Banana Pi BPi PicoW-S3 ESP32-S2 Board Launches for $5.5

SinoVoip Co, the company behind some of the most recent microcontroller boards including the Banana Pi BPi Leaf-S3, has just launched a new Banana Pi’s BPI-PicoW-S3 low-power board designed for IoT development.

The $5.50 IoT board is based on Espressif System ESP32-S3 MCU – a dual-core XTensa LX7 processor capable of running at 240 MHz and integrated with 512 KB internal SRAM, 2.4 GHz WiFi 4 and Bluetooth 5 connectivity. The board also features an on-chip 320 KB RAM, one micro USB slot, up to 27x GPIOs, one Neopixel LED, one temperature sensor, a wide variety of interfaces and support for Arduino and Micropython.

The new Banana Pi BPi Pico W-S3 board looks like one of Raspberry Pi’s full-fledged mini PCs, the Raspberry Pi Pi Pico W IoT board launched earlier this year. You can call take them as perfect alternatives to each other especially as they have almost the same size and shape despite being powered by different processors. The Banana Pi Pico W-S3 measures 51.88 by 21.03 mm while its Raspberry Pi variant measures 51.3 by 21 mm — close enough to be roughly interchangeable in hardware applications.

Here are some of the key features and specifications of the BPi Pico W-S3 Board:

  • Processor: 32-bit ESP32-S3 dual-core Tensilica LX7 up to 240 MHz
  • On-chip 384 KB ROM
  • On-chip 320 KB RAM
  • Onboard 2MB Flash ROM
  • On-chip 8MB PSRAM
  • 2.4 GHz 802.11 b/g/n WiFi 4
  • Bluetooth 5.0 and Bluetooth Mesh with long-range support, up to 2Mbps data rate.
  • Support for 8-bit to 16-bit DVP image sensor interface
  • Support for 8-bit to 16-bit parallel RGB
  • 1x micro USB
  • Up to 27x GPIOs including 8x 14-bit PWM, 18-bit analog inputs, 14x Touch, 2x MCPWM, 3x UART, 4x SPI, 2x I2C, 2x I2S, and 1x SDIO host interface
  • 1x Neopixel LED
  • 1x Temperature Sensor of -20°C to 110°C
  • 40 MHz external crystal
  • Secure boot and flash encryption
  • Power: 3.3V to 5.5V; 10uA
  • Operating Temperature: -40°C to 85°C
  • Dimensions: 21 mm x 51.88 mm
  • Operating System: ESP-IDF, Arduino, Micropython

The table below shows how the Banana BPi Pico W-S3 compares with the Raspberry Pi Pico W and the Banana Pi BPi Leaf-S3:

Further details on the Banana Pi BPI-PicoW-S3 board are available on AliExpress where the board is currently selling for $5.50. The board ships for an extra $10 for customers in the United States and $6 for those in South East Asia.

Zynq UltraScale+ MPSoC System on Modules for LiDAR

LiDAR has emerged as an essential remote-sensing technology for many scientific and military applications. It provides high-resolution & accurate measurements of 3D structures, easily convert the received data into 3D maps to interpret the surrounding, and remains unaffected even in even in challenging weather and lighting conditions.

The adaptability of Zynq UltraScale+ MPSoC to support LiDAR technology

The Zynq UltraScale+ MPSoC devices enable an adaptive SoC-based product design, which is extremely promising for LiDAR application implementation. Integrating both the processor and FPGA architecture into a single device allows rapid deployment of a flexible yet optimized solution for any given domain.

The programmability of FPGA provides a great deal of flexibility in developing custom capabilities for the product. Also, FPGAs have the potential to speed up processing by employing multi-level parallelism.

The Zynq UltraScale+ MPSoC series combines real-time control with soft and hard engines for graphics, video, waveform, and packet processing. As a result, MPSoC devices are powerful and flexible enough to deliver advanced capabilities for Lidar sensors: signal processing, point cloud pre-processing, and point cloud machine learning acceleration. Additionally, Zynq MPSoC devices are well known for being power efficient, which is critical for LiDARs.

