Sinusoidal Current Signal-Based Fire Detection System with Automatic Address Assignment

Author:

Lee Man HeeORCID,Chae Seog,Shin Soo YoungORCID

Abstract

In this paper, a novel sinusoidal current signal-based fire detection system is proposed with automatic address assignment. The system model employs a conventional power line to embed fire information, i.e., the address, rather than using an additional communication line. At the transmitter, different frequencies of the sinusoidal current signal are combined and transmitted through a power line. At the receiver, fast Fourier transform (FFT) is applied to distinguish the frequency bins, which can represent the addresses of fire detectors. The proposed system model is implemented and the numerical results are presented in terms of measurements.

Funder

Institute for Information & communications Technology Planning & Evaluation

National Research Foundation of Korea

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference19 articles.

1. Smart Factory Using IOT;Aashika;Int. J. Multidiscip. Res. Sci. Eng. Technol.,2019

2. Fires in Industrial and Manufacturing Properties;Campbell,2018

3. 2020 Analysis of Fire Statistics Safety Inspection Results for Special Buildings: South Korea,2020

4. Flexible longitudinal and transversal displacement sensors based on a composite of CI Disperse Orange 25 and carbon nanotubes;Ullah;Color. Technol.,2022

5. Multifunctional organic shockproof flexible sensors based on a composite of nickel phthalocyanine colourant, carbon nanotubes and rubber created with rubbing-in technology;Asghar;Color. Technol.,2022

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Design of OFDM‐based two‐wire bus communication system for fire safety;International Journal of Communication Systems;2024-05-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3