XGO-Rider is a 2-wheel self-balancing robot with an ESP32 controller plus either a Raspberry Pi CM4 or BBC Micro:bit (Crowdfunding)

XGO-Rider

XGO-Rider is a two-wheel self-balancing robot with an ESP32 controller for motor and servo control, USB-C charging, etc… and a choice between a Raspberry Pi CM4 module or a BBC Micro:bit board for display, audio, and camera (CM4-only). It’s not the first robot from Luwu Intelligence, since the company launched the XGO-Mini robot dog in 2021, followed by the XGO 2 Raspberry Pi CM4-powered desktop robotic dog with an arm which we reviewed last year. The new XGO-Rider builds on these earlier models but in a different form factor moving from four-legged robots to a 2-wheel self-balancing robot design with many of the same features including AI vision running on the Raspberry Pi CM4. XGO-Rider specifications: Host controller (one or the other) Raspberry Pi CM4 with 2GB RAM + ESP32 for main control, USB-C charging port, DIP switch BBC Micro:bit V2 + ESP32 for main control, USB-C charging port, DIP […]

SONOFF ZBMicro Zigbee USB smart adapter adds any USB device to your Smart Home setup

SONOFF ZBMicro

SONOFF Micro Zibgee USB Smart adapter, or SONOFF ZBMicro for shorts, is a Zigbee 3.0 USB adaptor to remotely control USB devices via your smartphone app or home automation solution based on Home Assistant or other solution to turn on/off the device, set timers to control charging times, configure smart scenes, or control with voice commands. The new home automation device from ITEAD is based on a Silicon Labs EFR32MG21 multiprotocol SoC, works with the usual eWelink app, as well as Home Assitant and OpenHAB open-source solutions when the server is fitted with a compatible Zigbee 3.0 USB dongle SONOFF ZBMicro specifications: Wireless MCU – Silicon Labs EFR32MG21 MCU core – Arm Cortex-M33 microcontroller @ 80 MHz Memory – 96KB SRAM Storage – 352KB flash, 1024KB ROM for protocols and library functions Wireless –  Zigbee 3.0 USB – USB 2.0 Type-A port Misc User Button – single press: Turn on/off […]

Sipeed MaixCAM is a RISC-V AI camera devkit with up to 5MP camera, 2.3-inch color touchscreen display, GPIOs

Sipeed MaixCAM

Sipeed MaixCAM is an AI camera based on SOPHGO SG2002 RISC-V (and Arm, and 8051) SoC with a 1 TOPS NPU that takes up to 5MP camera modules and comes with a 2.3-inch color touchscreen display. The development kit also comes with WiFi 6 and BLE 5.4 connectivity, optional Ethernet, audio input and output ports, a USB Type-C port, and two 14-pin GPIO headers for expansion that makes it suitable for a range of computer vision, Smart audio, and AIoT applications. Sipeed MaixCAM specifications: SoC – SOPHGO SG2002 CPU 1 GHz RISC-V C906 processor or Arm Cortex-A53 core (selectable at boot) running Linux 700 MHz RISC-V C906 core running an RTOS 25 to 300 MHz low-power 8051 processor NPU – 1 TOPS @ INT8 with support for models such as Mobilenetv2, YOLOv5, YOLOv8, etc… Video Codec – H.264, H.265, MJPEG hardware encoding and decoding up to 2K @ 30fps Memory […]

WCH CH32V006 RISC-V microcontroller adds more I/Os, memory, and storage compared to CH32V003

CH32V006 block diagram

WCH CH32V006 RISC-V microcontroller is an upgrade to the 10-cent CH32V003 microcontroller with more I/Os, up to four times the memory, storage, a wider supply voltage range, the addition of a TouchKey interface, as well as a new 32-bit V2C RISC-V core instead of the V2A core found in the CH32V003. More specifically that means we went from the CH32V003 with 2KB SRAM and 8KB flash, up to 8KB SRAM and 62KB for the CH32V006, and 6KB SRAM and 32KB flash for the CH32V005, a smaller sibling of the new RISC-V microcontroller. WCH CH32V005 & CH32V006 specifications (with highlights in bold to show differences against CH32V003): CPU – 32-bit “RISC-V2C” core up to 48 MHz Memory – 6KB SRAM (CH32V005) or 8KB SRAM (CH32V006) Storage – 32KB flash (CH32V005) or 62KB flash (CH32V006) Peripherals Up to 31x GPIO with interrupt support (CH32V003 had up to 18x GPIO) 2x USART interfaces […]

