Most of us have photos on our smartphones. Based on Gigaom’s research (2015), each person has about 630 photos stored in smartphone, and people take 150 new photos and 6 videos during a given month. These photos contain a number of memories: touching moments, beautiful things, unpleasant fragments, and enjoyable stories. They record the past and present. However, how many of us would revisit the photos again we took few months or years ago? Actually, photos are helpful for people to recall their happiness memories (Rubin, 2013), and positive memories can reduce the risk of mental illness such as depression (Harmelen, 2019). So, what I want to do is to alleviate negative emotions by retrieving positive memories from photos in smartphone. I formed this idea called DigPhoto.
Assume that user’s photos in mobile device have been stored in this machine. As you can see on the bottom of the poster, it is a rectangular machine with a screen on the top where has five emotion bars. Each one of it has a corresponding colour and a name on the surface. Based on user’s current emotion, he/she can place any items such as coins on the corresponding emotion bar. The weight of the items placed on the bar determines the intensity of the emotion. For instance, if a user feels depressed, then he can place something he has on the bar with depression. After that, all emotion bars would be invisible, and based on the selected emotion and its intensity, the filtered photos/videos (e.g. pleasant moments) would be displayed on the screen, and trying to reduce the feeling of the negative emotion. When his/her emotion is getting stable, he/she can gradually take out the items, and the style of the photos/videos would tend to be more relax and stable. Finally, the screen will back to the initial state after remove all items on the bar, which means user’s emotion becomes stable.
emotion memory photo