Master Thesis: Detection of Activities of Daily Living (ADL) via Smart Meter Data

12.02.2024, Abschlussarbeiten, Bachelor- und Masterarbeiten

Smart meters allow us to visualize, analyze, and optimize the energy consumption of our homes to enable demand-response optimizations and identify appliance usage. Smart meters can also be used to detect activities of daily living (ADLs, meal preparation, and personal hygiene) in the home environment. This can be particularly beneficial for older adults, as typical daily routines and, importantly, deviations from typical behavior can be monitored remotely, allowing these individuals to remain independent in their homes longer.

The proposed master thesis focuses on the analysis of smart meter data (power and water consumption) in collaboration with Veli-Care (link). The goal is to develop a pattern recognition algorithm to detect typical ADLs such as meal preparation (oven/stove, microwave, refrigerator, water kettle, etc) and personal hygiene (flushing the toilet, shower use, other water consumption). As a first step, this should be done for individual ADLs in single-household settings and, ideally, expanded to interleaving ADLs and cohabitation settings in a second step.

• 1-2 master theses
• Applicants should have prior experience with data processing and analysis (Matlab, R, etc).
• If interested please contact: christoph.hoechsmann@tum.de and indicate why you are interested in this research project.

Kontakt: christoph.hoechsmann@tum.de