GL.iNet Comet GL-RM1
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GL.iNet Comet (GL-RM1) low-cost KVM-over-IP solution supports up to 2K resolution

GL.iNet has entered the low-cost KVM-over-IP market with the Comet (GL-RM1) remote KVM to remotely control any computer over an Ethernet connection with an HDMI port for video and audio input and a USB-C port for keyboard and mouse emulation. It’s an alternative to the Sipeed NanoKVM (Cube) with a more powerful quad-core processor, 1GB RAM, an 8GB eMMc flash, a gigabit Ethernet port, and support for up to 2K (2160×1440) resolution at 60 FPS. Comet GL-RM1 specifications: SoC – Quad-core CPU @ 1.5 GHz System Memory – 1GB DDR3 Storage – 8GB eMMC flash Video & Audio Input – HDMI port up to 2K @ 60 FPS (2160 x 1440 @ 60 FPS); H.264 encodding with 30 to 60ms latency Networking – Gigabit Ethernet RJ45 port USB USB 2.0 Type-A port to connect peripherals like a Fingerbot or ATX power control board USB 2.0 Type-C port for mouse/keyboard emulation […]

reComputer J3010B Jetson Orin Nano Edge AI Computer
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Seeed reComputer J3010B Edge AI PC features NVIDIA Jetson Orin Nano with up to 67 TOPS of AI performance

Seeed Studio’s reComputer J3010B Edge AI PC is built around the NVIDIA Jetson Orin Nano module, which offers up to 67 TOPS AI performance (67 TOPS in super mode), with up to 8GB LPDDR5 memory, and a pre-installed 128GB NVMe SSD for storage. The mini PC features two USB 3.2 ports, HDMI 2.1 video output, a Gigabit Ethernet jack, M.2 slots for SSD and Wi-Fi, a mini PCIe socket for LTE, a 40-pin GPIO header, and a 12-pin UART header. With a compact aluminum case and active cooling, it has an operating temperature range of -10 to 60°C and can be powered via a DC 9-19V input. These features make this device useful for AI, IoT, and edge computing applications, such as smart lampposts for traffic monitoring, EV battery swapping and charging systems, smart recycling centers for waste management, and more. reComputer J3010B specifications: SoM options NVIDIA Jetson Orin Nano […]

ArmSoM RK3588 AIModule7 NVIDIA Jetson Nano-compatible SOM
OpenMV AE3 and N6 AI cameras
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MicroPython-programmable OpenMV N6 and AE3 AI camera boards run on battery for years (Crowdfunding)

OpenMV has launched two new edge AI camera boards programmable with MicroPython: the OpenMV AE3 powered by an Alif Ensemble E3 dual Cortex-M55, dual Ethos-U55 micro NPU SoC, and the larger OpenMV N6 board based on an STMicro STM32N6 Cortex-M55 microcontroller with a 1 GHz Neural-ART AI/ML accelerator. Both can run machine vision workloads for several years on a single battery charge. The OpenMV team has made several MCU-based camera boards and corresponding OpenMV firmware for computer vision, and we first noticed the company when they launched the STM32F427-based OpenMV Cam back in 2015. A lot of progress has been made over the years in terms of hardware, firmware, and software, but the inclusion of AI accelerators inside microcontrollers provides a leap in performance, and the new OpenMV N6 and AE3 are more than 100x faster than previous OpenMV Cams for AI workloads. For example, users can now run object […]

Waveshare CM5 NANO B Raspberry Pi CM5 carrier bord with CM5
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Waveshare CM5-NANO-B is a compact Raspberry Pi CM5 carrier board with the same dimensions as the Compute Module 5

Waveshare has just released the CM5-NANO-B, a compact Raspberry Pi CM5 carrier board, with the same dimensions as the Compute Module 5 and multiple peripheral interfaces making it suitable for industrial automation, IoT, embedded computing, AI development, and other space-constrained applications. Key features include a Gigabit Ethernet RJ45 port, an unpopulated 40-pin Raspberry Pi GPIO header, a USB 3.2 Gen1 Type-A port, dual MIPI 4-lane interfaces, a mini HDMI port supporting 4K output, a USB audio 3.5mm jack, a microSD card slot, and a 16-pin PCIe Gen2/3 x1 connector. Power is supplied via a USB-C port (5V/5A), and additional features include an RTC battery header, a 4-pin PWM fan header, a dual-color LED indicator, and user-configurable buttons. Waveshare CM5-NANO-B specifications: Compatibility – Raspberry Pi Compute Module 5 (CM5) Storage – MicroSD card slot (for Raspberry Pi CM5 Lite) Display Mini HDMI output up to 4K resolution Up to 2x MIPI […]

