Bots in an IoT context

At ThingTank (@thingtankBE), we are constantly looking to expose IoT data in different ways. A chat bot can be a great way to ask for device measurements or even instruct devices to perform actions. In this post, I will describe a bot that gets air quality data for a meeting room with Slack.

I chose to write the bot in Node.js for simplicity reasons and publish it to Azure’s App Service. The basics about writing a bot with Node.js can be found in the documentation of Microsoft’s Bot Framework here: https://docs.botframework.com/en-us/node/builder/overview.

Our bot is really simple for now. After getting the basics up and running, the bot can be enhanced with a natural language interface. What we want to do now:

• Set the room name and save it in the session (UserData)
• Change the room name and save it in the session
• Simple help: list the commands you can use
• Get air quality measurements (a subset)

To achieve the above, you use dialogs, intents and some simple regular expressions. Check out the source code to see how it is done (remember, this is a basic script to get it working at a minimum). The basic logic is as follows:

• If the intent is unknown, check if the room name is set. If not, switch to the /roomName dialog that asks for the room name and stores it in session.UserData
• if the intent matches commands, repond with a list of commands
• if the intent matches change room, switch to the /roomName dialog that asks for the room name
• if the intent matches air quality, get the measurements for the selected room using the getRoom function in an external module airq.js. Our real-time air quality data comes from a pubsub channel and the getRoom function just retrieves it from there

Writing an intent is very simple. The change room intent for instance:

intents.matches(/^change room/i, [
function (session) {
session.send(“Ok, let’s change the room name…”);
session.beginDialog(‘/roomName’);
},
function(session, results) {
session.send(‘Changed room to %s’, session.userData.roomName);
}
]);

If you look at the source code, you will see we use the Chat Connector. When you are writing your bot in the beginning, I recommend you use the ConsoleConnector instead. You can then simply run your bot with node .js and interact with it from the command line. In our case, we use the ChatConnector so you should use the Bot Framework Channel Emulator from here to interact with and test your bot.

To get the emulator working, you need to obtain an App Id and App Password from Microsoft and make sure you use those in both your bot source code and the emulator. In the source code, these two values come from environment variables.Note that for local testing, you can leave these values blank.

Now it’s time to publish the bot on the web so we can register it with Microsoft and then enable it on Slack. To publish the bot, use the instructions here. You will use the Azure CLI and git to make this work so be sure to install both on your machine. After the bot is installed and running on App Service, set the environment variables for App Id and App Password in the website properties. Next, you can test your bot using the Channel Emulator.

Important: when you test your bot in the cloud using the Channel Emulator, be sure to use ngrok as specified here: https://docs.botframework.com/en-us/tools/bot-framework-emulator/#using-the-emulator-with-ngrok-to-interact-with-your-bot-in-the-cloud.

Now we have the bot running, it’s time to register it with Microsoft at https://dev.botframework.com/bots/new. As part of the registration process, you need to supply the URL to your bot in the cloud and obtain a new App Id and App Password. Update the website settings with these new values. After registration, you get:

From the above page, you can test your bot and add other channels. One of those channels is Slack. When you add Slack as a channel, you will be guided to create an app in Slack, authenticate, and of course, create a Slack bot. In Slack, you will get something like:

To summarize:

• Creating a simple bot with the Bot Framework is easy; the fun starts when you want to enable things like natural language processing
• When you deploy you bot to the cloud and want to test it with the Channel Emulator, use ngrok
• When you want to deploy the bot to Slack, register the bot with Microsoft and simply add Slack as a channel