LearningCity: Knowledge Generation for Smart Cities

TL;DR

LearningCity introduces a novel approach for smart city knowledge creation through anomaly detection and data annotation, leveraging machine learning and crowdsourcing to enhance data utility in Santander's deployment.

Contribution

The paper presents LearningCity, a new system for smart city knowledge generation using automated and crowdsourced data annotation and anomaly detection.

Findings

Preliminary results show effective data annotation and anomaly detection.

System validated on Santander smart city deployment.

Combines large datasets with machine learning for insights.

Abstract

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.