The goal of the context-aware framework is to create an open, easy-to-use framework for application developers to retrieve information about the user's context. This context information includes low-level activites (walking, sitting, running, etc), places (home, work, travelling), nearby people (friends, strangers, etc) and more.
At present the project is in a research and data-collection phase. The applications presented below are intended to assist in gathering data which can be analysed to determine suitable algorithms and parameters to perform the detection necessary to correctly classify and extract context information. While they are published on the Android market and freely available to download, they do not provide any benefit to end users, so it is not anticipated that they will be widely used outside a small set of voluntary testers.
Issues, suggestions and feedback can be sent to me directly (either via the address published on the application's market page, or the details on my home page), or raised as issues on the project page over at GitHub.
Logs changes in accelerometer and magnetic field readings over a 50 second period. This data is combined with a user-supplied activity description, and uploaded for use in development, training and evaluation of an activity detection algorithm.
The application provides a link to a web-based portal where users can see a graph of their uploaded data, and the results of the activity detection algorithm will also be surfaced there.