Hi!

Today in this blog post, I will demonstrate you how to get started with MXChip AZ3166 that will let you build cloud powered IoT application in minutes using Microsoft Azure Services.

First of all, we need to prepare the development environment which includes:

• Visual Studio Code.
• Arduino
• An active Microsoft Azure Account/subscription.
• MXChip AZ3166 for hardware use.
• Extensions for Visual Studio Code:
  -Arduino
  -Azure IoT Tools
  -Azure IoT Hub Toolkit
  -Azure  IoT Device Workbench

We also need to install ST-Link driver ( Uses for communication with development machine), and  Arduino:Board manager which we can find by pressing the F1 for command option and install AZ3166.

So, now as we have developed the lab environment, we will use Azure Portal to create a resource group and Azure IoT Hub to register our device.

To configure the device we need to plug the USB cable to IoT DevKit and a PC. Finally, we need to configure WiFi for our IoT DevKit internet  connectivity. We will hold down button B, push and release reset the button and then it displays the service set identifier (SSID) and a WiFi configuration IP address.

For the WiFi connectivity first we need to connect our IoT DevKit SSID to PC  and enter 192.168.0.1 in the browser, now we are ready to use our device.

Now lets build the project as IoT DevKit contains  loads of sample projects which we can use to connect  with the IoT DevKit and explore Azure services such as Cognitive Service etc.

So, in the first step we have to open Visual Studio Code and press F1 for the command palette and search for Azure  IoT Device Workbench:Open Example and then select IoT DevKit

Next step, in Azure  IoT Device Workbench page we have to find Get Started sample and download the sample code.

After we have downloaded the sample code we need to “Provision Azure Services” and we can do that by pressing F1 and write in a command palette Azure IoT Device Workbench:Provision Azure Services.

Now, as we have successfully provisioned, we have to select the serial port and a board which we can find in bottom-right page in Visual Studio Code, and that is where the ST-Link driver is being used.

In next step we need to configure the device connection string. We can do that by running the command Azure IoT Device Workbench:Configure Device Setting. We then select the configure Device Setting and we will see the following steps:

1-Configure Device Connection String
2-Select  IoT hub Device Connection String.

On hardware side, we need to configure and save the connection string, we have to hold down button A, push and release the reset button.

Now, we are ready to upload the device code and you can upload it by running the command in command palette by pressing F1 and type Azure IoT Device Workbench:Upload Device Code.

We can test the project by opening the serial monitor port and then serial monitor will start displaying the messages which were sent to IoT Hub.

We can also see the device messages on the IoT Hub we created as you can see below:

I hope you found this blog post helpful. If you have any questions, please feel free to contact me muhammad.ahmad@kaispe.com

The post Working with MxChip AZ3166 IoT DevKit-Part II appeared first on KAISPE.

First of all, we need to install the Visual Studio Code and Node JS to set up the Lab Environment. Then use the Azure subscription we have so we can create the Azure side of IoT components.

Afterward, we create a Resource Group and Azure IoT Hub service using Azure Portal.

Ok, now its time to set up the hardware and register it with IoT hub. For this post, we will be using Raspberry Pi 3. We need to install the OS Raspbian Jessie on our Raspberry Pi device.

To configure the connection string, I have used Visual Studio Code and make sure that my VS code uses the bash on Ubuntu (on Windows) shell in Integrated Terminal Panel. Below is the code snippet to get Raspberry Pi connected with IoT Hub:

After we build and run the code, we must be able to send messages from Raspberry Pi to Azure IoT Hub as you can see below:

Awesome! Now as you can see the IoT Hub shows messages and a connected device, which in this case is our Raspberry Pi.

Now let’s connect a Photocell Sensor with our IoT device, so we can get some real data from the device. For this scenario, we are using the Light Dependent Resistor (LDR).

We will give different manual inputs to the sensor, so we can have brightness data to analyze.

Finally, we get reading from the photocell sensor to the cloud. However, we receive continuous data in the cloud as the sensor keeps emitting brightness readings and we cannot just use it as is, so how to handle it? We will use Stream Analytics that makes it easier to set up real-time data computation.

In order to configure Stream Analytics, we need to configure Input, Output, and Query to get the required data. We will also create a Service bus queue for data storage and perform Stream Analytics on it.

Stream Analytics Input:

Events from a data source are called Input. So, we will create a Stream Analytics Job in which we can use one of the following sources as an input for the Job.

• Blob Storage
• IoT Hub
• Event Hub

In our Scenario, we are using IoT Hub. IoT Hub is used to collect data from connected devices and provide two-way communication between Cloud to Device and Device to Cloud.

Stream Analytics Output:

Stream Analytics job takes incoming data and converts it to a stream of Data Output events. The processed data can be used on real time dashboard, to generate alerts or for batch processing.

Now let’s create a Stream Analytics job. We can use one of the following sources as Output for the job.

• Azure Data Lake Store
• Azure SQL Database
• Blob Storage
• Event Hub
• Table Storage
• Service Bus Queue
• Service Bus Topic
• Azure Cosmos DB
• etc.

In our Scenario, we will use Service Bus Queue. It offers FIFO (First In First Out) method and scalable message structure.

Stream Analytics Query:

Now the final part of our Stream Analytics Job is Query where we will specify the logic of our Stream Analytics job. The good thing is Stream Analytics Query syntax is very similar to the Structured Query Language (SQL), so you can easily write the queries here.

Our Stream Analytics query is:

SELECT

    brightness

INTO

    [ServiceBusQueue]

FROM

    [Hub]

WHERE

    brightness > 5

If we now run the Stream Analytics job, it will only show the data where brightness is greater than 5 and filter out the rest of the output messages.

