FLog: Automated Modeling of Link Quality for LoRa Networks in Orchards
Year: 2025
Type: article
Abstract: LoRa networks have been deployed in many orchards for environmental monitoring and crop management. An accurate propagation model is essential for efficiently deploying a LoRa network in orchards, e.g., determining gateway coverage and sensor placement. Although some propagation models have been studied for LoRa networks, they are not suitable for orchard environments, because they do not consider the shadowing effect on wireless propagation caused by the ground and tree canopies. This article presents FLog , a propagation model for LoRa signals in orchard environments. FLog leverages a unique feature of orchards, i.e., all trees have similar shapes and are planted regularly in space. We develop a three-dimensional model of orchards. Once we have the location of a sensor and a gateway, we know the media that the wireless signal traverses. Based on this knowledge, we generate the First Fresnel Zone (FFZ) between the sender and the receiver. The intrinsic path loss exponents of all media can be combined into a classic Log-Normal Shadowing model in the FFZ. Extensive experiments in almond orchards show that FLog reduces the link quality estimation error by 42.7% and improves gateway coverage estimation accuracy by 70.3%, compared with a widely used propagation model. The source codes and dataset are released at https://github.com/ycucm/Flog .
DOI: 10.1145/3718741
Authors: Kang Yang, Yuning Chen, Wan Du
Institution: University of California, Merced
Language: English
Topic: IoT Networks and Protocols
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4407813665