Performance Examination of Symbolic Aggregate Approximation in IoT Applications

arXiv:2405.19817v1 Announce Type: new
Abstract: Symbolic Aggregate approXimation (SAX) is a common dimensionality reduction approach for time-series data which has been employed in a variety of domains, including classification and anomaly detection in time-series data. Domains also include shape recognition where the shape outline is converted into time-series data forinstance epoch classification of archived arrowheads. In this paper we propose a dimensionality reduction and shape recognition approach based on the SAX algorithm, an application which requires responses on cost efficient, …

abstract anomaly anomaly detection applications approximation arxiv classification cs.cv cs.ro data detection dimensionality domains iot performance recognition series shape type