BOXER-8120AI is a Compact Jetson TX2 Mini PC for Drones, Robots and Surveillance Applications

Jetson TX2 Mini PC

AAEON has just launched BOXER-8120AI compact mini PC based on NVIDIA Jetson TX2 processor module with 8GB RAM, 32GB storage, and four Gigabit Ethernet ports. The fanless mini PC targets smart surveillance/ security/ parking, unmanned stores, drones and robotic controllers, or any applications that can leverage Jetson TX2’s 256 CUDA cores for A.I. workloads. BOXER-8120AI Jetson TX2 Mini PC specifications: Processor Module – NVIDIA Jetson TX2 with HMP Dual Denver 2 + Quad Arm A57, NVIDIA Pascal GPU with 256 CUDA cores, 4K (HEVC) video encoder, 4K 12-bit video decoder System Memory – 8GB LPDDR4 @ 59.7 GB/s Storage – 32GB eMMC 5.1 flash, MicroSD slot Display Interface – HDMI 2.0 type A Networking – 4x 10/100/1000Base-TX Ethernet USB – 2x USB 3.0 ports, 1x micro USB OTG port Serial – 2x COM ports (DB9) Misc – Power Button, Power LED, 2x SMA Holes, Remote Power On/Off Power Supply – 9~24V DC-in power input via lockable DC jack Dimensions – …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Pico-ITX i.MX8M Board Enables Offline Voice Control with Snips

Estone EMB-2238

A few days ago, we covered Estone Technology’s MJ-100 RK3399 rugged tablet. I’ve just realized Estone Technology used to promote their embedded product under the Habey USA brand, which we covered a few times here, and the company has also announced another new product ahead of Embedded World 2019 with their EMB-2238 Pico-ITX i.MX8M board specifically designed for voice control applications. The company setup two voice control demos with the board: one with Amazon Alexa Voice Service (AVS) and another with Snips that works locally without any Internet connection. We actually came across Snips previously for an article comparing microphone arrays, but I never looked into Snips into details or saw an actual demo. Let’s have a quick look at EMB-2238 board specifications first: SoC –  NXP i.MX 8MQuad  with 4x Arm Cortex-A53 cores @ 1.5GHz, 1x Arm Cortex-M4 realtime-core @ 266MHz, Vivante GC7000L/GC7000LVX with support for OpenGL/ES 3.1, OpenGL 3.0, Vulkan, OpenCL 1.2 System Memory – Onboard 2GB LPDDR4, …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Arm Helium Delivers up to 15x Performance Uplift for Machine Learning on Cortex-M MCUs

Arm Helium

Arm has just unveiled Armv8.1-M architecture that adds Arm Helium technology, the M-Profile Vector Extension (MVE) for the Arm Cortex-M cores that will improve the compute performance of Cortex-M based microcontrollers. Helium will deliver up to 15 times more machine learning (ML) performance and up to 5 times uplift to signal processing allowing local decision-making on low-power embedded devices. Helium instructions will enable new applications for Arm Cortex-M microcontrollers in audio devices, sensor hubs, keyword spotting, voice command control, power electronics, communications and still image processing. Helium and Neon (the Advanced SIMD technology for Arm Cortex-A processors) are similarities but Helium has been designed for efficient signal processing performance in small processors. One different illustrated below is that while NEON loads 128-bit instructions (e.g. VLDR, VLMA), Helium will split up 128‑bit wide instruction into four equally sized chunks, called “beats” (labelled A to D) due to difference between Cortex-M and Cortex-A cores as explained in details in an Arm Research …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Autoware is an “All-in-One” Open-source Software for Autonomous Driving

Autoware.AI Software Architecture

All major automotive companies, and some technology companies are all working on autonomous driving with the ultimate goal of achieving level 5 autonomous driving meaning no human intervention is needed at any stage. Development will take some more time, and companies are now competing with closed source software and hardware. But as I browsed through Linaro Connect Bangkok 2019 schedule, I found out there’s an open source autonomous driving software called Autoware.AI. Several “Autoware” projects are managed by the newly founded Autoware Foundation, a non-profit organization created to develop a synergy between corporate development and academic research in order to provide access to autonomous driving technology for everyone: Autoware.AI is the first version built on ROS 1, and Linux, and has been developed as a research and development platform is the second version built on ROS 2, and Linux, with a complete redesign. Autoware.IO is an interface project for Autoware to be extended with proprietary software and third-party libraries for …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Adding Machine Learning based Image Processing to your Embedded Product

