Imagine a world where your Nespresso machine knows when you’re running low on coffee and automatically orders more. Just think, no more painful mornings waking up to an empty Nespresso supply or those unbearable trips to the store to buy more. Meet NOM, the automated and self-aware Nespresso Ordering Machine.
Ok, perhaps we’re not sending rockets to the moon, but the concepts at work in this experiment are much larger than they appear, in fact it’s being dubbed the next industrial revolution. We’re talking about the Internet of Things – a world of connected and “smart” devices and appliances that communicate with each other over the Internet – and it’s not science fiction, it’s knocking down the door as we speak. The experts at IT research agency International Data Corporation are estimating 50 billion connected devices by 2020 with IoT solutions on track for a stratospheric $7.1 trillion (that’s trillion with a “T”) total addressable market.
Our in-house iOS expert Saül Baró took the lead on the NOM experiment along with a few other engineers that have a knack for Arduino and hardware projects. Now it gets a little technical from here on in so see if you can keep up.
The NOM system consists of an Arduino board, a weight sensor and a server-side application.
- The server-side application tracks the coffee supplies and, based on the parameters that we define, will automatically order more coffee whenever the specified conditions are met.
- This application will expose a REST API that any device will be able to consume to extend the system.
- The Arduino board sends updates to the server application using its network connection whenever there is a significant change on the weight sensor.
The steps of the NOM experiment are outlined as follows:
- Research the available Arduino boards and sensors, and select one or more to test.
- Once we have decided which model to use, we’ll start prototyping to validate if measuring weight alone will be enough or the task calls for an additional data set.
- If we can validate our hypothesis, we will develop the sensor+arduino product until we have a system that can send data to an external server application.
- From here, we will develop the server application and a basic back office dashboard so the user can set it up and modify their preferences.
- Then, we’ll implement the communication between the Arduino and the server application.
- Placing automated and recurring orders to Nespresso may be tricky because, as far as we know, Nespresso doesn’t have a public API, so we’ll likely have to build a workaround for this step in the process.
- Finally, we’ll house the system in a nice package. So far, we’re imagining a dispenser that can store all the coffee boxes as they arrive from the store with the sensor located on the bottom (see diagram below). Multiple dispensers can be stacked horizontally allowing for multiple coffee flavors to be tracked and ordered.
We are currently in Step 2 of the NOM experiment, and have decided to go with an Intel Galileo board that has the Arduino system, in addition to a x86 CPU that can run both Linux and Windows. This will be useful in future iterations of the project to setup the server application within the board itself.
Future versions of the NOM system may include a color sensor to determine the type of coffee we are tracking, swapping in an ultrasound sensor to replace the weight sensor, or using a different method to measure the amount of remaining coffee to support brands other than Nespresso.
In addition to entertainment and keeping us attuned to the latest technologies, we believe experiments like NOM keep our minds sharp as they push us outside of our comfort zone and force us to think creatively to discover new solutions. Furthermore, Mobile Jazz Experiments like this one help us create a culture of innovation and encourage proactive learning and discovery within our team, all of which is passed onto our current and future clients. If you want to learn more about the NOM project or other MJ Experiments, send an email to firstname.lastname@example.org.
Image credits: HTML coffee cup