Why use an SoM approach to build LiDAR products

Using a System on Module approach for building LiDAR products provides significant benefits by offloading several complexities involved in the design cycle. A product designer can focus on developing firmware and software stacks by eliminating the complex hardware part of the design. Which significantly reduces time to market with reduced product development costs.

Furthermore, a System on Modules provides enormous scalability and flexibility to a designer when migrating to a higher computing SoM without changing the design of a carrier card.

Zynq MPSoC System on Module features for lidar

The Zynq UltraScale+ MPSoC SoM features the heterogeneous ARM + FPGA architecture and provides a robust combination of the processing system (PS) and programmable logic (PL).

  • The PS contains a quad-core ARM Cortex-A53 processor operating at up to 1.5GHz and a real-time processing unit equipped with ARM Cortex-R5 processors operating at up to 600MHz
  • PL based on 16nm UltraScale+ architecture that contains up to 504K configurable logic block, Block RAM, and DSP elements

Other benefits include

  • Any-To-Any interfacing
  • Design toolchains
  • Image processing capabilities
  • Accelerate neural network
  • Safety and Security features

Any-To-Any interfacing

Compliance with different interfacing standards is a significant challenge presented by sensor interfacing and processing. A typical solution should have the capability to support high-speed interfaces such as MIPI, JESD204B, LVDS, and GigE to support high-bandwidth sensors such as cameras, RADAR, and LiDAR. Sensor interfacing and processing will also be required to interface with lower-bandwidth sensors that use standards such as CAN, SPI, I2C, and UARTs for accelerometers.

The Zynq UltraScale+ MPSoCs PS and PL support a variety of industry-standard interfaces such as CAN, SPI, I2C, UART, and GigE. The PL I/O flexibility allows for direct interfacing with MIPI, LVDS, and GigaBit Serial Links, allowing for higher levels of protocol implementation within the PL.

By providing the correct PHY in the hardware design, the PL enables any interface to be implemented, providing any-to-any interfacing.

Design toolchains

The Zynq UltraScale+ devices come with Vivado Design Suite to configure the PS and PL design. Vivado provides the complete PL development experience, including the support for synthesis, place & route, and simulation.

Vitis comes into play when it comes to developing software solutions. Vitis supports Embedded Linux development using PetaLinux and real-time operating systems such as FreeRTOS.

In addition to system development capabilities, Vitis supports kernel acceleration within the PL using OpenCL.

Image processing capabilities

Image processing is critical in LiDAR applications for navigation and monitoring. Typically, the algorithms used in these systems are created and modeled in high-level frameworks such as OpenCV.

An H.264/H.265 video codec unit is included in the Zynq UltraScale+ MPSoC EV series to support image processing.

Accelerate Neural Network

Aside from image processing, machine learning is a critical technology for developing automated applications. Machine learning helps classify objects on the highway or observe and monitor occupants.

To enable this, Viti AI provides Model Zoo, AI compiler, Optimizer, Quantizer, and profiler to deploy the application onto the deep learning processing unit.

Safety & Security features

The Advanced Encryption Standard (AES) is used to secure the configuration of Xilinx devices.

The Zynq UltraScale+ MPSoC devices further implement layered security solutions via configuration security unit (CSU) within the PS. The CSU supports AES 256-GCM, 4096 RSA Multiplier, and SHA-384, providing confidentiality, authentication, and integrity functions.

Anti-tamper response through the inbuilt system monitor enables the customer to track device voltages and die temperatures of the SoM.

Scalability across the iWave Zynq MPSoC SoM

iWave offers an extensive portfolio of System on Modules for Zynq UltraScale+ MPSoC series ranging from ZU4 to ZU19 variants. These modules serve a variety of industries, including high-end industrial, military, and defense.

