I. Introduction
A huge amount of personal data is generated in Ambient Assistant Living (AAL) and healthcare applications. Many different supporting techniques rely on data gathered from many different sensors for various purposes. E.g., while most fall detection algorithms [1] only base on data from the past few seconds, a fall risk assessment [2] may need data from a longer period of time, and when performing Activity of Daily Living (ADL) monitoring [3] nearly everything has to be stored for further processing and analyses.