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The Compact BOXER-6405U: The Gateway to Industry 4.0

Posted on 12 March, 201912 March, 2019 by mixos

AAEON, an award winning manufacturer of embedded PC solutions, is proud to announce the BOXER-6405U, a turn-key rugged embedded PC built to be flexible and adaptable to a wide range of Industry 4.0 applications, including machine vision, AI edge computing, and industrial IoT gateway.

The BOXER-6405U is built to be a go-anywhere, work-anywhere solution. Rugged design gives it a wide operating temperature range from -20°C to 50°C. It’s palm-sized compact size, only 37mm thick, allows it to squeeze into tight operating spaces, and it’s wide voltage input range of 9V to 24V allow it to easily integrate with industrial power sources. The BOXER-6405U even comes with wall-mount brackets to ensure it’s ready to install wherever you need it.

The BOXER-6405U features an Intel N3350 processor with 2G DDR3L 1600 memory and up to 32 GB eMMC storage onboard. The BOXER-6405U comes with four USB 3.0 and two Intel i211AT Gigabit Ethernet ports, perfect for machine vision applications. The BOXER-6405U has two internal expansion bays, one full-sized Minicard and one half-sized Minicard, supporting a wide range of options including AI modules such as AAEON’s own AI Core X with Intel Movidius Myriad X VPU. With support for WiFi or 4GLTE cards, the BOXER-6405U can also be used for remote edge computing or as an industrial IoT gateway.

The BOXER-6405U is a rugged turn-key solution that is ready to go out of the box. With AAEON’s manufacturer support, it can even be tailored to meet the specific needs of your application.

The BOXER-6405U is a cost effective solution for tough industrial environments,” said Ken Pan, Product Manager with AAEON’s System Platform Division. “It’s a compact embedded computer built for vertical market applications such as machine vision and industrial gateway.

more information on: www.aaeon.com

Google Coral – An i.MX8M dev board with Edge TPU AI chip

Posted on 8 March, 20198 March, 2019 by Rik

Single board computers are not a new wonder anymore and the market has already experienced so many different devices based on numerous SoC and SOM. So, why should we be excited this time about the launch of a $150 “Coral Dev Board”? Well, there are multiple reasons – but the most important one is, the Coral Dev Board is manufactured by Google – a relatively new player in the consumer market of SBC and i.MX8M dev boards. Also, the dev board along with a USB accelerator stick is built around Google’s Edge TPU, their purpose-built ASIC designed to run machine learning inference at the edge.

So, what is the Edge TPU? The Edge TPU is a small ASIC designed and built by Google that provides high-performance ML inferencing with a low power cost. For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at 100+ fps, in a power efficient manner. This allows you to add fast ML inferencing to your embedded AI devices in a power-efficient and privacy-preserving way. For more information on this ASIC, check out googles official documentation.

The NXP i.MX8m based Coral Dev Board appears to be an open-spec design. It would join other open-spec i.MX8M SBCs such as the HummingBoard Pulse. Like SolidRun’s Pulse, the Coral is a sandwich-style board with a removable computer module. The big difference from the expanding field of i.MX8M boards are that the Coral SOM module integrates Google’s Edge TPU neural network co-processor.

The Edge TPU is a stripped-down version of Google’s TPU Unit designed to run TensorFlow Lite ML models on Arm Linux based IoT gateways running on boards like the Coral. The gateways connect to Google Cloud services that are optimized with full-strength Cloud TPU chips to work together via Google’s new Cloud IoT Edge framework. Edge TPU enables concurrent execution of multiple AI models per frame on a high-resolution video at 30fps.

Coral Dev Board

The Coral Dev Board is a single-board computer with a removable system-on-module (SOM) that contains SOC, eMMC, wireless radios, and Google’s Edge TPU. It’s perfect for IoT devices and other embedded systems that demand fast on-device ML inferencing. The board has a layout that’s somewhat similar to the Raspberry Pi. It offers a 40-pin GPIO connector just like raspberry pi. The Coral SOM connects to the baseboard with 3x 100-pin connectors. The Coral board is equipped with a microSD slot, as well as GbE, USB 3.0 host, USB Type-C OTG, USB Type-C 5V power, and micro-USB 2.0 serial console ports. Media I/O includes a full-size, 4Kp60-ready HDMI 2.0a port and 4-lane MIPI-DSI and CSI interfaces via FFC connectors. It also features a good old 3.5mm audio jack.

