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LearningCity: Knowledge Generation for Smart Cities

arXiv 2104.05286 ↗First posted 12 Apr 2021cs.DC cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 39 references that are in the map. First posted on arXiv 12 Apr 2021.

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3 of 39 references.

References · 3

  1. 2017Deep Learning for IoT Big Data and Streaming Analytics: A Surveycited by 59
  2. 2018SONYC: A System for the Monitoring, Analysis and Mitigation of Urban Noise Pollutioncited by 5
  3. 2021Knowledge co-creation in the OrganiCity: Data annotation with JAMAiCAcited by 1

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