Heena Agrawal
Rahul Agrawal
Rohit Chandani
Sakshi Nema


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


Author Biography

Heena Agrawal, Shri Ramdeobaba College of Engineering and Management, Nagpur

Heena Agrawal is currently working as an Assistant Professor in the Computer Science
and Engineering Department, Shri Ramdeobaba College of Engineering and Management,

How to Cite
Heena Agrawal, Rahul Agrawal, Rohit Chandani, & Sakshi Nema. (2023). OPTIMAL WIFI POSITION DETECTION USING ARTIFICIAL INTELLIGENCE. International Journal of Next-Generation Computing, 14(1). https://doi.org/10.47164/ijngc.v14i1.1027


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