Evaluating experience sampling techniques in large scale mobile comfort perception sensing

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

Maintaining comfort is the purpose of buildings and energy is often needed for it. With more and more severe energy efficiency requirements and ever increasing building automation to achieve it, there is a need to gather the actual comfort sensation of building users, to optimise buidling control.

Yet comfort sensation is a subjective perception, that shows high variability among users, depending on their activity, their clothing, their environement, etc. The experience sampling approach allows to gather user perception about a given while they go about their normal doings.

The goal of this master project is to develop further a multi-platform mobile application to allow large scale gathering of comfort perception in real buildings through an experience sampling approach. Building on the outcomes of the project Relationship between subjective comfort perception and smartphone sensor data , the project will bring a similar apporach to a larger scale.

It will consist in

  1. Developing further an infrastructure composed of multi-platform mobile app (with availability in app stores) and data servers, possibly using indoor positioning methods relying on BT beacons/Wifi fingerprinting, 
  2. Testing the relevance and usability of several sampling techniques and strategies with real users
  3. Analyse comfort data gathered in large scale