相关论文: Practical Wi-Fi-based Motion Recognition Under Var…
Recently, Wi-Fi signals have emerged as a powerful tool for contactless sensing. During the sensing process, obtaining target direction information can provide valuable contextual insights for various applications. Existing direction…
WiFi sensing is an important part of the new WiFi 802.11bf standard, which can detect motion and measure distances. In recent years, some machine learning methods have been proposed for human activity recognition from WiFi signals. However,…
Thanks to the ubiquitousness of Wi-Fi access points and devices, Wi-Fi sensing enables transformative applications in remote health care, security, and surveillance. Existing work has explored the usage of machine learning on channel state…
Gesture recognition is a very essential technology for many wearable devices. While previous algorithms are mostly based on statistical methods including the hidden Markov model, we develop two dynamic hand gesture recognition techniques…
The success of enhanced sampling molecular simulations that accelerate along collective variables (CVs) is predicated on the availability of variables coincident with the slow collective motions governing the long-time conformational…
WiFi sensing technology has shown superiority in smart homes among various sensors for its cost-effective and privacy-preserving merits. It is empowered by Channel State Information (CSI) extracted from WiFi signals and advanced machine…
Wireless signal recognition (WSR) is crucial in modern and future wireless communication networks since it aims to identify properties of the received signal. Although many deep learning-based WSR models have been developed, they still rely…
We present a novel data-driven approach to perform smooth Wi-Fi/cellular handovers on smartphones. Our approach relies on data provided by multiple smartphone sensors (e.g., Wi-Fi RSSI, acceleration, compass, step counter, air pressure) to…
WiFi-based sensing has aroused immense attention over recent years. The rationale is that the signal fluctuations caused by humans carry the information of human behavior which can be extracted from the channel state information of WiFi.…
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…
Energy Efficiency of a wireless sensor network (WSN) relies on its main characteristics, including hop-number, user's location, allocated power, and relay. Identifying nodes, which have more impact on these characteristics, is, however,…
Sampling-based methods such as Rapidly-exploring Random Trees (RRTs) have been widely used for generating motion paths for autonomous mobile systems. In this work, we extend time-based RRTs with Control Barrier Functions (CBFs) to generate,…
WiFi-based human activity recognition (HAR) holds significant application potential across various fields. To handle dynamic environments where new activities are continuously introduced, WiFi-based HAR systems must adapt by learning new…
Wi-Fi sensing is gaining momentum as a non-intrusive and privacy-preserving alternative to vision-based systems for human identification. However, person identification through wireless signals, particularly without user motion, remains…
Wi-Fi gesture recognition based on Channel State Information (CSI) is challenged by high-dimensional noise and resource constraints on edge devices. Prevailing end-to-end models tightly couple feature extraction with classification,…
Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks…
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…
Human motion recognition (HMR) based on wireless sensing is a low-cost technique for scene understanding. Current HMR systems adopt support vector machines (SVMs) and convolutional neural networks (CNNs) to classify radar signals. However,…
This work proposes a tool to estimate the interference between nodes and links in a live wireless network by passive monitoring of wireless traffic. This approach requires deploying multiple sniffers across the network to capture wireless…
Wireless sensing has been recognized as a key enabling technology for numerous emerging applications. For decades, the sensing performance was mostly evaluated from a reliability perspective, with the efficiency aspect widely unexplored.…