报告标题：In Home Nonintrusive Human Identification through Environmental Sensors

报告人：张晴 高级研究员 （澳大利亚CSIRO电子医疗研究中心）

报告时间：2017年10月17日（星期二）上午10:00

报告地点：复杂系统研究所报告厅

报告摘要： Human identification is one of the main challenges for health monitoring systems in smart home. The majority of existing systems employ either wearable tags or video cameras to identify multiple residents in home environment. However, due to the inflexibility and inconvenience of wearable devices, and potential intrusiveness of video cameras, the adoption rate of these approaches remains low. In this talk, I will introduce several novel methods of non-wearable identification system to recognize multiple residents in a home environment, through ambient non-intrusive ultrasound and ultra-wide Band (UWB) sensors. I will also demonstrate the effectiveness of these systems in various application scenarios through experiments on our prototypes. Our findings show that the proposed feature learning and classification framework combined with the UWB radar technology provides an effective solution to human identification in multi-residential smart homes.

张晴高级研究员简介：主要研究领域为物联网，流数据和数据库，算法模型和分析等。1997年于清华大学获得理学学士学位，2005年于澳大利亚University of NSW获得计算机科学博士学位。现已发表学术论文60余篇，长期担任物联网，传感器，数据库等多个顶级国际期刊，会议的审稿，委员工作。现兼任IEEE Engineering in Medicine and Biology 昆士兰分部的副主席。张老师主导研究的智能房屋项目于2013年分别获得州和联邦科技创新奖。