In terms of logic density, I/O availability, number of transceiver lanes, and high-speed DDR design, these System on Modules provides excellent scalability for end applications. Thus, a designed carrier board can cover multiple I/O ports for a wide range of end products, from ZU4 with 192K logic cells to ZU19 with up to 1.1 M logic cells.

More information ZU7/ZU5/ZU4 Zynq UltraScale+ MPSoC SoM can be found here.

For more information visit – https://www.iwavesystems.com/platform/xilinx/

LattePanda 3 Delta – The Fastest Pocket-sized Windows 11/Linux Single Board Computer

Introduction

The growing adoption of IoT technology and related products has caused a corresponding growth in the market of single-board computers. In the past few years we have seen several SBC market manufacturers flood the market with different makes and types of boards, so much so that with the number of single-board computers available now in the market, an average maker/hobbyist may get confused trying to select the perfect SBC for a particular project.

To simplify decision-making for readers, our reviews help spotlight top-of-the-line products/tools that we have enjoyed using, and for this article, in the spirit of selecting some great SBCs of 2022, we’ll be taking a short review of the new LattePanda 3 Delta Single board computer designed by a Chinese electronics manufacturer (DFRobot) who had earlier released two generations of the LattePanda single board computer with Intel CPUs. Due to the fact that there has been a high-speed development in science and technology within the last few years, the LattePanda Team saw the need to develop a new product with the latest technology so as to meet the demands of current and future user scenarios, and well, from what we saw with the LattePanda 3, they didn’t do badly with that at all.

Loaded with improved features and capabilities, the LattePanda 3 Delta is the most user-friendly and cost-effective product that the company has ever made. The board is actually claimed to be the world’s smallest pocket-sized hackable computer poised to define a new era of computing and drive mega creativity for tech innovations.

When compared with its predecessors, we discovered that the LattePanda 3 Delta was designed to be faster in all aspects to allow abundant creativity and superfast smooth performance.

Package Includes:

  • 1 x LattePanda 3 Delta
  • 1 x Active Cooling Fan (Assembled)
  • 1 x 45w PD Power Adapter (with EU & US Standard Power Cord)
  • 2 x Dual-band Antenna
  • 1 x RTC Battery (Assembled)
  • 1 x User Manual
  • 1 x Activation Code Card (Windows 10 IoT Enterprise) – optional

Thermal Profile

The LattePamda 3 Delta features

  • 2x CPU performance: Unlike the previous versions which run on a Celeron N4100 processor, the LattePanda 3 Delta ships with Intel 11th generation Celeron N5105 processor with up to 2.9GHz burst frequency, making it 2 times faster than the predecessors.
  • 3x GPU performance
  • 2x Connectivity Speed: The single board computer uses WiFi 6 whose transfer speed is up to 2.4 Gb/s, about 2.7 times faster than the WiFi 5 found in the older models.
  • 2x USB speed: The board also uses a USB 3.2 gen 2 port which also happens to be twice as fast as the USB 3.2 gen 1 in others.
  • 2x Memory Performance and 2x Storage Capacity: LattePanda 3 Delta uses up to 8GB of LPDDR4 RAM with 2933 MHz high-frequency and up to 64 GB storage capacity, both of which doubles the performance of previous generations. So, there won’t be any need for additional/external storage in case you want to install more software and data.
  • Addition of a New Cooling Fan to ensure better cooling and sustain the best performance.
  • A More Extensive Display Support for an enhanced viewing experience: LattePanda 3 features a 3-way video output with a customized 12.5-inch 4K IPS touch display support.
  • Up to 42 expandable rich interfaces for true hackability and rich playability, and,
  • An onboard Gigabit Ethernet that allows you to connect to the internet at an extremely high speed.

eMMC vs NVMe Performance

onboard eMMC benchmark
M.2 NVMe benchmark

Highlight features and specifications of the LattePanda 3 Delta:

