1,765 research outputs found
A Discussion on Fall Detection Issues and Its Deployment: When cloud meets battery
IEEE International Conference on Cloud Computing and Big Data Analysis (3rd. 2018., Chengdu, China
Anti-Fall: A Non-intrusive and Real-time Fall Detector Leveraging CSI from Commodity WiFi Devices
Fall is one of the major health threats and obstacles to independent living
for elders, timely and reliable fall detection is crucial for mitigating the
effects of falls. In this paper, leveraging the fine-grained Channel State
Information (CSI) and multi-antenna setting in commodity WiFi devices, we
design and implement a real-time, non-intrusive, and low-cost indoor fall
detector, called Anti-Fall. For the first time, the CSI phase difference over
two antennas is identified as the salient feature to reliably segment the fall
and fall-like activities, both phase and amplitude information of CSI is then
exploited to accurately separate the fall from other fall-like activities.
Experimental results in two indoor scenarios demonstrate that Anti-Fall
consistently outperforms the state-of-the-art approach WiFall, with 10% higher
detection rate and 10% less false alarm rate on average.Comment: 13 pages,8 figures,corrected version, ICOST conferenc
Fall Detection Analysis Using a Real Fall Dataset
International Conference on Soft Computing Models in Industrial and Environmental Applications (13th. 2018. San Sebastián
Privacy Mining from IoT-based Smart Homes
Recently, a wide range of smart devices are deployed in a variety of
environments to improve the quality of human life. One of the important
IoT-based applications is smart homes for healthcare, especially for elders.
IoT-based smart homes enable elders' health to be properly monitored and taken
care of. However, elders' privacy might be disclosed from smart homes due to
non-fully protected network communication or other reasons. To demonstrate how
serious this issue is, we introduce in this paper a Privacy Mining Approach
(PMA) to mine privacy from smart homes by conducting a series of deductions and
analyses on sensor datasets generated by smart homes. The experimental results
demonstrate that PMA is able to deduce a global sensor topology for a smart
home and disclose elders' privacy in terms of their house layouts.Comment: This paper, which has 11 pages and 7 figures, has been accepted BWCCA
2018 on 13th August 201
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