LSTM Enabled Artificial Intelligent Smart Gardening System

M. Saad, Muhammad Toaha Raza Khan, M. Tariq, Dongkyun Kim
{"title":"LSTM Enabled Artificial Intelligent Smart Gardening System","authors":"M. Saad, Muhammad Toaha Raza Khan, M. Tariq, Dongkyun Kim","doi":"10.1145/3400286.3418260","DOIUrl":null,"url":null,"abstract":"In the present era, internet of things (IoT) is prevailing very much in our daily life serving the concept of the smart applications, in which one can operate remote objects from a distant place. However, connectivity of the billions of devices has become a major concern in most of the prevailing researches. Massive connected devices used for smart applications consumes the network resources such as bandwidth and consumes the power to operate. Due to limited bandwidth, intermittent connectivity issues arises between smart devices which incorporates delay in the network. LoRaWAN (Long range Low power wide area network) developed by SemtechTM is a MAC layer protocol developed primarily for the IoT devices. In this paper, we implemented Long Short Term (LSTM) based smart gardening system, where end nodes collect the data from surrounding and sends to gateway using LoRa protocol. Edge Server is installed with the gateway on which LSTM based machine learning algorithm is running which predicts the future sensor values. For the predicted interval of time gateway sends the message to end nodes to remain inactive which saves the network bandwidth and also increases the life of sensors.","PeriodicalId":326100,"journal":{"name":"Proceedings of the International Conference on Research in Adaptive and Convergent Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Research in Adaptive and Convergent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3400286.3418260","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

In the present era, internet of things (IoT) is prevailing very much in our daily life serving the concept of the smart applications, in which one can operate remote objects from a distant place. However, connectivity of the billions of devices has become a major concern in most of the prevailing researches. Massive connected devices used for smart applications consumes the network resources such as bandwidth and consumes the power to operate. Due to limited bandwidth, intermittent connectivity issues arises between smart devices which incorporates delay in the network. LoRaWAN (Long range Low power wide area network) developed by SemtechTM is a MAC layer protocol developed primarily for the IoT devices. In this paper, we implemented Long Short Term (LSTM) based smart gardening system, where end nodes collect the data from surrounding and sends to gateway using LoRa protocol. Edge Server is installed with the gateway on which LSTM based machine learning algorithm is running which predicts the future sensor values. For the predicted interval of time gateway sends the message to end nodes to remain inactive which saves the network bandwidth and also increases the life of sensors.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
LSTM支持的人工智能智能园艺系统
在当今时代,物联网(IoT)在我们的日常生活中非常盛行,服务于智能应用的概念,其中人们可以从遥远的地方操作远程对象。然而,数十亿设备的连接已成为大多数主流研究的主要关注点。智能应用中大量连接的设备消耗带宽等网络资源,也消耗运行的电力。由于带宽有限,智能设备之间出现间歇性连接问题,其中包含网络延迟。由SemtechTM开发的LoRaWAN(远程低功率广域网)是主要为物联网设备开发的MAC层协议。在本文中,我们实现了基于LSTM (Long Short Term)的智能园艺系统,在该系统中,终端节点通过LoRa协议从周围收集数据并发送到网关。边缘服务器安装了网关,在网关上运行基于LSTM的机器学习算法,该算法预测未来的传感器值。在预计的时间间隔内,网关向终端节点发送消息,使其处于非活动状态,从而节省了网络带宽,延长了传感器的寿命。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An Extrinsic Depth Camera Calibration Method for Narrow Field of View Color Camera Motion Mode Recognition for Traffic Safety in Campus Guiding Application Failure Prediction by Utilizing Log Analysis: A Systematic Mapping Study PerfNet Road Surface Profiling based on Artificial-Neural Networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1