  • Processor: Intel Celeron N5105 quad-core Jasper Lake processor @ 2.0 ~ 2.9 GHz Quad-Core, Four Thread, 10 watt; Intel UHD Graphics 605 @ 450 – 800 MHz
  • Co-Processor: Microchip ATmega32U4-MU 8-bit AVR Arduino Leonardo compatible microcontroller
  • Memory: 8GB LPDDR4 @ 2933 MHz
  • Storage: 64GB eMMC 5.1 flash, M.2 NVMe or SATA SSD support, microSD card slot
  • Wireless: 1x Dual-band 802.11ax WiFi 6 @ 2.4/5 GHz, 1x Bluetooth 5.2, 1x GbE, optional 4G or 5G modem via M.2 socket plus SIM card slot
  • Audio: Microphone plus Headphone combo connector
  • Display: 1x HDMI 2.0, 1x DisplayPort via USB Type-C port, 30-pin 2-lane eDP connector, Up to 3x independent displays
  • USB: 2x USB 3.2 Gen 1 Type-A, 1x USB 3.2 Gen 2 Type-A, 1x USB Type-C for power and data (480 Mbps), 1x USB 2.0 header
  • GPIO: 12x analog Inputs, Up to 23x Digital Input/Output (7 PWM), 1x UART, 1x I2C, 1x SPI, 1x Audio connector, 1x 4-pin header for power and switch, 1x 4-pin 1.25mm PWM 5V Fan port, 1x 4-pin RS232
  • 1x M.2 M Key, PCIe 3.0 2x, 1x M.2 B Key, PCIe 3.0 1x
  • NVMe SSD support, USB 2.0, USB 3.0 support
  • RTC with CR927 coin-cell battery, Reset Button, Watchdog
  • Security: TPM 2.0
  • Power: USB PD input; 12V DC input
  • Dimensions: 125 mm x 78 mm x 16 mm
  • Operating Temperature: 0°C ~ 75°C

Windows 11 & Linux Support

LattePanda 3 Delta maintains almost the same pinout and layout as its predecessors to allow for effortless system migration or upgrade. It is also worth mentioning that the LattePanda 3 Delta has support for Windows 11, alongside Windows 10 and Linux Operating System.

Video loading Win 11

Usage and Applications

Being an optimum development tool for creative developers, talented and eager individuals, LattePanda 3 Delta will find its usefulness in a wide range of applications in:

  • IoT Edge
  • Smart factory
  • Home Automation
  • Robotics
  • Handheld devices
  • AI localization

Pinout

What’s more? The LattePanda 3 Delta is going to be readily available across the globe as the Team also announced that it’s working hand in hand with Global electronic components distributors to ensure that the product choice for the board is passed on to customers in a quick and easy way.

“LattePanda Team is so proud to cooperate with the global electronic components distributors for this joint launch. It delivers an exciting message to our customers that they can gain fast, easy access to our high-performance and hackable LattePanda 3 Delta anywhere in the world,” said Sandy Zhang, CMO of the LattePanda Team. “Our collaboration will ensure even higher levels of customer service.”

The LattePanda 3 Delta currently sells for $279, for the model that comes with an unactivated version of Windows 10 and $339, for the one with an activated version of the Windows 10 IoT Enterprise

Documentation and more

More useful details about the LattePanda 3 Delta including getting started guides are available on the documentation website.

Useful Links:

You can also check the product page or the company’s blog post for details.

Geniatech XPI-3566 single-board computer follows the Raspberry Pi form factor

Geniatech XPI-3566 single-board computer

Geniatech, one of the leading OEM/ODM service providers, has announced the release of the XPI-3566 single-board computer that comes in  Raspberry Pi form factor to target retail and interactive applications. This XPI-3566 single-board computer is designed to boost its performance through the powerful Rockchip RK3566 with a Quad-core Cortex-A55 processor clocked up to 1.8 GHz.

The manufacturer offers 2GB of RAM by default, while the eMMC storage capacity is 16GB. On the other side of the board, there is a 64GB SD card slot for additional storage. The XPI-3566 has the same number of USB ports as other SBCs with comparable form factors, including two USB 2.0 ports, one USB 3.0 port, and one USB 2.0 port that solely supports On The Go (OTG) mode. The Geniatech XPI-3566 single-board computer is equipped with Wi-Fi and Bluetooth 4.0 connectivity in addition to a single HDMI port that can output video and digital audio.

