Energy-efficient forest fire prediction model based on two-stage adaptive duty-cycled hybrid X-MAC protocol

Jin Gu Kang, Dong Woo Lim, Jin Woo Jung

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

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.

Original languageEnglish
Article number2960
JournalSensors
Volume18
Issue number9
DOIs
StatePublished - 5 Sep 2018

Keywords

  • Adaptive
  • Duty-cycle
  • Energy efficient
  • Forest fire
  • Hybrid
  • Prediction model
  • Protocol
  • Sensors
  • Wireless sensor network
  • X-MAC

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