@conference{Griva2021,

title = {Performance Evaluation of LoRa Networks in an Open Field Cultivation Scenario},

author = { A. Griva and A.D. Boursianis and S. Wan and P. Sarigiannidis and G. Karagiannidis and S.K. Goudos},

url = {https://www.researchgate.net/publication/353498225_Performance_Evaluation_of_LoRa_Networks_in_an_Open_Field_Cultivation_Scenario},

doi = {10.1109/MOCAST52088.2021.9493416},

year  = {2021},

date = {2021-01-01},

journal = {2021 10th International Conference on Modern Circuits and Systems Technologies, MOCAST 2021},

abstract = {The employment of Internet of Things (IoT) technology in agriculture could be beneficial in managing the cultivation production in a highly-customizable way. LoRa (Long Range) is one of the most important technologies in cultivation fields mainly thanks to its ability to provide long-range transmission and low power consumption. In this paper, we evaluate the performance of LoRa networks in an open field cultivation scenario via simulations using FLoRa, an open-source framework in OMNeT++. The number of nodes, the number of gateways, the antenna gain, and the size of the deployment area have a considerable impact on both the data extraction rate and the energy consumption of a LoRa network. Our results show that the optimization of the parameters that affect the performance of a LoRa network could transform traditional agriculture into a new perspective of smart cultivation. Finally, we evaluate the impact of the density and the geometric characteristics of three types of crop (tomatoes, grapes, apples) on the number of intersections that were caused by the insertion of physical objects-obstacles in a LoRa network. © 2021 IEEE.},

keywords = {Data Extraction Rate, Internet of Things (IoT), Long Range (LoRa), Network Energy Consumption, Smart Agriculture},

pubstate = {published},

tppubtype = {conference}

}