Specifications of Geniatech XPI-3566 single-board computer

  • CPU: Rockchip RK3566
  • Processor: Quad-core Cortex-A55 processor up to 1.8 GHz
  • GPU: Arm Mali-G52 2EE GPU
  • Wireless connectivity: Wi-Fi 2.4GHz and 5GHz dual band, Bluetooth 4.0
  • Memory: 2GB and optional 1GB, 4GB, and 8GB
  • Storage: 1x microSD card and 16GB of eMMC storage with options of 8GB, 32GB, and 64GB
  • Interfaces: 1x GbE RJ45 port
  • Display: 1x HDMI up to 4Kp60 and 1x MIPI DSI
  • USB ports: 1x USB 3.0 Host, 2x USB 2.0, 1x USB 2.0 OTG
  • Expansion: A 40-pin header with up to 28x GPIOs
  • Power supply: DC 5V/3A (via USB Type-C)
  • Dimensions: 85x 55 mm

Geniatech XPI-3566 single-board computer image

For interfacing, MIPI-CSI and MIPI-DSI for camera and display, respectively, allow developers to further build robust, next-gen applications. Furthermore, 28 programmable GPIOs are accessible via a 40-pin header at the top of the board. When it comes to software, this hardware supports Android 11 and Debian10, yet there is no documentation for this board.

This credit card-sized, high-performance single-board computer is a DIY product designed specifically for teenagers. However, Geniatech has not released pricing or availability information. For more information on XPI-3566 SBC head to the official product page.

TB-RK1808M0 features Rockchip RK1808K SoC equipped with 3.0 TOPS AI Accelerator

Since the Rockchip RK1808 SoC series was released about three years ago, this is the first time we will see the chip being used in the mPCIe form factor, despite always finding its way into several single-board computers. Toybrick TB-RK1808M0 offers a more recent version of the Rockchip RK1808 SoC (RK1808K) with 1GB RAM, and 8 GB eMMC flash in a mini PCIe form factor.

Being the first from the company to be fully dedicated to artificial intelligence applications, the RK1808 SoC series features an NPU with an accelerator delivering up to 3.0 TOPS, a dual-core Arm Cortex-A35 processor which allows it to run Linux, 1GB RAM, and 8GB eMMC flash.

The RK1808K happens to be almost similar to the RK1808, except that it is qualified to operate with a much wider temperature range. Check the road map here to get an insight into the Rockchip processor history

The mini PCIe module does not seem to follow a standard footprint pinout, so it may not be possible to use it in a mini PCIe socket from any board. Carrier boards with USB or PCIe x1 were made available instead.

Features and Specifications of the Toybrick TB-RK1808M0 Include:

  • CPU: Rockchip RK1808K Dual-core Cortex-A35 processor running at up to 1.4 GHz
  • AI Accelerator: 3.0 TOPS NPU for INT8 inference (300 GOPs for INT16, 100 GFLOPs for FP16), Support for TensorFlow, Caffe, ONNX and Darknet models.
  • VPU: 1080@60 H.264 decode, 1080@30 H.264 encode
  • 1GB of DDR system memory
  • 8GB eMMC flash
  • Mini PCIe edge connector with USB 3.0, USB 2.0, UART and GPIO
  • Heatsink for cooling
  • Power supply input: 3.3 V @ 1 A
  • Dimensions: 51 mm x 30 mm
  • PCB: 8-layer board design, gold deposition process
  • Temperature range: -20°C to 85°C
  • Software: Debian 10

Compared with similar boards like the Google Coral development board which sells for around the same price but comes equipped with a MediaTek MT8167S quad-core Arm Cortex-A53 SoC, double the size of the RAM, and with 4 TOPS Google Edge TPU, one would realize that the Toybrick TB-RK1808M0 is really not a tough match for them, but, it can serve as a really good alternative particularly now when the Google board seems not to be available checking through from all known vendors.

