Compute Blade – A Rack-mountable PoE-powered Raspberry Pi CM4 carrier board with an NVMe SSD (Crowdfunding)

Compute Blade Raspberry Pi CM4 rack

Uptime Lab Compute Blade is yet another Raspberry Pi CM4 carrier board, but it’s kind of unique with its long design designed to be mounted in racks and the board features an M.2 socket for an NVMe SSD plus an Ethernet port with PoE+ support. The board is designed for high-density, low-power consumption, plug-and-play blade servers for home and data-center use and users can build Home labs, edge servers with lower latency than cloud services, and CI/CD systems (build farms) for testing and software development. Compute Blade specifications: SoM – Raspberry Pi CM4 support and potentially alternative system-on-modules such as Radxa CM3 and Pine64 SoQuartz Storage NVMe SSD socket up to 22110 (2230, 2242, 2260, 2280 also supported) Optional MicroSD card slot Video Output – Optional HDMI port up to 4Kp60 Networking – Gigabit Ethernet RJ45 port with PoE+ USB USB Type-C port to flash the bootloader, eMMC/SD card, and […]

VVenC & VVdeC H.266 open source video encoder and decoder work on x86 and Arm

H.266 video decoder windowslinux macOS android

VVenC and VVdeC are open-source software H.266/VCC video encoder and decoder respectively that are optimized to use SIMD instructions on x86 (SSE42/SIMDe and AVX2) and Arm, and the decoder runs on Windows, Linux, macOS, and Android. H.266, aka VCC (Versatile Video Coding) video compression standard was adopted in 2020 promising to reduce data requirements by around 50% compared to the previous H.265/HEVC standard at the same visual quality. H.266 should also outperform the royalty-free AV1 video codec. We hadn’t seen news since the announcement, but this may be changing with the Realtek RTD1319D processor unveiled with support for both 4K H.266 and AV1 video decoding last September, and progress made on the VVenC & VVdeC H.266 open-source software encoder/decoder as been discussed during FOSDEM 2023. The Fraunhofer HHI group has been working on VVdeC and VVenC since the specifications were finalized in 2022. Both are based on VTM reference software […]

Eoxys Xeno+ Nano ML board combines NuMicro M2354 or STM32L4 MCU with Talaria TWO ultra low power WiFi & BLE 5.0 module

Eoxys Xeno+ Nano ML board

Eoxys Xeno+ Nano ML is a wireless machine learning (ML) board with either Nuvoton NuMicro M2354 or STMicro STM32L4 microcontroller, InnoPhase IoT’s Talaria TWO ultra-low power Wi-Fi and BLE 5.0 module, and the Syntiant Core 2 NDP120 neural decision processor we first noticed in the Arduino Nicla Voice module a few weeks ago. The boards/modules are designed for intelligent and secure IoT devices for smart home, industrial, and medical automation applications, and the company claims it can be used in Wi-Fi IoT sensors with up to 10+ years thanks to the low-power chips and circuitry used in the design. Eoxys Xeno+ Nano ML specifications: General purpose MCU (one or the other) STMicro STM32L4 Arm Cortex-M4 microcontroller at 80MHz with 1MB flash, 128KB/352KB SRAM Nuvoton NuMicro M2354 Arm Cortex-M23 microcontroller at 96MHz with 1MB flash, 128KB SRAM. Wireless module Innophase Talaria TWO ultra-low-power 2.4GHz 802.11b/n/g WiFi 4 and Bluetooth LE 5.0 […]

The Wi-R protocol relies on body for data communication, consumes up to 100x less than Bluetooth

Wi-R vs Bluetooth

The Wi-R protocol is a non-radiative near-field communication technology that uses Electro-Quasistatic (EQS) fields for communication enabling the body to be used as a conductor and that consumes up to 100x less energy per bit compared to Bluetooth. In a sense, Wi-R combines wireless and wired communication. Wi-R itself only has a wireless range of 5 to 10cm, but since it also uses the body to which the Wi-R device is attached, the range on the conductor is up to 5 meters. While traditional wireless solutions like Bluetooth create a 5 to 10-meter field around a person, the Wi-R protocol creates a body area network (BAN) that could be used to connect a smartphone to a pacemaker, smartwatch, and/or headphones with higher security/privacy and longer battery life.   One of the first Wi-R chips is Ixana YR11 with up to 1Mbps data rate, and they are working on a YR21 […]

