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Author: search.filters.author.Vasantha, G.Subject: search.filters.subject.Internet of Things

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    IoT-based Human Activity Recognition Models based on CNN, LSTM and GRU
    (Institute of Electrical and Electronics Engineers Inc., 2022) Kolkar, R.; Singh Tomar, R.P.; Vasantha, G.
    Smartphones' ability to generate data with their inbuilt sensors has made them used for Human Activity Recognition. The work highlights the importance of Human Activity Recognition (HAR) systems capable of sensing human activities like the inertial motion of a human body. The sensors are worn on a body part and tracked from whole-body motions and monitoring. Real-time signal processing is used to sense human body movements using wearable sensors. The work aims to provide opportunities for promising health applications using IoT. There are many challenges to recognising human activities, including accuracy. This work analyses Human Activity recognition concerning CNN, LSTM, and GRU deep learning models to improve the accuracy of the human activity recognition in the UCI-HAR and WISDM datasets. The comparative analysis shows promising results for Human activity recognition. © 2022 IEEE.
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    Quantum-Chromodynamics-Inspired 2D Multicolor LED Matrix to Camera Communication for User-Centric MIMO
    (MDPI, 2022) Vasantha, G.; Salvi, S.
    With the high availability of low-cost and energy-efficient LEDs and cameras, there is increased interest in optical camera communication (OCC) to provide nonradio-frequency-based communication solutions in the domains of advertisement, vehicular communication, and the Internet of Things (IoT). As per the IEEE 802.15.7-2018 standard, new physical-layer clauses support low-frame-rate camera communication with allowable flickering. This paper proposes an OCC system that can provide user-centric multiple-input multiple-output (MIMO) loosely based on quantum-chromodynamics (QCD) concepts. A QCD–OCC simulator and prototype are proposed, implemented, and evaluated on the basis of the pixel intensity profile, peak signal-to-noise ratio (PSNR), the success of reception (%), bit-error rate (BER), and throughput under different ambient lighting conditions and distances. We observed 100% and 84% success of reception using the proposed prototype and simulator, respectively, for the data rate of 720 bps. The maximal tolerable BER of (Formula presented.) for IoT applications was observed at a maximal distance of 200 cm and a maximal data rate of 3600 bps. The proposed system was also compared with other existing OCC systems with similar hardware and implementation requirements. The proposed QCD–OCC system provided rotation support up to 90 degrees and throughput of 4.32 kbps for a 30 fps camera. © 2022 by the authors.