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Posts Tagged ‘cloud’

Renesas S5D9 IoT Fast Prototyping Board Combines Cortex M4F MCU, Sensors, and Ethernet

July 20th, 2017 No comments

Renesas S5D9 IoT Fast Prototyping board is a board designed – as its name implies – for the Internet of Things, with the company’s Synergy S5D9 ARM Cortex-M4F micro-controller, various sensors, various I/Os including protected digital inputs and outputs, and Ethernet for network connectivity instead of a Bluetooth or/and WiFi module.

Renesas S5D9 board specifications:

  • MCU – Renesas Synergy S5D9 ARM Cortex M4F MCU @120MHz with 2MB flash and 640KB SDRAM
  • Storage – 256Mbits (32MB) QSPI NOR flash
  • Connectivity – 1x 10/100Mbps Ethernet (RJ45)
  • USB – 1x micro USB Full Speed port
  • Sensors
    • Bosch BMC150 6-Axis sensor (digital compass)
    • AMS ENS210 environmental sensor for temperature and humidity data
    • TE Connectivity MS5637-02BA03 barometric pressure sensor
    • Knowles SPU0414HR5H-SB amplified SiSonic microphone
  • Expansion
    • 1x PMOD connector (SPI)
    • 2x Grove Connectors (UART, I2C, GPIO)
    • 2x Protected Digital Input (5.1V to 24V) + 2x Buffered Digital Output (up to 1A) via Molex 12 position header
    • 2x RS232 via Molex 8 position header and Intersil driver
  • Debugging – 10-pin JTAG connector
  • Misc – 5V/3V output jumper; 3x LEDs (Red, Yellow, Green)
  • Power Supply – 5V via micro USB port; ~300 mA @ 5V max power consumption
  • Dimensions – TBD

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The kit is supported by Renesas IoT Sandbox, which helps with the “IoT Fast Prototyping” part, as it allows the user to create IoT applications using “cloud services and real-time workflows by aggregating all event data from any source, whether it’s sensors, mobile apps, or an existing cloud, and performs real-time processing to extract intelligence or implement automation”. The board can also be programmed using the APIs in Renesas Synergy Software Package (SSP), Qualified Software Add-Ons (QSA), and Verified Software Add-Ons (VSA).

Data Monitoring in Renesas IoT Sandbox with pre-installed firmware – Click to Enlarge

You’ll find more technical details, example projects, and hardware design files in Seeed Studio Wiki, as well as IoTCommunity.io.

The board sells for $34.95 in Seeed Studio, but if you are part of IoTCommunity, you can get a $20 coupon bringing the price down to $14.95 + shipping.

MangOH Red Open Source Hardware Board Targets Cellular Industrial IoT Applications

June 14th, 2017 3 comments

Sierra Wireless has announced MangOH Red open source hardware platform designed for IIoT (Industrial IoT) applications with a snap-in socket for 2G to 4G & LTE-M/NB-IoT modules, built-in WiFi and Bluetooth, various sensors, a 26-pin expansion header, and more.

mangOH Red Board without CF3 / IoT Modules – Click to Enlarge

MangOH Red board specifications:

  • Snap-in socket to add any CF3-compatible modules, most of which based on Qualcomm MDM9215 ARM Cortex A5 processor including:
    • Airprime WP7502 LTE Cat 3, HSPA, WCDMA, EDGE/GPRS module
    • Airprime WP7504 LTE Cat 3, HSPA, WCDMA, CDMA module
    • Airprime WP7601 LTE Cat 4 module
    • Airprime WP7603 LTE Cat 4, WCDMA module
    • Airprime WP8548 HSPA, WCDMA, EDGE/GPRS, and GNSS module
    • AirPrime HL6528RD quad-band GSM/GPRS Embedded Wireless Module designed for the automotive market
    • And more….

