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December 4, 2017April 14, 2018 by Jean-Luc Aufranc (CNXSoft) - 12 Comments

Top 5 Most Powerful Arm SBCs & Development Boards in 2017 / Early 2018

Raspberry Pi, Orange Pi, and NanoPi boards among others are all great and inexpensive Arm Linux development boards that do good enough job for many tasks, but they may not cut it if you have higher requirements either in terms of CPU power, GPU capabilities and performance, I/O bandwidth, and in some cases software and support. So I’ve decided to make a list of 5 single board computers or development boards that I consider to be the most powerful in 2017, early 2018. I have limited the price to $1,000 maximum, the board must be easy to purchase for most people (e.g. you don’t need to be a tier-1 automotive supplier, or operate your own datacenter), and in case the board is not quite available yet, the likeliness of actual launch must be reasonably high. Those criteria for example exclude Intrinsyc Open-Q 835 development kit since it costs $1.149 and […]

December 1, 2017December 1, 2017 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

$45 AIY Vision Kit Adds Accelerated Computer Vision to Raspberry Pi Zero W Board

AIY Projects is an initiative launched by Google that aims to bring do-it yourself artificial intelligence to the maker community by providing affordable development kits to get started with the technology. The first project was AIY Projects Voice Kit, that basically transformed Raspberry Pi 3 board into a Google Home device by adding the necessary hardware to support Google Assistant SDK, and an enclosure. The company has now launched another maker kit with AIY Project Vision Kit that adds a HAT board powered by Intel/Movidius Myriad 2 VPU to Raspberry Pi Zero W, in order to accelerate image & objects recognition using TensorFlow’s machine learning models. The kit includes the following items: Vision Bonnet accessory board powered by Myriad 2 VPU (MA2450) 2x 11mm plastic standoffs 24mm RGB arcade button and nut 1x Privacy LED 1x LED bezel 1x 1/4/20 flanged nut Lens, lens washer, and lens magnet 50 mil […]

November 30, 2017 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

AWS DeepLens is a $249 Deep Learning Video Camera for Developers

Amazon Web Services (AWS) has launched Deeplens, the “world’s first deep learning enabled video camera for developers”. Powered by an Intel Atom X5 processor with 8GB, and featuring a 4MP (1080p) camera, the fully programmable system runs Ubuntu 16.04, and is designed expand deep learning skills of developers, with Amazon providing tutorials, code, and pre-trained models. AWS Deeplens specifications: SoC – Intel Atom X5 Processor with Intel Gen9 HD graphics (106 GFLOPS of compute power) System Memory – 8GB RAM Storage – 16GB eMMC flash, micro SD slot Camera – 4MP (1080p) camera using MJPEG, H.264 encoding Video Output – micro HDMI port Audio – 3.5mm audio jack, and HDMI audio Connectivity – Dual band WiFi USB – 2x USB 2.0 ports Misc – Power button; camera, WiFi and power status LEDs; reset pinhole Power Supply – TBD Dimensions – 168 x 94 x 47 mm Weight – 296.5 grams The […]

November 24, 2017November 24, 2017 by Jean-Luc Aufranc (CNXSoft) - 10 Comments

Cheap Evil Tech – WiFi Deauther V2.0 Board and Autonomous Mini Killer Drones

Most technological advances usually improve life of people, and with the costs coming down dramatically over the years, available to more people. But technology can be used for bad, for example by governments and some hackers. Today, I’ve come across two cheap hardware devices that could be considered evil. The first one is actually pretty harmless and can be use for education, but disconnects you from your WiFi, which may bring severe physiological trauma to some people, but should not be life threatening, while the other is downright scary with cheap targeted killing machines. WiFi Deauther V2.0 board Specifications for this naughty little board: Wireless Module based on ESP8266 WiSoC USB – 1x Micro USB type changed, more stable. Expansion – 17-pin header with 1x ADC, 10x GPIOs, power pins Misc – 1x power switch, battery status LEDs Power Supply 5 to 12V via micro USB port Support for 18650 […]

November 22, 2017November 23, 2017 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

JeVois-A33 Linux Computer Vision Camera Review – Part 2: Setup, Guided Tour, Documentation & Customization

Computer Vision, Artificial Intelligence, Machine Learning, etc.. are all terms we hear frequently those days. JeVois-A33 smart machine vision camera powered by Allwinner A33 quad core processor was launched last year on Indiegogo to bring such capabilities in a low power small form factor devices for example to use in robotics project. The company improved the software since the launch of the project, and has now sent me their tiny Linux camera developer kit for review, and I’ve already checked out the hardware and accessories in the first post. I’ve now had time to test the camera, and I’ll explained how to set it up, test some of the key features via the provided guided tour, and show how it’s possible to customize the camera to your needs with one example. Getting Started with JeVois-A33 In theory, you could just get started by inserting the micro SD card provided with […]

November 21, 2017 by Jean-Luc Aufranc (CNXSoft) - No Comments

Nexell NXC100 Voice Recognition Chip, NXP4330Q Processor, and ALTO Development Board

I wrote about NanoPi Fire2 & Fire3A boards based on Nexell S5P processors a few days ago, and at the time, as I checked out Nexell website, I found out about the company’s NXC100 Voice Recognition SoC that can be used in 4-mic array board. The chip can then be connected through SPI to a host processor, and Nexell appears to have a NXP4330Q Smart Voice kit based on their quad Cortex A9 processor of the same name. But since documentation is really limited, I looked for more details, and came across NXP4330Q based ALTO board design by InSignal, which sold the Exynos powered Arndale boards a few years back. Nexell NXC100 Voice Recognition SoC The chip is the only product from the “A.I related” section of therir website, but more are likely to come out as the company is working on GP-GPU (General Purpose GPU), machine learning, and even registered […]

November 17, 2017 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

Google Releases Tensorflow Lite Developer Preview for Android & iOS

Google mentioned TensorFlow Lite at Google I/O 2017 last may, an implementation of TensorFlow open source machine learning library specifically optimized for embedded use cases. The company said support was coming to Android Oreo, but it was not possible to evaluate the solution at the time. The company has now released a developer preview of TensorFlow Lite for mobile and embedded devices with a lightweight cross-platform runtine that runs on Android and iOS for now. TensorFlow Lite supports the Android Neural Networks API to take advantage of Machine Learning accelerators when available, but falls back to CPU execution otherwise. The architecture diagram above shows three components for TensorFlow Lite: TensorFlow Model – A trained TensorFlow model saved on disk. TensorFlow Lite Converter – A program that converts the model to the TensorFlow Lite file format. TensorFlow Lite Model File – A model file format based on FlatBuffers, that has been […]

October 28, 2017 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

Intel Speech Enabling Developer Kit Works with Alexa Voice Service, Raspberry Pi 3 Board

We’ve known Intel has been working on Quark S1000 “Sue Creek” processor for voice recognition for several months. S1000 SoC is based on two Tensilica LX6 with HiFi3 DSP, some speech recognition accelerators, and up to 8x microphones interfaces which allows it to perform speech recognition locally. The solution can also be hooked to an application processor via SPI, I2S and USB (optional) when cloud based voice recognition is needed. Intel has recently introduced their Speech Enabling Developer Kit working with Amazon Alexa Voice Service (AVS) featuring a “dual DSP with inference engine” – which must be Quark S1000 – and an 8-mic array. The kit also includes a 40-pin cable to connect to the Raspberry Pi 3 board. Intel only provided basic specifications for the kit: Intel’s dual DSP with inference engine Intel 8-mic circular array High-performance algorithms for acoustic echo cancellation, noise reduction, beamforming and custom wake word […]