Preprint Article Version 2 This version is not peer-reviewed

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

Version 1 : Received: 7 August 2018 / Approved: 7 August 2018 / Online: 7 August 2018 (09:10:12 CEST)
Version 2 : Received: 2 September 2018 / Approved: 3 September 2018 / Online: 3 September 2018 (10:09:11 CEST)

A peer-reviewed article of this Preprint also exists.

Kang, J.-G.; Lim, D.-W.; Jung, J.-W. Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol. Sensors 2018, 18, 2960. Kang, J.-G.; Lim, D.-W.; Jung, J.-W. Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol. Sensors 2018, 18, 2960.

Journal reference: Sensors 2018, 18, 2960
DOI: 10.3390/s18092960

Abstract

In this paper, we propose an adaptive duty-cycled hybrid X-MAC (ADX-MAC) protocol for energy-efficient forest fire prediction. The X-MAC protocol acquires the additional environmental status collected by each forest fire monitoring sensor for a certain period. And, based on these values, the length of sleep interval of duty-cycle is changed to efficiently calculate the risk of occurrence of forest fire according to the mountain environment. The performance of the proposed ADX-MAC protocol was verified through experiments the proposed ADX-MAC protocol improves throughput by 19% and was more energy-efficient by 24% compared to X-MAC protocol. As the probability of forest fires increases, the length of the duty cycle is shortened, confirming that the forest fires are detected at a faster cycle.

Subject Areas

Forest Fire; Prediction Model; Energy-Efficient; Sensors; WSN; X-MAC; Hybrid; Adaptive; Duty-Cycle; Protocol

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.