On-Device Deep Learning for IoT-based Wireless Sensing Applications
Recent Wi-Fi sensing literature uses deep neural networks to analyze wireless channel dynamics. This being a resource intensive process is usually carried out at the edge, but this isn’t always practical due to cost and bandwidth constraints. We propose on-device sensing for IoT platforms, introducing WISDOM to optimize inference models based on hardware and application needs. WISDOM achieves better utility than baseline models in over 85% of cases. It will be published in proceedings of PerCom Workshop 2024, Biarritz, France.