MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202641101592 A) filed by Sr University on August 22, 2026, for A Digital Twin And Machine Learning Enabled System For Predictive Fault Detection And Autonomous Service Reconfiguration In Uav-Assisted C-Ran Networks.
Inventors include Hareesh Ayanampudi; Shaik Thaherbasha; and Syed Nageena Parveen.
The application for the patent was published on August 28, 2026, under issue no. 35/2026.
Abstract: A DIGITAL TWIN AND MACHINE LEARNING ENABLED SYSTEM FOR PREDICTIVE FAULT DETECTION AND AUTONOMOUS SERVICE RECONFIGURATION IN UAV-ASSISTED C-RAN NETWORKS The present invention relates to a digital twin and machine learning enabled system for predictive fault detection and autonomous service reconfiguration in UAV- assisted Cloud Radio Access Network (C-RAN) networks. The system comprises one or more Unmanned Aerial Vehicles (UAVs), a baseband unit pool, sensors, a digital twin engine, a machine learning-based fault prediction engine, and an autonomous decision engine. The sensors monitor UAV parameters including battery state-of-charge, motor and rotor performance, radio-frequency impairments, wind, temperature, and humidity. A digital twin engine generates and updates virtual replicas of UAVs for representing hardware, software, environmental interactions, component couplings, and degradation patterns. The machine learning-based fault prediction engine predicts component-level failures and remaining useful life using multi-modal information from RF, mechanical, power, and environmental sensors. Based on predicted faults, the autonomous decision engine performs proactive service switching, health-aware UAV clustering, cluster-head selection, and dynamic resource reallocation including bandwidth, transmit power, altitude, or beam direction. Critical UAVs may return to base or enter low-power monitoring mode. The invention provides predictive self- healing, improved connectivity, energy efficiency, UAV safety, and operational lifetime for UAV-assisted C-RAN networks.
Disclaimer: Curated by HT Syndication.
