Planning Through Deliberation and Data
The system is mounted on a commercial electric assist bike and is able to combine sensor input that provides data on the bike’s electro-mechanical, geospatial, and environmental states. The system proposes sensor flexibility and modularity as key characteristics, and the abstraction framework conceptualizes the way in which these characteristics can be best exploited for city improvement.
We demonstrate the functionality of the system and framework through the creation of a use case implementation for clustering bike trip patterns using unsupervised learning clustering techniques. This platform outlines a way to shift from being primarily focused on solution finding to asking the right questions in order to satisfy citizens’ needs.