arXiv subjects

Nivedita Arora

Publications and source records attributed to Nivedita Arora.

6 recordsLinked to original sources

arXiv2026

Towards Knitted Textile Electromechanical Systems

E-textiles and wearable sensing technologies enable flexible, customizable interfaces for human-computer interaction, with capacitive sensing offering precise touch and pressure detection. While machine knitting provides scalable, mechanically tunable structures ideal for such sensors, few studies develop or characterize insulated conductive yarns engineered for knitting's complex structural geometry and high flexure strain. In this work, we present a yarn dip-coating process, driven by an adjusted dip-coating fluid dynamics model, that enables scalable, machine knittable fabrication of capacitive tactile pressure sensing arrays. We establish optimal dip-coating parameters and concentrations of thermoplastic polyurethane (TPU) dissolved in dimethylformamide (DMF) to create knitting-optimized coatings (~630 um thickness). These fabricated yarns are shown to maintain electromechanical characteristics with minimal deviation after knitting and washing, thus allowing the creation of knitted pressure sensors through multi-layered structures. This process demonstrates that machine knitting with insulated yarns is a viable and reliable manufacturing approach to integrate sensing functionality into wearable textiles.

cs.HC↗

arXiv2026

GlassTENG: Self-Powered Triboelectric Nanogenerator based Sensing of Pulse, Jaw, and Upper Facial Activity from Everyday Glasses

Smart glasses maintain near-continuous skin contact at multiple arterial and muscular sites, making them a promising platform for physiological sensing. In practice, though, two factors make sustained daily wear and longitudinal deployment impractical for the quantified self: the discomfort of prolonged sensor-skin contact (e.g., gels and adhesives) and the sensor power demands that increase battery size, weight, and maintenance burden. We present GlassTENG, an ultra-low-power sensor that embeds three custom-fabricated triboelectric nanogenerators (TENGs) into a glasses frame at the angular artery on the nasal bridge, the superficial temporal artery on an extended arm, and the temporalis muscle at the temple. Each GlassTENG sensor is self-powered in transducing mechanical energy to electrical energy and consumes 1.36 $μ$W per sensor at the analog front-end. GlassTENG enables simultaneous capture of arterial pulse waveforms, jaw kinematics (e.g., clenching, tapping, eating), and upper facial activity (e.g., blinking, eyebrow movement). In a 20-participant user study, we achieve 93.8% accuracy across six jaw and upper facial activities and estimate heart rate with a mean absolute error of 1.82 beats per minute (BPM) relative to a ground-truth chest-strap sensor in 30s windows. Together, these results establish a future pathway toward a longitudinally worn, ultra-low-power, glasses-based physiological monitoring platform.

cs.HC↗

arXiv2026

Towards a Frugal Photosynthesis Sensing Toolkit for Data-Driven Plant Science Education and Exploration

Rapid environmental change and advances in data-driven analysis highlight the need not only to use computational tools, but also to foster understanding of the natural world and inspire creativity. Photosynthesis, the process that fuels nearly all life on Earth, provides a compelling context for such learning, particularly in understanding how plants alter their photosynthetic strategies in response to environmental changes. However, existing tools for studying photosynthesis are often inaccessible or limited to demonstrating its presence, rather than capturing its temporal dynamics. We present PhytoBits, a frugal in situ gas-exchange sensing toolkit for distinguishing and teaching photosynthetic strategies. PhytoBits combines leaf enclosure with accessible materials, an off-the-shelf CO2 sensor, and a low-cost microcontroller, to support multi-day monitoring of plant gas-exchange in educational and research contexts. We validated PhytoBits against research-grade gas-exchange systems, confirming that it identifies C3 and CAM (Crassulacean Acid Metabolism) photosynthetic pathways. In addition to obligate CAM, PhytoBits also resolves facultative CAM and developmental CAM dynamics in plants. This work presents an early-stage hardware validation; user deployment studies, open-source code dissemination, and automated pathway classification are planned as future work.

cs.HC↗

arXiv2026

Towards Low-Cost Low-Power Activity-Aware Soil Moisture Sensing Platform for Large-scale Farming

Deep understanding of a field's soil moisture content is the leading indicator for predicting crop yields and making data driven decisions for irrigation and application of topical chemicals for drought resilience. Despite this importance, the cost of adopting and maintaining IoT infrastructure prevents modern farms from employing widespread real time soil moisture sensors. We present an end-to-end platform of buried battery-free sensor nodes and a mobile basestation that leverages the farmer's daily routine for data retrieval. Each node features a self-powered galvanic soil-moisture probe, employing a high impedance analog front end to enable durability. Operating entirely on harvested solar energy for up to 21 days on a single capacitor charge, each node collects soil moisture, temperature, and environment condition data. Using a predictable finite-state machine, handshake-based data exchanges occur with a basestation affixed to standard farming vehicles designed to listen for the nodes while moving through the farm. Our platform organizes all sensor, link-quality, and location data into an easy-to-interpret dashboard to seamlessly integrate with the farmer's everyday routine. Costing less than $35, the platform is a financially accessible, accurate, and easily scalable platform that enables persistent, regular data collection from the most rural plots without adding to or impeding farming operations. Experimental evaluation demonstrates reliable communication over 1 km at 2 dBm transmit power, stable sensor readings over 70 days of indoor operation, and continuous data recovery during multiple periods of intermittent connection.

cs.HC↗

arXiv2024

Sustainable Quantum Computing: Opportunities and Challenges of Benchmarking Carbon in the Quantum Computing Lifecycle

While researchers in both industry and academia are racing to build Quantum Computing (QC) platforms with viable performance and functionality, the environmental impacts of this endeavor, such as its carbon footprint, e-waste generation, mineral use, and water and energy consumption, remain largely unknown. A similar oversight occurred during the semiconductor revolution and continues to have disastrous consequences for the health of our planet. As we build the quantum computing stack from the ground up, it is crucial to comprehensively assess it through an environmental sustainability lens for its entire life-cycle: production, use, and disposal. In this paper, we highlight the need and challenges in establishing a QC sustainability benchmark that enables researchers to make informed architectural design decisions and celebrate the potential quantum environmental advantage. We propose a carbon-aware quantum computing (CQC) framework that provides the foundational methodology and open research questions for calculating the total life-cycle carbon footprint of a QC platform. Our call to action to the research community is the establishment of a new research direction known as, sustainable quantum computing that promotes both quantum computing for sustainability-oriented applications and the sustainability of quantum computing.

quant-ph↗

arXiv2021

MARS: Nano-Power Battery-free Wireless Interfaces for Touch, Swipe and Speech Input

Augmenting everyday surfaces with interaction sensing capability that is maintenance-free, low-cost (about $1), and in an appropriate form factor is a challenge with current technologies. MARS (Multi-channel Ambiently-powered Realtime Sensing) enables battery-free sensing and wireless communication of touch, swipe, and speech interactions by combining a nanowatt programmable oscillator with frequency-shifted analog backscatter communication. A zero-threshold voltage field-effect transistor (FET) is used to create an oscillator with a low startup voltage (about 500 mV) and current (< 2uA), whose frequency can be affected through changes in inductance or capacitance from the user interactions. Multiple MARS systems can operate in the same environment by tuning each oscillator circuit to a different frequency range. The nanowatt power budget allows the system to be powered directly through ambient energy sources like photodiodes or thermoelectric generators. We differentiate MARS from previous systems based on power requirements, cost, and part count and explore different interaction and activity sensing scenarios suitable for indoor environments.

cs.HC↗