Internet of Things Technology for Photovoltaic Smart Sprinkler Systems and Its Analysis

Author:

Chinonyelum Ejimuda1,Kingsley Okoli2,Lilian Uzodiagu3,Juliet Olusola4

Affiliation:

1. Department of Mechanical Engineering, Texas A & M University, USA/ Controls Lab, Texas A & M University, USA

2. Department of Computer Science and Knowledge Discovery, Saint Petersburg Electrotechnical University LETI, Saint Petersburg, Russia/ Artificial Intelligence Lab, University of Nigeria, Nsukka, Nigeria

3. Department of Electrical and Electronics Engineering, Bells University of Technology, Ota, Ogun State, Nigeria

4. Department of Electrical and Electronics Engineering, Afe Babalola University, Ado-Ekiti, Ekiti State, Nigeria

Abstract

Abstract The advancement of technology has brought about ease of life with the help of technology automation which can be applied virtually in all aspects of living. With the emergence of internet of things, prototyping real state systems has become less expensive and easy to embark on thus creating platforms for development in the oil & gas sector. This research aims to analyze, design, and develop an effortless system powered via solar energy for the control of a sprinkler system and liquid flow void of human intervention. The system was programmed using an Arduino board and other hardware at an adjustable set time with Arduino software. The research is geared at reducing human efforts in irrigation systems, to save cost and time in sprinkling liquid on any system. The use of some weather parameters like humidity, temperature, and moisture sensors; Arduino kits and GSM module constitutes the smart irrigation system setup. The system is automated to feed the necessary quantity of liquid to any given surface based on design parameters with the moisture sensor programmed within 0 to 1023 (0-100%) range. The system adapted a method of pump-start at 40% moisture reading. Various analysis of the research findings has been presented in the work with applicability in remote areas and oil fields void of human intervention.

Publisher

SPE

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3