Living Lab partnered with Qucit to employ its ‘ComfortPredict’ technology in Downtown Brooklyn to survey pedestrians to learn more about their perception of the area’s public spaces through machine learning technology.
Satellite view of the various points (in blue) where surveys were collected throughout Downtown Brooklyn
Over one week last summer, the team from Qucit conducted more than 800 surveys throughout Downtown Brooklyn. The survey consisted of twenty questions concerning the impressions of particular spaces, and the profiles of respondents (who remain anonymous). Most of the survey respondents live, work, or study in Downtown Brooklyn. Data was collected via Qucit’s proprietary protocol, which is able to collect a wide range of information in a short time frame. After the information was collected Qucit’s technology then organized its findings into maps and infographics, making it ready for Downtown Brooklyn Partnership to access this valuable data via the Qucit dashboard.
An example of an infographic generated on the Qucit dashboard. The graph above represents perceptions of the areas ‘cleanliness’ on a scale of 1-4, and according to visitor type e.g. tourist, resident, worker.
The resulting infographics represent various perceptions of the respondents’ regarding public space assets such as cleanliness, pleasantness, safety, and satisfaction with seating areas, stores, and availability of trash cans. In the graphic pictured below for example, the darker green areas represent a high level of satisfaction with cleanliness, while the yellow end of the spectrum represents a more negative reaction to sense of cleanliness.
Qucit’s technology gives Downtown Brooklyn Partnership powerful insight tools into specific problem areas within the areas surveyed. The next phase of the project will be to identify pain points within peoples’ perceptions of public spaces in Downtown Brooklyn, and to implement strategies to make changes and make improvements – all as a direct result of the insights reached by Qucit’s technology.
