Evaluating correlations in IoT sensors for smart buildings

Cesare Fabio Valenti, Johan Barthélemy, Nicolas Verstaevel, Davide Andrea Guastella, Bilal Arshad

Risultato della ricerca: Conference contribution

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.
Lingua originaleEnglish
Titolo della pubblicazione ospiteProceedings of the 13th International Conference on Agents and Artificial Intelligence ICAART 2021 - Volume 1
Pagine224-231
Numero di pagine8
Stato di pubblicazionePublished - 2021

All Science Journal Classification (ASJC) codes

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  • ???subjectarea.asjc.1700.1712???

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