The Coral Dev Board is a single-board computer with a removable system-on-module (SOM) that contains SOC, eMMC, wireless radios, and Google’s Edge TPU. It’s perfect for IoT devices and other embedded systems that demand fast on-device ML inferencing.

Google EdgeTPU ASIC — Google Edge TPU ASIC

Coral USB Accelerator

Google also unveils Coral USB Accelerator and PCIe Accelerator. The USB Accelerator is a plug-in USB stick that brings powerful ML inferencing capabilities to existing Linux systems. With the Edge TPU connected over USB 3.0 interface, it allows for quick prototyping of local AI applications. The USB accelerator can boost inference on any Linux machine, while the dev board’s array of pins and ports make it perfect for prototyping hardware and other experimental applications. The 65 x 30 mm² USB Accelerator can even work with a Raspberry Pi board, although only at USB 2.0 speeds. The stick computer is built around a 32-bit, 32MHz Cortex-M0+ chip with 16KB of flash and 2KB of RAM.

Google's Coral Accelerator — Google’s Coral USB Accelerator

The Coral USB Accelerator is a plug-in USB stick that brings powerful ML inferencing capabilities to existing Linux systems. With the Edge TPU connected over USB 3.0 interface, it allows for quick prototyping of local AI applications.

The development board is accompanied by the Coral Camera – built around a 5 megapixel (2582×1933 pixel) Omnivision OV5645 sensor. The camera is connected to the board using the CSI interface. The 25 x 25mm camera looks like below:

Now, let’s list the important specifications of the Coral Dev Board:

Processor (via Coral SOM):
- NXP i.MX8M (4x Cortex-A53 @ 1.5GHz)
- Vivante GC7000Lite/GC7000VLX for OpenGL/ES 3.1, OpenGL 3.0, Vulkan, OpenCL 1.2 GPU
- Cortex-M4 @ 266MHz
- separate Edge TPU Accelerator and crypto coprocessor
Memory/storage:
- 1GB LPDDR4 RAM (via Coral SOM)
- 8GB eMMC flash (via Coral SOM)
- MicroSD slot
Wireless (via Coral SOM): 802.11 b/g/n/ac 2×2 MIMO and Bluetooth 4.1 BLE
Networking: GbE port
Media I/O:
- HDMI 2.0a output port (4K)
- MIPI-DSI (4-lane)
- MIPI-CSI (4-lane)
- Optional 5-megapixel CSI camera
- 3.5mm audio jack
- 2x digital PDM microphones
- 4-pin terminal for stereo speakers
Other I/O:
- USB 3.0 host port
- USB 3.0 Type C OTG port
- USB 3.0 Type C 5V power port
- Micro-USB serial console port
Expansion: 40-pin GPIO connector
Power: 5v DC via USB Type-C; 2x PMICs via Coral SOM
Operating temperature: 0 to 50°C
Dimensions: 88.1 x 59.9 x 22.38 including fan (possibly 85 x 56mm)
Operating system: Debian Linux

The Coral Dev Board with Coral SOM is available for $150 at Google and Mouser, but currently only via phone orders. It should start shipping to early buyers within the week. The same schedule likely pertains to the $75 USB Accelerator. The Coral SOM and PCI-E Accelerator will be available later this year, with pricing undisclosed. More information on all these products may be found on Google’s Coral Beta website.

The top 10 linear voltage regulators according to SnapEDA

Posted on 8 March, 20198 March, 2019 by mixos

In electronics, linear voltage regulators are commonly used to stabilize voltages. Regardless of the input voltages or load conditions, they will provide fixed output voltages, thus protecting devices from fluctuating outputs, which can cause inefficient performance or even damage.

When designing a power supply for an application that requires a small difference between its input and output voltages, hardware designers should consider linear voltage regulators.

Simplicity and cost are the main advantages of using linear regulators over switching voltage regulators. Additionally, the absence of switching noise makes linear regulators particularly useful for audio and video communication, medical devices and other noise-sensitive applications.

On the downside, linear voltage regulators generate heat and their efficiency is rather poor, varying between 30% and 60%. This is why they are used mainly for low-powered devices and small differences between input and output voltages.

Compared to linear regulators, switching voltage regulators (also known as switch-mode regulators) are superior in terms of efficiency and generate much less heat, but are also more expensive and complex.

When choosing between different voltage regulators for your application, you should consider several factors, including their maximum input voltages, the differences between input and output voltages, current ratings, temperature ratings, and output noise.

