cnx-software.comPocketTerm35 – A Raspberry Pi 4/5-based handheld Linux terminal with 3.5-inch touch display and built-in keyboard
Trail Mate open-source firmware leverages Meshtastic and MeshCore for ESP32 off-grid handhelds
Trail Mate open-source firmware leverages Meshtastic and MeshCore for ESP32 off-grid handhelds
vicliu624's Trail Mate is an open-source firmware for off-grid communication and GPS coordinates sharing, leveraging the Meshtastic, MeshCore, and other projects, and designed for ESP32 handhelds such as LILYGO's T-LoRa Pager or M5Stack's Tab5 with a LoRaWAN module. The Trail Mate firmware provides a fixed north-up GPS map, direct LoRa text messaging through Meshtastic or MeshCore mesh networks without relying on a smartphone, and prioritizes stability, efficiency, and interoperability over feature density. Trail Mate user interface highlights: Simple main menu with four icons: GPS, LoRa chat, tracker, and system utilities. GPS map Fixed North-Up map orientation (no rotation) Fully offline map rendering from SD card tiles (png/jpg files) Three switchable base layers: OSM / Terrain / Satellite Optional contour overlay for terrain shape awareness Real-time position marker for the current GPS fix Discrete zoom levels optimized for embedded systems Simple breadcrumb trails for path awareness Fast in-page layer switching via
$15 STM32U575 development board features FPC display connector, microSD card slot, two 48-pin GPIO headers
$15 STM32U575 development board features FPC display connector, microSD card slot, two 48-pin GPIO headers
A few days ago, we looked at the WeAct Studio STM32U585CIU6 development board, which features an ultra-low-power STM32U5 Cortex-M33 MCU and was added to MicroPython v1.28. If you're looking for another STM32U5-based option, especially for compact UI projects, Maker Go now offers an STM32U575 board with a display connector, a microSD card slot, and many more GPIOs While the STM32U585 on the WeAct board features cryptographic accelerators, the STM32U575VGT6 MCU on the Maker Go board is closely related and still offers the same high-performance Cortex-M33 core running at 160 MHz, along with ultra-low-power capabilities. This new board also adds 8MB of external flash and is designed to accept 1.47-inch or 2.0-inch LCDs directly via a ribbon cable. STM32U575VGT6 board specifications: Microcontroller – ST STM32U575VGT6 Core – Arm Cortex-M33 Armv8-M core clocked at up to 160 MHz with FPU, Arm TrustZone Memory – 786 KB SRAM Flash – 1024 KB (1
SN1 Solar Node – An ESP32-C3-based board with IP67 enclosure, solar charging, ESPHome firmware
SN1 Solar Node – An ESP32-C3-based board with IP67 enclosure, solar charging, ESPHome firmware
Designed by Granz Scientific LLC, the SN1 Solar Node is an ESP32-C3-based IoT node/development board designed specifically for off-grid IoT projects. Development boards like Seeed Studio Wio Tracker, or industrial controllers like DFRobot LoRaWAN Control Terminal, allow you to handle your own battery management and weatherproofing, or on the other end, you have products like SenseCAP Solar Node P1 that come with everything integrated but do not allow adding custom hardware. This is where the SN1 Solar Node is different; it features an IP67-rated enclosure with an integrated solar panel on the lid, 18650 battery support, and prototyping strip-board areas for custom circuitry. It also includes a smart power switch that allows the battery to continue charging from the solar panel even when the board is powered off. Additionally, it provides battery voltage monitoring, breaks out most GPIOs for easy access, and includes optional jumpers for an onboard LED and
Entry-level Intel Core 3 304 Wildcat Lake processor details and benchmarks surface
Entry-level Intel Core 3 304 Wildcat Lake processor details and benchmarks surface
Intel discreetly introduced the Wildcat Lake Core Series 3 CPUs at CES 2026 with some high-level specifications, but no part numbers or exact CPU, GPU, and NPU frequencies. Some leaks reveal more details about the Wildcat Lake parts, notably the Intel Core 3 304 penta-core processor, for which we also have some benchmarks. Intel Wildcat Lake SKUs The data below comes from a post by Jaykihn on X. While we have six SKUs in the table above, the Intel Core 5 320/330 and Core 7 350/360 only differ in terms of SIPP (Intel Stable IT Platform Program) support. SIPP is an enterprise initiative that ensures that key platform components, such as processors, chipsets, graphics, storage, networking, and wireless, remain consistent with minimal or no changes for a guaranteed period. The GPU turbo clocks are much higher than in Alder Lake-N/Twin Lake chips (typically 1 GHz to 1.35 GHz), and LPDDR5x
Telink TL3228 – Low-power, low-latency dual-core RISC-V wireless MCU supports Bluetooth 6.0, 802.15.4, and 2.4 GHz proprietary
Telink TL3228 – Low-power, low-latency dual-core RISC-V wireless MCU supports Bluetooth 6.0, 802.15.4, and 2.4 GHz proprietary
Telink has launched the TL322x wireless MCU family, starting with the TL3228, featuring a 192 MHz dual-core RISC-V MCU, and supporting Bluetooth 6.0, Matter, Thread, Zigbee, RF4CE, and proprietary 2.4GHz protocols for Smart Home, asset tracking, "8K" gaming accessories, and more The chip supports the recent Bluetooth features such as Channel Sounding, AoA/AoD, and LE Audio, as well as the company’s proprietary HDT technology delivering up to 6 Mbps data rate and ultra-low latency. Telink TL3228 specifications: Dual-core CPU 32-bit Andes D25F RISC-V core with FPU up to 192 MHz 32-bit Andes N22 RISC-V core Memory - 384 KB SRAM Storage - 2.5 MB of NVM (Flash + RRAM) Connectivity Bluetooth 6.0 Channel Sounding Mesh Networking Bluetooth LE AoA/AoD location services 802.15.4 radio for Zigbee, Thread, Matter, RF4CE 2.4GHz Proprietary 2.4GHz radio data rates - 1Mbps, 2Mbps, 4Mbps, 6Mbps; Bluetooth LE PHY: LE 2M, LE Coded Bluetooth LE Multiple Connections - 4x
BLE VoiceTimers seem simple until they cause mysterious power drain or timing issues. The JL JieLi AC696N SDK provides two timer systems with different characteristics. Here's what I've learned debugging on the dev board.
