An RSSI-Based Device-Free Localization System for Smart Wards

Patient monitoring during hospitalization and intime assistance are essential tasks. However, it is always challenging for medical personnel to efficiently monitor duties, especially under raising attention to privacy issues. Advances in devicefree localization (DFL) technologies and the evolution of machine learning technologies made localization more accurate than ever. We take advantage of easily accessible Wi-Fi signals around the wards and perform privacy-preserving localization on patients using multi-scale convolutional neural network (CNN) and long short-term memory (LSTM) models. The results demonstrate high localization accuracy. Also, the system can be extended for emergent event detection, enabling medical personnel to react promptly.