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CoSDEO 2016 Keynote: A decade later — Challenges: Device-free passive localization for wireless environments

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TLDR
This talk gives a holistic overview of the area of contact-free ambient sensing based on RF technology, highlighting how it evolved over a decade from binary-detection in controlled environments to commercial systems for border protection and smart homes.
Abstract
The proliferation of RF networks coupled with the diverse and growing set of mobile devices, opened the doors for a new class of context awareness through contact-free ambient sensing. Since our initial challenges paper in 2007, the field of device-free passive sensing has witnessed an exponential growth; covering areas such as intrusion detection, mobile healthcare, whole-home gesture recognition, traffic estimation, border protection, among others. In this talk, we give a holistic overview of the area of contact-free ambient sensing based on RF technology, highlighting how it evolved over a decade from binary-detection in controlled environments to commercial systems for border protection and smart homes. We also give insights about the current trends and possible future research challenges.

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Proceedings ArticleDOI

Challenges: device-free passive localization for wireless environments

TL;DR: This talk gives a holistic overview of the area of contact-free ambient sensing based on RF technology, highlighting how it evolved over a decade from binary-detection in controlled environments to commercial systems for border protection and smart homes.
Proceedings ArticleDOI

E-eyes: device-free location-oriented activity identification using fine-grained WiFi signatures

TL;DR: This paper presents device-free location-oriented activity identification at home through the use of existing WiFi access points and WiFi devices (e.g., desktops, thermostats, refrigerators, smartTVs, laptops) in a low-cost system that can uniquely identify both in-place activities and walking movements across a home by comparing them against signal profiles.
Journal ArticleDOI

WiFall: Device-Free Fall Detection by Wireless Networks

TL;DR: This work analyzes the wireless signal propagation model considering human activities influence and proposes a novel and truly unobtrusive detection method based on the advanced wireless technologies, which it is called as WiFall, which withdraws the need for hardware modification, environmental setup and worn or taken devices.
Proceedings ArticleDOI

3D tracking via body radio reflections

TL;DR: WiTrack bridges a gap between RF-based localization systems which locate a user through walls and occlusions, and human-computer interaction systems like Kinect, which can track a user without instrumenting her body, but require the user to stay within the direct line of sight of the device.
Journal ArticleDOI

Capturing the human figure through a wall

TL;DR: RF-Capture tracks the 3D positions of a person's limbs and body parts even when the person is fully occluded from its sensor, and does so without placing any markers on the subject's body.
References
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Proceedings ArticleDOI

Whole-home gesture recognition using wireless signals

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Journal ArticleDOI

Radio Tomographic Imaging with Wireless Networks

TL;DR: A linear model for using received signal strength (RSS) measurements to obtain images of moving objects and mean-squared error bounds on image accuracy are derived, which are used to calculate the accuracy of an RTI system for a given node geometry.