IJSDR
IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: March 2024

Volume 9 | Issue 3

Impact factor: 8.15

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Paper Title: Smart and Safe Agriculture in Arid Locations Utilizing 5G, IOT and Machine Learning
Authors Name: A. Divya Chandana , S.Ghufrana Nousheen , G.Manasa , K.Jummelal
Unique Id: IJSDR2208011
Published In: Volume 7 Issue 8, August-2022
Abstract: Regardless of how people perceive the agricultural process, the truth is that today's agriculture business is more data-driven, accurate, and intelligent than ever. The fast rise of Internet-of-Things (IoT)-based technology changed nearly every industry, including smart agriculture, shifting the industry away from statistical to quantitative techniques. Such dramatic innovations are upsetting established agricultural systems and opening up new chances in the face of a variety of obstacles. This article discusses the possibilities of wireless sensors and IoT in agriculture, as well as the obstacles that will be encountered when this technology is integrated with traditional farming techniques. The Internet of Things devices and communication mechanisms related with wireless sensors used in agriculture applications are thoroughly examined. There is a list of sensors available for specialized agricultural applications such as soil preparation, crop status, irrigation, insect and pest detection. It is detailed how this technology assists producers throughout the agricultural phases, from seeding to harvesting, packaging, and shipping. In this study, we are not only detecting and diagnosing crop illnesses, but also forecasting the quantity of pesticides needed to prevent or manage pests. In this paper, the author claims that he will monitor crops using 5G connections and IOT devices, with IOT devices capturing crop images and then sending those images to a centralized server where machine learning algorithms will predict disease and suggest chemicals to farmers. However, we do not have such IOT sensors, so we are using the PLANT VILLAGE Disease dataset, which contains more than 20 different plant diseases. So, in this project, the dataset will be considered as the data collecting module, and we will then use the CNN machine learning model to forecast disease and prescribe drugs
Keywords: Agriculture, IOT, Sensors, CNN Algorithm, Machine Learning
Cite Article: "Smart and Safe Agriculture in Arid Locations Utilizing 5G, IOT and Machine Learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 8, page no.88 - 94, August-2022, Available :http://www.ijsdr.org/papers/IJSDR2208011.pdf
Downloads: 000336256
Publication Details: Published Paper ID: IJSDR2208011
Registration ID:200848
Published In: Volume 7 Issue 8, August-2022
DOI (Digital Object Identifier):
Page No: 88 - 94
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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