      mangOH Red with CF3 Module, Shield, and IoT Module – Click to Enlarge

  • Storage – micro SD slot
  • Wireless MCU Module – Wi-Fi 802.11 b/g/n and Bluetooth 4.2 BLE module with an ARM Cortex-M4 core MCU (Mediatek MT7697) providing access to real-time I/Os
  • Wireless Connectivity “Accessories”
    • Micro SIM card holder; ESIM
    • Main, GNSS, & Diversity antennas connectors, and WiFi/Bluetooth chip antenna
  • USB – 1x USB 2.0 host port
  • Audio – 3.5mm audio jack (unpopulated)
  • Sensors – Bosch Sensortec Accelerometer, Gyroscope, Temperature and Pressure sensors, Light sensors
  • Expansion
    • 26-pin Raspberry Pi compatible connector
    • IoT Expansion Card slot to plug in any technology based on the IoT Connector open standard
    • 6-pin real-time I/O header controlled by WiFi/BLE module.
    • 6-pin low power I/O header
  • Debugging – 1x micro USB port for serial console
  • Misc – LEDs; reset and user buttons;
  • Power Supply – 5V via micro USB port; battery connector; power source jumpers

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mangOH Red hardware design is fully open source with BoM, schematics (PDF an Allegro/OrCAD), PCB Layout (Intercept Pantheon), Gerber, and mechanical files available for download in the resources section, where you’ll also find other documentation and getting started guides for users and developers.  The CF3 modules run Legato Linux developed by Sierra Wireless, and open source with the source code on Github. Code specific to MangOH Red + WP8548 was also upstreamed in Linux 4.10.

The company also offers Sierra Wireless Smart SIM with up to 100 MB free data, but you can use the board any commercially available SIM car. The board also supports AirVantage IoT Platform to create, deploy and manage solutions in the cloud.

MangOH Red board can be purchased as a bareboard, but most people will probably want to get a Starter Kit with MangOH Red plus Air Prime WP8548, WP7502 or WP7504 sold on Digikey. I’m very confused by the price list, as $99 is shown for both the bare board, and kits including the board and a CF3 module. So I’ll assume $99 is for mangOH board only, and you’d likely have to pay $200+ for a board plus a CF3 module with the total price depending on the selected module. You may find additional details on MangOH Red product page.

Amazon AWS Greengrass Brings Local Compute, Messaging, Data Caching & Sync to ARM & x86 Devices

June 8th, 2017 No comments

Amazon Web Services (AWS) provides cloud computing services to manage & store data from IoT Nodes over the Internet, but in some cases latency may be an issue, and Internet connectivity may not be reliable in all locations. AWS Greengrass provides a solution to those issues by running some of the IoT tasks within the local network in ARM or x86 edge gateways running Linux.

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You can still manage your devices from AWS cloud, but a Linux gateway running Greengrass Core runtime will be able to run AWS Lambda functions to perform tasks locally, keep device data in sync, and communicate with devices running AWS IoT Device SDK.

Greengrass benefits include:

  • Response to Local Events in Near Real-time
  • Offline operation – Connected devices can operate with intermittent connectivity to the cloud, and synchronizes with AWS IoT once it is restored
  • Secure Communication  – AWS Greengrass authenticates and encrypts device data at all points of connection.
  • Simplified Device Programming with AWS Lambda – Greengrass execute Lambda functions locally, reducing the complexity of developing embedded software.
  • Reduce the Cost of Running IoT Applications – You can program filter device data locally, and only transmit the data you need to the cloud. This reduces the amount of raw data transmitted to the cloud and lowers cost

Greengrass Core’s minimum requirements are a 1GHz Processor with at least 128 MB, so it will run on most x86 products, as well as some ARM boards and devices, with Amazon recommending the following to get started quickly:

Greengrass Core works with Linux distributions with Linux 4.4.11+ or greater including Ubuntu 14.04 LTS, Debian Jessie, etc.. Canonical will also provide snap to easily install it on Ubuntu operating systems. Dependencies include SQLite 3 or greater, Python 2.7 or greater, Glibc 2.14, boto3 (latest), botocore (latest), OpenSSL 1.0.2 or greater, libseccomp and bash. You’ll find more detailed requirements in the FAQ.

