M.Sc. Nancy Elhady
PhD candidate

Email: nancy.elhady@tum.de

PhD research project

Robust diagnosis for Ambient Assisted Living:

According to the World Health Organization, the world’s population percentage of people aged over 60 is expected to double in the next decades, it will increase from 12% in 2015 to 22% in 2050. Ambient Assisted Living (AAL) integrates sensors in an unobtrusive intelligent way that can track the health status of the elderly people at home and detect early signs of diseases by monitoring their Activities of Daily Living.

My research project aims to propose a reliable AAL system that is capable of monitoring the elderly people without being intrusive to their lives by implementing fault detection and isolation.

A fault in one of the sensors of the AAL could lead to misleading result in the activity recognition (false positives or negatives). This can have dramatic consequences to the health of the inhabitant in emergency situations thus a reliable system is needed.

Research interests:

• Machine learning
• Fault detection and isolation
• Fault-tolerant systems
• Discrete event systems