Radio frequency (RF) sensing arises as a promising option for enabling the internet of things (IoT) applications that transform our life into a world of smart homes, smart cities, and smart industries. The innovation of IoT reveals the benefits of RF sensing across cost, pervasiveness, unobtrusiveness, and privacy. However, challenges...
Traditional localization techniques rely on triangulation or trilateration, where in a set of three or more stationary known locations is used to estimate a “client” position. For inertial navigation, these techniques can estimate client positions merely using the measured data from tri-axial accelerometers and gyroscopes. However, the use of double...
Deep learning is becoming the latest trend in sensitive applications, such as healthcare, criminal justice, and finance. As these new applications emerge, adversaries are circumventing them.
Further, there have been concerns about the possibility of bias and discrimination in predictive applications.
In order to address these issues, we propose an...
In this paper, a Direction of Arrival (DOA) based system is proposed. This method searches the direction relative to the array to find where the signal source is located. The proposed system can achieve sub-meter level accuracy with a near real-time update rate. Also, we introduced several refinement methods including...
The uncontrolled growth in domains such as surveillance systems, health care services, and finance produce a large amount of data and contain potentially sensitive data that can become public if they are not appropriately sanitized.
Motivated by this issue, we introduce a privacy filter (PF), a novel non-negative matrix factorization...
Accurate positioning has become an active research area in recent years. It has a wide range of applications in many fields such as navigation, asset tracking, health care, proximity marketing/location-based advertising, and sport analytics. Transmitter positioning via radio frequency (RF) signals is the most widely encountered scenario, and it uses...
This dissertation proposes the use of advanced time-varying approaches for modeling the dynamics of the multipath channel in wireless communication networks. These advanced time-varying approaches include linear Kalman innovation models in observable block companion form, and neural network-based models. The e˙ectiveness of these type of models is evaluated through three...
This work presents a novel CCRW receiver that utilizes a window of variable width, for e˙ectively mitigating multipath and ambiguity in both civil and military positioning applica-tions using Global Navigation Satellite Systems (GNSS). This CCRW receiver incorporates a single stroboscopic window, whose width is iteratively reduced until the e˙ect of...
The Internet of Things (IoT) paradigm brought an ever-increasing dependence on low-power devices to collect sensor data and transmit that information to the cloud, placing greater demand on connectivity and lifespan. In response, rapid worldwide innovation demonstrates the trade-offs in processing, communication, and energy consumption with diverse approaches to low-power...
Movement pattern detection can be applied in a variety of applications such as assisting independent living of seniors at home, behaviour understanding in surveillance systems, sports analytics, and robotics. This project develops a scheme that fuses information from different sensors to detect movement patterns. This report contains three main parts:...