Titulo Estágio
Activity Recognition @ Home
Área Tecnológica
Reconhecimento de Padrões
Local do Estágio
DEI - Departamento de Engenharia Informática
Enquadramento
The increase of elderly population has promoted the study and investigation on technology able to support the stay, well-being and autonomy of these individuals at their home. The sensing technologies existing in a Smart Home promote the concept of Ambient Assisted Living and are a useful tool for health monitoring and assistance to individuals with diseases as Alzheimer, for life style analysis and behavior mining. In this context, the recognition of daily living activities appears as requirement either to improve the interaction with the home or to send alerts to the caregivers.
Objetivo
The main goal of this work is to design an activity recognition algorithm to classify accurately as possible activities of daily living. For this purpose, the aim is to design an appropriate combination of classifiers using genetic algorithms to achieve the best performance in the real data sets CASAS.
Plano de Trabalhos - Semestre 1
1) State of the art revision: Sep-Oct 2013
2) Feature extraction and feature selection methods will be studied and preliminary tests done for the model being developed: Nov-Dec 2013
3) Empirical experimentation and analysis of results: Jan 2013
4) Intermediate report and plan of possible extensions or alternatives: Jan 2013
Plano de Trabalhos - Semestre 2
1) Model Ensemble Classification proposal and implementation: Feb-May 2013
2) Empirical Experimentation and Validation: Mar-May 2013
3) MSc thesis writing: May-Jun 2013
Condições
Strong skills in programming (Matlab, Java, Python, C/C++).
Other interesting (optional) skills/interests include Machine Learning and Pattern Recognition
Observações
The candidate curriculum is required.
Orientador
Bernardete Ribeiro e Marisa Figueiredo
bribeiro@dei.uc.pt 📩