A Framework for Consistent Experimentation in AmI

Abstract

Developing algorithms for Ambient Intelligence (AmI) environments involves testing algorithms using both simulated environments and user data. This has been traditionally done with simulators. While there are several datasets for Ambient Intelligence most of them have do not have an open format and a way to use them easily afterwards. We implement a software framework on top of an existing hardware platform for writing AmI applications that can also export a data dump consisting of heterogeneous sensor data matching several criteria from an AmI lab. Researchers using this framework can easily write AmI applications on top of shared datasets and easily test several algorithms against each other using real-world-data, a previously impossible endeavour.