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by Laura Bennett, Bradon Kanyid, Romeo Kienzler | Published August 29, 2017
Experts predict there will be over 20 billion IoT devices in the world by 2020, with a large percentage of those devices being located in our own homes. This developer journey will give you a head start on developing connected devices in the home. Using Node-RED and Watson IoT APIs, you’ll learn how to build a cognitive IoT application that detects irregularities in the voltage of your connected household devices.
The Internet of Things is now a reality, and according to a quick Google search, experts are predicting that at least 20 billion devices will be connected by 2020. Regardless of the type of development you do, whether enterprise systems or mobile games, you’ll be required to know how to connect a device — any device — to the wider IoT ecosystem.
Beyond adding to the sheer number of connected devices, IoT developers will also require an understanding of cognitive computing. Can your app take the inputs it’s given and learn from that data?
So, where do you start? Right here. This code pattern takes you through the process of building a cognitive IoT application. Your app will learn at the edge of your network; that is, you’ll push computing away from a cloud or data center towards the sensors that are receiving the input. Computations happen at the gateway, close to the sensors and actors (and they can take place even closer to the edge, on a microcontroller between the gateway and the sensors and actors).
In this code pattern, you’ll use the cloud to detect anomalies in a device familiar to everyone, your washing machine. Now, you might think it’s not that exciting to monitor your washing machine, but imagine what happens when you wash in hot water by mistake. There’ll be some excitement when your red towels turn your whole wardrobe pink. Or worse, what if the washer is running too fast? You certainly will get agitated if you have to replace a burned-out motor. And you’ll also be a little bit poorer.
Let’s assume that you have a washing machine with three sensors:
You can easily build an app that communicates with those sensors. When a sensor picks up instability, your app sends a command to deactivate. Additionally, you’ll be able to save and store data to perform batch analytics overnight. A machine-learning algorithm on the edge gateway can optimize the results and proactively notice, for example, the temperature is rising at a rapid rate. You can then deactivate the machine and send a service notification before a major catastrophe occurs.
You can see where this is going. Any developer who can write code that will save homeowners real money will be in demand. Complete this code pattern, learn to create valuable cognitive IoT applications, and keep your skills — and laundry — fresh.
Ready to put this code pattern to use? Complete details on how to get started running and using this application are in the README.
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