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WiSense Workshop aims to bring together the research community utilizing different types of wireless signals for sensing purposes, and the community dealing with computing for embedded and energy efficient systems, and have them benefit from each other's findings.Wireless sensing has recently attracted a lot of attention thanks to its non-intrusive and sensor-free nature.Contrary to the traditional sensor-based and wearable sensing, wireless sensing does not need any sensors but leverages the signal distortions and machine learning algorithms for sensing.Different types of wireless signals have been employed for sensing including WiFi, RFID, mmWave, UWB, and acoustic signals.Deploying the wireless sensing systems on edge devices is also important, to reduce their costs and make them scalable.However, this comes with several challenges due to the constrained resources (e.g., memory, computation power, energy) of edge nodes.Accordingly, in this workshop we also look for solutions that develop novel, lightweight and cost-efficient techniques that can run at the network edge, providing means to train and run machine learning models in an energy efficient manner.This year, we organized the first edition of WiSense Workshop.We accepted 7 papers (out of 12 submissions).They will be presented in three paper sessions.The program also includes a keynote talk by Prof.
Bulut et al. (Mon,) studied this question.