Droplet Computing Aims to Run Apps on any Device (Regardless of the Operating System)

Droplet-Computing

The most popular apps are normally ported to all commonly used operating systems such Windows, Mac OS, Linux, Android and iOS, but apps will a lower user base or older apps may not to ported to all operating systems due to the development time / costs involved. In order to solve this issue, UK based Droplet Computing has introduced Droplet Universal, a patent-pending application container solution that decouples applications from the operating system, and enables applications to run on any device, on- or offline. The solution relies on WebAssembly, and allows you to run the app – placed in a low footprint universal container – from a web browser with Chrome v60 (v62 for Android), Firefox v52, Safari v11, and Edge v16 or greater currently supported. Arm and x86 platform are supported, although it’s not yet possible to run Arm apps on x86 with Droplet Universal. It’s hard to know how well this works without testing it, but we may …

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GameSir X1 BattleDock is a Bluetooth Smartphone Dock with USB Ports for Keyboard and Mouse

Gaming-Dock-USB-Keyboard-Mouse-Smartphone

If you’ve ever wanted to easily connect a USB keyboard and/or mouse to your smartphone, GameSir X1 BattleDock may be for you. The dock holds your phone at an angle, and offers two USB ports for USB input  devices,  with the phone and dock communicating over Bluetooth. As the name implies, the system is apparently designed for gamers, but others might find it useful too.Some basic specifications for the dock: USB – 2x USB host ports Connectivity – Bluetooth 4.0 Misc – Mode switch button, status LEDs, foldable phone holder Battery – 3,000 mAh battery good for about 5 hours Power Supply – 5V via micro USB port Dimensions – approximately 13.5 x 10.2 x 3.1 cm when folded Weight – 272 grams The manufacturer claims the dock supports the most common FPS and battle royale games such as PUBG mobile, Rules of Survival, Knives Out, Dead trigger2, Modern Combat 5 and more. You can also customize keyboard buttons / …

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Sonoff Pow R2 is a Power Monitoring WiFi Smart Switch with Better Accuracy, Safety and Extra Features

Sonoff-POW-R2

ITEAD Studio released several wireless switches / sockets with power monitoring capability over the years. Recently they company launched Sonoff S31 smart socket that plugs directly into your AC socket and does not require any wiring, but earlier they introduced Sonoff Pow that is meant to be connected directly into your circuit via terminals. ITEAD has now launched an upgrade to the latter  – Sonoff Pow R2 – with many of the same features, including support for eWelink, but offering 99% measurement accuracy, overload protection defined by the user, and various other features like the ability to export data. Sonoff Pow R2 (Revision 2) specifications: WiSoC – Espressif ESP8266 (TBC) Connectivity – 802.11 b/g/n WiFi with WPA/WPA2 support Voltage Range – 90 to 250 VAC input Max Current – Up to 16A Max Power – 3,500 Watts Terminals – 6 terminal for mains and load’s ground, live and neutral signals. Misc – LEDs for power and WiFi status, power consumption …

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Wibeee Power Monitoring Device Plugs right into Your Home’s Circuit Breaker Box

We’ve covered several smart plugs or switches capable of monitoring electricity consumption and displaying results right in a smarphone app, or computer’s web browser with products such as Sonoff S31 or Broadlink SP2 WiFi smart sockets, or Sonoff POW switch. Those work for individual plugs, but if you want to cover your full house, you’d need several of those, and in some case it may not be so convenient as no plugs may be available for example for lights or air conditioner. Smilics Technologies has come up with an easier method, although less granular, thanks to their WIBEEE device that clips to your fuse / circuit breaker box using DINZERO “clip-on” technology, and available in single and  three phase models. Main features: Voltage Range – 85 to 265 V AC @ 50 ~ 60 Hz with 2% accuracy + variation in range of use depending on temperature, humidity, etc… Current Range – 500mA to 65A with 2% accuracy + variation …

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Open Source Software Releases – VLC 3.0 and Android-x86 7.1-r1

Two completely unrelated open source projects have released a stable version of their software this week, but instead of writing a post for each I’ll write about them in a single post. VLC 3.0 Vetinari VLC developers have just released version 3.0 – codenamed Vetinari – of the popular media player with new features such as ChromeCast support, and 8K video playback. Other highlights from the release include: Hardware decoding enabled by default to get 4K and 8K playback 10-bit and HDR support (only on Windows 10 Fall Creators Update for now) 360 video and 3D audio, up to Ambisoncics 3rd order Allows audio passthrough for HD audio codecs Can play Blu-Ray Java menus: BD-J Browsing of local network drives and NAS VLC 3.0 is also the first major version to be released for all platforms at the same time, and you can download VLC 3.0 for Windows, Mac OS X, Linux, Android, iOS, and Windows Phone / RT, and …

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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. But what may make the project worthwhile is built-in support …

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Fingbox Helps You Monitor & Manage Devices on Your Network with Your iOS/Android Smartphone

Fing network scanner mobile app available for iOS and Android that allows you to discover which devices are connected to your Wi-Fi network, map devices, detect intruders, assess network security risks, troubleshoot network problems, and optimize wireless network performance. But in order to go beyond network monitoring, the developers have designed Ubuntu Core based Fingbox hardware to add features such as access control (e.g. parental control), analyze the usage of bandwidth for each clients, find Wi-Fi sweet spots/ avoid black spots, verify your Internet speed, monitor devices in your network, and protects it with a digital fence that works against threats. From a hardware perspective Fingbox is a round shaped Ethernet node with the following specifications: Processor – ARMv7 processor System Memory – 1GB RAM Connectivity – Gigabit Ethernet The Linux (Ubuntu Core) device just needs to be connected to your network via an Ethernet cable, and powered by its adapter. You’d then run Fing app on Android or iOS, …

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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 optimized for maximum speed and minimum size. The model file …

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