Voice Controlled Comparator Improvement Based on Resource Utilization in SoC Ecosystem for Parking Assist System

Authors

  • Sethakarn Prongnuch Department of Robotics Engineering, Faculty of Industrial Technology, Suan Sunandha Rajabhat University, 1 U-Thong Nok Rd., Dusit, Bangkok, Thailand
  • Suchada Sitjongsataporn Department of Electronic Engineering, Mahanakorn Institute of Innovation (MII), Faculty of Engineering and Technology, Mahanakorn University of Technology, 140 Cheumsamphan Rd., Nongchok, Bangkok, Thailand https://orcid.org/0000-0002-2357-2365

DOI:

https://doi.org/10.13052/jmm1550-4646.1846

Keywords:

Voice controlled parking assist system, SoC development board, Normalized cross correlation

Abstract

This paper introduces the voice controlled comparator improvement for maneuvering a miniature electric vehicle based on the resource utilization in the system-on-chip (SoC) ecosystem. An intelligent parking assist is to support the driver outside a car while parking in the crowded locations. Voice controlled improvement based on the resource utilization on the SoC ecosystem is modified to command for moving vehicle. The normalized cross correlation (NCC) technique is proposed for voice controlled system with low utilization on the SoC ecosystem. Hardware and software co-design by the Xilinx VIVADO and Vitis software are used to design on an ARM multicore processor and field programmable gate array (FPGA) system inside a ‘Zedboard’ development board. We perform the experiments for Thai command word recognition via Bluetooth using the proposed NCC method to identify the basic command stored on SD card in Zedboard. Empirical results show the voice controlled improvement based on the Pearson’s correlation coefficient (PCC), modified PCC and proposed NCC methods on a Zedboard. The resource utilization on Zedboard are less than as 17.57% in look-up table (LUT), 29.12% in look-up table random access memory (LUTRAM), 6.44% in flip-flop (FF) and 2.38% in input/output (I/O) as compared with a ZYBO system. An average execution time of Zedboard using proposed NCC method is less than PCC and modified PCC as 5.12%, 1%, respectively. Results of proposed NCC of Thai voice command controlled show the validate workability at average percentage accuracy at 90% in the outdoor environments.

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Author Biographies

Sethakarn Prongnuch, Department of Robotics Engineering, Faculty of Industrial Technology, Suan Sunandha Rajabhat University, 1 U-Thong Nok Rd., Dusit, Bangkok, Thailand

Sethakarn Prongnuch received his B.Eng. degree in computer engineering from the Rajamangala University of Technology Phra Nakhon in Bangkok, Thailand in 2011, and the M.Eng. and D.Eng. degrees in Computer Engineering from the Mahanakorn University of Technology in Bangkok, Thailand in 2013 and 2019, respectively. He has worked as a lecturer at the department of Robotics Engineering at Faculty of Industrial Technology in Suan Sunandha Rajabhat University in Bangkok, Thailand since 2013. His research interests include computer architectures and systems, embedded system, heterogeneous system architecture, and robotics.

Suchada Sitjongsataporn, Department of Electronic Engineering, Mahanakorn Institute of Innovation (MII), Faculty of Engineering and Technology, Mahanakorn University of Technology, 140 Cheumsamphan Rd., Nongchok, Bangkok, Thailand

Suchada Sitjongsataporn received the B.Eng. (First-class honours) and D.Eng. degrees in Electronic Engineering from Mahanakorn University of Technology, Bangkok, Thailand in 2002 and 2009. She has worked as lecturer at department of Electronic Engineering, Mahanakorn University of Technology since 2002. Currently, she is an Associate Professor and Associate Dean for Research at Faculty of Engineering and Technology in Mahanakorn University of Technology. Her research interests are mathematical and statistical models in the area of adaptive signal processing for communications, networking, embedded system, image and video processing.

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Published

2022-03-16

Issue

Section

ICEAST 2020