First demonstrated at Microsoft’s 2016 Ignite Conference in Atlanta, GA, the IoT Asset Management Starter Kit is a boiler plate project comprised of Node.js and Angular 2 that facilitates the quick development of an IoT project for Asset Management. The project brings all the necessary components – Azure IoT Hub, Stream Analytics, Heroku, MongoDB and Raspberry Pi 3 – together to build a working end-to-end IoT solution.

After a couple of weeks of writing copy, I’ve finally got the starter kit available in GitHub with instructions on how to configure and implement.  This blog post isn’t very long as much of the content is in the GitHub documentation – this post is really just an announcement.  You can view the GitHub project documentation here.


The list of prerequisites is pretty small.  You’ll need a hosting server, of course, and this can be either Azure or Heroku.  Regarding repositories, the application is designed to use a NoSQL database, so DocumentDB or MongoDB will suffice.  Then, there are a couple of key components in Azure for IoT messaging.  Finally, you’ll need a couple of Raspberry PI 3 Model B’s and a couple of iBeacon transmitters.  The instructions show you how to configure RadBeacon Dot‘s which are fairly inexpensive, very good quality and easy to configure.


The installation steps are included in the GitHub documentation.  Installation and initial configuration should really take no longer than 1-1.5 hours.  It’s fairly simple and straightforward.  The documentation covers some aspects of the architectural components so this is a great way to learn about IoT while configuring Azure for it at the same time.  You will need an Azure account to follow the tutorial, but the costs are very low.  Additionally, you can utilize Heroku and mLab for hosting the site and MongoDB, respectively, should you choose.


Configuring the web application, the Raspberry PI’s and the iBeacons is the simplest piece of the puzzle.  For the PI’s, you can either follow the instructions in the documentation or you can download and flash an SD card (8GB) with the pre-built image.  After updating a couple of lines in the source code – for both the website and the PI’s – with your specific connection strings, you should be ready to rock and roll.

Hope this helps you all.  Let me know if you have any questions.