So, as you can see above, it shows 80 input events and 44 output events because of the filtering we have done using Stream Analytics query.

Next is we want to visualize the data using some kind of BI dashboard, so we can have better insights. For this purpose, let’s use Microsoft Power BI.

Following are the steps to create a Power BI dashboard:

• Create a dashboard using Power BI desktop application
• Add a Consumer Group to our IoT Hub. The consumer group is used by all applications to read data from Azure IoT hub
• Use the same Stream Analytics Job as we created above and have Power BI as the Output of job
• Once the above steps are completed, we can visualize Real-Time data into our dashboard

I hope you have found this blog post helpful. For any queries, please feel free to contact me farrukh.ahmed@kaispe.com.

The post Visualize Real-Time Device Data using Microsoft Azure IoT and Power BI Dashboard appeared first on KAISPE.

What is MxChip IoT DevKit AZ3166?

MxChip AZ3166 IoT DevKit allows you to develop and prototype Internet of Things (IoT) solutions using Microsoft services Azure.This IoT kit provides you intelligent and high quality smart hardware solution with latest Microsoft cloud services.

Why MxChip is more useful?

• This is the first Arduino compatible development device to optimize developer experience.
• The Kit is simple and easy to use.
• Makes it easier for developers to implement cloud integration on device side.
• Provides you the best security protection.
• It has most commonly used sensors like:
• Temperature
• Humidity
• Pressure
• Gyroscope
• Magnetometer
• Accelerometer
• It also has a Security IC which helps your Connection secure
• You can easily build an IoT application that integrates services like Azure IoT Hub and Cognitive Services.

MxChip Best Features

• Low power consumption wifi module
• High resolution 128 * 64 OLED which you can use for sensors readings, fun stuff like animated GIF
• Led lights
• Sensors (Temperature, humidity, motion (gyroscope, magnetometer, accelerometer)
• Security IC
• There are few built-in programmable buttons
• It also has an audio jack and a microphone and more

Why all in one?

This IoT DevKit offers a bunch of different components in one place that allows you to rapidly prototype and implement a solution idea. You can pretty much start programming immediately on this board without getting stressed out.

I hope you have got the basic understanding about the kit.

The post Working with MxChip AZ3166 IoT DevKit – Part I appeared first on KAISPE.

The Internet of Things is a Business Revolution enabled by technology and it is rightly called the next industrial era. It will impact Everything and Everyone in our business and everyday life.

The Internet of things is a network of internet-connected devices that communicate embedded sensor data for further processing in order to make intelligent decisions.

Why IoT?

IoT is not around just devices and data, it has been called the future extreme that can change many views of our lives. Machines are coming online. Smart Air Condition Systems that know you are at home or not? Refrigerators that can notify you if you are going low on foods. Smart Cities, Smart Buildings, Transportation with Smart Vehicles and many more.

Now let’s try to understand what make the devices as IoT devices. Typically, the IoT devices must have:

• Internet Access
• Intelligent Features
• On-Spot Indicators
• Configurable
• Weather Resistant
• Secure
• Ability to Communicate
• Can be Programmed
• Environmentally Flexible
• Can be Replaced

There might be plenty of other specific requirements but these are the basic ones an IoT device must have.

What is an IoT Solution?

The IoT Solution provides you efficient resource utilization as well as monitor natural resources, business resources, industrial resources, home appliances, etc. The IoT Solution reduce manual work because the devices communicate with each other and do plenty of tasks as far as we are concerned.

Probably the best approach to understand an IoT solution is to observe at how one might be used in a realistic scenario.

In the sections below, we will try to understand the concept of IoT using a hypothetical business scenario:

Problem Statement:

The city authorities want the area green and so urging people to maintain their lawns, however they also don’t want people to misuse water which is in limited supply during the summer time. They need an IoT solution to collect data in order to check how people actually use water in the lawns and will use that data to take the decision like how much water they should supply during the summer time.

Proposed IoT Solution:

For the purpose of collecting the data, the IoT solution provider selected 150 random houses across the city area and installed small water sensing devices in the lawns that will identify the amount of moisture in the soil and transmit the data over the Wi-Fi connection to a central cloud based solution to store and process the data.

Device Requirements for This Proposed Solution:

• Devices have to be small and unnoticeable
• Devices have to be capable to connect with Wi-Fi
• Devices have to be battery operated
• Devices have to be able to identify moisture in the soil using required sensors
• Devices have to be able to store data for a 12-hour period if the connection with the Wi-Fi router is lost
• Devices have to be able to provide an early failure signal

Again, there might be plenty of other device requirements but these are the basics the device must have in this hypothetical scenario.

Implementation of Devices:

The engineers visited each house that has agreed to install the device, placed the device in the garden at a designated place, established the connection to the Wi-Fi and tested the connection with the cloud service.

Gathering Data:

The device is programmed to collect moisture data every hour for a 12-hour period and a single average reading is sent to the cloud service for storage. The set of data includes the device Id, date/time stamp, soil moisture and other related information needed.

Cloud Service:

The engineers also developed a cloud based solution using Microsoft Azure IoT platform to collect, process and visualize the data coming from each device. The cloud service also gives attention for failure indications and can notify the engineers of a genuine or pending device failure. The Azure IoT solution has an IoT Gateway that handles back and forth communication with the devices and manages individual device identification. The solution also includes a data storage, job to process the device data and a dashboard developed using Microsoft Power BI to visualize the processed data and get insights for decision making.

Conclusion:

In this scenario, the authorities were able to use the collected data using an IoT solution to find out typical usage of water in lawns. They were able to analyze the data by getting better insights using Microsoft Power BI dashboard. Finally, they were able to supply the water as per the requirements of that area and hence saved money and resources to effectively use them in other operations.

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