Computer Science Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1593

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Subject: search.filters.subject.low-power sensing

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    Structure Assisted Spectrum Sensing for Low-power Acoustic Event Detection
    (Association for Computer Machinery (ACM), 2023-05-09) Garg, Nakul; Takawale, Harshvardhan; Bai, Yang; Shahid, Irtaza; Roy, Nirupam
    Acoustic sensing has conventionally been dependent on highfrequency sampling of analog signals and frequency domain analysis in digital domain which is power-hungry. While these techniques work well for regular devices, low-power acoustic sensors demand for an alternative approach. In this work, we propose Lyra, a novel low-power acoustic sensing architecture that employs carefully designed passive structures to filter incoming sound waves and extract their frequency components. We eliminate power-hungry components such as ADC and digital FFT operations and instead propose to use low-power analog circuitry to process the signals. Lyra aims to provide a low-power platform for a range of maintenance-free acoustic event monitoring and ambient computing applications.
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    Sirius: A Self-Localization System for Resource-Constrained IoT Sensors
    (Association for Computer Machinery (ACM), 2023-06-18) Garg, Nakul; Roy, Nirupam
    Low-power sensor networks are transforming large-scale sensing in precision farming, livestock tracking, climate-monitoring and surveying. Accurate and robust localization in such low-power sensor nodes has never been as crucial as it is today. This paper presents, Sirius, a self-localization system using a single receiver for low-power IoT nodes. Traditionally, systems have relied on antenna arrays and tight synchronization to estimate angle-of-arrival (AoA) and time-of-flight with known access points. While these techniques work well for regular mobile systems, low-power IoT nodes lack the resources to support these complex systems. Sirius explores the use of gain-pattern reconfigurable antennas with passive envelope detector-based radios to perform AoA estimation without requiring any kind of synchronization. It shows a technique to embed direction specific codes to the received signals which are transparent to regular communication channel but carry AoA information with them. Sirius embeds these direction-specific codes by using reconfigurable antennas and fluctuating the gain pattern of the antenna. Our prototype demonstrates a median error of 7 degrees in AoA estimation and 2.5 meters in localization, which is similar to state-of-the-art antenna array-based systems. Sirius opens up new possibilities for low-power IoT nodes.