Project overview
The aim of the project was to deliver a sophisticated concept by using the data-enabled design approach presented by Philips. The focus was to design a tool for better indoor air quality because clean air improves productivity and health. We deployed a sensor kit in the house of a user to measure certain air parameters and self-reported user actions. With the sensor data acquired in this first deployment and the interviews held afterward, we explored the design context in order to come up with promising design interventions. We chose to design a supportive tool to grow the world’s most sustainable air filter, a plant. We deployed a second prototype with different user. By making use of new live sensor data and semi-structured interviews we held in between, we iteratively developed our concept a few times more from distance. In this way, we explored different methods to incite users to improve their indoor air quality. In the prototyped plant coaster, there was light feedback integrated to unobtrusively show feedback of the sensor data. After this second in-depth field deployment, we concluded by incorporating our findings into our final concept: Pebble. Pebble is a sensor kit mimicking the shape of a pebble, with a soil-moisture sensor fixed to the bottom. The kit supports users via a mobile application what plant fits an environment best and it provides feedback on how to grow the customized air filter, the plant, over time. Pebble measures CO2 levels, temperature, and humidity. This design is not validated and only represents the findings as described in the report retrievable below.
My contribution
In this course, I used large-scale data with the aid to get new knowledge about the design. I adapted prototypes based on sensor data and also qualitative data, which was very important in approaching a state of truly understanding users. Furthermore, I prototyped one of the sensor kits and gathered valuable insights remotely within a context for field deployments.
