Hacarus Embedded AI Computing Kit Leverages Sparse Modeling Technology

Hacarus AI Computing Kit Sparse Modeling Technology

AI training often requires thousands of samples to become accurate, and it can be costly and time-consuming, for example, if you want to train a model to detect manufacturing defects you’d need to provide images with both defective samples and good samples. Japanese AI experts at Hacarus have been working on a solution called Sparse Modeling which requires about 50 samples or even less for training, and worked with Congatec to provides an embedded AI computing kit leveraging the technology. Sparse Modeling Technology Hacarus does not go into great detail but explains Sparse Modeling technology is using a data modeling approach that focuses on identifying unique characteristics, in a way that humans recognize friends and family without having to look at everything from feet to head. That means algorithms based on Sparse Modeling do not need as much data as traditional AI solutions, leading to much smaller AI footprint suitable […]

The Case for Running Chromium OS on IoT Devices

Chromium OS IoT Device

The concept of Chromium OS for IoT was presented by Linaro Veteran Khasim Syed Mohammed at Linaro Connect 2019,  In his presentation, he talked about the possibilities and advantages of using Chromium OS for IoT devices. This approach looks promising since it’s running on a Linux Kernel base, and Chromium OS uses a lightweight graphics stack that relies on Linux DRM APIs. This may help to create an IoT device with a graphics interface, without consuming too many hardware resources. Why Chromium OS From the architecture front, chromium OS has impressive advantages compared to other lightweight Linux operating systems, such as Direct Rendering Manager, support for web-based applications, etc… Graphics Stack In  Linux-based operating systems, most of the time the graphics/display stack is handled by the X-Window system (Xserver and clients). This increases the complexity of development, consumes a large number of hardware resources and increases the product development life […]

Galerdo AI Swimming Tracker Gives Audio Feedback, Plays Music – No Ear Buds Needed (Crowdfunding)

Galerdo Beker Pro Galerdo is a simple to use, swimmers attendant, that holds tight to the head and collects data.  It offers interactive audio, AI advice underwater and even plays music through bone-conduction.  We previously reported on fitness and swimming tracker Makibes F69 IP68 Smartwatch but it lacked audio support. Feature Awards for Galerdo Galerdo won the CES 2020 Innovation Award for Swim Tracker, AI Voice Assistant and Handset Free features. Previous and Present Devices Galerdo Inc has a previous bone-conduction audio device that offered music underwater to swimmers, without the need for a headband or earbuds.  The latest device simply called Galerdo adds AI data collection and spoken advice as the user is swimming, in real-time. Quick Run Down on Bone-Conduction The AI technology that is used in the Galerdo is further enhanced by the bone-conduction transfer of sound and is a technology industry that is growing rapidly. It […]

MINIX NEO G41V-4 Mini PC Review – Part 2: Windows 10 Pro

MINIX NEO G41V-4 HDMI + VGA

MINIX NEO G41V-4 is the latest mini PC from the Hong Kong-based company, and this time they’ve gone fanless with a new design that should allow proper cooling with a large heatsink, plenty of ventilation holes on the top, as well as a dust-resistant meshing to present dust from entering inside the enclosure. I’ve now had time to review the fanless mini PC, and I’ll report my experience with Windows 10 Pro, while Ian did his part with Ubuntu 18.04. Switching to Windows 10 Boot from SSD I had installed the optional 240GB SSD in the first part of the review. It offers an easy way to get more storage and performance, and you don’t need to reinstall Windows 10 Pro since it’s already installed in the SSD. You just need to change some settings in the BIOS as explained in the user manual. To be on the safe side, […]

Getting Started with Embedded Linux on RISC-V in QEMU

RISC-V Linux QEMU Buildroot

RISC-V is getting more and more popular, but if you want to run Linux on actual hardware it’s currently fairly expensive since you either need to rely on HiFive Unleashed SBC ($999), or expensive FPGAs. Another solution is running Linux RISC-V via QEMU emulator,  and I showed how to do this using BBL (Berkeley Boot Loader),  Linux 4.14, and busybear rootfs. If you check the comments section of that earlier post you could also try out Fedora RISC-V images in QEMU. Bootlin has now published a presentation showing how to run embedded Linux on RISC-V in QEMU with many of the same components as in the previous instructions, but with a more up-to-date Linux kernel (5.4), and using Buildroot to build everything from scratch including the toolchain, BBL, the Linux kernel, and a Busybox based root file system. They explain each step in detail in the 45-page presentation to allow […]

Khadas VIM3 NPU ToolKit Release & Video Demo

Khadas VIM3 NPU Toolkit

Khadas VIM3 board based on Amlogic A311D processor with a 5TOPS Neural-network Processing Unit (NPU) launched last June. We’ve reviewed VIM3 with Android 9 shortly after launch, but until recently it was not possible to leverage the NPU since the software was not quite ready yet. The goods news is that Khadas has now released the NPU toolkit for both VIM3, and the cheaper VIM3L boards. The NPU toolkit contains the following directory: docs – Model conversion documentation acuity-toolkit – Model conversion tools linux_sdk – Linux SDK android_sdk – Android SDK The toolkit works in host PCs running Ubuntu 16.04 or 18.04 with Tensorflow framework, and inference can run on both Linux and Android OS in Khadas VIM3/3L board. It includes an Inception v3 sample with 299×299 sample photos, among other demos. You’ll find documentation to get started with model conversion and inference in Linux on Khadas Wiki. You can […]

Bangle.js is an Hackable, Open Source JavaScript and TensorFlow-driven Smartwatch (Crowdfunding)

Espruino brought JavasScript to the Microcontroller, now Bangle.js is bringing Javascript plus TensorFlow Lite to your smartwatch. There has been some movement by some developers that says that JavaScript should be used for everything, even though I find that idea ridiculous, I still find JavaScript a fascinating language. The NeaForm Research team and Gordon Williams (the brain behind Espruino) have all teamed up in launching Bangle.js Smartwatch. Bangle.js isn’t your ordinary smartwatch, at the heart of it is the open-source ecosystem. JavaScript plus TensorFlow Lite and of course, a cool looking Smartwatch is what Bangle.js is offering. Bangle.js was launched at the recently concluded NodeConf EU conference, and the goal is to bootstrap an Open Health Platform hopefully. NodeWatch is the specific implementation of Bangle.js for NodeConf EU 2019, co-developed by Espruino and NearForm Research. This project has the potential to bootstrap a community-driven open health platform where anyone can […]

Shine Assistant AI-Powered Toilet Cleaning System Aimed at the Mass Market (Crowdfunding)

Shine Assistant AI For The Bathroom Entering the consumer market with an AI device can be tricky, it is difficult to explain how and why they work. Shine Bathroom has entered into the arena of smart bathrooms, which are starting to pop up with more frequency. Shine Assistant is the latest, stand-alone smart toilet automated cleaner and maintenance system on the market. The Smart Toilet Market The smart toilet has been reported on in the articles on Kohler Novita, an AI toilet called the “Therapy Bidet” and the Lixil AI-based toilet that can analyze feces to help in healthcare, especially for the elderly. The Shine Assistant Features and Advantages The Shine Assistant is a device that attaches to any toilet, mounts to the wall or side of the toilet, and leverages AI for cleaning and maintenance. The system has a number of features and advantages over human-based cleaning and maintenance. […]

EmbeddedTS embedded systems design