ToDo - Voice Activated IoT RPi ToDo List
Today's Hardware Friday project is from Microsoft Azure MVP Herve Roggero and it's a great example of how a much of different technologies and services can be meshed to create something kind of cool...
Ever wanted to write a voice activated system on an IoT device to keep track of your “todo list”, hear your commands being played back, and have the system send you a text message with your todo list when it’s time to walk out the door? Well, I did. In this blog post, I will provide a high level overview of the technologies I used, why I used them, a few things I learned along the way, and partial code to assist with your learning curve if you decide to jump on this. I also had the pleasure of demonstrating this prototype at Microsoft’s Community Connections in Atlanta in front of my colleagues.
How It Works
I wanted to build a system using 2 Raspberry Pis (one running Windows 10 IoT Core, and another running Raspbian) that achieved the following objectives:
- Have 2 RPis that communicate through the Azure Service Bus
This was an objective of mine, not necessarily a requirement; the intent was to have two RPis running different Operating Systems communicate asynchronously without sharing the same network
- Learn about the Microsoft Speech Recognition SDK
I didn’t want to send data to the cloud for speech recognition; so I needed an SDK on the RPi to perform this function; I chose the Microsoft Speech Recognition SDK for this purpose
- Communicate to multiple cloud services without any SDK so that I could program the same way on Windows and Raspbian (Twilio, Azure Bus, Azure Table, SharePoint Online)
- I also wanted to minimize the learning curve of finding which SDK could run on a Windows 10 IoT Core, and Raspbian (Linux); so I used Enzo Unified to abstract the APIs and instead send simple HTTPS commands allowing me to have an SDK-less development environment (except for the Speech Recognition SDK). Seriously… go find an SDK for SharePoint Online for Raspbian and UWP (Windows 10 IoT Core).
The overall solution looks like this:
In order to achieve the above objectives, I used the following bill of materials:
Things to Know
Creating a prototype involving the above technologies will inevitably lead you to collect a few nuggets along the way. Here are a few. ...
How It Looks Like
A picture is worth a thousand words… so here is the complete setup:
Since this is an ongoing prototype I will not share the complete code at this time; however I will share a few key components/techniques I used to make this work.
This prototype demonstrated that while there were a few technical challenges along the way, it was relatively simple to build a speech recognition engine that can understand commands using Windows 10 IoT Core, .NET, and the Microsoft Speech Recognition SDK.
Further more, the intent of this project was also to demonstrate that Enzo Unified made it possible to code against multiple services without the need for an SDK on the client side regardless of the platform and the development language. Abstracting SDKs through simple HTTP calls makes it possible to access Twilio, SharePoint Online, Azure services and much more without any additional libraries on the client system.