利用人工智能优化wifi位置检测

IF 0.3
Heena Agrawal, Rahul Agrawal, Rohit Chandani, Sakshi Nema
{"title":"利用人工智能优化wifi位置检测","authors":"Heena Agrawal, Rahul Agrawal, Rohit Chandani, Sakshi Nema","doi":"10.47164/ijngc.v14i1.1027","DOIUrl":null,"url":null,"abstract":"The placement of WI-FI routers in the network is an intensive problem concerning connectivity and coverage.It directly affects the transmission loss, installation cost, operational complexity, wi-fi network coverage, etc.However, optimizing the location of the routers can resolve these issues and increase network performance. Thus,using major deep-learning models the problem is resolved. The proposed model concentrates on the optimization of the objective function in terms of the empty spaces, hindrances such as concrete walls, metallic objects, etc. in the area, maximum client coverage in the location, and the network connectivity. It is an initial step to ensure the desired network performance such as throughput, connectivity, and coverage of the network.. Furthermore, a Wi-Fi analyzing system for generating the results based on the observations of the Wi-Fi router network is implemented. It analyzes the wireless network, devices in the network, and the connected users. The model also gives a WLAN report of the Wi-Fi router","PeriodicalId":42021,"journal":{"name":"International Journal of Next-Generation Computing","volume":"44 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"OPTIMAL WIFI POSITION DETECTION USING ARTIFICIAL INTELLIGENCE\",\"authors\":\"Heena Agrawal, Rahul Agrawal, Rohit Chandani, Sakshi Nema\",\"doi\":\"10.47164/ijngc.v14i1.1027\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The placement of WI-FI routers in the network is an intensive problem concerning connectivity and coverage.It directly affects the transmission loss, installation cost, operational complexity, wi-fi network coverage, etc.However, optimizing the location of the routers can resolve these issues and increase network performance. Thus,using major deep-learning models the problem is resolved. The proposed model concentrates on the optimization of the objective function in terms of the empty spaces, hindrances such as concrete walls, metallic objects, etc. in the area, maximum client coverage in the location, and the network connectivity. It is an initial step to ensure the desired network performance such as throughput, connectivity, and coverage of the network.. Furthermore, a Wi-Fi analyzing system for generating the results based on the observations of the Wi-Fi router network is implemented. It analyzes the wireless network, devices in the network, and the connected users. The model also gives a WLAN report of the Wi-Fi router\",\"PeriodicalId\":42021,\"journal\":{\"name\":\"International Journal of Next-Generation Computing\",\"volume\":\"44 1\",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2023-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Next-Generation Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47164/ijngc.v14i1.1027\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Next-Generation Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47164/ijngc.v14i1.1027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

WI-FI路由器在网络中的位置是一个涉及连接和覆盖的密集问题。它直接影响到传输损耗、安装成本、操作复杂性、wi-fi网络覆盖等。而优化路由器的位置可以解决这些问题,提高网络性能。因此,使用主要的深度学习模型可以解决这个问题。所提出的模型侧重于目标函数的优化,包括区域内的空空间、混凝土墙、金属物体等障碍物、位置内最大客户覆盖率和网络连通性。这是确保所需的网络性能(如吞吐量、连接性和网络覆盖)的第一步。此外,还实现了基于对Wi-Fi路由器网络的观察产生结果的Wi-Fi分析系统。它分析了无线网络、网络中的设备和连接的用户。该模型还给出了Wi-Fi路由器的WLAN报告
本文章由计算机程序翻译,如有差异,请以英文原文为准。
OPTIMAL WIFI POSITION DETECTION USING ARTIFICIAL INTELLIGENCE
The placement of WI-FI routers in the network is an intensive problem concerning connectivity and coverage.It directly affects the transmission loss, installation cost, operational complexity, wi-fi network coverage, etc.However, optimizing the location of the routers can resolve these issues and increase network performance. Thus,using major deep-learning models the problem is resolved. The proposed model concentrates on the optimization of the objective function in terms of the empty spaces, hindrances such as concrete walls, metallic objects, etc. in the area, maximum client coverage in the location, and the network connectivity. It is an initial step to ensure the desired network performance such as throughput, connectivity, and coverage of the network.. Furthermore, a Wi-Fi analyzing system for generating the results based on the observations of the Wi-Fi router network is implemented. It analyzes the wireless network, devices in the network, and the connected users. The model also gives a WLAN report of the Wi-Fi router
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
International Journal of Next-Generation Computing
International Journal of Next-Generation Computing COMPUTER SCIENCE, THEORY & METHODS-
自引率
66.70%
发文量
60
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信