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Evaluating correlations in IoT sensors for smart buildings

  • Authors: Guastella D.A.; Verstaevel N.; Valenti C.; Arshad B.; Barthelemy J.
  • Publication year: 2021
  • Type: Contributo in atti di convegno pubblicato in volume
  • OA Link:


In this paper we introduce a dataset of environmental information obtained via indoor and outdoor sensors deployed in the SMART Infrastructure Facility of the University of Wollongong (Australia). The acquired dataset is also made open-sourced along with this paper. We also propose a novel approach based on an evolutionary algorithm to determine pairs of correlated sensors. We compare our approach with three other standard techniques on the same dataset: on average, the accuracy of the evolutionary method is about 62,92%. We also evaluate the computational time, assessing the suitability of the proposed pipeline for real-time applications.