SparkFun GNSS L1/L5 Breakout Board
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SparkFun’s latest GNSS breakout board features u-Blox NEO-F10N L1/L5 dual-band receiver for urban environments

The SparkFun GNSS L1/L5 Breakout is a standard precision GNSS board with meter-level positional accuracy that features the u-Blox NEO-F10N dual-band module, an SMA antenna connector, and a USB-C port for power and data. As its name implies, the board relies on the L1/L5 bands of the NEO-F10N instead of the more commonly seen L1/L2 bands and delivers better performance in urban environments. That’s because the L5 band falls within the protected ARNS (aeronautical radionavigation service) frequency band leading to less RF interference. SparkFun GNSS L1/L5 Breakout specifications: GNSS u-Blox NEO-F10N module with L1/L5 dual-band GNSS receiver Concurrent Reception of GPS, Galileo, and Beidou Integrated SMA Connector Time to First Fix: 28s (cold), 2s (hot) Max Navigation Rate for Single GNSS Configuration (GPS): 20 Hz Positional Accuracy (GPS) – 1.5m Time Pulse Accuracy – 30ns Operational Limits Max G: ≤ 4G Max Altitude: 80km Max Velocity: 500m/s Supports NMEA, UBX […]

Renesas EK-RA2A2 evaluation board
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Renesas RA2A2 Arm Cortex-M23 microcontroller offers high-resolution 24-bit ADC, up to 512KB dual-bank flash

Renesas Electronics RA2A2 Arm Cortex-M23 microcontroller (MCU) group offers a 7-channel high-resolution 24-bit Sigma-Delta ADC, as well as dual-bank flash and bank swap function for an easier implementation of firmware over-the-air (FOTA) updates. The 48MHz MCU also comes with 48KB SRAM, up to 512KB code flash, various interfaces, and safety and security features that make it suitable for smart energy management, building automation, medical devices, consumer electronics, and other IoT applications that can benefit from high-resolution analog inputs and firmware updates. Renesas RA2A2 specifications: MCU core – Arm Cortex-M23 Armv8-M core clocked at up to 48 MHz Arm Memory Protection Unit (Arm MPU) with 8 regions Memory 48 KB SRAM Memory Protection Units (MPU) Memory Mirror Function (MMF) Storage Up to 512 KB code flash memory in dual bank (256 KB × 2 banks); bank swap support 8 KB data flash memory (100,000 program/erase (P/E) cycles) Peripheral interfaces Segment LCD […]

ArmSoM RK3588 AIModule7 NVIDIA Jetson Nano-compatible SOM
Raspberry Pi 5 NAS HAT
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Radxa Penta SATA HAT adds up to five SATA drives to the Raspberry Pi 5 for NAS applications

The Radxa Penta SATA HAT leverages the PCIe interface on Raspberry Pi 5  SBC to add up to five 2.5-inch or 3.5-inch SATA drives through four SATA connectors and an eSATA connector and enables NAS designs with the latest SBC from Raspberry Pi Limited. The Radxa’s Penta SATA HAT was initially launched in 2019 as an accessory for the Rock Pi 4 SBC powered by a Rockchip RK3399 processor and an M.2 PCIe socket since Raspberry Pi competitors have been exposing PCIe interfaces for years. It turns out the exact same Penta SATA HAT design can be reused with the Raspberry Pi 5 by providing a new PCIe FPC cable and updating the configuration scripts. Radxa Penta SATA HAT for Raspberry Pi 5 specifications: 4x SATA interfaces + 1x eSATAp for up 100TB storage via 5x 2.5″ or 3.5″ HDD/SSD Host Connection – Flat cable with 2-lane PCIe 2.1 via […]

trekko pico gps logger front
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SB Components’ Trekko Pico is an open-source, RP2040-powered GPS logger with multi-GNSS support

After the success of their Kickstarter campaign, SB Components has now made the Trekko Pico GPS logger available for pre-order. The Trekko Pico is a small location logger for travelers and outdoor enthusiasts that makes it easy to track routes and record their travels. A Raspberry Pi RP2040 powers the Trekko Pico, providing the programming, connectivity, and data logging functionality. The Quectel GNSS L76K module supports the concurrent reception of GPS, GLONASS (or BeiDou), Galileo, SBAS, and QZSS signals, with 32 tracking and 72 acquisition channels. There is a JST 2-pin connector that can be used to attach an external battery, and the Microchip MCP73831 controller is responsible for battery charging and management. Also, users can slot a coin cell into the holder at the back of the board to power a real-time clock for data backup purposes. Potential applications for the Trekko Pico GPS logger include surveillance, telematics, Geographic […]

AMD Versal AI Edge Evalboard with VE2302 SoC
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Trenz Electronic TE0950-03-EGBE21A – An AMD Versal AI Edge VE2302 SoC FPGA evaluation board

