A good pin reference is like a map for hardware development. Here's a verified pin mapping for the JL JieLi AC6966B (AC696N series) development board, straight from actual hardware testing.
Whether you're reviewing schematics, bringing up a custom board, or debugging firmware, having this reference handy saves hours of probing and tracing.
#JieLi #AC696N #AC6966B #Pinout #HardwareDesign #EmbeddedSystems #BluetoothAudio #DevelopmentBoard #UART #ReferenceDesign
The second is the Neuro N6, an STM32N6-powered Feather-format #microcontroller development board built with edge... err, computer vision in mind. Milliwatt-power CV on-board, its creators promise - all accessible via extension to the #Arduino IDE.
#Technology #News #Hackster #Crowdfunding #DevelopmentBoard #ComputerVision #MachineLearning
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
Clintech Pico – The first Raspberry Pi RP2354B board offers 48 GPIOs in Raspberry Pi Pico form factor
Designed by Clintech Ltd. in Bulgaria, the Clintech Pico Board appears to be the first development board based on the Raspberry Pi RP2354B chip with 2MB on-chip memory. It retains the same form factor as a Raspberry Pi Pico 2 but adds extra GPIOs to make use of the 48 general-purpose GPIOs provided by the RP2354B chip. Like the Raspberry Pi Pico 2, this board features 40 castellated and through holes on the sides, exposing GPIOs 0–22 and 26–28, along with 3 debug pins. Additionally, the board includes 27 extra on-board through holes that break out the remaining GPIOs (23–25 and 29–47) as well as the QSPI interface (SD0–SD3 and SCLK) for external memory. Clintech Pico specifications: SoC - Raspberry Pi RP2354B CPU Dual-core Arm Cortex-M33 @ 150 MHz with Arm Trustzone, Secure boot Dual-core 32-bit RISC-V Hazard3 @ 150 MHz (3-stage in-order pipeline; RV32IMAC with Zba, Zbb, Zbs, Zbkb, Zcb, Zcmp, and
Rabbit-Labs Flipper Zero ESP32-C5 multi-board features CC1101, GPS, and dual-band Wi-Fi 6
Designed by Rabbit-Labs EU, the Flipper Zero ESP32-C5 multi-board is an expansion board for the Flipper Zero built around the ESP32-C5 dual-band Wi-Fi 6 (2.4 GHz and 5 GHz) microcontroller. The board also features a TI CC1101 sub-GHz transceiver, a GPS module, an SD card slot, and a USB-C port for power and programming. Last month, we wrote about the ESP32 Marauder 5G Apex 5 module, another ESP32-C5-based add-on for the Flipper Zero that comes with dual-band Wi-Fi 6, two sub-GHz radios, an NRF24 radio, and a built-in GPS module, which makes it quite bulky, to say the least. Compared to that, Rabbit Labs' multi-board can be considered a stripped-down, simpler alternative, with a more compact design and straightforward setup. ESP32-C5 multi-board specifications: Main module – ESP32-C5-WROOM-1U SoC – Espressif Systems ESP32-C5 CPU Single-core 32-bit RISC-V processor @ up to 240 MHz Low-power RISC-V core @ 40 MHz acting as the
SparkFun OpenScale IoT – An ESP32 board with HX711 ADC for smart scales with WiFi and Bluetooth connectivity
The SparkFun OpenScale - IoT project is a ready-to-use ESP32-based IoT smart scale with open-source hardware and firmware support that makes it easy to read precise weight data from load cells without writing custom code from scratch for basic operation. It handles amplification via the HX711 24-bit ADC, calibration, temperature compensation (using the onboard TMP102 and an optional external DS18B20 probe), and serial output/configuration through a simple text-based menu. It also features Wi-Fi for live data and OTA firmware updates, requiring no dedicated apps—just standard terminal tools and a browser for viewing data. Additionally, there is a Qwiic I²C connector for adding extra sensors or displays. The board operates from 5 V with a typical current consumption of 80 to 100 mA, supports selectable output data rates of 10 or 80 SPS, and includes an adjustable gain for accurate measurements in long-term monitoring setups. SparkFun OpenScale - IoT Specifications: Wireless
Rockchip RK3538 TV Box SoC and RK3572 mid-range HMI processor are coming soon
