MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641080904 A) filed by Madhankumar C; Dr. V. Arulmozhi; Ramu Pasam; Geetha R; Jackson J; Ms. Indra Priya; and Mr. F. Ravindaran on July 01, 2026, for Self-Evolving Blockchain-Secured Quantum Digital Twin Architecture For Smart Cities, Renewable Energy Optimization, And Autonomous Infrastructure Intelligence.
Inventors include Dr. V. Arulmozhi; Ramu Pasam; Geetha R; Jackson J; Ms. Indra Priya; and Mr. F. Ravindaran.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: Self-Evolving Blockchain-Secured Quantum Digital Twin Architecture for Smart Cities, Renewable Energy Optimization, and Autonomous Infrastructure Intelligence Abstract The rapid growth of smart cities demands intelligent, secure, and autonomous infrastructure capable of managing increasingly complex urban environments while ensuring sustainability, resilience, and real-time decision-making. Conventional digital twin frameworks often suffer from centralized architectures, limited scalability, cybersecurity vulnerabilities, and inefficient coordination among heterogeneous urban systems. To address these challenges, this research proposes a Self-Evolving Blockchain-Secured Quantum Digital Twin Architecture (SBQ-DTA) that integrates blockchain technology, quantum inspired optimization, artificial intelligence, edge computing, and digital twin intelligence into a unified next-generation smart city ecosystem. The proposed framework creates real-time digital replicas of critical urban assets, including renewable energy grids, transportation networks, water distribution systems, healthcare facilities, and public infrastructure. Internet of Things (IoT) sensors continuously collect multidimensional environmental and operational data, while AI-driven learning models analyze system behavior to predict failures, optimize resource allocation, and autonomously adapt to changing urban conditions. A blockchain-enabled trust layer provides decentralized authentication, immutable data storage, secure identity management, and transparent transaction validation, ensuring data integrity and resistance against cyber threats. Furthermore, quantum-inspired optimization algorithms enhance large-scale scheduling, energy balancing, traffic routing, and resource distribution with significantly improved computational efficiency. Unlike traditional digital twins, the proposed architecture incorporates a self evolving cognitive intelligence engine that continuously learns from historical data, citizen behavior, environmental dynamics, and infrastructure performance. Reinforcement learning and federated learning mechanisms enable decentralized model training while preserving data privacy across multiple city departments. Autonomous decision-making modules dynamically optimize renewable energy generation, electric vehicle charging, smart grid stability, waste management, disaster response, and predictive maintenance without requiring centralized human intervention. The architecture also integrates explainable artificial intelligence (XAI) to improve transparency and interpretability of automated decisions, allowing city administrators to understand optimization strategies and policy recommendations. Digital twin synchronization between physical and virtual environments enables real-time simulation, risk assessment, and scenario forecasting for emergency management, climate resilience, and sustainable urban planning. Edge-cloud collaboration minimizes communication latency while improving scalability and reliability for mission-critical smart city applications. The expected outcomes include enhanced cybersecurity, reduced operational costs, increased renewable energy utilization, lower carbon emissions, improved infrastructure reliability, optimized traffic flow, intelligent resource management, and resilient urban services. Experimental evaluation will compare the proposed framework with existing blockchain-enabled and AI-based smart city architectures using performance metrics such as prediction accuracy, latency, energy efficiency, blockchain transaction throughput, resource utilization, fault detection rate, scalability, privacy preservation, and Quality of Service (QoS). The proposed Self-Evolving Blockchain-Secured Quantum Digital Twin Architecture establishes a transformative foundation for future autonomous smart cities by combining trusted decentralized intelligence, adaptive digital twins, quantum-inspired optimization, and sustainable infrastructure management, thereby contributing to the realization of secure, intelligent, and carbon-neutral urban ecosystems.
Disclaimer: Curated by HT Syndication.
