WinnerMicro W806 32-bit XT804 microcontroller @ 240 MHz with 1MB Flash, 288KB RAM, FPU, DSP, crtypto engine Expansion – 2x 24-pin headers with (based on MCU specs) 1x SDIO host with support for SDIO 2.0, SDHC, MMC 4.2 1x SDIO device up to […]
RK3399-based programmable wheeled robot works across multiple floors
SLAMTEC Hermes robot platform is a programmable wheeled robot that can take payloads of up to 60 kg across multiple floors thanks to an optional elevator controller, which makes it suitable for hotels, hospitals, airports, warehouses, transportation hubs, surveillance robot, and more. Powered by a Rockchip RK3399 mainboard, the Hermes robot platform supports autonomous path-finding, robot collaboration, cross-floor delivery, smart obstacle avoidance, safety features, and autonomous Recharging. It can be controlled with a REST API, programmed with C++ SDK, or a program called RoboStudio available for Windows and Android. Hermes wheeled robot platform specifications: Mainboard – Rockchip RK3399 SBC Video Output – HDMI Audio – 3.5mm audio (mic+headphone) jack, dual-channel 5W/8Ω amplifier header Network connectivity – Gigabit Ethernet RJ45 port, dual-band WiFi, 4G cellular with SIM card slot USB – USB 3.0 Type-C port Motion 6.5-inch in-Wheel motor Up to 1.2m/s (4.3 km/h) by default, but can be customized to […]
Raspberry Pi smart audio devkit features AISonic IA8201 DSP, microphone array
Knowles AISonic IA8201 Raspberry Pi development kit is designed to bring voice, audio edge processing, and machine learning (ML) listening capabilities to various systems, and can be used to evaluate the company’s AISonic IA8201 DSP that was introduced about two years ago. The kit is comprised of three boards with an adapter board with three buttons connecting to the Raspberry Pi, as well as the AISonic IA8210 DSP board itself connected via a flat cable to a microphone array. Knowles AISonic Raspberry Pi development kit Knowles did not provide the full details for the development but says it enables wake-on-voice processing for low latency voice UI, noise reduction, context awareness, and accelerated machine learning inferencing for edge processing of sensor inputs. Some of the use cases include Low Power Voice Wake to listen for specific OEM keywords to wake the host processor, Proximity Detection when combined with an ultrasonic capable […]
Allwinner V833 AI video development board runs Tina Linux or Melis RTOS
Lindenis V833 is an AI video/camera development board based on Allwinner V833 single-core Cortex-A7 processor with a 400 MOPS AI accelerator (NPU) and running OpenWrt-based Tina Linux or Melis RTOS based on the RT-Thread kernel. The board comes with up to 3GB RAM, a MicroSD card socket, MIPI DSI, MIPI CSI, and BT1120 interfaces for video output and input, Gigabit Ethernet, 2.4 GHz WiFi, and a few other I/Os. Lindenis V833 specifications: SoC – Allwinner V833 single-core Arm Cortex-A7 processor @ up to 1.2 GHz with H.265/H.265 1080p video encoder, MJPEG 1080p video encoder, 400 MOPS AI accelerator (See PDF datasheet) System Memory – Up to 3GB DDR3/DDR3L Storage – MicroSD card slot with support for SDHC and SDXC, SPI NOR flash Display Interfaces 4-lane MIPI-DSI up to 1080p BT1120 output Touch panel header Video In 4-lane MIPI-CSI camera interface BT1120 input Audio – 3.5mm Line-in jack, built-in microphone Connectivity […]
Station M2 business-card sized Android 11 mini PC, also supports Ubuntu & Buildroot
