Matching smart home data exploitation results with users' real behaviour

Teachers: 
Julien Nembrini
Agnes Lisowska
Denis Lalanne
Project status: 
Open
Year: 
2017

Home-based digital devices increasingly record data and send it to cloud services (vacuum robot data for sale). Beyond the obvious privacy problem, there are open questions of how this data matches with the self-representation users have of their own behaviour, or even the degree to which the interpretation of the data faithfully represents their actual behaviour.

In collaboration with a swiss startup which already equipped more than 2000 flats with smart home technology, the project will explore means to exploit the data generated by the occupants interacting with the smarthome application and appliances. Based on electricity, heating, and water consumption and device interaction data, machine learning algorithms will be used to categorize/clusterize occupants' behaviour. These data-centric categories will then be evaluated with the help of qualitative questionnaires to produce personas that faithfully represents users' needs and behaviours.

During the project, the participant will have the opportunity to integrate the startup team to benefit from their approach and competences.