Most of the linear voltage regulators in our Top 10 list have overcurrent and thermal protection. Most also have maximum input voltages ranging from 5.5V up to 40V and output voltages ranging from 3.3V to 15V. The most popular vendors for voltage regulators on SnapEDA are Diodes Inc, Richtek USA Inc, Microchip, STMicroelectronics, and Texas Instruments.

Let’s now take a look at the Top 10 Linear Voltage Regulators on SnapEDA!

#10 – LP2985-33DBVR by Texas Instruments

This low dropout regulator has 16V Maximum input voltage, 3.3V output voltage, 150mA output current, 280mV Dropout voltage and -40°C to 125°C junction temperature range. The average price across distributors: $0.60

#9 – L7805ACD2T by STMicroelectronics

This positive regulator has 35V maximum input voltage, 5V output voltage, 1.5A output current, 2V dropout voltage and 0°C to 125°C junction temperature range. The average price across distributors: N/A

#8 – L7805CV-DG by STMicroelectronics

This positive regulator has 35V maximum input voltage, 5V output voltage, 1.5A output current, 2V dropout voltage, and 0°C to 125°C junction temperature range. The average price across distributors: $0.52

#7 – REG1117 by Texas Instruments

This low dropout positive regulator has 15V maximum input voltage, 1.8V output voltage, 800mA output current and -40°C to 125°C junction temperature range. The average price across distributors: $2.02

#6 – L7805CV by STMicroelectronics

This positive regulator has 35V maximum input voltage, 5V output voltage, 1.5A maximum output current, 2V dropout voltage and 0°C to 125°C junction temperature range. The average price across distributors: $0.41

#5 – LD1117S33CTR by STMicroelectronics

This low drop voltage regulator has 15V maximum input voltage, 3.3V output voltage, 950mA maximum output current, 1V dropout voltage and -40°C to 125°C junction temperature range.The average price across distributors: $0.36

#4 – AP2112K-3.3TRG1 by Diodes Inc.

This positive regulator has 6V maximum input voltage, 3.3V output voltage, 600mA maximum output current, 0.4V Dropout voltage and -40°C to 85°C junction temperature range. The average price across distributors: $0.24

#3 – RT9193-33GB by Richtek USA Inc.

This low dropout regulator has 5.5V maximum input voltage, 3.3V output voltage, 300mA maximum output current, 0.3V dropout voltage, and -40°C to 125°C junction temperature range. The average price across distributors: $0.50

#2 – MIC29302WU by Microchip

This low dropout regulator has 26V maximum input voltage, 3.3V output voltage, 3A output current, 0.6V maximum dropout voltage, and -40°C to 125°C junction temperature range. The average price across distributors: N/A

#1- LM1117MP-3.3 by Texas Instruments

This low dropout regulator has 15V maximum input voltage, 3.3V output voltage, 800mA maximum output current, 1.2 dropout voltage, and 0°C to 125°C junction temperature range. The average price across distributors: N/A

PYNQ-Z1: Python Productivity for Zynq-7000 ARM/FPGA SoC

Posted on 8 March, 20198 March, 2019 by mixos

Python Productivity for Zynq – A Special Project from Xilinx University Program

The PYNQ-Z1 board is designed to be used with PYNQ, a new open-source framework that enables embedded programmers to exploit the capabilities of Xilinx Zynq All Programmable SoCs (APSoCs) without having to design programmable logic circuits. Instead the APSoC is programmed using Python, with the code developed and tested directly on the PYNQ-Z1. The programmable logic circuits are imported as hardware libraries and programmed through their APIs in essentially the same way that the software libraries are imported and programmed.

The PYNQ-Z1 board is the hardware platform for the PYNQ open-source framework. The software running on the ARM A9 CPUs includes:

A web server hosting the Jupyter Notebook design environment
The IPython kernel and packages
Linux
Base hardware library and API for the FPGA

For designers who want to extend the base system by contributing new hardware libraries, Xilinx Vivado WebPACK tools are available free of cost.

