IoT and Machine Learning Approaches for Automation of Farm Irrigation System

被引:86
作者
Vij, Anneketh [1 ]
Vijendra, Singh [2 ]
Jain, Abhishek [1 ]
Bajaj, Shivam [1 ]
Bassi, Aashima [1 ]
Sharma, Arushi [1 ]
机构
[1] NorthCap Univ, Dept Comp Sci, Sect 23-A, Gurugram 122017, Haryana, India
[2] Univ Petr & Energy Studies, Sch Comp Sci, Dept Informat, Dehra Dun, Uttarakhand, India
来源
INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND DATA SCIENCE | 2020年 / 167卷
关键词
IoT; WSN; Machine Leaming; Algorithms; Technology; Agriculture;
D O I
10.1016/j.procs.2020.03.440
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the current age of high competition and risk in markets, technological advancements are a must for better growth and sustainability. The same applies to the agriculture industry. Every farmer has high stakes on the crops, their yield and quality. Rising water issues and need for proper methodologies for farm maintenance is a hot issue that needs to be tackled at utmost propriety. An automation of irrigation systems in farms is proposed in this research. The proposed solution is based on the Internet of Things (IoT), which would be a cheaper and more precise solution to the farm needs. A Monitoring system whose main purpose is to solve the over irrigation, soil erosion and crop -specific irrigation problem will be developed to ease and efficiently manage Irrigation problems. Since it is a well-known fact that the water is a scarce resource and over wastage of such an essential resource should be minimized The proposed solution will be developed by establishing a distributed wireless sensor network (WSN), wherein each region of the farm would be covered by various sensor modules which will be transmitting data on a common server. Machine learning (ML) algorithms will support predictions for irrigation patterns based on crops and weather scenarios. So, a sustainable approach to irrigation is provided in this paper. (C) 2020 The Authors. Published by Elsevier B.V.
引用
收藏
页码:1250 / 1257
页数:8
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