DeepHeteroIoT: Deep Local and Global Learning over Heterogeneous IoT Sensor Data

arXiv:2403.19996v1 Announce Type: new
Abstract: Internet of Things (IoT) sensor data or readings evince variations in timestamp range, sampling frequency, geographical location, unit of measurement, etc. Such presented sequence data heterogeneity makes it difficult for traditional time series classification algorithms to perform well. Therefore, addressing the heterogeneity challenge demands learning not only the sub-patterns (local features) but also the overall pattern (global feature). To address the challenge of classifying heterogeneous IoT sensor data (e.g., categorizing sensor data types like temperature …

abstract algorithms arxiv challenge classification cs.lg data eess.sp etc global internet internet of things iot location measurement sampling sensor series time series type