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...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Ain Shams University
2025
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| Online Access: | http://psasir.upm.edu.my/id/eprint/121006/ http://psasir.upm.edu.my/id/eprint/121006/1/121006.pdf |
| _version_ | 1848868271589163008 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Saleh, Nur Luqman |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T14:49:44Z |
| format | Article |
| id | upm-121006 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:49:44Z |
| publishDate | 2025 |
| publisher | Ain Shams University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1210062025-10-22T02:32:55Z http://psasir.upm.edu.my/id/eprint/121006/ Peatland forest monitoring and management solution in Peninsular Malaysia: optimal parameters for LoRa data 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 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. Ain Shams University 2025 Article PeerReviewed text en cc_by_nc_nd_4 http://psasir.upm.edu.my/id/eprint/121006/1/121006.pdf Saleh, Nur Luqman and Sali, Aduwati and Jiun Terng, Liew and Syed Ahmad Abdul Rahman, Sharifah Mumtazah and Mohd Ali, Azizi and Mohd Ali, Borhanuddin and Mohd Razali, Sheriza and Nuruddin, Ahmad Ainuddin and Ramli, Nordin (2025) Peatland forest monitoring and management solution in Peninsular Malaysia: optimal parameters for LoRa data. Ain Shams Engineering Journal, 16 (6). art. no. 103374. pp. 1-14. ISSN 2090-4479 https://linkinghub.elsevier.com/retrieve/pii/S2090447925001157 10.1016/j.asej.2025.103374 |
| spellingShingle | 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 Peatland forest monitoring and management solution in Peninsular Malaysia: optimal parameters for LoRa data |
| title | Peatland forest monitoring and management solution in Peninsular Malaysia: optimal parameters for LoRa data |
| title_full | Peatland forest monitoring and management solution in Peninsular Malaysia: optimal parameters for LoRa data |
| title_fullStr | Peatland forest monitoring and management solution in Peninsular Malaysia: optimal parameters for LoRa data |
| title_full_unstemmed | Peatland forest monitoring and management solution in Peninsular Malaysia: optimal parameters for LoRa data |
| title_short | Peatland forest monitoring and management solution in Peninsular Malaysia: optimal parameters for LoRa data |
| title_sort | peatland forest monitoring and management solution in peninsular malaysia: optimal parameters for lora data |
| url | http://psasir.upm.edu.my/id/eprint/121006/ http://psasir.upm.edu.my/id/eprint/121006/ http://psasir.upm.edu.my/id/eprint/121006/ http://psasir.upm.edu.my/id/eprint/121006/1/121006.pdf |