Precision agriculture using IoT data analytics and machine learning

被引:167
作者
Akhter, Ravesa [1 ]
Sofi, Shabir Ahmad [1 ]
机构
[1] Natl Inst Technol Srinagar, Dept Informat Technol, Hazratbal 190006, Jammu & Kashmir, India
关键词
Internet of things (IoT); Data analytics (DA); Machine learning (ML); WIRELESS SENSOR NETWORKS; DATA INTEGRATION; CROP LOSSES; THINGS IOT; INTERNET; YIELD; FERTILIZATION; NITROGEN; SYSTEMS; CLOUD;
D O I
10.1016/j.jksuci.2021.05.013
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In spite of the insight commonality may have concerning agrarian practice, fact is that nowadays agricul-tural science diligence is accurate, precise, data-driven, and vigorous than ever. The emanation of the technologies based on Internet of Things (IoT) has reformed nearly each industry like smart city, smart health, smart grid, smart home, including "smart agriculture or precision agriculture". Applying machine learning using the IoT data analytics in agricultural sector will rise new benefits to increase the quantity and quality of production from the crop fields to meet the increasing food demand. Such world-shattering advancements are rocking the current agrarian approaches and generating novel and best chances besides a number of limitations. This paper climaxes the power and capability of computing techniques including internet of things, wireless sensor networks, data analytics and machine learning in agriculture. The paper proposed the prediction model of Apple disease in the apple orchards of Kashmir valley using data analytics and Machine learning in IoT system. Furthermore, a local survey was conducted to know from the farmers about the trending technologies and their effect in precision agriculture. Finally, the paper discusses the challenges faced when incorporating these technologies in the traditional farming approaches.(c) 2021 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:5602 / 5618
页数:17
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