Amazon’s announcement today was about AWG GreeenGrass availability to all customers, but it has already been used successfully in the industry by customers such as Enel, the largest utility in Europe, Konecranes now having 15,000 connected cranes, Pentair plc for their aquaculture customers, and Rio Tinto mining group to improve management and safety of their truck fleet.

Greengrass is free to try for one year with up to 3 devices, and costs $0.16 per month or $1.49 per year per device for up to 10,000 devices. If you are going to manage more than 10,000 devices you’d have to contact Amazon for pricing options. You can find more info and get started on Amazon Greengrass page.

 

Top Programming Languages & Operating Systems for the Internet of Things

May 19th, 2017 3 comments

The Eclipse foundation has recently done its IoT Developer Survey answered by 713 developers, where they asked  IoT programming languages, cloud platforms, IoT operating systems, messaging protocols (MQTT, HTTP), IoT hardware architectures and more.  The results have now been published. So let’s have a look at some of the slides, especially with regards to programming languages and operating systems bearing in mind that IoT is a general terms that may apply to sensors, gateways and the cloud, so the survey correctly separated languages for different segments of the IoT ecosystem.

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C and C++ are still the preferred languages for constrained devices, and developers are normally using more than one language as the total is well over 100%.

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IoT gateways are more powerful and resourceful (memory/storage) hardware, so it’s no surprise higher level languages like Java and Python join C and C++, with Java being the most used language with 40.8% of respondents.

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When it comes to the cloud with virtually unlimited resources, and no need to interface with hardware in most cases, higher level languages like Java, JavaScript, Node.js, and Python take the lead.

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When it comes to operating systems in constrained IoT devices, Linux takes the lead with 44.1%, in front of bare metal (27.6%) and FreeRTOS (15.0 %). Windows is also there in fourth place probably with a mix of Windows IoT core, Windows Embedded, and WinCE.

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Linux is the king of IoT gateways with 66.9% of respondent using it far ahead of Windows in second place with 20.5%. They have no chart for the cloud, probably because users just don’t run their own Cloud servers, but relies on providers. They did ask specifically about the Linux distributions used for IoT projects, and the results are a bit surprising with Raspbian taking the lead with 45.5%, with Ubuntu Core following closely at 44.4%.

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Maybe Raspbian has been used during the prototyping phase or for evaluation, as most developers (84%) have been using cheap development boards like Arduino, BeagleBone or Raspberry Pi. 20% also claim to have deployed such boards in IoT solutions.

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That’s only a few slides of the survey results, and you’ll find more details about Intel/ARM hardware share, messaging & industrial protocols, cloud solutions, wireless connectivity, and more in the slides below.

Via Ubuntu Insights

Banana Pi BPI-M64 Board Gets Allwinner R18 Processor with Google Cloud IoT Core Support

May 18th, 2017 30 comments

Banana Pi BPI-M64 board was launched with Allwinner A64 processor, but a few days ago, I noticed the board got an option for Allwinner R18. Both processors are likely very similar since they are pin-to-pin compatible, and Pine64 was first seen with Allwinner R18, so I did not really feel it was newsworthy. But today, Google announced Google Cloud IoT Core cloud service working with a few app partners such as Helium and Losant, as well as several device partners including ARM, Marvell, Microchip, Mongoose OS, NXP… and Allwinner, having just announced the release of an Allwinner R18 SDK with libraries supporting Google Cloud IoT Core.

