Intelligent Network Signal Strength Optimization using Machine Learning and Real-Time Analytics

Ganesh, P. Shree; Mohamed, I. Raja; Suriya, V.; Eekash, E.

doi:https://doi.org/10.55041/ijsmt.v2i4.381

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INTELLIGENT NETWORK SIGNAL STRENGTH OPTIMIZATION USING MACHINE LEARNING AND REAL-TIME ANALYTICS

AUTHORS:

P. Shree Ganesh

I. Raja Mohamed

V. Suriya

E. Eekash

Mentor

K. Dasarathi Shohi

Affiliation

Artificial Intelligence and Data Science, M.I.E.T. Engineering College Trichy, India

DOI: 10.55041/ijsmt.v2i4.381

CC BY 4.0 License:

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract

The growing reliance on wireless communication has made network signal strength essential for seamless connectivity. However, users often experience issues such as weak signals, interference, and network congestion, especially in indoor and dense environments. This paper proposes a Network Signal Strength Optimization App that uses Artificial Intelligence (AI) and Machine Learning (ML) to monitor and analyze key parameters like RSSI, SNR, and Latency in real time. The system provides personalized recommendation, predictive insights, and signal heat maps to improve connectivity. The proposed solution enhances user experience, ensure reliable network performance, and offers a scalable and efficient approach to modern wireless communication challenges.

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✓ All ethical standards met

This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.

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