MUMBAI, India, June 22 -- Intellectual Property India has published a patent application (202641048935 A) filed by E Kanaka; S. Keerthipriya; Dr. T. Poonkodi; K. Fouzia Sulthana; Dr. T,julie Mary; and Dr, B. Gunasundari on April 17, 2026, for Digital Twin Based Predictive Maintenance Framework For Smart Cities.
Inventors include E Kanaka; S. Keerthipriya; Dr. T. Poonkodi; K. Fouzia Sulthana; Dr. T,julie Mary; and Dr, B. Gunasundari.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: ABSTRACT The rapid development of smart city infrastructure requires intelligent systems to monitor asset health and predict potential failures. This study proposes a Digital Twin-based predictive maintenance framework for smart cities that integrates real-time sensor data with artificial intelligence to monitor critical infrastnicture such as transportation systems, power grids, and utility networks. The framework creates a digital twin, a virtual representation of physical assets, enabling continuous monitoring and analysis of system performance. The proposed framework employs the Extreme Gradient Boosting (XGBoost) algorithm to analyze sensorgenerated time-series data, including temperature, vibration, pressure, and energy consumption. The collected data is preprocessed and synchronized with the digital twin model to reflect the real-time state of the physical system. The XGBoosf model learns relationships between operational parameters and equipment health to predict potential failures in advance. When the system detects a high risk of failure, maintenance alerts are generated to enable proactive intervention, reducing downtime and operational costs. The proposed framework improves the reliability and efficiency of infrastructure management in smart cities by combining digital twin technology with advanced machine learning techniques
Disclaimer: Curated by HT Syndication.