The mini PCIe module also comes preinstalled with optimized Debian 10 and other system software libraries required for AI development such as RKNN, MPP, and RGA.

Further details on the TB-RK1808M0 board can be found on AliExpress where it currently sells for $93 or for $128 if you are buying it with either a mini PCIe to USB 3.0 or mini PCIe to PCIe carrier board (shipping included). You would also find other useful resources like the hardware files and Linux images here.

Smart Bee Designs’ Bee S3 ultra-low power development boards is an affordable option

Smart Bee Designs' Bee S3

US-based Smart Bee Design LLC provides an ESP32-S3 powered ultra-low power development board for home applications and hobbyist use cases. Inside the hardware platform is an Xtensa LX7 microcontroller that lets users build low-power projects at a very affordable cost of only $10.00 USD. However, the board is currently sold out and interested people are requested to join the waitlist, more of them will be available soon.

Espressif ESP32-S3 is a new AIoT-designed system-on-chip that features a dual-core Xtensa LX7 microcontroller that is capable of running up to a clock frequency of 240MHz. The hardware also comes with integrated 2.4GHz wireless connectivity– IEEE802.11b/g/n Wi-Fi and Bluetooth 5. With a rich set of peripherals, the ESP32-S3 has 45 programmable general-purpose input/output ports.

Specifications of Smart Bee Designs’ Bee S3:

  • CPU: Espressif ESP32-S3 microcontroller
  • Processor: Dual-core XTensa LX7
  • Memory: 512kB of internal SRAM
  • Wireless connectivity: Integrated 2.4 GHz 802.11 b/g/n Wi-Fi and Bluetooth 5 (LE) connectivity
  • GPIOs: 45x programmable GPIOs
  • Serial communication: SPI, I2S, I2C, and UART
  • Power: Ultra-low power and battery voltage monitoring built-in
  • LED: RGB led
  • Interface: USB Type-C interface port
  • Software: Supports Arduino, MicroPython, and Circuit Python

Smart Bee Designs' Bee S3 Pinout

For any advanced system-on-chip, artificial intelligence acceleration is very important. Espressif ESP32-S3 has support for vector instructions in the microcontroller which provides acceleration for neural network computing and signal processing workloads. Engineers and developers can leverage these vector instructions through ESP-DSP and ESP-NN libraries for better optimization of specific applications.

In terms of security, ESP32-S3 provides necessary security protocols for building applications without requiring any external security. The hardware platform supports AES-XTS-based flash encryption, RSA-based secure boot, digital signature, and HMAC. These security features enable the user to implement functions in a trusted-execution environment.

Recently, Arduino IoT Cloud released support for more Espressif microcontroller devices, which also includes the latest ESP32-S3 system-on-chip. This means that Smart Bee Designs’ Bee S3 can now be remotely monitored and managed through Arduino IoT Cloud.

BBC launches a new Web Python Editor for micro:bit

BBC Web Python Editor

BBC micro:bit has announced the release of a new web Python editor that will let young developers from educational institutions build applications, breaking entry-level barriers. BBC’s Make It Digital initiative launched micro:bit educational program to allow young school students to explore the world of digital transformation through an embedded ecosystem. The Python editor is designed for young people to learn programming skills for various embedded applications.

The Micro:bit Educational Foundation took 18 months to develop a Python editor that will address the barriers users can face in working with text-based languages by creating a more user-friendly, creative, and intuitive learning experience. The free access is given in multiple languages, including English, French, Japanese, Korean, and Spanish. This will help school students to get hands-on experience with programming lessons.

“To truly address the digital skills gap – and the digital diversity gap – we need to remove the barriers that surround learning text-based languages,” commented Lucy Gill, Product Manager at the Micro:bit Educational Foundation.

Some of the interesting features that come with the cloud-native web Python editor are drag-and-drop code examples, code structure and error highlighting, auto-complete, a simulator, and quick ideas to get started. Drag and drop is my favorite feature as it lets the students easily discover examples that can be dragged into the code to make a new logic function.

