Arduino Portenta H7 Gets Embedded Vision Shield with Ethernet or LoRa Connectivity

Portenta Vision Shield

[Update January 28, 2021: The LoRa version of Portenta Vision Shield is now available] Announced last January at CES 2020, Arduino Portenta H7 is the first board part industrial-grade “Arduino Pro” Portenta family. The Arduino MKR-sized MCU board has plenty of processing power thanks to STMicro STM32H7 dual-core Arm Cortex-M7/M4 microcontroller. It was launched with a baseboard providing access to all I/Os and ports like Ethernet, USB,  CAN bus, mPCIe socket (USB), etc… But as AI moves to the very edge, it makes perfect sense for Arduino to launch Portenta Vision Shield with a low-power camera, two microphones, and a choice of wired (Ethernet) or wireless (LoRA) connectivity for machine learning applications. Portenta Vision Shield key features and specifications: Storage – MicroSD card socket Camera – Himax HM-01B0 camera module with 324 x 324 active pixel resolution with support for QVGA Image sensor – High sensitivity 3.6μ BrightSense pixel technology […]

DevEBox STM32H7 Development Boards are made for Factory Automation

STM32H7XX-M7 Development Board

When it comes to STMicroelectronics’ STM32H7 series, there are three product lines- Dual-core lines, Single-core lines, and Value lines. ARM Cortex-M7 based – STM32H7 MCU series is capable of delivering 1327 DMIPS/ 3224 CoreMark. These MCUs are designed for factory automation (HMI, process control, power management), connectivity & security (Alarm panel, Wireless Modules). To continue with the growth of the STM32H7 series, we have China-based MCUdev DevEBox’s STM32H7XX-M development boards taking a single-core line and a value line module. The two STM32H7XX-M development boards use STM32H743VIT6 and STM32H750VBT6 core modules. The STM32H743VIT6 comes from a single core line that offers ARM Cortex-M7 gets up to 2 Mbytes of dual-bank flash memory and 1 Mbytes of RAM. While the STM32H750VBT6 module from the value line is one of the cost-effective STM32H7 devices featuring 128 Kbytes of flash memory. STM32H7 Development Boards These boards from MCUdev measure approximately 40mm x 68mm in […]

Arduino MKR inspired MKR Windy board is equipped with STM32WL LoRa SoC

MKR Windy board

We recently wrote about MKR SharkyPro BLE, Zigbee, OpenThread development board based on STM32WB55 MCU and following Arduino MKR form factor, but it turns out Midatronics has also launched a similar-looking board with LoRa connectivity. MKR Windy board features the company’s Windy STM32WL module with an uFL connector and following the same Arduino MKR layout. MKR Windy specifications: Wireless Module – Windy module (MDX-STWLU-R01) Wireless MCU – STMicro STM32WLE5JX/STM32WL55JX Arm Cortex-M4 MCU @ 48 MHz with up to 256KB flash, 64KB SRAM Connectivity Semtech SX126x sub-GHz radio with LoRa, (G)FSK, (G)MSK, and BPSK modulation, 150 MHz to 960 MHz frequency range RX Sensitivity: –123 dBm for 2-FSK,  -148 dBm for LoRa Antenna – uFL connector for external antenna Supply Voltage – 1.8 V to 3.6 V Dimensions : 16 x 26 mm Temperature Range – 40°C to + 85 °C USB – 1x Micro USB port for power and programming […]

USB2IO high-speed interface explorer tool combines Intel Cyclone 10 FPGA and STM32H7 MCU

USB2IO interface explorer

In the second part of 2020, we’ve seen a fair amount of USB debugging tools for electronics designers and hardware hackers including the Glasgow Interface explorer with an ICE40 FPGA. But if you need even more flexibility or higher I/O speeds (up to 300 MHz), DAB Embedded USB2IO interface explorer should help thanks to the combination of an STMicro STM32H7 MCU and an Intel Cyclone 10 FPGA. USB2IO interface explorer hardware specifications: MCU – STMicro STM32H743 Arm Cortex-M7 @ 480MHz CPU clock An external 64MB QSPI flash for extra FPGA code storage; FPGA  – Intel Cyclone 10LP (10CL040) with 40k logic elements, 1,134 Mbit embedded memory, 126 DSP blocks External memory – 32MB SDRAM for MCU and FPGA (64MB in total) Storage – 64MB QSPI for connected to MCU for FPGA code storage I/Os via 20-pin external header/connector 16 x GPIO mode (single-ended), 8x LVDS pair mode or a mix […]

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

MKR SharkyPro I STM32WB55 board

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 […]

STM32WB5MMG Wireless Module simplifies Bluetooth LE, Zigbee, OpenThread connectivity

STM32WB5MMG Wireless Module

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 […]

Protocol Droid is a USB bridge board to I2C, CAN Bus, RS485, UART, SPI, etc. (Crowdfunding)

Protocol Droid

We’ve seen some interesting USB hardware hacking/debugging boards in the last two months with Tigard, Ollie, and Glasgow Interface Explorer each with their own price point and features, but with the goal of replacing multiple other programming or debug boards you may need for your projects. Protocol Droid is another one of such USB boards for electronics designers and hardware hackers. It offers I/O connectivity via terminal blocks for I2C, CAN Bus, RS485, UART, SPI, and other interfaces. Protocol Droid key features and specifications: MCU – Unnamed STMicro microcontroller Host interface – Micro USB port Core Interfaces: I²C controller & peripheral modes SPI controller & peripheral modes RS485 controller & peripheral modes CAN Bus UART 2x PWM 2x ADC 2x DAC Debugging / programming interfaces – 7-pin JTAG/SWD unpopulated header Power Sources – 3V & 5V DC with limited current via 2-pin terminal blocks All interfaces are available simultaneously through […]

Use AutoTVM and uTVM to optimize ML workloads on embedded devices & microcontrollers

MicroTVM example

We are seeing a massive increase in resource-constraints for embedded devices due to a lack of mature software stacks. With the increase in open-source hardware, the available software support takes a considerable amount of time to develop AI/ML/DL applications. Some of the challenges faced today are that bare-metal devices do not have on-device memory management, and they do not have LLVM support. They are also hard to debug because of rigid programming and cross-compilation interfaces. Due to this, “optimizing and deploying machine learning workloads to bare-metal devices today is difficult”. To tackle these challenges, there have been developments to support TVM, an open-source machine learning compiler framework for CPUs, GPUs, and machine learning accelerators, on these bare-metal devices, and Apache TVM is running an open-source foundation to make this easy. “µTVM is a component of TVM that brings broad framework support, powerful compiler middleware, and flexible autotuning and compilation capabilities […]

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