Cargando…

Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol

This paper proposes an adaptive duty-cycled hybrid X-MAC (ADX-MAC) protocol for energy-efficient forest fire prediction. The Asynchronous sensor network protocol, X-MAC protocol, acquires additional environmental status details from each forest fire monitoring sensor for a given period, and then cha...

Descripción completa

Detalles Bibliográficos
Autores principales: Kang, Jin-Gu, Lim, Dong-Woo, Jung, Jin-Woo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165158/
https://www.ncbi.nlm.nih.gov/pubmed/30189668
http://dx.doi.org/10.3390/s18092960
_version_ 1783359770855473152
author Kang, Jin-Gu
Lim, Dong-Woo
Jung, Jin-Woo
author_facet Kang, Jin-Gu
Lim, Dong-Woo
Jung, Jin-Woo
author_sort Kang, Jin-Gu
collection PubMed
description This paper proposes an adaptive duty-cycled hybrid X-MAC (ADX-MAC) protocol for energy-efficient forest fire prediction. The Asynchronous sensor network protocol, X-MAC protocol, acquires additional environmental status details from each forest fire monitoring sensor for a given period, and then changes the duty-cycle sleep interval to efficiently calculate forest fire occurrence risk according to the environment. Performance was verified experimentally, and the proposed ADX-MAC protocol improved throughput by 19% and was 24% more energy efficient compared to the X-MAC protocol. The duty-cycle was shortened as forest fire probability increased, ensuring forest fires were detected at faster cycle rate.
format Online
Article
Text
id pubmed-6165158
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-61651582018-10-10 Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol Kang, Jin-Gu Lim, Dong-Woo Jung, Jin-Woo Sensors (Basel) Article This paper proposes an adaptive duty-cycled hybrid X-MAC (ADX-MAC) protocol for energy-efficient forest fire prediction. The Asynchronous sensor network protocol, X-MAC protocol, acquires additional environmental status details from each forest fire monitoring sensor for a given period, and then changes the duty-cycle sleep interval to efficiently calculate forest fire occurrence risk according to the environment. Performance was verified experimentally, and the proposed ADX-MAC protocol improved throughput by 19% and was 24% more energy efficient compared to the X-MAC protocol. The duty-cycle was shortened as forest fire probability increased, ensuring forest fires were detected at faster cycle rate. MDPI 2018-09-05 /pmc/articles/PMC6165158/ /pubmed/30189668 http://dx.doi.org/10.3390/s18092960 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kang, Jin-Gu
Lim, Dong-Woo
Jung, Jin-Woo
Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol
title Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol
title_full Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol
title_fullStr Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol
title_full_unstemmed Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol
title_short Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol
title_sort energy-efficient forest fire prediction model based on two-stage adaptive duty-cycled hybrid x-mac protocol
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165158/
https://www.ncbi.nlm.nih.gov/pubmed/30189668
http://dx.doi.org/10.3390/s18092960
work_keys_str_mv AT kangjingu energyefficientforestfirepredictionmodelbasedontwostageadaptivedutycycledhybridxmacprotocol
AT limdongwoo energyefficientforestfirepredictionmodelbasedontwostageadaptivedutycycledhybridxmacprotocol
AT jungjinwoo energyefficientforestfirepredictionmodelbasedontwostageadaptivedutycycledhybridxmacprotocol