The BBC also has a list of projects developed in Python programming languages, searchable by computing topic, level, and micro:bit features. There are a total of 74 projects developed in Python programming language that cover many device features, including accelerometer, buttons, compass, LED display, sound, radio, light sensor, temperature sensor, speaker, pins, microphone, and many more.

“With over six million of our devices in use globally, we have been able to draw on a broad scope of insights and data to redefine how we teach Python and make it more accessible to a broader spectrum of users. This is purpose-designed to make the step up from beginner feel far smaller and to bring code to life with a physical device, keeping learners more engaged and motivated.”

To get hands-on experience with the all-new web Python editor, head to the official page and start your programming journey.

Pimoroni Automation 2040 W Mini– An industrial and automation controller with wireless connectivity

Pimoroni Automation 2040 W Mini

A UK-based embedded device manufacturer and supplier, Pimoroni Ltd., has launched an industrial and automation controller that can support 2.4GHz of wireless connectivity– Pimoroni Automation 2040 W Mini. The company has previously worked on a carrier board that could fit the Raspberry Pi Pico W development board, Pimoroni Inventor 2040 W. This time the Automation 2040 W Mini is taking a step forward to be able to hold the all-new Raspberry Pi Pico W.

Pimoroni has provided the hardware platform with many analog channels, powered outputs, buffered inputs, and a relay for industrial applications inside the automation controller. To control pumps, fans, solenoids, chunky motors, and electronic locks, the Pimoroni Automation 2040 W Mini is expected to serve the purpose.

Specifications of Pimoroni Automation 2040 W Mini:

  • Mainboard: Raspberry Pi Pico W
  • CPU: Dual-core Arm Cortex-M0+ running at up to 133MHz clock frequency
  • Memory: 264kB of SRAM
  • Flash memory: 2MB of QSPI flash supporting XiP
  • Wireless connectivity: 2.4GHz wireless
  • ADC: 3x 12-bit ADC inputs up to 40V
  • Digital inputs: 2x digital inputs up to 40V
  • Digital outputs: 2x digital sourcing outputs at V+
  • Relay: 1x relay
  • Buttons: 2x tactile buttons with LED indicators and a reset button
  • Connectors: 1x Qw/ST connector for breakout boards
  • Software: C/C++ and MicroPython libraries
  • Power supply: Compatible with 12V, 24V, and 36V systems, requires a supply of 6-40V and can provide 5V up to 0.5A for lower voltage applications

Pimoroni Automation 2040 W Mini Image

The carrier board has indicator LEDs to show what’s happening with the setup and test the program without having hardware connected. For more digital inputs, outputs, and relays, the company has provided a larger board with 4x digital inputs, 3x digital sourcing outputs, and 3x relays. Also, if the user wants to mount the board inside the switch cabinet or any other electrical enclosure, Pimoroni has provided DIN rail mounts, specifically for the carrier board.

For connecting external breakout boards, the Pimoroni Automation 2040 W Mini carrier board has Qw/ST connector that makes it easy for the user to connect up Qwiic or STEMMA QT breakouts. The developer can directly plug it in with a JST-SH to JST-SH cable.

The board is currently available for sale on the official manufacturers’ website for £39 (approx. $43 USD).

DFRobot Beetle RP2040 mini development board aims for home appliance control

DFRobot Beetle RP2040 mini development board

DFRobot is known for manufacturing many famous electronic embedded devices for home applications, hobbyists, and professional use. In the meantime, Adafruit QT Py received a lot of attention due to its small form factor and improved performance with the latest microcontrollers on board. To capitalize on this momentum, DFRobot has launched the Beetle RP2040 Mini development board with a size measuring 27×20 mm only.

