Bolt IoT Platform Combines ESP8266, Mobile Apps, Cloud, and Machine Learning (Crowdfunding)

There are plenty of hardware to implemented IoT projects now, but in many cases a full integration to get data from sensors to the cloud requires going though a long list of instructions. Bolt IoT, an Indian and US based startup, has taken up the task to simplify IoT projects with their IoT platform comprised of ESP8266 Bolt WiFi module, a cloud service with machine learning capabilities, and mobile apps for Android and iOS. Bolt IoT module hardware specifications: Wireless Module – A.I Thinker ESP12 module based on ESP8266 WiSoC Connectivity – 802.11 b/g/n WiFi secured by WPA2 USB – 1x micro USB for power and programming Expansion – 4-pin female header and 7-pin female header with 5 digital I/Os, 1x analog I/O, and UART Misc – Cloud connection LED The hardware is not the most interesting part of Bolt IoT, since it offers similar functionalities as other ESP8266 boards. […]

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 […]

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 […]

Google Pixel Visual Core is a Custom Designed Co-Processor for Smartphone Cameras

Google unveiled their latest Pixel 2 & Pixel 2 XL premium smartphones powered by Snapdragon 835 SoC earlier this month, and while they are expected to go on sale tomorrow, reviewers have got their hands on samples, and one of the key feature is the camera that takes really good photos and videos as reported here and there. You’d think the ISP and DSP inside Snapdragon 835 SoC would handle any sort of processing required to take photos. But apparently that was not enough, as Google decided to design their own custom co-processor – called Pixel Visual Core -, and integrated it into Pixel 2 phones. The co-processor features a Cortex A53 core, an LPDDR4 memory interface, PCIe interface and MIPI CSI interface, as well as an image processing unit (IPU) IO block with 8 IPU cores. Google explains the IPU block will allow 3rd party applications to leverage features […]

NVIDIA DRIVE PX Pegasus Platform is Designed for Fully Autonomous Vehicles

Many companies are now involved in the quest to develop self-driving cars, and getting there step by step with 6 levels of autonomous driving defined based on info from  Wikipedia: Level 0 – Automated system issues warnings but has no vehicle control. Level 1 (”hands on”) – Driver and automated system shares control over the vehicle. Examples include Adaptive Cruise Control (ACC), Parking Assistance, and Lane Keeping Assistance (LKA) Type II. Level 2 (”hands off”) – The automated system takes full control of the vehicle (accelerating, braking, and steering), but the driver is still expected to monitor the driving, and be prepared to immediately intervene at any time. You’ll actually have your hands on the steering wheel, just in case… Level 3 (”eyes off”) – The driver can safely turn their attention away from the driving tasks, e.g. the driver can text or watch a movie. The system may ask […]

Google’s Teachable Machine is a Simple and Fun Way to Understand How Machine Learning Works

Artificial intelligence, machine learning, deep learning, neural networks… are all words we hear more and more today, as machines get the ability to recognize objects, answer voice requests / commands, and so on. But many people may not know at all the basics of how machine learning works, and with that in mind, Google launched Teachable Machine website to let people experiment and understand the basics behind machine learning without having to install an SDK or even code. So I quickly tried it with Google Chrome, as it did not seem to work with Mozilla Firefox. It’s best to have audio on, as a voice explains how to use it. Basically you connect your webcam, authorize Chrome too use it, and you should see the image in the input section on the left. After you’re being to train the machine in the learning section in the middle with three difference […]

ARM Cortex-A75 & Cortex-A55 Cores, and Mali-G72 GPU Details Revealed

We’ve already seen ARM Cortex A75 cores were coming thanks to leak showing Snapdragon 845 SoC will feature custom Cortex A75 cores, but we did not have many details. But since we live in a world where “to leak is glorious”, we already have some slides originally leaked through VideoCardz with the post now deleted, but Liliputing & TheAndroidSoul got some of the slides before deletion, so let’s see what we’ve got here. ARM Cortex A75 So ARM Cortex-A75 will be  about 20% faster than Cortex A73 for single thread operation, itself already 30% faster than Cortex A72. It will also be the first DynamIQ capable processor together with Cortex A55 with both cores potentially used in big.LITTLE configuration. Cortex A75 performance is only better for peak performance, and remain the same as Cortex-A73 for sustained performance. The chart above does not start at zero, so it appear as though […]

Google Releases Android O Developer Preview 2, Announces Android Go for Low-End Devices, TensorFlow Lite

After the first Android O developer preview released in March, Google has just released the second developer preview during Google I/O 2017, which on top of features like PiP (picture-in-picture), notifications channels, autofill, and others found in the first preview, adds notifications dots, a new Android TV home screen, smart text selection, and soon TensorFlow Lite. Google also introduced Android Go project optimized for devices with 512 to 1GB RAM. Notifications dots (aka Notification Badges) are small dots that show on the top right of app icons – in supported launchers – in case a notification is available. You can then long press the icon to check out the notifications for the app, and dismiss or act on notifications. The feature can be disabled in the settings. Android TV “O” also gets a new launcher that allegedly “makes it easy to find, preview, and watch content provided by apps”. The […]

Exit mobile version
UP 7000 x86 SBC