Practical Tip
Test both on the AC696N development board. Add serial prints to see which thread the callback runs in.
Both timer systems support one-shot timeouts—choose whichever fits your context needs.
#JieLi #AC696N #Timers #EmbeddedSystems #Firmware #LowPower #ISR #CaptureMode
PineTime Pro smartwatch to feature dual-core Cortex-M33 MCU, 2.13-inch AMOLED, GPS, and more
PineTime Pro smartwatch to feature dual-core Cortex-M33 MCU, 2.13-inch AMOLED, GPS, and more
Pine64 has announced progress on the PineTime Pro smartwatch, powered by a dual-core Cortex-M33 microcontroller with Bluetooth 5.2 Classic and LE and 800KB SRAM. The watch also features a 2.13-inch AMOLED display, GPS support, a heart rate monitor, and a 6-axis motion sensor. It's an upgrade to the PineTime project unveiled in September 2019, and one of the most popular Pine64 devices thanks to open-source software projects such as InfiniTime firmware. For reference, the PineTime ships with a Nordic nRF52 Arm Cortex-M4 Bluetooth MCU with 64 KB SRAM, a 1.3-inch display, and basic HRM and accelerometer. The PineTime Pro is a massive upgrade that should support a wider range of firmware. PineTime Pro specifications: SoC - Unnamed wireless MCU CPU - Arm Cortex-M33 MCU @ up to 200 MHz Memory - 800 KB SRAM Wireless - Bluetooth 5.2 Classic (BR/EDR) & Low Energy (additional Cortex-M33) Memory - 8 MB PSRAM
Ohm Lab Neuro N6 – Modular STM32N6 AI Vision devkit supports rolling shutter, global shutter, or thermal camera (Crowdfunding)
Ohm Lab Neuro N6 – Modular STM32N6 AI Vision devkit supports rolling shutter, global shutter, or thermal camera (Crowdfunding)
Ohm Lab Neuro N6 is a compact, modular, Arduino-compatible Edge AI/AI Vision development board powered by an STMicro STM32N6 Arm Cortex-M55 microcontroller with a 600 GOPS Neural-ART accelerator. The Adafruit Feather-sized board features 64MB PSRAM, 32MB flash, a built-in microphone, a 6-axis IMU and magnetometer, a USB-C port for power and programming, and takes power from USB-C (5V) or a LiPo battery. The bottom side of the board features 40-pin and 30-pin high-density connectors for expansion boards, adding a camera (rolling shutter, global shutter, or thermal), a microSD card slot, Ethernet, WiFi, a TFT display, and more. Neuro N6 specifications: MCU – STMicro STM32N6 MCU Core – 32-bit Arm Cortex-M55 CPU @ up to 800MHz with Arm Helium and Arm MVE GPU – Neo-Chrom 2.5D GPU, Chrom-ART Accelerator (DMA2D) NPU – ST Neural-ART accelerator @ 1 GHz, 600 GOPS BPU – Hardware-accelerated H.264 and JPEG encoders Memory – 4.2MB SRAM
Radxa AICore DX-M1M M.2 2242 low-power AI module delivers 25 TOPS of edge AI performance for just 3W of power
Radxa AICore DX-M1M M.2 2242 low-power AI module delivers 25 TOPS of edge AI performance for just 3W of power
Radxa AICore DX-M1M is a compact, low-power M.2 edge AI acceleration module built around the DeepX DX-M1M neural processing unit (NPU) and delivers up to 25 TOPS (INT8) of AI performance while consuming only 3W of power. Designed for industrial robot arms, autonomous mobile robots (ARM), edge servers, drones, and AIoT devices, the module delivers high-performance AI and ML capabilities without blowing the power budget. It relies on a PCIe Gen3 x2 interface and works with both x86 and Arm systems, including the Raspberry Pi 5 and Radxa ROCK SBCs. AICore DX-M1M specifications: AI Accelerator – DeepX DX-M1M neural processing unit (NPU) with up to 25 TOPS AI System Memory – 1GB LPDDR4X @ 4266 MT/s (on-chip, supports up to 8GB according to DeepX) Storage – 1Gbit QSPI NAND / NOR flash Host Interface - PCIe Gen 3.0 x4 (supports Gen 1/2/3 and x1/x2) via M.2 M + B Key connector