As the name suggests, the development board is equipped with the Raspberry Pi’s in-house silicon tape-out RP2040 microcontroller, which features a dual-core Arm Cortex-M0+ processor core clocked up to 133MHz frequency. On top of that, the RP2040 microcontroller has 264kB internal RAM and supports USB1.1 devices, allowing users to focus on the function implementation instead of spending time on improving the program.

Specifications of DFRobot Beetle RP2040 Mini Development Board:

  • CPU: Raspberry Pi RP2040 microcontroller
  • Clock frequency: 133MHz
  • Internal RAM: 264kB
  • Flash memory: 2MB
  • Power support: 3V3 to 5V DC
  • Interface: USB Type-C port
  • GPIOs: 8
  • Serial communication: 2x I2C, 2x UART, 1x SPI
  • Digital port: 8
  • Analog port: 2
  • Button: 1x reset button and 1x boot button
  • LED: 1
  • USB interface: USB1.1 port
  • Software: C++, MicroPython, Arduino C, Mind+ graphical programming
  • Dimensions: 27x20x4.91 mm
  • Weight: 20 grams without packaging

DFRobot Beetle RP2040 mini development board Pin layout

Thanks to the compact size, the hardware device can be embedded into smaller devices and projects. The company has adopted a beginner-friendly large pad design which is essential to reduce the entry-level barriers and reduce the difficulty of soldering. This rich set of interfaces helps users attach external hardware sensors through various ports available on the DFRobot Beetle RP2040 mini development board.

DFRobot has provided the hardware platform with a BOOT button. If the RP2040 program is running incorrectly, then this can cause a program error and download failure. The solution to this is to hold the BOOT button and plug in the USB cable to the computer at the same time, then the USB drive will be ejected.

DFRobot Beetle RP2040 mini development board is commercially available on the official product page for $6.90. The company has also provided a detailed product wiki page for more information.

Imagination Technologies – Baidu PaddlePaddle co-developed ML library for Model Zoo

Model Zoo Library

A UK-based startup that provides silicon and software IP, Imagination Technologies has partnered with Baidu PaddlePaddle, a provider of artificial intelligence solutions, to co-develop an open-source machine learning library for Model Zoo. The new AI model will cover several AI processing, which includes image classification, image segmentation, and object detection. The jointly developed Model Zoo library is aimed at supporting a wide range of industries, such as consumer, automotive, data center, and desktop markets.

To support the co-developed Model Zoo library, both companies have come together to present more details on September 28, 2022, to offer developers and manufacturers more resources. Imagination Technologies and Baidu PaddlePaddle have been collaborating on various other AI solutions in the past, and the Model Zoo library is an extension to continue their pledge for advanced machine learning algorithms.

“As a leading supplier of processing technology and IP, Imagination enabled Baidu Paddle to construct a highly efficient and flexible software stack solution,” said Yanjun Ma, general manager of Baidu AI Platform and Ecosystem. “The solution is developed based on the deep learning open-source PaddlePaddle framework and Imagination’s heterogenous computing IP through co-designing and optimization. The collaboration will expand to other areas including data center, consumer, and RISC-V.”

The collaboration leverages Baidu PaddlePaddle’s software flexibility with high-performance computation capabilities for Imagination Technologies’ heterogeneous AI accelerator cores. As part of the hardware ecosystem co-creation program, the companies aim to support chip and application developers to create an optimized AI solution for a wide range of deep learning-based use cases.

According to AI experts, the joint program will accelerate the development and deployment of AI models and also provide a verified list of software models, including image classification (EfficientNet), image segmentation (HRNet), and object detection (PP -YOLOE).

“PaddlePaddle is a long-time partner of Imagination, and we share a common vision for the future,” said Wallace Pai, chairman of Imagination China. “We want to ensure that developers and manufacturers have access to the right tools for AI innovation. Our co-created AI ecosystem will continue to leverage our advanced capabilities in AI computing, enabling more support for software and SoC creators in the industry.”

For more information on the Model Zoo deployment, head to the official workshop page for registration. The workshop will cover an end-to-end workflow for the deployment of the Baidu PaddlePaddle model on Imagination Technologies hardware.

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