Sensing Human Comfort: An Inclusive Implementation of Indoor Environmental Data Collection

Teachers: 
Hamed Alavi
Denis Lalanne
Student: 
Léonard Stalder
Project status: 
Finished
Year: 
2015

Today, in developed countries, people spend more than 90% of their time indoor. Comfortable indoor conditions have great impact on our health, well-being, and performance. On the other hand, providing indoor comfort entails considerable energy consumption and  indeed buildings take a large share of the world’s total energy. In Switzerland, for example, approximately 50% of primary energy consumption is attributed to buildings. Assuming that people will increasingly stay inside, how can we improve their life quality and ensure the best user experience in a building while reducing energy consumption? This Master project investigate this question from a technological point of view. More precisely, we aim at integrating a sensor network into the built environment, which can also compile the collected data and compute the comfort level in a given context. This can be employed to assess a new energy saving strategy to see how it compares to the other energy systems in terms of occupants' comfort.

In this thesis plan, the first goal is to understand and sort out the existing studies about Human Indoor Comfort and Human-Building Interactions. Built on top of the first part’s results we design a sensor-system that collects data in order to measure the parameters that influence thermal, visual, acoustic, and respiratory comfort. In the second development iteration our sensor system includes a system of human-building interaction tracking. We conjecture that actions such as “opening a window” or “manipulating the ventilation” can complete our objective measurements towards a more context-aware sensing system.

We believe that the result of this work, coupled with a visual feedback system, can inform novel occupant experience design as well as future energy saving strategies.