Peatland forest monitoring and management solution in Peninsular Malaysia: optimal parameters for LoRa data

Peatland forest fires threaten biodiversity, ecosystems, and human health in Southeast Asia, especially during the dry season. Limited in-situ data collection necessitates Long Range (LoRa) sensor-based remote monitoring for its long-range communication, low power consumption, and cost-effectiveness...

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Bibliographic Details
Main Authors: Saleh, Nur Luqman, Sali, Aduwati, Jiun Terng, Liew, Syed Ahmad Abdul Rahman, Sharifah Mumtazah, Mohd Ali, Azizi, Mohd Ali, Borhanuddin, Mohd Razali, Sheriza, Nuruddin, Ahmad Ainuddin, Ramli, Nordin
Format: Article
Language:English
Published: Ain Shams University 2025
Online Access:http://psasir.upm.edu.my/id/eprint/121006/
http://psasir.upm.edu.my/id/eprint/121006/1/121006.pdf
Description
Summary:Peatland forest fires threaten biodiversity, ecosystems, and human health in Southeast Asia, especially during the dry season. Limited in-situ data collection necessitates Long Range (LoRa) sensor-based remote monitoring for its long-range communication, low power consumption, and cost-effectiveness. However, dense vegetation affects Low-Power Wide Area Network (LPWAN) signal propagation through scattering, reflection, and diffraction, impacting data transmission. This study investigates LoRa RF propagation in peatland environments through a measurement campaign at Raja Musa Forest Reserve (RMFR), Selangor. File transfer success rate (FT%) across various land-cover types was analyzed using six Data Rate (DR) and Spreading Factor (SF) configurations. Results show that DR5/SF7 and DR0/SF12 achieve over 80% FT% in moderate and dense vegetation, respectively. The findings enhance LoRa RF planning in challenging ecosystems, offering practical guidelines to improve data transmission reliability in RMFR and other peatlands.