DOI

Internet of Things (IoT) technologies represent the future challenges of computing and communications. They can also be useful to improve traditional farming practices worldwide. Since the areas where agricultural land is located in remote places, there is a need for new technologies. These technologies must be suitable and reliable for communication over long distances and, at the same time, consume little energy. In particular, one of these relatively new technologies is the LoRa communication protocol, which uses long waves to work over long distances. This is extremely useful in agriculture, where the communicating areas are broad fields of crops and greenhouses. This study developed a greenhouse monitoring system based on LoRa technology, designed to work over long distances. The edge computing paradigms with a machine learning mechanism are proposed to analyze and control the state of the greenhouse, and in particular, to reduce the mount of data transmitted to the server.

Язык оригиналаанглийский
Название основной публикацииDistributed Computer and Communication Networks - 23rd International Conference, DCCN 2020, Revised Selected Papers
РедакторыVladimir M. Vishnevskiy, Dmitry V. Kozyrev, Konstantin E. Samouylov, Dmitry V. Kozyrev
ИздательSpringer Nature
Страницы113-125
Число страниц13
ISBN (печатное издание)9783030664701
DOI
СостояниеОпубликовано - 2020
Событие23rd International Conference on Distributed Computer and Communication Networks, DCCN 2020 - Moscow, Российская Федерация
Продолжительность: 14 сен 202018 сен 2020

Серия публикаций

НазваниеLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Том12563 LNCS
ISSN (печатное издание)0302-9743
ISSN (электронное издание)1611-3349

конференция

конференция23rd International Conference on Distributed Computer and Communication Networks, DCCN 2020
Страна/TерриторияРоссийская Федерация
ГородMoscow
Период14/09/2018/09/20

    Предметные области Scopus

  • Теоретические компьютерные науки
  • Компьютерные науки (все)

ID: 87324492