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oai:gredos.usal.es:10366/1615842026-01-22T11:21:06Zcom_10366_4386com_10366_4349com_10366_3946com_10366_3823col_10366_4387

Rosero Montalvo, Paul David López Batista, Vivian Félix Peluffo-Ordóñez, Diego H. 2025-01-10T12:08:36Z 2025-01-10T12:08:36Z 2022 Rosero-Montalvo, P. D., López-Batista, V. F., & Peluffo-Ordóñez, D. H. (2022). A New Data-Preprocessing-Related Taxonomy of Sensors for IoT Applications. Information (Switzerland), 13(5). https://doi.org/10.3390/INFO13050241 2078-2489 http://hdl.handle.net/10366/161584 10.3390/INFO13050241 2078-2489 [EN]IoT devices play a fundamental role in the machine learning (ML) application pipeline, as they collect rich data for model training using sensors. However, this process can be affected by uncontrollable variables that introduce errors into the data, resulting in a higher computational cost to eliminate them. Thus, selecting the most suitable algorithm for this pre-processing step on-device can reduce ML model complexity and unnecessary bandwidth usage for cloud processing. Therefore, this work presents a new sensor taxonomy with which to deploy data pre-processing on an IoT device by using a specific filter for each data type that the system handles. We define statistical and functional performance metrics to perform filter selection. Experimental results show that the Butterworth filter is a suitable solution for invariant sampling rates, while the Savi–Golay and medium filters are appropriate choices for variable sampling rates. This research was funded by Novo Nordisk Fonden, grant number NNF20OC0064411, with the project Privacy through Co-Design for Real-World Data Analytics in the cloud. application/pdf eng MDPI Internet of Things Sensor Machine learning Computational intelligence Data analytics Data pre-processing 1203 Ciencia de los ordenadores A New Data-Preprocessing-Related Taxonomy of Sensors for IoT Applications info:eu-repo/semantics/article info:eu-repo/semantics/draft https://doi.org/10.3390/info13050241 info:eu-repo/semantics/openAccess Information 13 5 241