Features

ZYNQ XC7Z020-1CLG400C:
- 650MHz dual-core Cortex-A9 processor
- DDR3 memory controller with 8 DMA channels and 4 high performance AXI3 slave ports
- High-bandwidth peripheral controllers: 1G Ethernet, USB 2.0, SDIO
- Low-bandwidth peripheral controller: SPI, UART, CAN, I2C
- Programmable from JTAG, Quad-SPI flash, and microSD card
- Artix-7 family programmable logic
  - 13,300 logic slices, each with four 6-input LUTs and 8 flip-flops
  - 630 KB of fast block RAM
  - 4 clock management tiles, each with a phase-locked loop (PLL) and mixed-mode clock manager (MMCM)
  - 220 DSP slices
  - On-chip analog-to-digital converter (XADC)
Memory:
- 512MB DDR3 with 16-bit bus @ 1050Mbps
- 16MB Quad-SPI Flash with factory programmed globally unique identifier (48-bit EUI-48/64™ compatible).
- MicroSD slot
Power:
- Powered from USB or any 7V-15V source (see recommended products)
USB and Ethernet:
- USB-JTAG Programming circuitry
- USB-UART bridge
- USB OTG PHY (supports host only)
- Gigabit Ethernet PHY
Audio and Video:
- Electret microphone with pulse density modulated (PDM) output
- 3.5mm mono audio output jack, pulse-width modulated (PWM) format
- HDMI sink port (input)
- HDMI source port (output)
Switches, push-buttons, and LEDs:
- 4 push-buttons
- 2 slide switches
- 4 LEDs
- 2 RGB LEDs
Expansion Connectors:
- Two standard Pmod ports
  - 16 Total FPGA I/O
- Arduino/chipKIT Shield connector
  - 49 Total FPGA I/O
  - 6 Single-ended 0-3.3V Analog inputs to XADC
  - 4 Differential 0-1.0V Analog inputs to XADC

To find out more about PYNQ, please see the project webpage at www.pynq.io. Here you will find materials to help you get started and a forum for contacting the supporting community.

4DSystems – Diablo16- and Picaso-based LCD modules

Posted on 8 March, 20198 March, 2019 by mixos

RS Components, a global multi-channel provider of industrial and electronic products and solutions, has introduced the Gen4 Series of integrated TFT LCD modules and related starter packs from embedded graphics specialist 4D Systems. Gen4 display modules are designed for ease of integration and use by electronics design engineers developing touch screen interfaces, achieving high functionality with a limited space requirement. Gen4 Series LCD modules are powered by either a Diablo16 or a Picaso GPU, both manufactured by 4D Systems and incorporating advanced graphics functionality. The displays come in a number of sizes from 2.4″ (240 x 320 pixels) up to 7.0″ (800 x 480 pixels). Resistive and capacitive touch screen options are available, and RS can also offer non-touch-sensitive versions.

Each module incorporates a 30-pin ZIF (zero insertion force) FFC (flexible flat cable) socket for easy connection to an application or motherboard, or to peripheral boards providing additional functionality. An onboard microSD memory card connector allows for multimedia storage and data logging, while a dedicated PWM audio pin enables sound generation via an external amplifier.

The Gen4 Series is fully compatible with the 4D Systems Workshop4 IDE, which offers a choice of four development environments: Designer, for programming in native 4DGL (4D Graphics Language) code; ViSi, providing drag-and-drop object placement to aid 4DGL code generation, and allowing the developer to visualise how the display will look when in use; the fully object oriented ViSi-Genie, which performs all 4DGL coding automatically; and a Serial mode that allows the Gen4 module to be controlled from a host device with a serial port.

As a space-saving measure, all display related circuitry in Gen4 Series modules is recessed into the plastic mounting base. A pre-installed cover lens bezel (CLB) option — a glass cover with overhanging edges — allows the display to be mounted flush within a panel or enclosure using double-sided adhesive tape on the overhanging glass, without the need for any mounting hardware.

For first-time 4D Systems users, RS recommends the Gen4 Starter Kit range, which bundles all hardware required to get up and running. Starter kits typically include a Gen4 display module, an interface module, a programming adaptor, a 4 Gbyte microSD card, a 5-way cable for easy connection to a breadboard or host, a 150 mm 30-way FFC and a quick start guide.

The 4D Systems Gen4 Series is shipping now from RS.

CUI’s MEMS Microphones deliver enhanced audio quality

Posted on 7 March, 20197 March, 2019 by mixos

CUI’s analog and digital MEMS microphones deliver enhanced audio quality in extremely compact packages.

CUI’s MEMS microphones provide users with improved audio quality and performance in compact, low-profile packages as small as 2.75 mm x 1.85 mm x 0.95 mm. Featuring sensitivity ratings from -44 dB up to -26 dB, signal-to-noise ratios from 57 dBA up to 65 dBA, and sensitivity tolerances as low as ±1 dB, these MEMS microphones are ideal for a range of portable consumer electronics applications.