After introducing Station P2 Rockchip RK3568 mini PC in March of this year, Firefly has now launched another, cheaper model with the ultra-thin Station M2 computer based on the company’s ROC-RK3566-PC single board computer equipped with Rockchip RK3566 SoC. Station M2 is only slightly larger than a business card, but packs up to 8GB RAM, M.2 SSD storage, HDMI 2.0, Gigabit Ethernet, and USB 3.0/2.0 ports. Station M2 specifications: SoC – Rockchip RK3566 with a quad-core Cortex-A55 processor @ up to 1.8GHz. Arm Mali-G52 2EE GPU with support for OpenGL ES 1.1/2.0/3.2. OpenCL 2.0. Vulkan 1.1, 0.8 TOPS AI accelerator, 4K H.265/H.265/VP9 video decoder, 1080p100 H.265/H.264 video encoder. System Memory – 2GB or 4GB LPDDR4 (8GB optional) Storage – 32GB or 64GB (128GB eMMC optional), M.2 PCIe 2.0 socket for 2242 NVMe SSD, MicroSD card socket Video Output – 1x HDMI port up to 4Kp60 Audio – 3.5mm headphone jack, […]
Vecow ABP-3000 AI Edge gateway combines Hailo-8 AI accelerator with Intel Whiskey Lake processor
We first discovered Hailo-8 AI accelerator with claims of up to 26 TOPS performance and 3TOPS/W efficiency in October 2020. Since then, we’ve seen several integrate an Hailo-8 M.2 module into their design including EdgeTuring Edge AI camera and Vecow VAC-1000 gateway with a 24-core Foxconn processor. Vecow has now integrated the Hailo-8 AI accelerator into another gateway, but instead of relying on an Arm processor, the Vecow ABP-3000 AI computing system features an 8th generation Intel Core Whiskey Lake processor. Vecow ABP-3000 specifications: SoC – Intel Core i7-8665UE or i3-8145UE quad-core Whiskey Lake processor with Intel UHD Graphics 620; 15W TDP System Memory – 2x DDR4 2400MHz SO-DIMM, up to 64GB Storage – 1x M.2 Key B Socket (PCIe x2/SATA) AI Accelerator – Hailo-8 AI Processor, up to 26 TOPS with TensorFlow, ONNX frameworks support System IO chip – IT8786E Video Output – 2x DisplayPort up to 4096 x […]
NVIDIA TAO Transfer Learning Toolkit (TLT) 3.0 released with pre-trained models
NVIDIA first introduced the TAO (Train, Adapt and Optimize) framework to eases AI model training on NVIDIA GPU’s as well as NVIDIA Jetson embedded platforms last April during GTC 2021. The company has now announced the release of the third version of the TAO Transfer Learning Toolkit (TLT 3.0) together with some new pre-trained models at CVPR 2021 (2021 Conference on Computer Vision and Pattern Recognition). The newly released pre-trained models are applicable to computer vision and conversational AI, and NVIDIA claims the release provides a set of powerful productivity features that boost AI development by up to 10 times. Highlights of TAO Transfer Learning Toolkit 3.0 Various computer vision pre-trained models for Computer vision: Body Pose estimation model that supports real-time inference on edge with 9x faster inference performance than the OpenPose model. Emotion recognition Facial landmark License plate detection and recognition Heart rate estimation Gesture recognition Gaze estimation […]
TI AM64x 7-core processor is made for PLC’s, motor drives, industrial robots
Texas Instruments AM64x is a family of 64-bit Arm processors with functional safety designed for Programmable Logic Controllers (PLC), motor drives, remote I/O, and industrial robots. The top-end processor of the family, AM6442, comes with seven cores including two Cortex-A53 application cores, four Cortex-R5F real-time cores, and one Cortex-M4F isolated core. AFAICT, while the documentation is dated January 2021 and TI announced the processor in February in a blog post with a cryptic title, it was only first picked up by Embedded Computing in early May. Besides the processor itself, TI also provides an AM64x starter kit and a full-featured AM64x evaluation kit, and several companies are already preparing development boards and modules as we’ll see further below. TI AM64x processor AM64x key features & specifications: CPU cores Dual-core Arm Cortex-A53 processor @ 1.0 GHz with 256KB L2 shared cache with SECDED ECC, 32KB L1 D-cache, 32KB L1 I-cache Up […]