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Evaluating correlations in IoT sensors for smart buildings

Conference Paper


Abstract


  • 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.

Publication Date


  • 2021

Citation


  • Guastella, D. A., Verstaevel, N., Valenti, C., Arshad, B., & Barthélemy, J. (2021). Evaluating correlations in IoT sensors for smart buildings. In ICAART 2021 - Proceedings of the 13th International Conference on Agents and Artificial Intelligence Vol. 1 (pp. 224-231).

Scopus Eid


  • 2-s2.0-85103840462

Start Page


  • 224

End Page


  • 231

Volume


  • 1

Abstract


  • 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.

Publication Date


  • 2021

Citation


  • Guastella, D. A., Verstaevel, N., Valenti, C., Arshad, B., & Barthélemy, J. (2021). Evaluating correlations in IoT sensors for smart buildings. In ICAART 2021 - Proceedings of the 13th International Conference on Agents and Artificial Intelligence Vol. 1 (pp. 224-231).

Scopus Eid


  • 2-s2.0-85103840462

Start Page


  • 224

End Page


  • 231

Volume


  • 1