4.8 Article

Collection of Data With Drones in Precision Agriculture: Analytical Model and LoRa Case Study

期刊

IEEE INTERNET OF THINGS JOURNAL
卷 8, 期 22, 页码 16692-16704

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2021.3075561

关键词

Drones; Sensors; Agriculture; Logic gates; Data models; Data collection; Base stations; Drones; Internet of Things (IoT); long range (LoRa); optimal data collection; precision agriculture

资金

  1. EU's Horizon 2020 Programme through Project SHAPES [857159]
  2. Spanish Ministry of Economy and Competitiveness through Project PLATINO [TEC2017-86722-C44-R]
  3. Regional Government of Castilla-La Mancha through Project SymbIoT [SB-PLY/17/180501/000334]
  4. Progetto TEBAKA [ARS01_00815, 1735]

向作者/读者索取更多资源

This article examines how drones using LoRa radio need to fly over sensors to ensure quality data collection, providing analysis for proper spacing of sensors during deployment, drone selection, and addressing tradeoffs related to field size, drone autonomy, and data collection paths.
Unmanned aerial vehicles (UAVs) are autonomous devices employed as data collectors in precision agriculture to support a large number of applications. These UAVs gather data from on-the-ground wireless sensor networks, especially in scenarios that lack any kind of fixed communication infrastructure or where the available infrastructure does not fit the application requirements. Sensors on the ground can store sensing data, and in scenarios that do not require a real-time observation and analysis of the data, like in smart farming, a drone can be used maybe once or two times each day to collect and report the data to a command-and-control center that use them directly, without any other infrastructure (cloud or edges). In this article, we study analytically how close the drone, that uses a LoRa radio, needs to fly over the sensors to collect data with a given quality of data collection. This can be used to properly spacing the sensors on the field at deployment time, to select among different type of drones, and to properly solve some tradeoff related to field size vs autonomy of the drones and the path used by the latter when collecting the data.

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