MPE SS 2018: Student projects

Last semester’s design task of the Mobile (App) Prototyping and Evaluation (MPE) lecture at DECO was to create, prototype and evaluate innovative applications and solutions for improving the personal use of big data for individual users by utilising the theoretical concept of unlimited availability of big data, themed “Turning Big Data into Small Data”.

Three teams of two to four students completed the seminar, resulting in creative, useful and innovative applications. We proudly present the mobile application concepts of our participating student teams:

StableMatch – a location-sensitive social dating app for matching persons close to each other based on their personal preferences retrieved from various data sources like social networks

RunningGroceries – an educational app supporting users with the managing of their groceries and tracking of the corresponding expiration dates by giving insights and statistics regarding the behaviour (like wasting food) combined with big data

DejaVu – an app that aggregates a user’s personal data from various sources like social networks to highlight the best experiences and moments in a customisable timeline

StableMatch

Aniela Gratz, Florian Hochreiter, Benjamin-A. Ottersbach, Filip Pantovic

Description: “StableMatch helps you to find exciting people in the area with the same interests as you. Our smart algorithms will match hobbies, opinions, positive but also negative attributes that make you compatible with a certain someone. These attributes are collected from your social feeds like Facebook, Xing, Spotify and many more. Over are the days of meaningless encounters arranged via other apps solely based on superficial features like a cleavage or six-pack.

Once you allowed StableMatch to get access to your personal networks and create a profile you are ready to go. Enable GPS-based tracking, see clouds of interesting people clustered into a heatmap in the main map view and get matched or find matches. The person with the higher threshold (person A, threshold ie. 90%) may contact the one with the lower threshold (person B, i.e. 89%) when the matching coefficient is reached or surpassed (i.e. 91%). The decision for contacting person B can be based upon the additional information presented which are specific common factors.

Contacting is done by person A sending a picture to person B. At this point the app experience turns into a little hide and seek game, being matched to another person during this period is not possible. Matches are in the same area (about 25-100m) but not immediately next to one another. The image sent should contain features of person A’s surrounding or could be a selfie. Each person’s location is known by the app but not shown to the users for privacy reasons. However, the app will show the approximate distance between each other and is updated constantly.

Once the users are close enough they may close the app and engage into a real world conversation about the common interest like a certain band, french literature or YuGiOh.”

StableMatchStableMatch

Watch a short video of StableMatch on youtube (German).

RunningGroceries

Ulrike Oberndorfer, Patrick Rudigier, Michael Tischler

Description: “RunningGroceries is an app about the daily use of groceries. With RunningGroceries it is possible to have a quick overview of the user’s own food. The user needs to scan the QR-Code from a receipt to get the needed information about his groceries. The app then reminds the user, if his food gets out of date and reminds him to use it before it’s wasted. The app contains statistics about the users behaviour, like categories of food he wastes a lot or how much he spends on food that goes to waste. It as well provides a sharing function to share food that is no longer needed by the user or which can be used if the user needs some food of others.”

RunningGroceriesRunningGroceries

Watch a short video of RunningGroceries on youtube (German).

DejaVu

Nenad Steric, Michael Winsauer

Description: “DejaVu is an app that gathers data from multiple sources and displays them in a timeline. The data might be sourced from local storage, like pictures, or from external social media feeds such as Facebook, Instagram or Twitter. The app uses public information, e.g. Tweets and public profiles. Additionally, it’s possible to add your own social media accounts. It parses events from your data and displays the events that are most relevant to you. There are several views for this data – the main view which displays these events in chronological order and groups them by year, month, week or day. An event has also a detail view where all the entries belonging to it are shown on one page.”

DejaVuDejaVu

Watch a short video of DejaVu on youtube.