Related papers: RASID: A Robust WLAN Device-free Passive Motion De…
Wi-Fi signals-based person identification attracts increasing attention in the booming Internet-of-Things era mainly due to its pervasiveness and passiveness. Most previous work applies gaits extracted from WiFi distortions caused by the…
Locating the persons moving through an environment without the necessity of them being equipped with special devices has become vital for many applications including security, IoT, healthcare, etc. Existing device-free indoor localization…
Advances in wireless localization techniques aiming to exploit context-dependent data has been leading to a growing interest in services able of localizing or tracking targets inside buildings with high accuracy and precision. Hence, the…
Human sensing is significantly improving our lifestyle in many fields such as elderly healthcare and public safety. Research has demonstrated that human activity can alter the passive radio frequency (PRF) spectrum, which represents the…
This paper explores the use of ambient radio frequency (RF) signals for human presence detection through deep learning. Using WiFi signal as an example, we demonstrate that the channel state information (CSI) obtained at the receiver…
Indoor positioning systems have received a lot of attention recently due to their importance for many location-based services, e.g. indoor navigation and smart buildings. Lightweight solutions based on WiFi and inertial sensing have gained…
Wireless sensor networks are dynamically formed over the varying topologies. Wireless sensor networks can assist in conducting the rescue operations and can provide search in timely manner. Long time monitoring applications are environment…
Wi-Fi devices can effectively be used as passive radar systems that sense what happens in the surroundings and can even discern human activity. We propose, for the first time, a principled architecture which employs Variational…
Device-free human activity recognition plays a pivotal role in wireless sensing. However, current systems often fail to accommodate signal transmission through walls or necessitate dedicated noise removal algorithms. To overcome these…
Human activity recognition (HAR) holds significant importance in smart homes, security, and healthcare. Existing systems face limitations because of the insufficient spatial diversity provided by a limited number of antennas. Furthermore,…
We present a human state estimation framework that allows us to estimate the location, and even the activities, of people in an indoor environment without the requirement that they carry a specific devices with them. To achieve this "device…
This study explored an indoor system for tracking multiple humans and detecting falls, employing three Millimeter-Wave radars from Texas Instruments. Compared to wearables and camera methods, Millimeter-Wave radar is not plagued by mobility…
Device-free human tracking is an essential ingredient for ubiquitous wireless sensing. Recent passive WiFi tracking systems face the challenges of inaccurate separation of dynamic human components and time-consuming estimation of…
The past years have witnessed increasing research interest in achieving passive human localization with commodity WiFi devices. However, due to the fundamental limited spatial resolution of WiFi signals, it is still very difficult to…
We present experimental results and theoretical methods for the precise determination of the presence and the number of persons in an observed area by using Wi-Fi signals. Our setup does not require active cooperation of persons present in…
Falls have serious consequences and are prevalent in acute hospitals and nursing homes caring for older people. Most falls occur in bedrooms and near the bed. Technological interventions to mitigate the risk of falling aim to automatically…
Human identification plays an important role in human-computer interaction. There have been numerous methods proposed for human identification (e.g., face recognition, gait recognition, fingerprint identification, etc.). While these methods…
This paper presents an end-to-end deep learning framework using passive WiFi sensing to classify and estimate human respiration activity. A passive radar test-bed is used with two channels where the first channel provides the reference WiFi…
RF sensor networks are used to localize people indoor without requiring them to wear invasive electronic devices. These wireless mesh networks, formed by low-power radio transceivers, continuously measure the received signal strength (RSS)…
This paper presents a comprehensive dataset intended to evaluate passive Human Activity Recognition (HAR) and localization techniques with measurements obtained from synchronized Radio-Frequency (RF) devices and vision-based sensors. The…