Let’s go through the board specifications first which are exactly the same as for the original BPI-M64 board, except for the processor:

  • SoC – Allwinner R18 quad core ARM Cortex A53 processor with Mali-400MP2 GPU
  • System Memory – 2GB DDR3
  • Storage – 8GB eMMC flash (16, 32 and 64GB options), micro SD slot up to 256 GB
  • Video Output / Display interface – HDMI 1.4 up to 4K resolution @ 30 Hz, MIPI DSI interface
  • Audio – HDMI, 3.5 mm headphone jack, built-in microphone
  • Connectivity – Gigabit Ethernet + 802.11 b/g/n WiFi & Bluetooth 4.0 (AP6212)
  • USB – 2x USB 2.0 host ports, 1x micro USB OTG port
  • Camera – MIPI CSI interface (which I guess you support parallel cameras via some kind of bridge)
  • Security – Hardware security enables ARM TrustZone, Digital Rights Management (DRM), information encryption/decryption, secure boot, secure JTAG and secure efuse
  • Expansion – 40-pin Raspberry Pi 2 somewhat-compatible header
  • Debugging – 3-pin UART header
  • Misc – IR receiver; U-boot, reset and power buttons;
  • Power – 5V via power barrel; 3.7V Lithium battery header; AXP803 PMIC

So from hardware perspective, there’s no advantage of getting the board with the new R18 processor. But the SDKs are somehow different, and based on Allwinner’s press release, only R18 processor gets Google Cloud IoT Core support.

Cloud IoT Core Overview

Some of the key benefits of Cloud IoT Core include:

  • End-to-end security – Enable end-to-end security using certificate-based authentication and TLS; devices running Android Things or ones supporting the Cloud IoT Core security requirements can deliver full stack security.
  • Out-of-box data Insights – Use downstream analytic systems by integrating with Google Big Data Analytics and ML services.
  • Serverless infrastructure: Scale instantly without limits using horizontal scaling on Google’s serverless platform.
  • Role-level data control – Apply IAM roles to devices to control access to devices and data.
  • Automatic device deployment – Use REST APIs to automatically manage the registration, deployment and operation of devices at scale.

Both Foxconn/SinoVoIP and Pine64 can offer Allwinner R18 platforms compatible with Google Cloud IoT Core via their Banana Pi BPI-M64 and Pine A64+ boards respectively.

ESP8266, Mongoose OS & Grove Sensors – An Alternative Solution for Hackathons

April 12th, 2017 5 comments

CNXSoft: This is a guest post by Cesanta

If you walked into any Hardware hackathon over the last year, you would see they are about innovation and bringing new ideas to this world and most of them are centered around the connected devices nowadays. However, just walk the floor, talk to the teams and you can quickly see an elephant in the room. The Hackathons are about connected devices, but with the ‘recommended’ and frequently sponsored hardware distributed to the teams such as Intel Galileo, Raspberry Pi, etc…. developers may struggle for a long time to even connect it to the cloud!

Not to mention the innovation is usually hindered by a tedious environment setup which takes hours, things to learn about the specific hardware and how it can be programmed using low level languages. So many teams spent most of the time fighting with those issues and oftentimes still do not have their prototype ready and connected by the end of hackathon.

This situation can be improved by using ESP8266 boards with Mongoose OS and SeeedStudio Grove Sensors. The solution brings the following benefits:

  1. Low price:
    • ESP8266 development board is $4-15 depending on the board;
    • Seeed Studio Sensors are priced  $3 to $15 each, but you can also save by purchase them as a part of Grove Starter Kit for $39.
  2. The solution is solderless & plug and play – so anyone can actually use it fast.
  3. With Mongoose OS the firmware logic can be coded within few minutes using JavaScript code
  4. The data can be pushed to any cloud or public MQTT server such as Mosquitto, HiveMQ, AWS IoT, etc…

Let’s jump into the action and get ESP8266 & Seeed Light Sensor up and running with Mongoose OS in a few minutes. This example below shows how to get the hardware (sensor) data and send it to the cloud.

