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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