The document describes a prototype mobile and web application developed by VTT Technical Research Centre that utilizes context-based awareness cues to generate story-like status updates for social media platforms like Facebook and Twitter. It gathers contextual data from various sensors on a device and allows users to select context items for status updates, which are then stored in a semantic model for future recommendations. The application also aims to showcase collaborative context exchange among devices and explore machine learning possibilities through saved context data.

1. VTT TECHNICAL RESEARCH CENTRE OF FINLAND
www.vtt.fi
ContextCapture
Using Context-based Awareness Cues to Create Story-like Status Updates
Ville Antila (ville.antila@vtt.fi), Jussi Polet (jussi.polet@vtt.fi)
The prototype consists of a mobile application and a
web application, which is integrated with Facebook
and Twitter. The mobile application gathers context
data from the device itself, available sensors and
from nearby devices via Bluetooth. The sensed
context information is presented to the user along
with proposals for other descriptions, which have
been used to describe similar contexts earlier. After
selecting the context items and their abstractions, the
status update is sent to the server application, which
stores the received context data into a semantic
model and creates a story-like status update for
Facebook and / or Twitter.
Goals
The application demonstrates technical aspects
of collaborative context e.g. how the contextual
information can be exchanged between different
devices and used for UX-related testing issues.
Machine learning can be enabled by saving the
selected abstractions and associated raw data.
This will create a collectively created database of
context semantics that can be shared between
users. The stored data can be used for future
purposes, such as the basis for situation-aware
recommendations.
Context gathering Solution
The context recognition is based on different • mobile application and a related web applica-
sensors of activity such as : tion integrated with Facebook and Twitter
• the accelerometer • easy and fast addition of context-awareness
• ambient light sensor cues into status updates
• GPS data • pre- and user-defined context descriptions
• open applications on the device and five most used description recommenda-
• device system information tions
• nearby Bluetooth devices
• WLAN access points Cross-platform smartphone support :
• Android 2.2 +
Context descriptions are shown to the user based • MeeGo
on this data. • Symbian^3 (also Symbian S60 5th)