PineTab V RISC-V Tablet Debian
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Updated PineTab-V RISC-V tablet ships with Debian 12-based Linux image

Pine64 has launched an updated version of the PineTab-V RISC-V tablet with the same StarFive JH7110 SoC, 8GB RAM, and 128GB eMMC flash, but a few small hardware changes, and a Debian-based Linux image maintained by StarFive themselves. The PineTab-V is not exactly a new RISC-V tablet since it was launched in 2023, but at the time it was reserved for developers since it shipped with nothing… Users had to install the OS (that did not support the display yet) themselves, and work on the software/OS to improve it. The new model still targets developers and enthusiasts/early adopters, but at least now there’s a Debian 12 image optimized for the PineTab-V. The hardware is mostly the same, except Pine64 added an accelerometer, a status LED, an ID for the PineTab-V in the EEPROM, and a fix for slow charging while the tablet is turned off. PineTab-V (2025) specifications: SoC – […]

UNIHIKER K10
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UNIHIKER K10 low-cost TinyML education platform supports image detection and voice recognition

UNIHIKER K10 is a low-cost STEM education platform for TinyML applications that leverages the ESP32-S3 wireless microcontroller with vector extensions for workloads such as image detection or voice recognition. The UNIHIKER K10 also features a built-in 2.8-inch color display, a camera, a speaker, a 2-microphone array, a few sensors, a microSD card, and a BBC Micro:bit-like edge connector for power signals and GPIOs. It’s a cost-optimized version of its Linux-based big brother – the UNIHIKER M10 – first unveiled in 2022. Arnon also reviewed the UNIHIKER in 2023, showing how to configure it, use the SIoT platform with MQTT message, and program it with Jupyter Notebook, Python, or Visual Studio Code. Let’s have a closer look at the new ESP32-S3 variant. UNIHIKER K10 specifications: Core module – ESP32-S3-WROOM-1 MCU – ESP32-S3N16R8 dual-core Tensilica LX7 up to 240 MHz with 512KB SRAM, 8MB PSRAM, 16MB flash Wireless – WiFi 4 and […]

Rockchip RK3568, RK3588 and Intel x86 SBCs and SoMs in 2025
PicoCalc kit
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PicoCalc Kit is a Raspberry Pi Pico handheld terminal with a backlit STM32 QWERTY keyboard

ClockworkPi has made several Linux handheld terminals over the years such as the GameShell or DevTerm, but the PicoCalc Kit is quite different since it relies on the Raspberry Pi Pico board plus an STM32 microcontroller to handle its built-in keyboard. The PicoCalc Kit is based on the ClockworkPi v2.0 mainboard that takes an RP2040-based Pi Pico H board, connects to a 4-inch IPS display with 320×320 resolution and stereo speakers, integrates a backlit QWERTY keyboard, and ships with a 32GB SD card with an optimized BASIC firmware. PicoCalc Kit specifications: ClockworkPi v2.0 mainboard Compatible boards – Headers for Raspberry Pi Pico H/WH, and Raspberry Pi Pico 2 / 2W MCU – STM32 for keyboard and backlight programmable with the Arduino IDE or STM32 official development tools Storage – SD card slot Display – Screen connector (SPI) Audio 2x speaker connectors 3.5mm audio jack 67-key QWERTY keyboard (I2C) Expansion Connector […]

Renesas RZ V2N MPU
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Renesas RZ/V2N low-power AI MPU integrates up to 15 TOPS AI power, Mali-C55 ISP, dual MIPI camera support

Renesas has recently introduced the RZ/V2N low-power Arm Cortex-A55/M33 microprocessor designed for machine learning (ML) and computer vision applications. It features the company’s DRP-AI3 coprocessor, delivering up to 15 TOPS of INT8 “pruned” compute performance at 10 TOPS/W efficiency, making it a lower-power alternative to the RZ/V2H. Built for mid-range AI workloads, it includes four Arm Cortex-A55 cores (1.8GHz), a Cortex-M33 sub-CPU (200MHz), an optional 4K image signal processor, H.264/H.265 hardware codecs, an optional Mali-G31 GPU, and a dual-channel four-lane MIPI CSI-2 interface. The chip is around 38% smaller than the RZ/V2H MPU and operates without active cooling. The RZ/V2N is suitable for applications like endpoint vision AI, robotics, and industrial automation. Renesas RZ/V2N specifications CPU Application Processor – Quad-core Arm Cortex-A55 @ 1.8 GHz (0.9V) / 1.1 GHz (0.8V) L1 cache – 32KB I-cache (with parity) + 32KB D-cache (with ECC) per core L3 cache – 1MB (with ECC, […]

Boardcon CM3588 Rockchip RK3588 System-on-Module designed for AI and IoT applications