A Novel Relay-Node Deployment Method Guided by Installation Heat for Fixed Rubber Tapping Machine Group in Rubber Forest

The fixed rubber tapping machine (FRTM) is a key piece of equipment for mechanized rubber tapping and is characterized by high-density, large-group deployment under the forest canopy. With the application of artificial intelligence technology, group communication control for FRTMs has become an important and novel research direction. In this paper, based on a LoRa communication network, a novel relay-node deployment method guided by an installation heat mode (a deployment-priority index for FRTM installation) is proposed for FRTM groups in rubber forests and is applied for testing. By integrating installation dimensions, latex yield, and trunk quasi-cylindricity across rubber trees, a novel installation heat mode for FRTMs is constructed based on diameter at breast height (DBH). A logarithmic path loss model is established for a specific rubber plantation in Danzhou and D724W1-LoRa relay nodes; the effective range of the relay nodes is determined, and their forest communication performance and group sleep strategy are evaluated experimentally. The deployment positions of the relay nodes are determined using a finite-depth enumeration search algorithm. A hybrid mesh-star network comprising FRTMs and relay nodes is deployed in Baodao Xincun, Danzhou, achieving an average communication failure rate of 0.6% under normal and rainy weather conditions and demonstrating high reliability. The proposed method provides a practical solution for large-scale FRTM cluster management in tropical plantations.

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Publication Details

Journal
Agriculture
Published
2026-09-27
DOI
https://doi.org/10.3390/agriculture16192097
Primary Topic
IoT Networks and Protocols
Type
article
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A Novel Relay-Node Deployment Method Guided by Installation Heat for Fixed Rubber Tapping Machine Group in Rubber Forest

Xin Su, Suwei Xiao, Zihao Wang, Bo Fan et al.
Agriculture
IoT Networks and Protocols
article

A Novel Relay-Node Deployment Method Guided by Installation Heat for Fixed Rubber Tapping Machine Group in Rubber Forest

Xin Su, Suwei Xiao, Zihao Wang, Bo Fan, Sihao Wu, Jianhua Cao
article en

Abstract

The fixed rubber tapping machine (FRTM) is a key piece of equipment for mechanized rubber tapping and is characterized by high-density, large-group deployment under the forest canopy. With the application of artificial intelligence technology, group communication control for FRTMs has become an important and novel research direction. In this paper, based on a LoRa communication network, a novel relay-node deployment method guided by an installation heat mode (a deployment-priority index for FRTM installation) is proposed for FRTM groups in rubber forests and is applied for testing. By integrating installation dimensions, latex yield, and trunk quasi-cylindricity across rubber trees, a novel installation heat mode for FRTMs is constructed based on diameter at breast height (DBH). A logarithmic path loss model is established for a specific rubber plantation in Danzhou and D724W1-LoRa relay nodes; the effective range of the relay nodes is determined, and their forest communication performance and group sleep strategy are evaluated experimentally. The deployment positions of the relay nodes are determined using a finite-depth enumeration search algorithm. A hybrid mesh-star network comprising FRTMs and relay nodes is deployed in Baodao Xincun, Danzhou, achieving an average communication failure rate of 0.6% under normal and rainy weather conditions and demonstrating high reliability. The proposed method provides a practical solution for large-scale FRTM cluster management in tropical plantations.

AgricultureVol. 16(19)
Chinese Academy of Tropical Agricultural Sciences (CN), Huazhong Agricultural University (CN), Rubber Research Institute (CN), Puer University (CN)
Life in Land
Openalex Percentile: Top 21%
IoT Networks and Protocols
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A Novel Relay-Node Deployment Method Guided by Installation Heat for Fixed Rubber Tapping Machine Group in Rubber Forest — Xin Su, Suwei Xiao, et al. · Agriculture (2026) | TGRS Research Map | TGRS