AI RESEARCH
Dywave: Event-Aligned Dynamic Tokenization for Heterogeneous IoT Sensing Signal
arXiv CS.LG
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ArXi:2605.14014v1 Announce Type: new Internet of Things (IoT) systems continuously collect heterogeneous sensing signals from ubiquitous sensors to intelligent applications such as human activity analysis, emotion monitoring, and environmental perception. These signals are inherently non-stationary and multi-scale, posing unique challenges for standard tokenization techniques. This paper proposes Dywave, a dynamic tokenization framework for IoT sensing signals that constructs compact input representations aligned with intrinsic temporal structures and underlying physical events.