MUMBAI, India, Oct. 12 -- Intellectual Property India has published a patent application (202641118906 A) filed by Mlr Institute Of Technology; and Marri Laxman Reddy Institute Of Technology And Management on October 05, 2026, for A System And Method For Wifi Usage Monitoring And Network Performance Prediction In Hostel Networks.
Inventors include Mrs. D. Sravanthi; Mr. Shashank Guduri; Mr. Ch. Lokesh Sai; Ms. A. Harika; and Mr. K. Shyam.
The application for the patent was published on October 09, 2026, under issue no. 41/2026.
Abstract: The present invention relates to a WiFi usage monitoring and network performance prediction system for hostel networks shared by multiple users. The system is configured to collect, process, store, and analyze network performance parameters, including download speed, upload speed, latency, jitter, and packet loss, using automated speed testing and operating system-based ping commands. The collected data is stored in a local SQLite database and accessed through a Flask-based Representational State Transfer (REST) Application Programming Interface (API). A web-based dashboard provides real-time visualization of network performance through trend charts, peak usage heatmaps, and alerts. The system further incorporates a Random Forest machine learning model trained on historical network measurements using seventeen engineered features to predict network performance for subsequent hours, along with associated confidence intervals. A recommendation module identifies and ranks upcoming time slots based on predicted download speeds to assist users in selecting periods of improved network availability. The system employs a modular architecture capable of supporting multiple access points and concurrent users, facilitating integration with existing hostel network infrastructures. Data privacy and security mechanisms are incorporated to protect user-related information while enabling aggregated network analysis. The system further supports potential extensions for automated bandwidth management, anomaly detection, and administrator notifications, thereby facilitating data-driven network monitoring and management in shared hostel environments.
Disclaimer: Curated by HT Syndication.
