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Authors: Davide Andrea Guastella 1 ; 2 ; Nicolas Verstaevel 3 ; Cesare Valenti 1 ; Bilal Arshad 4 and Johan Barthélemy 4

Affiliations: 1 Dipartimento di Matematica e Informatica, Università degli Studi di Palermo, Italy ; 2 Institut de Recherche en Informatique de Toulouse, Université Toulouse III Paul Sabatier, France ; 3 Institut de Recherche en Informatique de Toulouse, Université Toulouse 1 Capitole, France ; 4 SMART Infrastructure Facility, University of Wollongong, Wollongong 2522, NSW, Australia

Keyword(s): Smart Building, Smart Cities, IoT Sensors, Evolutionary Approach, Sensors Correlation.

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.

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Paper citation in several formats:
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; ISSN 2184-433X, SciTePress, pages 224-231. DOI: 10.5220/0010210502240231

@conference{icaart21,
author={Davide Andrea 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},
issn={2184-433X},
}

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
IS - 2184-433X
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
PB - SciTePress

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