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Indoor localization plays a vital role in the era of the IoT and robotics, with WiFi technology being a prominent choice due to its ubiquity. We present a method for creating WiFi fingerprinting datasets to enhance indoor localization…
Localization is a key component of the wireless ecosystem. Machine learning (ML)-based localization using channel state information (CSI) is one of the most popular methods for achieving high-accuracy localization with low cost. However, to…
Identification of a person from fingerprints of good quality has been used by commercial applications and law enforcement agencies for many years, however identification of a person from latent fingerprints is very difficult and…
Cross-Technology Interference (CTI) poses challenges for the performance and robustness of wireless networks. There are opportunities for better cooperation if the spectral occupation and technology of the interference can be detected.…
The human hand possesses distinctive features which can reveal gender information. In addition, the hand is considered one of the primary biometric traits used to identify a person. In this work, we propose a large dataset of human hand…
Heatstroke and life threatening incidents resulting from the retention of children and animals in vehicles pose a critical global safety issue. Current presence detection solutions often require specialized hardware or suffer from detection…
This paper presents a method for continuous indoor-outdoor environment detection on mobile devices based solely on WiFi fingerprints. Detection of indoor outdoor switching is an important part of identifying a user's context, and it…
There is growing interest in enabling wireless sensing systems to interpret human motion from unsegmented wireless signals; however, existing CSI-based applications rely heavily on accurate signal segmentation and predefined action labels,…
In recent years the amount of secure information being stored on mobile devices has grown exponentially. However, current security schemas for mobile devices such as physiological biometrics and passwords are not secure enough to protect…
Nowadays, mobile smart devices are widely used in daily life. It is increasingly important to prevent malicious users from accessing private data, thus a secure and convenient authentication method is urgently needed. Compared with common…
This paper presents BodyPIN, which is a continuous user authentication system by contactless wireless sensing using commodity Wi-Fi. BodyPIN can track the current user's legal identity throughout a computer system's execution. In case the…
In this paper, we first present a single-input, multiple-output convolutional neural network that can estimate both heart rate and respiration rate simultaneously by exploiting the underlying link between heart rate and respiration rate.…
Secure and scalable device provisioning is a notorious challenge in Wi-Fi. WPA2/WPA3 solutions take user interaction and a strong passphrase for granted. However, the often weak passphrases are subject to guessing attacks. Notably, there…
Device-free crowd-counting using WiFi Channel State Information (CSI) is a key enabling technology for a new generation of privacy-preserving Internet of Things (IoT) applications. However, practical deployment is severely hampered by the…
Passive object sensing with communication signals is a key enabler of perceptive mobile networks and integrated sensing and communication. In practical bistatic deployments, transmitter-receiver asynchrony and hardware impairments introduce…
Numerous indoor localization techniques have been proposed recently to meet the intensive demand for location based service, and Wi-Fi fingerprint-based approaches are the most popular and inexpensive solutions. Among them, one of the main…
Monitoring respiratory health with the use of channel state information (CSI) has shown promising results. Many existing methods focus on monitoring only the respiratory rate, while others focus on monitoring the motion of the chest as a…
While Wi-Fi sensing offers a compelling, privacy-preserving alternative to cameras, its practical utility has been fundamentally undermined by a lack of robustness across domains. Models trained in one setup fail to generalize to new…
We propose behavior-oriented services as a new paradigm of communication in mobile human networks. Our study is motivated by the tight user-network coupling in future mobile societies. In such a paradigm, messages are sent to inferred…
In this work, a real-time hand gesture recognition system-based human-computer interface (HCI) is presented. The system consists of six stages: (1) hand detection, (2) gesture segmentation, (3) use of five pre-trained convolutional neural…