Convert model tensorflow runtime to NNEF

CNXSoft: This is a guest post by Greg Lytle, V.P. Engineering, Au-Zone Technologies. Au-Zone Technologies is part of the Toradex Partner Network. Object detection and classification on a low-power Arm SoC Machine learning techniques have proven to be very effective for a wide range of image processing and classification tasks. While many embedded IoT systems deployed to date have leveraged connected cloud-based resources for machine learning, there is a growing trend to implement this processing at the edge. Selecting the appropriate system components and tools to implement this image processing at the edge lowers the effort, time, and risk of these designs. This is illustrated with an example implementation that detects and classifies different pasta types on a moving conveyor belt. Example Use Case For this example, we will consider the problem of detecting and classifying different objects on a conveyor belt. We have selected commercial pasta as an example but this general technique can be applied to most other …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

96Boards HiChips Parrot Board and 3-Mic Array Work with Amazon Alexa

96boards Parrot Board Amazon-AVS 3-Mic far field board

Early last year, Banana Pi unveiled Allwinner SoC-Only 3-Mic Far-Field Development Kit for Amazon AVS, a board powered by Allwinner R18 processor extended with an external 3-mic array board, officially supported by Amazon Alexa Voice Service (AVS), and sold for $129 plus shipping. There’s now a compatible board following 96Boards CE Extended form factor, and selling for just $79.99 plus shipping on Alibaba or 555.99 CNY on The board looks almost the same as the original 3-Mic far-field development kit, apart from the LS and HS connectors found in the 96Boards hardware platforms. Hichips Parrot board should not be confused with Allwinner R16 based Parrot board that was used by Allwinner internally, and never made available to the general public. Hichips Parrot board specifications: SoC – Allwinner R18 quad-core Cortex-A53 processor @ 1.15GHz with Mali400MP2 GPU System Memory – 1GB DDR3 Storage – 8GB eMMC flash, micro SD card slot Video Output – HDMI Audio – 3x Microphones, 2x …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Intel RealSense Tracking Camera T265 is Designed for Autonomous Devices

Intel RealSense Tracking Camera T265

Intel has just launched another smart camera with RealSense Tracking Camera T265 powered by the company’s Myriad 2 VPU (Vision Processing Unit) also found in the first Neural Compute Stick, and designed for autonomous robots, drones, and augmented/virtual reality applications. The T265 camera is said to use proprietary visual inertial odometry simultaneous localization and mapping (V-SLAM) technology “delivering high-performance guidance and navigation”. Intel RealSense tracking camera T265 hardware specifications: VPU – Intel Movidius Myriad 2 vision processing unit with 12 VLIW 128-bit vector SHAVE processors optimized to run V‑SLAM at low power Cameras – 2x Omnivision OV9282 high-speed image sensors with Fisheye lenses for a combined 163±5° FOV; infrared cut filter Sensor – Bosch BMI055 6-axis IMU (Inertial Measurement Unit) to measure rotation and acceleration of the device USB – 1x USB 3.1 Gen 1 Micro B port to transfer pose data, or pose + image data. Dimensions – 108 x 24.5 x 12.5 mm; 2x M3 0.5mm pitch mounting sockets (50 mm apart) The V-SLAM …

Support CNX Software – Donate via PayPal or become a Patron on Patreon

Toybrick RK3399Pro Board is equipped with Rockchip RK3399Pro AI processor

We’ve heard about Rockchip RK3399Pro processor that adds an NPU (Neural-network Processing Unit) to Rockchip RK3399 hexa-core processor for about a year now. We’ve seen the official Rockchip RK3399Pro EVB in action last November, but this type of board is not usually for sale to the general public. The first RK3399Pro board that you could technically spend money on was Khadas Edge-1S via a crowdfunding campaign, but it’s still unclear when it will ship. Another option that I just discover is Toybrick RK3399Pro (TB-RK3399Pro) single board computer by VAMRS. Toybrick RK3399Pro board preliminary specifications: SoC – Rochchip RK3399Pro hexa-core big.LITTLE processor with 2x Cortex A72 cores up to 1.8/2.0 GHz, 4x Cortex A53 cores @ 1.4 GHz, and an Arm Mali-T860 MP4 GPU with OpenGL ES 1.1 to 3.2, OpenVG1.1, OpenCL 1.2 and DX 11 support, and NPU delivering up to 3 TOPS System Memory – 3 or 6 GB memory Storage – micro SD card slot + 16 or …

Support CNX Software – Donate via PayPal or become a Patron on Patreon