Building generalizable deep learning solutions for mobile sensing - Xu, Huatao (Nanyang Technological University, 2024)
In an era where embedded and mobile devices are becoming ubiquitous, the intersection of Artificial Intelligence and the Internet of Things (AIoT) is rapidly transforming various fields. This thesis delves into the challenges and innovations in this domain, particularly focusing on the development of generalized sensing models for wearable sensor data. We introduce novel approaches to leverage the abundant unlabeled sensor data, physical sensing knowledge, and common knowledge embedded in Large Language Models (LLMs) to significantly enhance AIoT models.