Toward ubiquitous sensing: Researchers turn WiFi signals into human activity patterns

Abstract

Jianfei Yang, a principal investigator and postdoc at Nanyang Technological University (NTU), and his student Xinyan Chen have developed a comprehensive benchmark and library for WiFi sensing. Their Patterns paper highlights the advantages of deep learning for WiFi sensing and provides constructive suggestions on model selection, learning scheme, and training strategy for developers and data scientists in this field. They talk about their view of data science, their experience with interdisciplinary WiFi sensing research, and the future of WiFi sensing applications.