Mathematics (Faculty of)

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Browsing Mathematics (Faculty of) by Author "Abari, Omid"

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    LOW-RESOLUTION CUSTOMIZABLE UBIQUITOUS DISPLAYS
    (University of Waterloo, 2023-09-22) Irudayaraj, Antony Albert Raj; Vogel, Daniel; Abari, Omid
    In a conventional display, pixels are constrained within the rectangular or circular boundaries of the device. This thesis explores moving pixels from a screen into the surrounding environment to form ubiquitous displays. The surrounding environment can include a human, walls, ceiling, and floor. To achieve this goal, we explore the idea of customizable displays: displays that can be customized in terms of shapes, sizes, resolutions, and locations to fit into the existing infrastructure. These displays require pixels that can easily combine to create different display layouts and provide installation flexibility. To build highly customizable displays, we need to design pixels with a higher level of independence in its operation. This thesis shows different display designs that use pixels with pixel independence ranging from low to high. Firstly, we explore integrating pixels into clothing using battery-powered tethered LEDs to shine information through pockets. Secondly, to enable integrating pixels into the architectural surroundings, we explore using battery-powered untethered pixels that allow building displays of different shapes and sizes on a desired surface. The display can show images and animations on the custom display configuration. Thirdly, we explore the design of a solar-powered independent pixel that can integrate into walls or construction materials to form a display. These pixels overcome the need to recharge them explicitly. Lastly, we explore the design of a mechanical pixel element that can be embedded into construction material to form display panels. The information on these displays is updated manually when a user brushes over the pixels. Our work takes a step forward in designing pixels with higher operation independence to envision a future of displays anywhere and everywhere.
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    Performance Evaluation of WiFi Backscatter Systems
    (University of Waterloo, 2020-09-29) Dehbashi, Farzan; Abari, Omid
    WiFi backscatter communication has been proposed to enable battery-free sensors to transmit data using WiFi networks. The main advantage of WiFi backscatter technologies over RFID is that data from their tags can be read using existing WiFi infrastructures instead of specialized readers. This can potentially reduce the complexity and cost of deploying battery-free sensors. Despite extensive work in this area, none of the existing systems are in widespread use today. We hypothesize that this is because WiFi-based backscatter tags do not scale well in WiFi networks, and their range and capabilities are limited when compared with RFID. This thesis uses real-world experiments to test this hypothesis. Our results show that existing WiFi backscatter tags cannot rely on RF harvesting (on the contrary to RFID tags) due to their high power consumption. We find that WiFi backscatter tags must be quite close to a WiFi device to work robustly in non-line-of-sight scenarios, limiting their operating range. Furthermore, our results show that some WiFi backscatter systems can cause significant interference for existing WiFi traffic since they do not perform carrier sensing. Moreover, we compare WiFi backscatter with RFID in terms of range, bitrate, and RF harvesting capabilities. Finally, we provide some insights into addressing several challenges in building practical WiFi backscatter systems.
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    PLOX: A Secure Serverless Framework for the Smart Home
    (University of Waterloo, 2021-08-17) Friesen, Micheal; Mashtizadeh, Ali; Abari, Omid
    Smart hubs play a key role in the modern smart home in executing code on behalf of devices locally or on the cloud. Unfortunately, smart hubs are prone to security problems due to misconfigurations, device over permissioning and network mismanagement. In this work, I show the major vulnerabilities and attacks currently targeting smart hubs, and provide a brief overview of the literature that addresses these issues. After discussing the limitations found in the literature as well as the available off the shelf smart hubs, I provide an overview of PLOX, an end-to-end approach designed to combat a large number of the common vulnerabilities and security/privacy risks that impact smart hubs, while maintaining a moderate overhead. PLOX is designed to sandbox applications on the home WiFi router. This allows for increased network controls, as well as lower latency in direct communication with devices. PLOX provides a new hybrid security model that combines a mandatory access control (MAC) system with information flow control (IFC), providing developer familiarity while addressing the overtainting issue found within taint based IFC systems through a serverless execution pattern. In our evaluations, PLOX outperforms Amazon Lambda by 500% and an open source smart hub solution, Home Assistant, by 13%, all while providing finer grained security policies and improved security guarantees. This is due to PLOX's locality and its light weight nature. This work demonstrates that PLOX, an open source end-to-end solution for the smart home is well suited to address a large number of the security and privacy problems that the smart home suffers from. This work also highlights a number of novel approaches to smart hub designs, including the use of the home router to maintain device isolation, and combination of manifest and IFC based permission systems.
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    Road Condition Sensing Using Deep Learning and Wireless Signals
    (University of Waterloo, 2020-08-14) Ameli, Soroush; Abari, Omid
    Similar to human car drivers, future driverless cars need to sense the condition of road surfaces so that they can adjust their speed and distance from other cars. This awareness necessitates the need for a sensing mechanism that enables cars to sense the surface type (gravel versus asphalt) and condition (dry versus wet) of a road. Unfortunately, existing road sensing approaches have major limitations. Vision-based approaches do not work in bad weather conditions and darkness. Mechanical-based approaches are either expensive or do not have enough resolution and robustness. In this thesis, we introduce VIVA, which uses mmWave to enable robust and practical road sensing. Our key insight is that mmWave radar devices enable high resolution ranging, which can be used to scan the roughness of a road surface. Moreover, mmWave radar devices use high-frequency signals, which are significantly reflected by water, and hence can be used to sense the moisture level of a road. However, due to the high sensitivity of mmWave radar devices, other factors such as car vibration also impact their signals, resulting in noisy measurements. To extract information about road surfaces from noisy signals, we have developed a cross-modal supervised model that uses mmWave measurements to sense road surfaces. Our prototype of VIVA costs less than $300 and achieves more than 98% accuracy in classifying road types (gravel versus asphalt) and 99% accuracy in classifying road conditions (wet versus dry), even in bad weather and darkness.