Features

Compact sizes as small as 2.75 mm x 1.85 mm
Depths as low as 0.95 mm
Analog and digital pulse density modulation (PDM) output types
Sensitivity ratings from -44 dB ~ -26 dB
Sensitivity tolerances as low as ±1 dB
Signal-to-noise ratios from 57 dBA ~ 65 dBA
Current consumption as low as 80 µA
300 Ω output impedance rating
Top port and bottom port versions

more information: www.oemsecrets.com & www.digikey.com

BeagleBone SBC features dual Cortex-A15 Soc and AI support

Posted on 7 March, 20197 March, 2019 by Tope Oluyemi

Open source community BeagleBoard.org has announced their BeagleBone AI SBC which features a dual Cortex-A15 TI AM5729 SoC that enables AI support via dual C66x DSPs and 4x EVE cores. The SBC comes with 1GB RAM, 16GB eMMC, WiFi, and GbE. The SoC includes four powerhouse embedded-vision-engine (EVE) cores with AI capabilities. BeagleBoard.org’s limited product page says the SoC can run AI code on its dual TI C66x DSPs and the four new EVE cores.

The AI-enabled chips are supported via an optimized TIDL machine learning OpenCL API with pre-installed tools, says the open source project.

BeagleBoard claims that the calculations for computer-vision models on the AM5729 run at 8x times the performance per watt in comparison to the EVE-less AM5728. The EVE cores were designed by TI for automotive vision applications via a Vision AcclerationPac architecture. BeagleBoard does not provide any clock rate for the AM5729’s dual -A15 cores, but judging from the AM5728 which clocks at 1.5GHz, the AM5729 might clock around 1.5GHz also. The SoC also features a PowerVR SGX544 3D GPU and Vivante GC320 Core 2D accelerator.

Built on the proven BeagleBoard.org open source Linux approach, BeagleBone AI fills the gap between small SBCs and more powerful industrial computers. Based on the Texas Instruments AM5729, developers have access to the powerful SoC with the ease of BeagleBone Black header and mechanical compatibility. BeagleBone AI makes it easy to explore how artificial intelligence (AI) can be used in everyday life via the TI C66x digital-signal-processor (DSP) cores and embedded-vision-engine (EVE) cores supported through an optimized TIDL machine learning OpenCL API with pre-installed tools. Focused on everyday automation in industrial, commercial and home applications.

Feature highlights

BeagleBone Black mechanical and header compatibility
TI AM5729 processor featuring 4 PRUs and 4 EVEs
1GB RAM and 16GB on-board eMMC flash with high-speed interface
USB type-C for power and superspeed dual-role controller; and USB type-A host
Gigabit Ethernet and high-speed WiFi
Zero-download out-of-box software experience

Just like the other BeagleBone SBC variants, the AM5729 has 4x programmable, real-time PRU cores. The AI SBC’s RAM is increased to 1GB and the eMMC storage is increased to 16GB compared to the BB Black. The board offers GbE and high-speed WiFi. It is also further equipped with a USB Type-A port and a USB Type-C port, which enables power and superspeed dual-role controller. According to BeagleBoard.org. The BeagleBone AI will offer BeagleBone Black header and mechanical compatibility, as well as a “zero-download out-of-box software experience.”

TI Vision AcclerationPac architecture with EVE cores

The SBC will likely continue to run Linux and will ship with open specifications. BeagleBoard.org. Says the SBC is aimed at “everyday automation in industrial, commercial and home applications.” Information on pricing and availability are unknown for the BeagleBone AI, but you can sign up for notifications at the BeagleBone AI product page.

More AI! 🤖📸🦴✨ pic.twitter.com/2OklS7klUY

— Drew Fustini (@pdp7) 27 Φεβρουαρίου 2019

ATtiny85 Thermocouple Thermometer measures up to +1350°C

Posted on 7 March, 2019 by mixos

This project describes a thermocouple thermometer, capable of measuring temperatures up to +1350°C, using just an ATtiny85 and an OLED display. by David Johnson-Davies @ technoblogy.com

It uses the ATtiny85’s analogue-to-digital converter with a x20 gain option to measure the thermocouple voltage, and the internal temperature sensor to measure the ambient temperature (shown on the bottom line of the display), and it gives readings accurate to better than 5°C. Some possible applications include a cooking thermometer, a soldering-iron temperature monitor, or a wood burning stove temperature display.