While we are eagerly waiting for the RK3668 and RK3688 high-end processors, Rockchip is planning to launch two mid-range SoCs with the RK3538 quad-core Cortex-A55 processor designed for TV boxes, and the RK3572 hexa-core Cortex-A73/A53 SoC for HMI (Human Machine Interface) applications. Rockchip RK3538 TV box SoC Rockchip RK3538 specifications: CPU - Quad-core Arm Cortex-A55 processor with NEON, FPU, ARMv8 Crypto... Cache 32KB L1 instruction cache 32KB L1 data cache and 64KB L2 data cache 512KB unified system L3 cache GPU Arm Mali-G310 3D GPU with support for OpenCL 3.0, OpenGL ES1.1/2.0/3.2, Vulkan 1.2 2D Graphics Engine VPU Decoder H.265, H.264, AV1 (up to two simultaneous 1080p60 channels) VP8, VC1, MPEG-4, MPEG-2, MPEG-1 yp to 1920x1088 @ 60 FPS (1088 is not a typo) H.263 up to 720p60 (M)JPEG up to 8176x8176 @ 76 million pixels per second Encoder - N/A MCU core - RISC-V MCU in PMU domain with
MediaTek unveils 50 TOPS Genio Pro 5100 Cortex-X925/X4/A720 SoC, 7.2 TOPS Genio 420 Cortex-A78/A55 SoC for AIoT applications
After launching the Genio 360/360P hexa/octa-core SoCs last month, MediaTek has now expanded the lineup with the Genio Pro 5100 and Genio 420 AIoT SoCs at Embedded World 2026. The Genio Pro 5100 is a 3nm SoC with an "all big-core" architecture and a 50+ TOPS NPU for Edge AI applications. The Genio 420, on the other hand, is a cost-efficient 6nm platform designed for smart home, retail, and industrial IoT devices. MediaTek Genio Pro 5100 The Genio Pro 5100 integrates one Cortex-X925, three Cortex-X4, and four Cortex-A720 cores, as well as an Arm Immortalis-G925 GPU, and supports LPDDR5X memory up to 8533 Mbps. It can handle up to three 4K displays, up to 16 cameras via virtual channels, and 8K30 video encode/decode, and offers interfaces such as PCIe Gen4, USB 3.2 Gen2, USB 2.0, and dual 2.5GbE MAC. Genio Pro 5100 (MT8894) specifications: CPU - 8-core Arm v9.2 processor
Texas Instruments MSPM0G5187 and AM13Ex MCUs integrate TinyEngine NPU for Edge AI applications
Texas Instruments MSPM0G5187 and AM13Ex are two new microcontroller (MCU) families featuring the company's TinyEngine neural processing unit (NPU) to enable low-latency, high-efficiency Edge AI/Machine Learning inference on the chips. TI claims that the TinyEngine NPU can run AI models with up to 90 times lower latency and more than 120 times lower energy utilization per inference than similar MCUs without an accelerator. The MSPM0G5187 is a general-purpose, low-power Arm Cortex-M0+ MCU, while the AM13Ex Arm Cortex-M33 microcontroller targets real-time motor control, starting with the AM13E23019 SKU. TI MSPM0G5187 general-purpose Cortex-M0+ MCU Key features and specifications: CPU - Arm Cortex-M0+ @ 80 MHz Memory - 32 KB RAM with ECC Storage - 128 KB flash with ECC, 8 KB data flash with ECC Accelerators TinyEngine NPU for AI/ML delivering up to 2.56GOPS (Giga Operations Per Second) at 80MHz MATHACL math accelerator Peripherals USB - 1x USB 2.0 (12 Mbps) Audio
NXP i.MX 937 cost-effective Cortex-A55/M7/M33 MPU is a drop-in replacement for NXP i.MX 95 SoC family
The 1 .4 GHz NXP i.MX 937 quad-core Cortex-A55 microprocessor (MPU) for HMI and Edge AI applications aims to fill the gap between entry-level NXP i.MX 93 SoCs and higher-end parts like the NXP i.MX 952 processor family, while offering pin-to-pin compatibility with the latter. The i.MX 937 MPU also features a dedicated 667 MHz Arm Cortex -M7 for real-time workloads and a low-power Arm Cortex-M33 core for system management tasks, supports LPDDR4x or LPDDR5 memory, integrates an Arm Mali G310 3D GPU, a VPU for 1080p H.26x video encoding and decoding, and a 2 eTOPS NXP eIQ Neutron NPU for machine learning (ML) acceleration. Since it targets HMI applications, we'll also find MIPI DSI and LVDS display interfaces, and a 4-lane MIPI CSI camera interface, plus various other I/Os. NXP i.MX 937 specifications: (highlights in bold compared to other i.MX 93 parts) CPU Up to 4x Arm Cortex-A55 cores
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Gareth Halfacree
cnx-software.com