6533b856fe1ef96bd12b26fb
RESEARCH PRODUCT
Evaluating Correlations in IoT Sensors for Smart Buildings
Nicolas VerstaevelCesare ValentiJohan BarthelemyBilal ArshadDavide Andrea GuastellaDavide Andrea Guastellasubject
Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSmart BuildingSettore INF/01 - Informaticabusiness.industryComputer science020206 networking & telecommunications02 engineering and technology7. Clean energy[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation030218 nuclear medicine & medical imaging[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]03 medical and health sciences0302 clinical medicineEvolutionary ApproachSmart Cities[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Sensors Correlation0202 electrical engineering electronic engineering information engineeringSystems engineeringbusinessInternet of ThingsIoT SensorsBuilding automationdescription
International audience; 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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2021-02-04 |