$23 C790 HDMI to MIPI CSI adapter adds HDMI and audio input to Raspberry Pi SBCs

Raspberry Pi 4 HDMI Input board

C790 is an HDMI to MIPI CSI-2 board compatible with Raspberry Pi single board computers featuring a 40-pin GPIO header that adds both HDMI input up to 1080p60 and I2S audio input to the popular Arm SBC. The solution can be useful for IP KVM solutions as we’ve seen with the PiKVM v3 and PiCast portable KVM switch, or to capture video and audio from a camera that outputs HDMI with audio through the board’s MIPI CSI camera interface and I2S input signals on the GPIO header. C790 specifications: Supported SBC’s – Raspberry Pi Zero, 3B, 3B+, 4B, CM3, CM4 with MIPI CSI-2 input port (Note: Raspberry Pi 4 is limited to 1080p50 due to 2-lane MIPI CSI-2, CM4 supports 1080p60) Main chip – Toshiba TC358743XBG HDMI to CSI-2 bridge chip up to 1920×1080, 60 FPS Video and audio input – HDMI port up to 1080p60 Video Output – 2-lane […]

GIGAIPC PICO-N97A is a Pico-ITX SBC powered by an Intel Processor N97 CPU

Intel Processor N97 Pico-ITX SBC

GIGAIPC PICO-N97A Pico-ITX SBC features an Intel Processor N97 quad-core Alder Lake-N processor coupled with up to 16GB DDR5 SO-DIMM memory and M.2 SATA or NVMe storage designed for passively cooled and enclosed systems for Industry 4.0 applications in the smart cities, retail, and healthcare sectors. The single board computer supports up to two independent displays via HDMI and LVDS interfaces. It also provides dual Gigabit Ethernet, two USB 3.1 ports, an additional M.2 Key-B socket for wireless, and various headers for RS232/RS422/RS485, GPIO, USB 2.0, and more. GIGAIPC PICO-N97A specifications: SoC – Intel Processor N97 CPU – Alder Lake-N quad-core/quad-thread processor @ up to 3.6 GHz Cache – 6MB cache GPU – 24 EU Intel UHD graphics @ up to 1.20 GHz TDP: 12W System Memory – Up to 16GB DDR5-4800 via a single SO-DIMM socket Storage – SATA or NVMe SSD via M.2 M-Key socket (See expansion) Video […]

BitNetMCU project enables Machine Learning on CH32V003 RISC-V MCU

Neural networks on the CH32V003

Neural networks and other machine learning processes are often associated with powerful processors and GPUs. However, as we’ve seen on the page, AI is also moving to the very edge, and the BitNetMCU open-source project further showcases that it is possible to run low-bit quantized neural networks on low-end RISC-V microcontrollers such as the inexpensive CH32V003. As a reminder, the CH32V003 is based on the QingKe 32-bit RISC-V2A processor, which supports two levels of interrupt nesting. It is a compact, low-power, general-purpose 48MHz microcontroller that has 2KB SRAM with 16KB flash. The chip comes in a TSSOP20, QFN20, SOP16, or SOP8 package. To run machine learning on the CH32V003 microcontroller, the BitNetMCU project does Quantization Aware Training (QAT) and fine-tunes the inference code and model structure, which makes it possible to surpass 99% test accuracy on a 16×16 MNIST dataset without using any multiplication instructions. This performance is impressive, considering […]

Arduino Pro Opta D1608E/D1608S expansions feature electromechanical or solid-state relays, 16 I/Os

Arduino Pro Opta Ext D1608S and D1608E

Arduino has recently announced two new expansions to their Arduino Pro Opta PLC series – the Arduino Pro Opta Ext D1608E and Arduino Pro Opta Ext D1608S, the main difference between the two is that the D1608E features 8 electromechanical relays (EMRs) whereas the D1608S features solid-state relays (SSRs). Other than that both expansion modules have 16x programmable I/Os (0-24 V digital / 0-24 V analog) which doubles the number of I/Os we have seen on the Opta micro PLC. Both are compatible with the Arduino IDE and the PLC IDE and are easy to install on a DIN rail. These features make it suitable for control, monitoring, and predictive maintenance applications. Previously we have seen Arduino launch a PLC Starter Kit for those who want to get started with PLCs. Additionally, we have written about ESP32-powered PLCs, Raspberry Pi-powered PLCs, and more. Feel free to check those out if you […]

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