Nordic Semi nRF7002 DK low-power dual-band WiFi 6 IoT development kit launched for $56 and up

nRF7002-DK development kit

Nordic Semi nRF7002 DK is an IoT development kit based on the nRF5340 dual-core Cortex-M33 multi-protocol wireless SoC and nRF7002 companion chip adding low-power dual-band (2.4GHz and 5.0 GHz) WiFi 6 connectivity. When Nordic Semi introduced the nRF7200 dual-band WiFi 6 companion chip for nRF52840 and nRF5340 wireless SoCs and nRF9160 cellular IoT SiP last summer, the “nRF7002-PDK” development kit was only mentioned in passing with a 3D render and not much else. The company has now announced the availability of the nRF7002 DK to help developers create low-power Wi-Fi 6 IoT applications. nRF7002 DK specifications: Wireless MCU – Nordic Semi nRF5340 dual-core Arm Cortex-M33 microcontroller @ 128/64 MHz with 1 MB Flash + 512 KB RAM for the application core and 256 KB Flash + 64 KB RAM for the network core, Bluetooth 5.1 LE with direction-finding support, Bluetooth mesh, NFC, Thread, Zigbee, 802.15.4, ANT, and 2.4 GHz proprietary […]

XGO 2 – A Raspberry Pi CM4 based robot dog with an arm (Crowdfunding)

XGO 2 robot dog with arm

XGO 2 is a desktop robot dog using the Raspberry Pi CM4 as its brain, the ESP32 as the motor controller for the four legs and an additional robotic arm that allows the quadruped robot to grab objects. An evolution of the XGO mini robot dog with a Kendryte K210 RISC-V AI processor, the XGO 2 robot offers 12 degrees of freedom and the more powerful Raspberry CM4 model enables faster AI edge computing applications, as well as features such as omnidirectional movement, six-dimensional posture control, posture stability, and multiple motion gaits. The XGO 2 robot dog is offered in two variants – the XGO-Lite 2 and the XGO-Mini 2 – with the following key features and specifications: The company also says the new robot can provide feedback on its own postures thanks to its 6-axis IMU and sensors for the joints reporting the position and electric current. A display […]

STM32Cube.AI Developer Cloud generates AI workloads for STM32 microcontrollers

STM32Cube.AI developer cloud

STMicroelectronics has just announced the STM32Cube.AI Developer Cloud opening access to a suite of online AI development tools for the STM32 microcontrollers (MCUs) allowing developers to generate, optimize, and benchmark AI working on the company’s 32-bit Arm microcontrollers. The company sus the STM32Cube.AI Developer Cloud is based on the existing STM32Cube.AI ecosystem of desktop tools with the added benefit of being able to remotely benchmark models on STM32 hardware through the cloud in order to save on workload and cost. Some of the highlights of the online tools include: An online interface to generate optimized C-code for STM32 microcontrollers without requiring prior software installation. Access to the STM32 model zoo, a repository of trainable deep-learning models and demos. It currently features human motion sensing for activity recognition and tracking, computer vision for image classification or object detection, audio event detection for audio classification, and more. You’ll find those on GitHub […]

Arduino Nicla Voice enables always-on speech recognition with Syntiant NDP120 “Neural Decision Processor”

Arduino PRO Nicla Voice with LiPo battery

Nicla Voice is the latest board from the Arduino PRO family with support for always-on speech recognition thanks to the Syntiant NDP120 “Neural Decision Processor” with a neural network accelerator, a HiFi 3 audio DSP, and a Cortex-M0+ microcontroller core, and the board also includes a Nordic Semi nRF52832 MCU for Bluetooth LE connectivity. Arduino previously launched the Nicla Sense with Bosch SensorTech’s motion and environmental sensors, followed by the Nicla Vision for machine vision applications, and now the company is adding audio and voice support for TinyML and IoT applications with the Nicla Voice. Nicla Voice specifications: Microprocessor – Syntiant NDP120 Neural Decision Processor (NDP) with one Syntiant Core 2 ultra-low-power deep neural network inference engine, 1x HiFi 3 Audio DSP, 1x Arm Cortex-M0 core up to 48 MHz, 48KB SRAM Wireless MCU – Nordic Semiconductor nRF52832 Arm Cortex-M4 microcontroller @ 64 MHz with 512KB Flash, 64KB RAM, Bluetooth […]

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