tinyRadar for Gesture Recognition: A Low-power System for Edge Computing

Kankipati, D and Munasala, M and Nikitha, DS and Yadav, SS and Rao, S and Thakur, CS (2023) tinyRadar for Gesture Recognition: A Low-power System for Edge Computing. In: UNSPECIFIED, pp. 75-79.

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Abstract

Hand gesture recognition (HGR) plays a pivotal role in improving human-machine interaction across domains like smart homes/vehicles and wearable devices. While vision-based HGR systems encounter challenges with lighting, complex backgrounds, and occlusion, radar-based systems overcome these limitations by harnessing electromagnetic principles. This paper presents tinyRadar, a real-time, low-power, single-chip radar solution for HGR. By leveraging miniaturized mmWave radar hardware, tinyRadar offers a compact and cost-effective HGR solution. The Texas Instruments IWRL6432 radar is utilized, achieving a total power consumption of less than 80mW and a memory footprint of 11 KB for the quantized inference model and < 256 KB for the entire system. The solution utilizes quantized depthwise separable convolutions and integrates a hardware accelerator and Cortex®-M4 microcontroller for real-time inference. With its small form factor and low power requirements, tinyRadar facilitates on-edge implementation, delivering 95 real-time inference accuracy for six gestures. This paper contributes to developing wearable gadgets and IoT devices that seamlessly incorporate HGR technology. © 2023 IEEE.

Item Type:	Conference Paper
Publication:	Proceedings - 2023 19th IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2023
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords:	Automation; Computing power; Cost effectiveness; Edge computing; Gesture recognition; Intelligent buildings; Millimeter waves; Palmprint recognition, Angle-time map; Depthwise separable convolution; Edge computing; Hand-gesture recognition; Iwrl6432 single-chip mmwave radar; Low Power; Mm waves; Single-chip; Time maps; Velocity-time map, Convolution
Department/Centre:	Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology)
Date Deposited:	26 May 2024 08:45
Last Modified:	26 May 2024 08:45
URI:	https://eprints.iisc.ac.in/id/eprint/85158

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