OPTIMAL WIFI POSITION DETECTION USING ARTIFICIAL INTELLIGENCE

Heena Agrawal, Rahul Agrawal, Rohit Chandani, Sakshi Nema
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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
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利用人工智能优化wifi位置检测
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
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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
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