Evaluating Correlations in IoT Sensors for Smart Buildings

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

2021

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.

Paper Citation

in Harvard Style

Guastella D., Verstaevel N., Valenti C., Arshad B. and Barthélemy J. (2021). Evaluating Correlations in IoT Sensors for Smart Buildings.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-484-8, pages 224-231. DOI: 10.5220/0010210502240231

in Bibtex Style

@conference{icaart21,
author={Davide Guastella and Nicolas Verstaevel and Cesare Valenti and Bilal Arshad and Johan Barthélemy},
title={Evaluating Correlations in IoT Sensors for Smart Buildings},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2021},
pages={224-231},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010210502240231},
isbn={978-989-758-484-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Evaluating Correlations in IoT Sensors for Smart Buildings
SN - 978-989-758-484-8
AU - Guastella D.
AU - Verstaevel N.
AU - Valenti C.
AU - Arshad B.
AU - Barthélemy J.
PY - 2021
SP - 224
EP - 231
DO - 10.5220/0010210502240231