Moodbox is a musical device created by a group of students (Iskra Uscumlic, Cyrus Kamath, Luca Mustacchi, Dario Loerke) to explore how we might set the mood in a studio space through music. They created it using Genuino Uno during the Interaction Design Programme at CIID with the help of Massimo Banzi and Dario Buzzini.

Moodbox enables you to set the perfect ambience and trigger different emotions:

Taking inspiration from the classic bar jukebox and its ability to influence the mood, we recognized that music and the atmosphere created by it are inextricably linked. When selecting a song to play in a social setting there is always a sense of negotiation involved. The person choosing has to consider the environment, the people around them, the current mood and that they would like to create.

With this in mind we set out to explore new opportunities for interaction in the communal space, using the environment of the studio as the setting.

As you can see in the video above, you can adjust the vibe of any space using four scales of emotions – from love to kill, serious to fun, chill to hype and dreamy to focus:

Emotions may be combined and fine-tuned with retro-style rotary knobs to dial-in feelings and get the perfect song choice. Like a jukebox, songs are queued once the selection is made. To provide visual feedback, lights also respond to the changes in mood, enhancing the overall influence on the space.

Moodbox connects to your iTunes account, with the rotary knobs sending information via a Genuino Uno and JavaScript to sort through a playlist. Our custom emotional algorithm then picks the right song and triggers mood lighting depending on the selection.

[Hunter] wanted to do something a bit more interesting for his holiday lights display last year. Rather than just animated lights, he wanted something that was driven by data. In this case, his display was based on the mood of people in his city. We’ve seen a very similar project in the past, but this one has a few notable differences.

The display runs off of an Arduino. [Hunter] is using an Ethernet shield to connect the Arduino to the Internet. It then monitors all of the latest tweets from users within a 15 mile radius of his area. The tweets are then forwarded to the Alchemy Sentiment API for analysis. The API uses various algorithms and detection methods to identify the overall sentiment within a body of text. [Hunter] is using it to determine the general mood indicated by the text of a given tweet.

Next [Hunter] needed a way to somehow display this information. He opted to use an LED strip. Since the range of sentiments is rather small, [Hunter] didn’t want to display the overall average sentiment. This value doesn’t change much over short periods of time, so it’s not very interesting to see. Instead, he plots the change made since the last sample. This results in a more obvious change to the LED display.

Another interesting thing to note about this project is that [Hunter] is using the snow in his yard to diffuse the light from the LEDs. He’s actually buried the strip under a layer of snow. This has the result of hiding the electronics, but blurring the light enough so you can’t see the individual LEDs. The effect is rather nice, and it’s something different to add to your holiday lights display. Be sure to check out the video below for a demonstration.