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A set of applications for the mining of Activities of Daily Living
The recognition of Activities of Daily Living (ADL) has represented one of the most developed research areas in recent years. Its objective is to determine what daily activity is developed by the inhabitants of a smart environment. In this project, an ontology-based framework for the mining of ADL with a generic ontology and a modular architecture is proposed.
A mobile application to create accelerometer based activityrecognition models directly on the phone. The configuration of the segmentation and feature extraction process chain requires expert knownledge. The prototype was developed in 2012 in a bachelor thesis at the University of Kassel and was optimized and enhanced for an experiment in 2015.
SIMACT is a 3D smart home simulator for activityrecognition developped at LIARA during the summer 2009. The goal of SIMACT is to enable scientist to simulate execution sequence of activity inside a smart home to conduct their research.