LearningCity: Knowledge Generation for Smart Cities
This addresses the challenge of simplifying data use for smart city service consumers, though it appears incremental by building on existing deployments and ecosystems.
The paper tackles the problem of underutilized data in smart cities by proposing LearningCity, a system for knowledge creation through anomaly detection and data annotation, validated in Santander with preliminary results from combining large datasets and machine learning.
Although we have reached new levels in smart city installations and systems, efforts so far have focused on providing diverse sources of data to smart city services consumers while neglecting to provide ways to simplify making good use of them. In this context, one first step that will bring added value to smart cities is knowledge creation in smart cities through anomaly detection and data annotation, supported in both an automated and a crowdsourced manner. We present here LearningCity, our solution that has been validated over an existing smart city deployment in Santander, and the OrganiCity experimentation-as-a-service ecosystem. We discuss key challenges along with characteristic use cases, and report on our design and implementation, together with some preliminary results derived from combining large smart city datasets with machine learning.