@article{ART003063562},
author={Jae-Won Kwak and 최인엽},
title={Addressing Inter-floor Noise Issues in Apartment Buildings using On-Sensor AI Embedded with TinyML on Ultra-Low-Power Systems},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={3},
pages={75-81},
doi={10.9708/jksci.2024.29.03.075}
TY - JOUR
AU - Jae-Won Kwak
AU - 최인엽
TI - Addressing Inter-floor Noise Issues in Apartment Buildings using On-Sensor AI Embedded with TinyML on Ultra-Low-Power Systems
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 3
PB - The Korean Society Of Computer And Information
SP - 75
EP - 81
SN - 1598-849X
AB - In this paper, we proposes a method for real-time processing of inter-floor noise problems by embedding TinyML, which includes a deep learning model, into ultra-low-power systems. The reason this method is feasible is because of lightweight deep learning model technology, which allows even systems with small computing resources to perform inference autonomously. The conventional method proposed to solve inter-floor noise problems was to send data collected from sensors to a server for analysis and processing. However, this centralized processing method has issues with high costs, complexity, and difficulty in real-time processing. In this paper, we address these limitations by employing On-Sensor AI using TinyML. The method presented in this paper is simple to install, cost-effective, and capable of processing problems in real-time.
KW - TinyML;Deep Learning;ultra-low-power system;On-Sensor AI;inter-floor noise
DO - 10.9708/jksci.2024.29.03.075
ER -
Jae-Won Kwak and 최인엽. (2024). Addressing Inter-floor Noise Issues in Apartment Buildings using On-Sensor AI Embedded with TinyML on Ultra-Low-Power Systems. Journal of The Korea Society of Computer and Information, 29(3), 75-81.
Jae-Won Kwak and 최인엽. 2024, "Addressing Inter-floor Noise Issues in Apartment Buildings using On-Sensor AI Embedded with TinyML on Ultra-Low-Power Systems", Journal of The Korea Society of Computer and Information, vol.29, no.3 pp.75-81. Available from: doi:10.9708/jksci.2024.29.03.075
Jae-Won Kwak, 최인엽 "Addressing Inter-floor Noise Issues in Apartment Buildings using On-Sensor AI Embedded with TinyML on Ultra-Low-Power Systems" Journal of The Korea Society of Computer and Information 29.3 pp.75-81 (2024) : 75.
Jae-Won Kwak, 최인엽. Addressing Inter-floor Noise Issues in Apartment Buildings using On-Sensor AI Embedded with TinyML on Ultra-Low-Power Systems. 2024; 29(3), 75-81. Available from: doi:10.9708/jksci.2024.29.03.075
Jae-Won Kwak and 최인엽. "Addressing Inter-floor Noise Issues in Apartment Buildings using On-Sensor AI Embedded with TinyML on Ultra-Low-Power Systems" Journal of The Korea Society of Computer and Information 29, no.3 (2024) : 75-81.doi: 10.9708/jksci.2024.29.03.075
Jae-Won Kwak; 최인엽. Addressing Inter-floor Noise Issues in Apartment Buildings using On-Sensor AI Embedded with TinyML on Ultra-Low-Power Systems. Journal of The Korea Society of Computer and Information, 29(3), 75-81. doi: 10.9708/jksci.2024.29.03.075
Jae-Won Kwak; 최인엽. Addressing Inter-floor Noise Issues in Apartment Buildings using On-Sensor AI Embedded with TinyML on Ultra-Low-Power Systems. Journal of The Korea Society of Computer and Information. 2024; 29(3) 75-81. doi: 10.9708/jksci.2024.29.03.075
Jae-Won Kwak, 최인엽. Addressing Inter-floor Noise Issues in Apartment Buildings using On-Sensor AI Embedded with TinyML on Ultra-Low-Power Systems. 2024; 29(3), 75-81. Available from: doi:10.9708/jksci.2024.29.03.075
Jae-Won Kwak and 최인엽. "Addressing Inter-floor Noise Issues in Apartment Buildings using On-Sensor AI Embedded with TinyML on Ultra-Low-Power Systems" Journal of The Korea Society of Computer and Information 29, no.3 (2024) : 75-81.doi: 10.9708/jksci.2024.29.03.075
