MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202641081457 A) filed by Madhankumar C; Mrs. V. Nandhini; D. Hemamalini; E. Anitha; A. Sri Sakthi - Kpr Institute Of Engineering And Technology, Arasur, Coimbatore, Tamil Nadu, India; Thulir B; and Mr. Rajesh Thangella on July 02, 2026, for Quantum-Ai Enabled Bio-Cybernetic Smart Ecosystem For Autonomous Disease Prediction, Secure Healthcare Communication, And Adaptive Nano-Robotic Therapy.
Inventors include Mrs. V. Nandhini; D. Hemamalini; E. Anitha; A. Sri Sakthi - Kpr Institute Of Engineering And; Thulir B; and Mr. Rajesh Thangella.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: Quantum-AI Enabled Bio-Cybernetic Smart Ecosystem for Autonomous Disease Prediction, Secure Healthcare Communication, and Adaptive Nano-Robotic Therapy Abstract The rapid evolution of healthcare technologies demands intelligent, secure, and autonomous systems capable of providing real-time disease diagnosis and personalized treatment. This invention presents a Quantum-AI Enabled Bio Cybernetic Smart Ecosystem that integrates Quantum Artificial Intelligence (Quantum AI), bio-cybernetic sensing, secure healthcare communication, digital twin technology, and adaptive nano-robotic therapy into a unified intelligent healthcare framework. The proposed ecosystem continuously acquires physiological, biochemical, genetic, and environmental data through wearable sensors, implantable biomedical devices, and IoT-enabled healthcare networks. Advanced Quantum AI algorithms process these multidimensional datasets to detect hidden disease patterns, predict disease progression, and recommend personalized treatment strategies with enhanced computational efficiency. To ensure secure transmission and privacy of sensitive medical information, the system employs blockchain-assisted encryption, post-quantum cryptographic mechanisms, and decentralized healthcare communication protocols, enabling tamper-resistant and trustworthy medical data exchange among hospitals, physicians, laboratories, and patients. A real-time bio-cybernetic digital twin of each patient is dynamically generated to simulate physiological responses, evaluate treatment outcomes, and optimize therapeutic interventions before actual clinical implementation. Furthermore, the ecosystem incorporates adaptive nano-robotic therapeutic agents capable of targeted drug delivery, localized tissue repair, continuous disease monitoring, and intelligent therapeutic adjustment based on real-time patient conditions. Reinforcement learning continuously optimizes nano-robotic behavior to maximize treatment effectiveness while minimizing adverse effects. Edge computing and federated learning enable low-latency decision-making and collaborative model training without exposing sensitive patient data. The proposed architecture significantly improves early disease prediction accuracy, treatment personalization, healthcare security, communication reliability, computational efficiency, and patient safety. The invention is applicable to smart hospitals, precision medicine, chronic disease management, oncology, cardiovascular care, neurological disorders, remote healthcare monitoring, military medicine, and next-generation autonomous healthcare systems, thereby establishing a secure, intelligent, and self-evolving ecosystem for future digital healthcare.
Disclaimer: Curated by HT Syndication.