  1. Get your ESP8266 (e.g. NodeMCU) and Seeedstudio Light Sensor and Button ready.
  2. Download and install mOS tool for Mongoose OS. This works in Linux, Mac OS X, or Windows operating systems
  3. Connect the hardware
    • Power the Grove base shield: connect GND and VCC pins to the NodeMCU GND and VCC pins
    • Connect light sensor to slot 7 on the Grove base shield
    • Connect slot 7 to the ADC pin on the NodeMCU board
    • Connect NodeMCU board to your computer
  4. Program the board to retrieve the light sensor data and send it to the cloud (HiveMQ in this example)
    • Start mos tool, switch to the prototyping mode, edit init.js file
    • Click ‘Save and reboot device”
  5. Go to http://www.hivemq.com/demos/websocket-client/, connect and subscribe to the topic “my/topic”
  6. Press a button and see how light sensor reading is sent to the MQTT server

Light Sensor Data Shown on HiveMQ Dashboard – Click to Enlarge

Now you can see how easy it was! Want to play with other Seedstudio sensors from Grove Kits? Check video tutorials for button, motion sensor, moisture sensor, UV sensor, relay, buzzer, etc… including the one below with the light sensor.

Canonical Refocuses Ubuntu Development Efforts on Cloud and IoT, Drops Convergence and Mobile

April 6th, 2017 15 comments

Mark Shuttleworth has published a new blog post in Ubuntu Insights, and this is not all good news, as the title “Growing Ubuntu for Cloud and IoT, rather than Phone and convergence” implies. Canonical has decided to drop Unity8, and replace it with Gnome in Ubuntu 18.04, and by extension stop any investment in Ubuntu phone and convergence.

The main reasons given for the drop were that few commercial partners were interested in the project, preferring to stick with the most popular mobile operating systems like Android, and the community did not see the work as innovation, but instead fragmentation, probably referring to the Mir vs Wayland saga.

On the better news, Canonical is still committed to work on Ubuntu desktop, and will focus on the Cloud and IoT applications such as automotive, robotics, networking, and machine learning, for which the company has gone well so far with multiple commercial partners.

The video below shows the work done so far on Unity8. Sadly it will never be used in a meaningful way.

Texas Instruments CC3200 WiFi SensorTag is Now Available for $40

March 15th, 2017 No comments

Texas Instruments launched SensorTag in 2013, and at the time there was just a Bluetooth 4.0 LE version with 6 different sensors. I bought one for $25 at the time, and tried it with a Raspberry Pi board and a BLE USB dongle. Since then, the company has launched a new multi standard model (CC2650STK) supporting Buetooth low energy, 6LoWPAN, and ZigBee, and has just started to take orders for CC3200 WiFi SensorTag for $39.99, which seems expensive in a world of $2 ESP8266 modules.

But let’s see what the kit has to offer:

  • Wireless MCU – Texas Instruments CC3200 SimpleLink ARM Cortex-M4 MCU @ up to 80 MHz, with up to 256KB RAM, Hardware Crypto Engine, DMA engine
  • Storage – 1 MB serial flash memory
  • Connectivity – 802.11 b/g/n WiFi with on-board inverted-F antenna with RF connector for conducted testing
  • Sensors – Gyroscope, accelerometer, compass, light sensor (OPT3001), humidity sensor (HDC1000), IR temperature sensor (TMP007), and pressure sensor (BMP280)
  • Expansion – 20-pin DevPack SKIN connector
  • Debugging – Debug and JTAG interface for flash programing
  • Misc – 2x buttons, 2x LEDs, reed relay MK24, digital microphone, and a buzzer for user interaction
  • Power – 2x AAA batteries good for up to 3 months (with 1 minute update interval)

So it has plenty of sensors to play with, and rather long battery life for a WiFi evaluation platform. The kit ships with one CC3200 WiFi SensorTag, two AAA batteries, and a getting started guide.

WiFi SensorTag Mobile App – Click to Enlarge

Resources includes hardware design files (schematics, PCB layout, BoM, etc..), iOS and Android apps and source code, IoT Device Monitor for Windows, Code Composer Studio, and cloud-based development tools. Note that there’s no embedded software for the Wi-Fi SensorTag, it is only a a demo platform, while you can modify cloud-based applications, you can’t modify the firmware. If you want an embedded development platform, you’d have to go with CC3200 LaunchPad board. You can still have some fun SensorTag using Android or iOS app, or connecting it to IBM Watson IoT Platform.

Visit SensorTag page for further information.