ATtiny85 Thermocouple Thermometer measures up to +1350°C – [Link]

Getting Started with a PIC16 programming

Posted on 7 March, 20197 March, 2019 by mixos

Getting Started with a PIC16, Specifically, a PIC16f18326, by Mattia Maldini @ medium.com:

Today I’m going to make a quick tutorial on how to program a bare PIC16, specifically the PIC16f18326. No demo boards and no USB cable, just the MCU, a breadboard and a dedicated programmer.

One of the main reasons for this tutorial is the new MPLAB SNAP programmer. Up until about a year ago the cheapest option to program a PIC device was the PicKit3, sitting at the abundant price of ~40 Euros — far from the typical budget for an hobbist to get started. The SNAP finally fills that hole by coming as cheap as 13 Euros while keeping most of the functionality. It’s still pricey when compared to low-end options from competitors (I’m thinking about the 2 Euros ST-Link programmers), but an improvement nonetheless. You can grab one from Microchip’s official store.

Getting Started with a PIC16 programming – [Link]

Arduino IoT Cloud Public Beta Version brings new opportunities

Posted on 6 March, 20197 March, 2019 by Ayo Ayibiowu

Arduino has never ceased to impress everyone, and recently have launched the Beta version of their IoT cloud that brings in more awesomeness. The beta version brings autonomy to the Arduino and Makers ecosystem. Now, the connection between an Arduino board and cloud is no more dependent upon services like “ThingSpeak”, “Thinger.io” and several others.

The Arduino IoT Cloud is a simple and quite powerful Internet of Things platform. It makes it very simple for anyone to develop and manage IoT applications – freeing us from the most complex tasks and enabling us to focus on solving real problems in our business or everyday life. Built-in Arduino cloud services compatibility makes it aligned for all the processing you can think of. Data transfer from a board to the cloud has never been that much safe, especially when working with other less known and trustworthy platforms. With Arduino IoT platform, you don’t have to worry about that.

Another exciting feature of the new platform is the “auto-sketching“. Previously, you had to write a sketch program and upload it on the device to connect a board to the cloud, but this is a thing of the past. The Arduino IoT Cloud can do this for you, and it can quickly generate a sketch when setting things up. It frees you from the hectic work, and the device will be ready to run within 5 minutes, and of course, you can still add your own code. Arduino boards support HTTP REST API and MQTT. While as usual Command-Line Tools, Javascript, and Websockets are also integrated and supported.

What will the cloud offer?

Based on the Arduino environment familiar to millions of users
Build and deploy remote sensor monitoring using widgets
Connect to a spreadsheet, database, or automate alerts using webhooks
Devices secured using X.509 certificate-based authentication
Developers can create custom apps using Arduino IoT Cloud APIs
Based on open hardware and open IoT standards

While developing your own connected system, security is the utmost priority. To cope with it, X.509 certificate-based authentications are used. It is secure enough for all the data transferring through the system.

To get your started, create an account on Arduino loT cloud. Choose the board which you want to configure on the interface. For this purpose, you would need an Arduino MKR board. Afterward, follow the instructions and the rest of the process is easy. It will ask you to download a plugin for that. All the processes are performed under one interface.

Local connections are not a headache to Arduino these days. Regarding configurations you have vast of options. All of these are possible on the beta version of Arduino loT Cloud, which will soon be launched in full version.

Arduino now offers a complete platform with the MKR family providing a streamlined way to create local IoT nodes and edge devices using a range of connectivity options and compatibility with third-party hardware, gateway, and cloud systems. Whilst the Arduino IoT Cloud allows users to manage, configure and connect not only Arduino hardware but the vast majority of Linux-based devices – truly democratizing IoT development.

— Massimo Banzi, Arduino CTO and Co-Founder

In past, users building connected applications had to get the hardware boards from one manufacturer and then get it connected to a cloud platform somewhere else. Updates which are supposed to solve issues, don’t always do that, but they could create compatibility issues. I once had a problem like that with PubNub platform, but this is gone now-days. One company offering all these functionalities, not only improves efficiency of development but also adds convenience.

Although all these sound like a promising concept, a question that creeps into me is – Is is a good idea if one organization to manage everything? is Arduino planning on becoming the Amazon of Hardware? Will over dependency on one platform be good for the maker’s community in the long run? Anyways, let’s enjoy the development for the time being.