Trenz Electronic recently announced the TE0950-03-EGBE21A an evaluation board with AMD Versal AI Edge XCVE2302-1LSESFVA784 SoC FPGA. This board features 8 GB of DDR4 SDRAM and 128 MB of SPI Flash (as the primary boot option), a microSD card slot, a 32 GB eMMC flash (secondary boot), and an EEPROM with a MAC address. Additionally, the board supports a range of VE-series devices, such as VE2002, VE2102, VE2202, VE2302, and VM1102, enhancing its application versatility. The AMD Versal is a family of adaptive compute acceleration platforms (ACAPs) designed by AMD. Following its acquisition of Xilinx, it integrates CPU, GPU, and FPGA technologies along with dedicated software support to create a highly flexible development environment. Trenz Electronic VE2302 Evaluation Board Specifications: SoC – AMD Versal AI Edge XCVE2302-1LSESFVA784, A784 package, compatible with multiple VE-series devices RAM – 8 GB DDR4 SDRAM Storage 128 MB SPI Flash (primary boot option) MicroSD card […]

Edge Impulse NVIDIA TAO Models
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Edge Impulse machine learning platform adds support for NVIDIA TAO Toolkit and Omniverse

Edge Impulse machine learning platform for edge devices has released a new suite of tools developed on NVIDIA TAO Toolkit and Omniverse that brings new AI models to entry-level hardware based on Arm Cortex-A processors, Arm Cortex-M microcontrollers, or Arm Ethos-U NPUs. By combining Edge Impulse and NVIDIA TAO Toolkit, engineers can create computer vision models that can be deployed to edge-optimized hardware such as NXP I.MX RT1170, Alif E3, STMicro STM32H747AI, and Renesas CK-RA8D1. The Edge Impulse platform allows users to provide their own custom data with GPU-trained NVIDIA TAO models such as YOLO and RetinaNet, and optimize them for deployment on edge devices with or without AI accelerators. NVIDIA and Edge Impulse claim this new solution enables the deployment of large-scale NVIDIA models to Arm-based devices, and right now the following object detection and image classification tasks are available: RetinaNet, YOLOv3, YOLOv4, SSD, and image classification. You can […]

Rockchip RK3568, RK3588 and Intel x86 SBCs and SoMs in 2025
tinyvision board
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TinyVision is a compact Allwinner V851S/V851S3-powered Linux board for vision-based applications

Unrelated to tinyVision.ai, the TinyVision development board is a computer vision board from Chinese developer YuzukiTsuru powered by either the Allwinner V851S or the V851S3 and is billed as an “ultimate all-in-one solution for Linux motherboards, IPCs, servers, routers, and more.” It packs features such as a Cortex-A7 core running at 1200MHz, a 2-channel MIPI CSI input, and an independent image signal processor (ISP) capable of a maximum resolution of 2560 x 1440 in a compact form factor. TinyVision specifications: Processor – Allwinner V851SE / V851s3 with Cortex-A7 core @ 1200MHz and RISC-V E907GC core @ 600MHz NPU: 0.5TOPS (tera operations per second) @ INT8 precision Memory – 64MB DDR2 (V851se), 128MB DDR3L (V851s3) Storage – MicroSD card slot (supports UHS-SDR104), onboard SD NAND via SPI Display – 2-lane MIPI DSI (1280 x 720 @ 60fps), RGB LCD (320 x 240 @ 60fps) Video Input ISP with a maximum resolution […]

Sipeed MaixBox M4N AI box
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Sipeed MaixBox M4N AI Box with 43.2 TOPS AXera AX650N SoC can decode/encode up to 32 videos

Sipeed MaixBox M4N is an AI box for video analytics and computer vision equipped with an AXera-Pi Pro (AX650N) octa-core Cortex-A55 SoC with a 43.2 TOPS (INT4) or 10.8 TOPS (INT8) AI accelerator and an H.265/H2.64 video encoder/decoder supporting up to 32 1080p30 videos. The AI box is based on the Sipeed Maix-IV motherboard, an upgrade to the Maix-III devkit with an AX620A quad-core Cortex-A7 SoC with a 14.4 TOPS AI accelerator (INT4). It comes with 8GB RAM shared for Linux and the AI accelerator, 32GB eMMC flash and an M.2 SATA socket for storage, two HDMI outputs, two gigabit Ethernet ports, optional WiFi or 4G LTE mini PCIe module, a few USB ports, and RS232 and RS485 interfaces. Sipeed MaixBox M4N specifications: SoC – AXera AX650N CPU – Octa-core Arm Cortex-A55 @ 1.7 GHz with NEON support NPU – 43.2 TOPS @ INT4, 10.8 TOPS @ INT8 with support […]

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